The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study [1 ed.] 9783954896295, 9783954891290

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Daniel Kowalski

The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany

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A Prefeasibility Study

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

Kowalski, Daniel: The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study. Hamburg, Anchor Academic Publishing 2014 Buch-ISBN: 978-3-95489-129-0 PDF-eBook-ISBN: 978-3-95489-629-5 Druck/Herstellung: Anchor Academic Publishing, Hamburg, 2014 Bibliografische Information der Deutschen Nationalbibliothek: Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über http://dnb.d-nb.de abrufbar. Bibliographical Information of the German National Library: The German National Library lists this publication in the German National Bibliography. Detailed bibliographic data can be found at: http://dnb.d-nb.de

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

 

Abstract 

 The prefeasibility study at hand proposes to integrate driverless vehicles in commercial carsharing schemes in Germany. It finds indications that carsharing has the potential to become a significant mode of transport because it responds to social and business change. On the other hand, the study shows that it is the human component in traffic causing the majority of accidents, which is why driverless vehicles are expected to reduce traffic accidents and improve road safety. By making use of the business management tools SWOT analysis and an ad hoc STEPLED analysis, the study conducts a micro-environmental and macroenvironmental analysis of the German carmakers BMW and Daimler in regard to the proposed concept. The main finding is that the technology is generally expected to be marketable within the next two decades, if not much earlier. It can be expected that customers will accept driverless vehicle technologies and that many new target groups could be reached by the realisation of the concept. Carmakers should benefit from this potential and might be able to offset possible losses in their core business. The analysis does also show, however, that the current legislation poses several obstacles and might, if unchanged, delay the introduction of driverless vehicle technologies. It is recommended for carmakers to become active and start a public debate similar to the one in the United States. Moreover, it is recommended to collaborate closely with other mobility providers in order to avoid lobbying against the idea.

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

 

Acknowledgements 

The last five months have been a challenging time and I want to thank all those that supported me. William Sheward, my supervisor, who always took the time to discuss my ideas, not only for this study, but also for other assignments and on several other occasions. His feedback was consistently valuable and the directions he gave me helped to focus on the essential while not neglecting the complexity at the same time. I also want to thank Paul Sheeran, course leader and tutor of my MA programme Managing Contemporary Global Issues, for uncountable inspiring discussions and also for always emphasising the sheer complexity of our world. I want to thank Natalia Yakovleva, another tutor of my programme, whose interesting and challenging lectures were packed with many different study methods – one a little game which eventually led to the idea for this study. Thanks also to my fellow students and friends, Adeniyi Asifat and Robert Finegold, with who I developed the idea in the lecture. I also want to thank Nachiket Pusalkar, a true friend, who was always there for me, always listened to my ideas and supported me throughout the year; Jean Paul Pollock and Dan Wilkinson, for lively debates and feedback on my topic; my parents Ramona and Jürgen, who did their best to support me in every way; as well as my brother Marco, who distracted me every now and then which was equally important. The biggest thank-you goes to my amazing girlfriend Echo Yu, soon to be my wife Echo Kowalski. She is always there, listening to me crazy ideas, challenging my concepts and

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predictions, and supports me in just about every possible way. Love you honey.



Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.



Table of Contents

 Introduction .............................................................................................................................. 1 0.1 Overview ......................................................................................................................... 1 0.2 Definitions ....................................................................................................................... 2 0.3 Structure of the Study ...................................................................................................... 4 0.4 Rationale .......................................................................................................................... 5 0.5 Case Study: Germany ...................................................................................................... 6 0.6 Aim and Objectives ......................................................................................................... 6 0.7 Methodology.................................................................................................................... 7 0.8 Limitations ....................................................................................................................... 8 Part 1: Carsharing ................................................................................................................. 10 1.1 Introduction ................................................................................................................... 10 1.2 Background.................................................................................................................... 11 1.3 Social and Business Change regarding Mobility........................................................... 16 1.3.1 From “Generation Golf” to “Generation Hire Car” ............................................... 16 1.3.2 From Carmaker to Mobility Provider..................................................................... 18 1.3.3 Sustainability Concerns .......................................................................................... 20 1.4 Carsharing as a Response to Social Change .................................................................. 21 1.4.1 Generation Hire Car ............................................................................................... 21 1.4.2 Carmaker or Mobility Provider .............................................................................. 23 1.4.3 Sustainability Concerns .......................................................................................... 24 1.5 Limitations of Carsharing .............................................................................................. 27 1.5.1 Parking ................................................................................................................... 27

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1.5.2 Availability ............................................................................................................. 28 Part 2: Driverless Vehicles..................................................................................................... 30 2.2 Background.................................................................................................................... 31 2.3 Social Issue Traffic Accidents ....................................................................................... 33 2.3.1 Background ............................................................................................................ 33 2.3.2 The Role of the Driver in Car-related Traffic Accidents ........................................ 34



Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.



 

Table of Contents

 2.3.3 Traffic Accidents in Germany ................................................................................ 41 2.3.4 Economic Costs of Traffic Accidents ..................................................................... 46 2.4 Automation in Passenger Vehicles as a Response to Traffic Accidents ........................ 47 2.4.1 Driver Assistance Systems ..................................................................................... 47 2.4.2 Advanced Driver Assistance Systems .................................................................... 47 2.4.3 Car Drivers, Customers, and Advanced Driver Assistant Systems ........................ 48 2.5 Fully-Automated Vehicles ............................................................................................. 49 Part 3: Prefeasibility Study ................................................................................................... 53 3.1 Introduction ................................................................................................................... 53 3.2 The Concept ................................................................................................................... 54 3.3 Micro-Environmental Analysis: SWOT ........................................................................ 54 3.3.1 Strengths ................................................................................................................. 55 3.3.2 Weaknesses ............................................................................................................. 56 3.3.3 Opportunities .......................................................................................................... 57 3.3.4 Threats .................................................................................................................... 60 3.4 Macro-Environmental Analysis: STEPLED.................................................................. 62 3.4.1 Society .................................................................................................................... 62 3.4.2 Technology ............................................................................................................. 64 3.4.3 Environment ........................................................................................................... 68 3.4.4 Politics .................................................................................................................... 69 3.4.5 Legislation .............................................................................................................. 70 3.4.6 Ethics ...................................................................................................................... 73

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3.4.7 Demographics......................................................................................................... 74 Conclusion .............................................................................................................................. 76 Recommendations .................................................................................................................. 79 Bibliography ........................................................................................................................... 82



Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.



List of Tables 



 Table 1. Comparison of traditional and commercial carsharing schemes............................... 12 Table 2. Proposed definitions for different stages of the automation of the driving task ....... 34 Table 3. Activities car drivers said they would engage in while driving ................................ 36 Table 4. Risk Rankings ........................................................................................................... 37 Table 5. How many car drivers answer and make phone calls while driving ......................... 38 Table 6. How many car drivers set up and take a reading from their satellite navigation while driving ..................................................................................................................... 39 Table 7. Expected demographic change in Germany by 2050................................................ 75

          

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

 

List of Figures 

 Figure 1. How often cars caused accidents with other road users and how many people died comparatively............................................................................................... 43 Figure 2. Share of seriously-injured car drivers in total population ....................................... 43 Figure 3. Accidents per 1,000 population and erratic behaviour causing them ...................... 44 Figure 4. Distribution of accidents in which people were injured (within city limits) over a week...................................................................................................................... 45



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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.



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Abbreviations

ABS

Anti-lock Brake System

ACC

Adaptive Cruise Control

ACE

Auto Club Europa (Automobile Club Europe)

ADAS

Advanced Driver Assistance Systems

ADAC

Allgemeiner Deutscher Automobil-Club (General German Automobile Club)

AEB

Autonomous Emergency Braking assistant

AHS

Automated Highway System

AltfahrzeugV

Altfahrzeug-Verordnung (End-of-Life Vehicle Regulations)

BAC

Blood Alcohol Concentration

BASt

Bundesanstalt für Straßenwesen (Federal Road Research Institute)

BGB

Bundesgesetzbuch (Civil Code)

BMVBS

Bundesministerium für Verkehr, Bau und Stadtentwicklung (Federal Ministry for Transport, Construction and Urban Development)

BZP

Bundes-Zentralverband Personenverkehr – Taxi und Mietwagen (federal association personal transport – taxi and hire car)

DARPA

Defense Advanced Research Projects Agency

DAS

Driver Assistance Systems

DAT

Deutsche Automobil Treuhand (German Automobile Trust)

DB

Deutsche Bahn (German Railways)

DLR

Deutsches Zentrum für Luft- und Raumfahrt (German Aerospace Center)

DVR

Deutscher Verkehrssicherheitsrat (German Traffic Safety Association)

DRUID

Driving under the Influence of Drugs, Alcohol and Medicines

 

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ESP

Electronic Stability Programme

EV

Electric Vehicle

HAVEit

Highly Automated Vehicles for Intelligent Transport

KBA

Kraftfahrt-Bundesamt (Federal Office for Motor Traffic)

NASA

National Aeronautics and Space Administration

NHTSA

National Highway Traffic Safety Administration

ProdHaftG

Produkthaftungsgesetz (Product Liability Act)

StBA

Statistisches Bundesamt (

STEEPLED

Society, Technology, Economics, Environment, Politics, Legislation, Ethics, Demographics

STEPLED

Society, Technology, Environment, Politics, Legislation, Ethics, Demographics

StGB

Strafgesetzbuch (criminal code)

StVG

Straßenverkehsgesetz (Road Traffic Act)

StVO

Straßenverkehrsordnung (Highway Code)

StVZO

Straßenverkehrs-Zulassungs-Ordnung (National Vehicle Safety Standard)

SWOT

Strengths, Weaknesses, Opportunities, Threats analysis

TAP

Temporary Auto Pilot

UNECE

United Nations Economic Commission for Europe

WP 29

United Nations Working Party 29, the World Forum for Harmonization of Vehicle Regulations

WZB

Wissenschaftszentrum Berlin für Sozialforschung (Center of Social Sciences Berlin)









Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.



Introducon 0.1 Overview The world population recently reached 7 billion people and is expected to rise to 10 billion by 2050 (UN, 2012a [online]). At the same time the share of people living in urban areas has been steadily increasing, from 29% in 1950 to nearly 52% in 2010 (UN, 2012b [online]). Because people move to cities in search of work and a better life (Firnkorn & Müller, 2012 [online]), this number is expected to rise further as well, to more than 67% by 2050 (UN, 2012b [online]). Growing cities are the consequent result of both trends (Firnkorn & Müller, 2012 [online]) and have led to various problems for respective local communities, ranging from poverty and the creation of slums, to water scarcity, health issues or pressure on the local and surrounding environment. One problem that is shared by urban agglomerations all over the globe is the increasing traffic density. In general, road transportation provides benefits to individuals and societies as a whole, such as enabling economic markets (WHO, 2009 [online]). However, the aforementioned trends concerning population growth and increasing urban populations are accompanied by the process of the motorisation of the individual. In the political East and South this process has, from a historical point of view, just started, while demand for individual motorised mobility in Western and Northern societies has not yet reached full saturation levels (Firnkorn & Müller, 2012 [online]; Shell Deutschland Oil GmbH, 2009 [online]). The consequences of all these trends, however, are negative for the individual and the community. Traffic accidents and the resulting congestion in combination with the increasing traffic density cause mental stress, physical pain and economic inefficiencies (IMechE, 2012 [online]; OECD & ITF, 2008 [online]; Shankar & Singh, 2012 [online]; Straube, 2011 [online]); United Nations (n.d. [online]): people die or get injured in traffic accidents Copyright © 2013. Diplomica Verlag. All rights reserved.

(UNECE, 2012 [online]), properties are damaged (Statistisches Bundesamt, 2012a [online]), noise and exhaust emissions pose a danger to the health of locals (Senatsverwaltung für Stadtentwicklung, 2006 [online]), time of individuals is wasted (Bratzel, 2011 [online]), and the environment is damaged (Union Investment, n.d. [online]). This result, depending on regions, countries and cities admittedly in vastly varying degrees, is expected to worsen further with a continuation of the abovementioned trends. The study at hand suggests a new mobility concept which would make use of carsharing and driverless vehicle technologies,

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and has the potential to tackle the abovementioned disadvantages of individualised transport while offering the same and even additional benefits. 0.2 Definitions Different administrative approaches have been undertaken to tackle traffic-related issues, such as banning specific road users from certain areas (Firnkorn & Müller, 2012 [online]), strengthening public transport (Reidenbach et al, 2008 [online]) or encouraging residents to walk or make use of bicycles (UNECE, 2012 [online]). Private people, associations and companies, on the other hand, may also become a key in contributing to the solution. One of these grassroots approaches is called carsharing, which is based on the idea that several people can share one car while at the same time enjoying fewer disadvantages compared to possessing an own car. The concept, which started within small groups of private persons, offers a new transport mode with the potential to reduce car ownership and consequently traffic density (Martin, Shaheen & Lidicker, 2010 [online]). These environmental reasons have strongly contributed to the early attractiveness of carsharing (BFE, 2006 [online]) and led to the first schemes in the 1980s, which were organised by associations and clubs (Autotipps.net, n.d. [online]; Schlesiger, 2011 [online]). In these usually small traditional carsharing schemes, customers can find available cars at specific stations in a city and rent them spontaneously or after reservation (Lawinczak & Heinrichs, 2008 [online]). Customers are charged with a monthly basic fee and a price based on rental time or distance, which includes all costs such as petrol, taxes, insurance, maintenance and repairs (Lawinczak & Heinrichs, 2008 [online]). Increasing numbers of participant and schemes started to indicate a strong market potential (Zhao, 2010 [online]) and eventually attracted corporations who commercialised the idea (Daimler, 2008 [online]; DriveNow, 2011 [online]). In these commercial carsharing schemes, companies increased the flexibility for customers because cars can be parked on all public

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parking spaces as well as on specific stations (Lawinczak & Heinrichs, 2008 [online]), while customers can find the next available car by using smartphone or internet applications (Firnkorn & Müller, 2012 [online]). Moreover, commercial carsharing schemes distinguish themselves from traditional ones because of their minute-based charging and the absence of monthly fees (Firnkorn & Müller, 2012 [online]) and environmental commitments (Kramper, 2012a [online]).

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

These current commercial carsharing programmes, the study at hand proposes, should be combined with driverless vehicles, also called autonomous vehicles (Kalra, Anderson & Wachs, 2009 [online]) or robot cars (Davis, 2006 [online]). The technology is not yet sold to the public but recent developments indicate that the technology is likely to be released eventually. Two different approaches can be observed in the development of driverless vehicles. The first approach is characterised by the development of so-called driver or advanced driver assistance systems (DAS or ADAS) by companies from the automotive industry. These systems like the anti-lock brake system (ABS), the electronic stability programme (ESP) or some more advanced ones like the adaptive cruise control (ACC) and the autonomous emergency braking assistant (AEB), address specific deficits of drivers and seek to make driving saver (Kubitzki, J., personal communication [email], 17/7/2012). With the continuous improvement of existing and the constant development of new systems, it is believed that technologies will gradually improve until fully autonomous driving is eventually achieved (Bohr, 2011 [online]). The internet search provider Google, on the other hand, aims directly at fully-autonomous driving. The company does not manufacture the cars itself but attaches various sensors and cameras to cars and hopes to be able to improve algorithms, which make sense out of the data which is gathered by sensors and operate the car, until no more human intervention is needed for the driving task (Vanderbilt, 2012d [online]). That this approach could also deliver a marketable product indicates Google’s fleet of several driverless vehicles which had travelled almost 500,000 km in August 2012 (Urmson, 2012 [online]). Impressed by this success, United States’ Nevada was the first administration in the world to allow the official testing of autonomous vehicles on public roads, whereas Google was the first company to receive a licence under these new regulations (Nevada DMV, 2012a [online]).

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While Google has not yet released any official statements on when its technology may be ready to go on sale, the automotive industry widely believes that its approach will lead to marketable solutions at latest within the next 20 years (Bohr, 2011 [online]). Either way, the successful realisation of such technologies is expected to improve the safety of car drivers and other road users such as pedestrians and bicyclists immediately (Urmson, 2012 [online]) and, with more cars making use of this technology, improve the traffic flow and fuel efficiency of the overall traffic in the long term (Kalra, Anderson & Wachs, 2009 [online]).

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The study at hand proposes to combine both components by integrating such driverless vehicles in commercial carsharing schemes in the future. Customers could use these vehicles much like taxis which pick up customers where and when they want and bring them where they want to go, thereby driving fully autonomously and offering customers to use the travel time for other purposes. Some limitations of current carsharing schemes, such as limited parking spaces and the need to find available vehicles, would be solved as well, and the overall traffic safety could be improved. 0.3 Structure of the Study The study, which will use Germany as a case study (see 0.5), will start with an analysis of the carsharing concept in the first part. It will be shown that carsharing offers a relatively new form of mobility and thereby responds to a changing mobility behaviour caused by social and business change. Moreover, the current limitations of carsharing will be explored to understand how the proposed concept could tackle those weaknesses. The second part is concerned with traffic safety and how improving driver assistance systems benefit road users. It will be shown that the vast majority of car-related traffic accidents are caused by erratic behaviour of drivers, and that traffic accidents are a huge societal issue in terms of costs and physical and psychological pain. The part will continue to introduce current ADAS to show how carmakers and suppliers make driving saver, before it will close with a short analysis of the status quo of driverless vehicle development in order to understand the problems of the technology that have to be overcome before the introduction, the limitations it may encounter due to its system limitations, as well as to understand the potential such technologies have to improve traffic safety. The third part constitutes a prefeasibility study. It starts by first describing the proposed concept and suggesting some components which would be required for the realisation. In order to analyse how the concept would impact on companies, the study makes use of two

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business management tools, the SWOT and an ad hoc STEPLED analysis (see 0.6 Methodology). This part will help to understand possible obstacles to the realisation but also benefits the proposed concept might bring to providers. The conclusion will discuss the results before recommendations close the study.

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0.4 Rationale The study at hand proposes to integrate driverless vehicles, when available, in commercial carsharing schemes and will be evaluated from the perspective of carmakers for several reasons. These providers do already offer carsharing schemes and build up competences in the field. The proposed concept would thus suggest a mere logical and evolutionary step to make use of more technologies in carsharing vehicles, which are developed by carmakers for their regularly sold cars anyway. Moreover, other than small private associations or large government entities, carmakers have the potential to create an economic market with fewer inefficiencies and a higher customer penetration. On the other hand, with the possibility that the individual mobility behaviour is about to change, away from private car ownership towards other modes of transport such as carsharing, carmakers’ core business of manufacturing and selling cars may be significantly affected (BMW, 2008 [online]). The proposed concept would offer carmakers several opportunities in the future to reduce the reliance on the core business and take advantage of latest developments, three of which are described in the following paragraphs. First, making use of the concept can potentially increase sales of driverless vehicles. The technology is widely regarded as the future of the automobile (HAVEit, 2011b [online]) and is thus expected to be offered by carmakers eventually (Bohr, 2011 [online]). Letting go off the wheel completely and putting one’s life at a car’s mercy, however, may pose a huge barrier to many customers for the adaption of such technologies (ADAC, personal communication [email], 17/7/2012). To overcome these fears it had been shown that customers become accustomed better with innovative products when they can test and associate positive experiences with those (Jansson, 2011 [online]). This effect is already used in carsharing schemes in order to make customers familiar with electric cars (Herz, 2011 [online]) and could thus be equally used for driverless vehicle technologies.

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Second, the proposed concept has the potential to strengthen a carmaker’s competitive position and subsequently ensure an important share in the growing carsharing market. As will be shown in the first part of this study, carmakers are increasingly seeking to enlarge their business area by becoming mobility providers (BMW, 2008 [online]). While posing a threat to carmakers’ core business by negatively affecting private car ownership, carsharing and the proposed concept in particular may offer a new business field with the potential to partly or completely compensate those losses.

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Not only are these opportunities advantageous for companies, but the concept should also be considered for a third reason. Analysts assume that carsharing is an attractive market with a huge customer potential (Zhao, 2010 [online]). Carmakers will have to retain a competitive advantage over other providers (Schlesiger, 2011 [online]) in order to survive in a changing industry (BMW, 2008 [online]). Keeping in mind that Google’s system could be attached to almost every car (Lavrinc, 2012a [online]), which would enable basically everyone to offer a similar mobility concept, potential future competition needs to be considered especially in terms of first-mover advantages. 0.5 Case Study: Germany The study will use Germany as a case study. Concerning the three trends mentioned at the beginning, Germany fits almost each other society in regard to traffic. Its urban population is expected to increase from currently 73.8% to nearly 82% by 2050 (UN, 2012b [online]) and the figures for private car ownership are expected to increase further (Shell Deutschland Oil GmbH, 2009 [online]). Only the overall population is expected to decline (Statistisches Bundesamt, 2012b [online]) which should therefore positively impact on traffic density. The study will use Germany as a case study, moreover, because it perfectly meets the criteria to introduce smart mobility solutions (Schlesiger, 2011 [online]). Global market leaders are located in Germany, such as carmakers and suppliers, or manufacturers of electrical components and providers of telematics (Schlesiger, 2011 [online]), and its automotive industry is regarded to be the most innovative (Fuß, 2011 [online]). Because of its importance for the country’s economic performance, the automotive industry is also comparatively wellsupported by political parties and respective communities. On the other hand, the German market for automobiles is seen as one of the toughest worldwide due to high expectations and requirements of customers. This, in combination with supportive economic and political conditions, may not only allow introducing the proposed concept in Germany, but also to test

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and improve it there, before exporting it to other cities, countries and continents. 0.6 Aim and Objectives The aim of the study is first, assessing the current social and business environment for the proposed concept as well as evaluating the potential to reduce traffic accidents by making use of driverless vehicles. Taking the perspective of carmakers, this study is subsequently going to analyse the feasibility of the proposed concept and will examine first, the strengths and weaknesses of carmakers in terms of their potential to introduce the proposed concept and

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also which opportunities and threats may result from the introduction of such a scheme. The study continues to analyse current states and possible future developments of the macroenvironmental elements society, technology, environment, politics, legislation, ethics and demographics regarding the proposed concept. 0.7 Methodology This report, because driverless vehicle technologies are in an early stage, will be conducted as a prefeasibility study. This type differs from a feasibility study insofar that it does not conduct specific calculations or surveys to determine specific price range or market potential, but rather seeks to find out whether the idea indicates to be profitable, for example, because of customer acceptance, technologies or costs (Lohmann, 2010 [online]). The study at hand makes use of components suggested specifically for prefeasibility studies by Carsten Lohmann (2012 [online]) from the economisation and innovation centre of the German economy association, such as conducting internet and literature reviews and talking with potential suppliers, cooperation partners and internal employees. The study at hand contains three main parts. In the first two parts the study will concern itself with the two components of the proposed concept, carsharing and driverless vehicle technologies. After giving an overview of the general topic, both parts start by reflecting current scholarly debates concerning the respective topic. The theoretical debates are applied to the case study Germany by using primary data, such as [1] news releases and financial reports of companies; [2] legal texts, publications and statistics from governmental institutions, as well as secondary data, such as [1] book, journal and news articles; [2] reports and statistics from researchers and private organisations; and [3] statements of experts. In the next step the study shows how both concepts, carsharing and driverless vehicle technologies, have the potential to respond to the respective societal issues. By showing at the end of each part the current limitations of carsharing and issues that have to be overcome for the introduction of driver-

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less vehicles respectively, the study seeks to indicate the potential for improvement in carsharing schemes as well as giving a realistic outlook on the challenges until driverless vehicles will be available to the public. The third part makes use of two business management tools, the SWOT analysis and an ad hoc STEPLED analysis. The former synonym stands for strengths, weaknesses, opportunities and threats, and will be used to analyse micro-environmental factors. The first section will focus on strengths and weaknesses of carmakers concerning the proposed concept while the

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second section will explore possible opportunities and threats for carmakers. The second analysis tool STEPLED is an ad hoc tool created from STEEPLED, which will help to understand the current and possible future development of the macro-environmental factors society, technology, environment, politics, legislation, ethics and demographics. Because of the long-term outlook of the study at hand, the economic element (the second E in STEEPLED) will be left out and thus the analysis will be subsequently called STEPLED. The reason for this is that economic conditions such as interest rates or unemployment rates will hardly influence the overall development towards the proposed concept but also because such factors would rather require attention when preparing the actual introduction of a business proposal. This part conducts the analysis of the developments presented in the first two parts and uses statements of experts in their respective fields, either collected from publicly available interviews or used in private correspondence with the author of this study. The advantage of the abovementioned approach is that no other study has tried to combine carsharing and driverless vehicles, despite being a popular theme in science fiction movies and future scenarios. The study does not only bring together two different trends but, from the knowledge of the author, for the first time proposes and analyses the potential concept in terms of the feasibility from the perspective of carmakers. This combination indicates possible future consequences but also necessary steps that require action. 0.8 Limitations The proposed concept makes use of a technology which is neither available to the public yet nor is there a guarantee that it definitely will be in the future. The general view in the automotive industry and of Google is that the technology will be marketable eventually, however, the study could become obsolete if developers would encounter problems concerning driverless vehicle technologies which cannot be overcome. The study will furthermore not analyse the possible advantages of increased fuel efficiency

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and improved traffic flow because both benefits would only be realised after a sufficiently large number of road users had switched to driverless vehicles (Kalra, Anderson & Wachs, 2009 [online]). Moreover, similar to the proposed concept are systems called personal rapid transit systems (CityMobile, 2011 [online]). Although some systems are already in operation, such as the ULTra PRT system at Heathrow Airport in London (CityMobile, 2011 [online]), these systems are not included in this research because their autonomously driving vehicles require

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separate lanes or tunnels. The proposed concept, on the other hand, would make use of the existing road infrastructure, without the need to invest in new infrastructure.



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Part1:Carsharing There is no human right to possess an own car. Chandran Nair founder and CEO of the think tank Global Institute for Tomorrow 1.1 Introduction This part is going to introduce the first of two components required for the proposed concept, carsharing. The background section gives an overview of recent developments in the carsharing market, which indicate that carsharing has a strong growth potential and could be established as an alternative mobility concept. The following section investigates observable social and business change regarding mobility to show that [1] the automobile may further decline as a status symbol in the future with decreasing private car ownership levels, that [2] carmakers have started to change their traditional business models to become mobility providers, and that [3] sustainability considerations play a role for customers and carmakers and have the potential to influence purchase decisions. The subsequent analysis focuses on how carsharing can respond to these changes. It will be shown that carsharing is currently especially used by the young generation who could do without an own car but demand environmentally-friendly mobility with high flexibility and low costs. This behaviour indicates that mobility patterns in Germany may be about to change sustainably. Carmakers, it will be shown, are seeking to respond to such trends by

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extending their core businesses in order to offer new mobility services. Whereas criticism revolves around the problem that an increased carsharing engagement may negatively influence sales figures, carmakers expect to bind young customers to their brands so that their brands would be considered as an option for a possible future purchase. In this context, the example of the electric car will be used to highlight how carmakers introduce new technologies in carsharing schemes to make their customers familiar with innovative technologies.

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The very same approach, the study suggests, can be used to integrate driverless vehicles in commercial carsharing schemes. The last section of this part will focus on the two main limitations of current programmes, parking and the availability of cars. This overview will be used in the third part of this study to show how the second component of the proposed concept, driverless vehicles, could tackle most of carsharing’s current weaknesses. 1.2 Background Carsharing is an organised form of joint car usage and offers, from the perspective of the customer, a mode of transport placed between car hire and private car ownership (Lawinczak & Heinrichs, 2008 [online]). The most significant carsharing models in terms of customer numbers are traditional carsharing schemes, organised by associations or clubs, and commercial schemes, offered by carmakers such as BMW and Daimler, the maker of Mercedes automobiles. In general, both types work similarly. After having signed up, customers can rent available cars either after reservation or spontaneously, and drive to their desired destination. Opposed to traditional carsharing, customers of commercial schemes are limited to drive within certain areas, usually city centres, while they are not required to return the car to specific stations (Finanztest, 2012 [online]). In commercial schemes subsequent customers can find the randomly parked cars via customer hotlines, internet or smartphone applications (Firnkorn & Müller, 2012 [online]). Another difference is that customers of commercial schemes pay a fixed price per minute whereas carsharing associations usually require their customers to pay a monthly fee and offer different prices depending upon the vehicle customers choose and the duration or length of the trip (Lawinczak & Heinrichs, 2008 [online]). In both types, however, fees include all costs such as petrol, parking, insurance, tax, cleaning, maintenance or repairs (Grundhoff, 2008 [online]; Kramper, 2012a [online]; Lawinczak & Heinrichs, 2008

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[online]; Finanztest, 2012 [online]). Table 1 summarizes the major differences of traditional and commercial carsharing schemes.





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Tradionalcarsharing

Commercialcarsharing







Findingavehicle

Atdesignatedstaonsonly,via smartphoneandinternet applicaons

Via hotlines, smartphoneand internetapplicaons







Drivingrestricons

Time:Usuallyupto24h Distance:nolimitaons

Time:norestricons Distance:limitedtobusiness areaofrespecvescheme

Necessarytoreturnthecarto originalstaon

Notnecessarytoreturnthecar tostarngpoint

Ondesignatedstaonsonly

Ondesignatedstaonsor randomlyonpublicparkinglots

Pricing

Monthlyfees(inmostschemes) plusduraonbasedordistance basedfee

Priceperminute







Environmentalcom mitments 

Requiredinsomeschemes

Notrequired





 Returningthecar

 Parkingthecar



Table1.Comparisonoftradionalandcommercialcarsharingschemes 

Having started in Germany in 1988 (Autotipps.net, n.d. [online]), carsharing was made popular by independent organisations (Schlesiger, 2011 [online]). More than 110 of these organisations operated 4,600 cars for 158,000 customers in 285 German cities and communities in 2011, growing on average by 15.8% annually since 2005 (Loose, 2011 [online]). In October 2008 Daimler was the first company to offer its own carsharing scheme called car2go. Having started as a pilot project with 200 Smarts for its employees in Ulm (Daimler, 2008 [online]), Daimler extended the scheme to the public in March 2009 because of its huge Copyright © 2013. Diplomica Verlag. All rights reserved.

success (Daimler, 2009 [online]). Offering carsharing that was as easy to use as mobile phones (Grundhoff, 2008 [online]), car2go attracted more than 10% of Ulm’s population within the first three months (Daimler, 2009 [online]). Daimler established a joint venture with the car hire provider Europcar (Daimler, 2011c [online]) so that the scheme was able to expand quickly to other cities and countries (car2go, n.d.b [online]). So far, car2go has acquired more than 120,000 customers in twelve cities (Daimler, 2012f [online]) who have travelled around 20 million kilometres (Daimler, 2012d [online]). In the near future, car2go is

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planned to be offered in forty to fifty cities (Daimler, 2011 [online]) and, according to car2go’s CEO Robert Henrich, Daimler wants to set itself at the peak of this trend to become the market leader (Bund, 2011 [online]). Despite the overall success, the scheme currently operates at a loss. Daimler, however, sees a huge potential in carsharing (Becker, 2010 [online]; Daimler, 2010 [online]) and expects profits by 2014 (Bund, 2011 [online]). Other market entries of BMW, Volkswagen and Peugeot reflect that Daimler is not the only carmaker to believe in the success of carsharing (Firnkorn & Müller, 2012 [online]). Because Volkswagen’s Quicar (VW, 2011 [online]) and Peugeot’s Mu (Mu by Peugeot, n.d. [online]) rather resemble traditional carsharing and car hire respectively, however, this work will primarily focus on Daimler’s car2go and BMW’s carsharing scheme called DriveNow. The latter started almost three years after Daimler’s car2go, in June 2011 (DriveNow, 2011 [online]). According to BMW’s CEO Norbert Reithofer (2012 [online]), the scheme has gained more than 27,000 customers in Berlin, Munich and Dusseldorf in the first eleven months and is planning to expand its programme to Cologne in September 2012 (DriveNow, 2012c [online]). Similarly to Daimler, BMW opted for a joint venture with a car hire company, SIXT, but tries to distinguish itself from competition by offering premium cars in its scheme (SIXT, 2011 [online]). Of the major German carmakers, only Audi, which is sceptical towards carsharing schemes (Magenheim, 2011 [online]), and Opel, which struggles with its own survival, are not engaged in carsharing (Hucko, 2012 [online]). This is surprising because many studies see a huge potential for carsharing. According to research from business consultancy Frost & Sullivan (Zhao, 2010 [online]), for example, “carsharing membership is expected to reach 4.4 million in North America and 5.5 million in Europe by 2016.” By comparing the advantages and disadvantages of carsharing with the other mass motorised transport modes [1] private car, [2] hire car, [3] taxi, and [4] public transport, the following paragraphs show reasons for

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this potential. First, an own car provides, according to research project of the Bundesministerium für Verkehr, Bau und Stadtentwicklung (BMVBS, Federal Ministry for Transport, Construction and Urban Development) conducted by Jana Lawinczak & Eckhart Heinrichs (2008 [online]), unrestricted mobility and serves as a status symbol. Whereas the latter is intangible and varies for each person, the former can be measured in costs. When comparing the costs of an own car and those for carsharing, different calculations have been made available. Considering

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that these comparisons usually focus on traditional carsharing, one must be aware that the explanatory power of the following paragraph is limited in regard to commercial carsharing. In general, the literature agrees that carsharing is cheaper for people living in urban areas who drive less than 12,000 to 15,000 kilometres annually (Finanztest, 2012 [online]; Lawinczak & Heinrichs, 2008 [online]; Zhao, 2010 [online]). Finanztest (2012 [online]), an independent foundation testing financial products, calculated costs of €0.49 per kilometre for a private car compared to €0.36 per kilometre with the same car of a traditional carsharing scheme respectively. Because DriveNow and car2go charge their customers by time (each programme charges €0.29 per minute), it is hard to compare these results with the above mentioned costs. For example, when using the vague statistics published by car2go, the average price per kilometre ranges between €0.69 and €1.39. This calculation neglects, however, that the above mentioned costs calculated by Finanztest contained travel times on rural roads and motorways. It can be assumed that the average speed on these roads is higher, or from another perspective, that the average speed within urban areas would be lower. The costs of traditional carsharing schemes and private cars may thus be higher if rural roads and motorways were excluded from the calculation. Other cost advantages of carsharing over private car ownership are highlighted by Lawinczak and Heinrichs (2008 [online]). They point out, for example, that customers of carsharing schemes have no need and also no costs for a parking lot, do not have to finance a car individually, and save time which would be required for the maintenance of the car. Other authors such as Gernot Kramper (2012a [online]) and Michael Specht (2010 [online]) from Stern magazine highlight, however, that carsharing is neither suitable nor economical for daily commutes. Moreover, because carsharing cannot substitute the private car, costs for carsharing add up to other costs such as for public transport, which increases the overall price of mobility for the individual.

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Second, Lawinczak & Heinrichs (2008 [online]) state two advantages of car hire over carsharing in their article from 2008, which are now offset by the schemes of BMW and Daimler: the availability of one-way journeys and the absence of monthly charges. Car hire, however, is still advantageous over these commercial schemes for all customers that plan longer or out-of-city journeys and it is also cheaper than carsharing for all those that only occasionally need a car (Finanztest, 2012 [online]).

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Carsharing, on the other hand, has many advantages over car hire, for example, that each new trip does not require a new contract, that stations and cars are located within urban centres which can thus be accessed easier by the majority of customers, that cars can be rented for very short time periods or that cars do not have to be refuelled after each journey (Lawinczak & Heinrichs, 2008 [online]). Third, being driven in a taxi has several advantages over driving a vehicle in carsharing schemes oneself. For example, customers do not have to locate an available car and walk to it before each journey but can easily use customer hotlines or smartphone applications to call a taxi, and will be picked up exactly where they are. Once in the taxi, customers can engage in other activities and are not required to pay attention to traffic or even to be sober. The taxi driver can take more than the two customers which fit in car2go’s Smarts and take the customer to the exact destination while the passenger is not required to find a parking lot (Kramper, 2012a [online]). Moreover, when the Allgemeiner Deutscher Automobil-Club (ADAC, German Automotive Society) tested taxis in several European cities, they found that 92.5% of drivers in German cities helped with luggage and 82.5% knew the destination right away (ADAC, 2011a,b,c,d,e [online]), which can also be advantageous over carsharing. However, the test also emphasised some weaknesses of taxis compared to carsharing. Two drivers made costly detours, two others did not pay attention to traffic rules and three drove too fast, one of them as fast as 92 km/h were 50 km/h were allowed so that he brought the tyres to squeak in curves. One driver almost caused an accident with a bicyclist and another drove over two red lights and so aggressive that the tester got sick (ADAC, 2011a,b,c,d,e [online]). As opposed to taxis, customers in carsharing schemes can drive in a way so that they feel save. Moreover, Finanztest (2012 [online]) highlighted that carsharing users only pay 40% of the costs of a taxi. Forth, public transport in urban areas is usually a service that contains bus lines, trams, light-

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rail traffic and, in some instances, a metro. The service generally covers a wide area of a city as opposed to the rather small business areas which are covered by commercial schemes so far. While also being usually cheaper than carsharing, customers have to orient their journeys on fixed time tables, may have to change between (different) transport modes, including the walking time to get from one station to another, and in the majority of cases are neither picked up where they are nor brought to where they want to go. Carsharing customers as well have to go (and even find) vehicles each time they want to make a travel. On the other hand,

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customers can rent a car flexibly whenever they want and can drive wherever they want to go faster because they do not have to stop at all stations or walk to change the mode of transport. Some of the abovementioned disadvantages with traditional transport modes, like walking to a car, finding a parking space or not being able to use the travel time for other purposes than driving, would be offset by the proposed concept. This would increase the benefits for customers and potentially increase the market potential of carsharing significantly (see part three). 1.3 Social and Business Change regarding Mobility The following section looks at three aspects of cultural change that can be observed in regard to mobility. The first covers the social change among the young generation which could indicate a broader change of the German population in the future. The second section concentrates on the changing business behaviour in the automotive industry and the third section covers sustainability concerns which, it can be argued, increasingly become a driver for customers’ purchase decisions and companies’ business orientations. 1.3.1 From “Generation Golf” to “Generation Hire Car” Although some studies have shown that the vast majority of young people enjoys driving (Progrenium, 2010 [online]; Steiler, 2012 [online]), Robert Schönduwe (2011 [online]) from the Goethe University Frankfurt am Main claims that the young generation is fundamentally changing: the Generation Golf, a concept termed by Florian Illies to describe how young people gained mobility and flexibility due to cheap and affordable cars such as the VW Golf that had become status symbols at the turn of the millennium, may become the Generation Hire Car, which refers to the book by Michael Adler that was released eleven years after Florian Illies’ book in 2011 and describes how the young generation opts for mobility as opposed to cars as status symbols.

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Indeed, Ballweg and Ebbing, 2011 [online]) suggest that the old maxim ‘one driving licence, one car’ does not seem to be true anymore. According to the youth study Timescout, 75% of young people have a driving licence but only 45% possess an own car (Lamparter, 2010 [online]). While a study of the Kraftfahrt-Bundesamt (KBA, Federal Office for Motor Traffic) (KBA, 2012a [online]) indicates that the numbers of young people acquiring a driving licence seems to have decreased, the Center of Automotive at the University of Bergisch Gladbach found that 31% without a car still enjoy access to one (Bratzel, 2011 [online]). The same

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study, however, also found that the number of 18-24 year-olds who are living in urban areas and have no access to a car, increased from 21% to 33% within five years (Bratzel, 2011 [online]). Another study of a German mobility panel (Das Deutsche Mobilitätspanel, 2011 [online]), shows that that the group of people aged 18-35, who hold a driving licence and have a car at their disposal, has declined from 84.2% in 2000 to 67.5% in 2010, while figures for those holding a driving licence but who possess no car increased from 7.1% to 19.3% in the same period. A report from the Deutsche Automobil Treuhand (DAT, German Automobile Trust) (DAT, 2012 [online]) which measures the purchase intention for cars, shows that the number of those not planning to buy a car anymore, has increased from 4% in 2004 to 12% in 2012. To describe the observed data, Schönduwe (2011 [online]) suggests analysing the following determinants. First, possessing a car has become too expensive for many people, not only the young (Schönduwe, 2011 [online]). The business consultancy Progenium (2012 [online]) compared the costs of small, medium-sized and premium vehicles between 1980 and 2012. The result is that the costs for small vehicles increased by 9%, the costs for medium-sized vehicles went up by a third and those for premium cars almost doubled. The ADAC (2010 [online]) published an index in 2010 which depicts how various costs had developed between 1995 and 2010. This index shows that whereas the general living expenses increased by 24.6% in this period, expenses for cars increased by 41.6%. These developments hit the young generation especially hard because they only have an average amount of €500 a month at their disposal (Bratzel, 2011 [online]). Thus Stefan Bratzel (2011 [online]) from the Center of Automotive believes that costs have become the number one reason why cars increasingly fail to connect to young people on an emotional level. Second, the value orientation is changing away from owning to using, which means that a car is not seen as a status symbol by the young generation anymore but used as a mean of transport (Schönduwe, 2011 [online]). This assumption is supported by several studies, such Copyright © 2013. Diplomica Verlag. All rights reserved.

as by Puls (Steiler, 2012 [online]), which found that roughly half of all participants see the car as a transport mode only, or by Progenium (2010 [online]), which found that 41% consider the car as a mode of transport only. The latter study also asked participants to rate different things according to their status potential: holidays, iPhones, watches and exclusive mountain bikes, among others, were all rated higher than a Smart, Golf or Opel, with only 17% of participants regarding an automobile as a status symbol (Progenium, 2010 [online]). Another study of the Center of Automotive found that almost half of the interviewees said

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they prefer spending money on expensive holiday trips or leisure activities rather than on cars (Bratzel, 2011 [online]). Third, biographies in Germany have changed (Schönduwe, 2011 [online]). The trend towards single and two-person households (Statistisches Bundesamt, 2012b [online]) combined with a reproduction rate below 1.4 (Statistisches Bundesamt, 2012c [online]) and the development that women are giving birth to their firstborn later, significantly influence private car ownership (Schönduwe, 2011 [online]). Schönduwe (2011 [online]) highlights in this regard that all families with children but 4% possess a car, compared to 18% of the average German household. Thus Schönduwe (2011 [online]) suggests that more families would require more cars and could thus influence car ownership rates positively. Forth, new mobility services are pushed into the market and offer new flexibility (Schönduwe, 2011 [online]). New media offering forums and social networks give more information on mobility services and have led, among others, to car-pooling and the increased use of carsharing or bicycle hire (Schönduwe, 2011 [online]). These determinants imply that car ownership among young people might decrease, however, data is ambiguous. Shell Deutschland Oil GmbH (2009 [online]) and the Deutsches Zentrum for Luft- und Raumfahrt (DLR, German Aerospace Center) (DLR, 2007 [online]) predict that car ownership will rise, and the business consultancy Ernst & Young concluded their survey that cars will remain an attractive product for customers (Fuß & Forst, 2012 [online]). Other studies, however, show that almost 80% of young people aged 18-25 could imagine a life without cars (Bratzel, 2011 [online]) and, again 80%, believe that they do not need an automobile in cities (Lamparter, 2010 [online]). Whether the changing car ownership behaviour is a long-term trend or just the result of delayed purchase decisions, for example, because of the delayed start of having a family, cannot be answered clearly. Schönduwe (2011 [online]) believes that a new mobility behav-

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iour is the reality in urban areas. 1.3.2 From Carmaker to Mobility Provider For more than a century, selling cars to private owners has been a successful business strategy (Firnkorn & Müller, 2012 [online]). Even though readmissions are on the rise (KBA, 2012a [online]), studies have shown that more European automobile industry experts expect

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stagnation or even declining growth rates in the premium segment, where German carmakers are commonly seen as the global market leaders. In the light of these developments carmakers have started to rethink their business models. According to Kramper (2012a [online]), carmakers are changing from being sellers of automobiles to becoming mobility service providers in order to, as Daimler (2011a [online]) puts it, “offer customers mobility services that match the requirement for traffic concepts in urban areas.” While this may sound at first as a threat to automakers’ traditional business model of selling cars, Jörg Firnkorn and Martin Müller (2012 [online]) from the University of Ulm present three reasons that could be the driver behind carmakers’ decisions to the introduction of new mobility services. First, Firnkorn and Müller (2012 [online]) argue that in some countries the saturation levels of cars per inhabitants have already been reached. According to Shell’s forecast, Germany is a partly saturated market. While car ownership among men will only slightly increase from 700 to 715 cars per 1,000 men by 2030, women’s car ownership is expected to increase from 340 to 430 (Shell Deutschland Oil GmbH, 2009 [online]). However, compared to other countries, especially in Asia and Latin America, where the number of vehicles is expected to more than double by 2020 compared to 2000 (Sperling & Claussen, 2004 [online]), German figures are rather low and could be interpreted as describing a saturated market. Second, carmakers seek new business opportunities in continuously growing cities (Firnkorn & Müller, 2012 [online]). Christian Schlesiger (2011 [online]), author for the news magazine Die Zeit, estimates that more than 80% of today’s economic value is created in cities, which means that the largest market lies within urban environments. Considering that the majority of Germany’s total population (UN, 2012a [online]) is currently living in urban areas (73.8%) and that this share is expected to increase to nearly 82% by 2050, this means that the main market for carmakers will further shift towards urban areas in Germany. However, consider-

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ing the growth of cities and the emergence of megacities especially in developing and emerging countries, it can also be assumed that companies do not only see German cities as a new market but as a test field for the further expansion in global markets. Third, Firnkorn and Müller (2012, p. 265 [online]) believe that automakers may also consider their “moral responsibility for the environmental externalities of their products,” such as greenhouse gas emissions or traffic jams, by addressing the pressure from their stakeholders who demand more corporate responsibility. A survey of Ernst & Young’s among companies

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of the automotive industry (Fuß, 2011 [online]) seems to prove this point because it has shown that companies expect that protecting the environment and reducing emission levels will become an important issue in the industry. It is hardly possible to determine which of the aforementioned reasons, if any, led the German carmakers BMW and Daimler to offer new mobility services. However, both entered the market and seek to become the leaders. BMW has given up seeing the automotive market from the perspective of a supplier but puts customer orientation and service appreciation into the centre of its new business strategy, considering the complete area of individual mobility as their future business (BMW, 2008 [online]). BMW believes that carmakers are going to face the biggest challenge in the third millennium and only those that try to tackle this challenge will be able to survive (BMW, 2008 [online]). Daimler prepares itself for the future challenges and believes that those who offer the best mobility services will enjoy competitive advantages over many years (Lamparter, 2010 [online]). Thomas Weber, Head of Daimler’s research and development, states that it is better to be on top of a trend than being behind (Lamparter, 2010 [online]). This offers a fourth aspect, not mentioned by Firnkorn and Müller, which could be the fear to be left behind in a social environment that changes (see 1.3.1). 1.3.3 Sustainability Concerns The concept of sustainable development is widely defined according to the Brundtland Commission (1987 [online]) which wrote that “Sustainable development seeks to meet the needs and aspirations of the present without compromising the ability to meet those of the future.” Today, sustainability considerations have become a driver of customers and corporations as a result of resource exploitation and climate change. In terms of mobility, Shell (Shell Deutschland Oil GmbH, 2009 [online]) defines sustainable mobility as the capability of a society to move freely and exchange extensively without

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causing other important social or ecological disadvantages. Considering the following figures it can be argued that the current mobility regarding cars can hardly be described sustainable in Germany: the number of registered cars has increased from 11 million to around 42 million since 1952 (KBA, 2012a [online]). Considering that around 5,000 kilograms of raw materials for the production of a single car are needed (Union Investment, n.d. [online]), it becomes clear that this development is apparently not sustainable in terms of the definition of the Brundtland Commission and will thus very likely compromise the ability to meet the needs of

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the future. Recycling is seen as one possible solution to the problem. At the moment, section 5 of the Altfahrzeug-Verordnung (AltfahrzeugV, End-of-Life Vehicle Regulations) makes it mandatory to recycle 85% of a car’s weight (Bundesministerium der Justiz, 2012a, [online]). However, even recycling 100% will not provide more materials to the production process than what was returned to be recycled in the first place. While many advocates concentrate their criticism on developing and emerging countries in Asia and Latin America and demand a need to acknowledge that those cannot afford to have the same amount of cars per capita as in the West (see, for example, Uken, 2011 [online]), the question should be allowed whether the present needs of Germany can only be fulfilled by having statistically more than one car for every two people (Statistisches Bundesamt, 2012d [online]; Statistisches Bundesamt, 2012e [online]). Weert Canzler, scientist at the Wissenschaftszentrum Berlin für Sozialforschung (WZB, Center of Social Sciences Berlin), estimates that the average private car is unused for 23 hours a day (Brenner, 2011a [online]). This means that, in theory, one car could be shared by several people without decreasing the value for the individual which would then reduce the need for resources to build more cars (Brenner, 2011a [online]). Studies have shown that especially young buyers are willing to pay a premium of up to 10% to protect the environment (Bratzel, 2011 [online]). Moreover, the recently offered electric and thus more environmentally-friendly Smarts in some car2go cities are sought by customers and used above average (Daimler, 2012e [online]), which also indicates that sustainability considerations play a role for customers. As mentioned above, carmakers as well consider the environment as a top priority in the near future (Fuß, 2011 [online]). 1.4 Carsharing as a Response to Social Change Considering the aforementioned social changes of customers and carmakers, this study will now analyse which role carsharing can take in responding to these changes.

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1.4.1 Generation Hire Car As the CEO of car2go Robert Henrich puts it, carsharing has become a lifestyle (Bund, 2011 [online]), which is especially true for the young generation. According to official figures of Daimler (2010 [online]) and a study among car2go users conducted by Firnkorn and Müller (2012 [online]), approximately 60% of the scheme’s customers are 18-35 years old; official figures of DriveNow were not available. This is a significant differently customer profile

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compared to traditional carsharing schemes, where two thirds of customers are between 30 and 50 years old (Finanztest, 2012 [online]). A study among young adults not older than 30 years by the marketing research institute Puls showed that 25% have already made use of carsharing (Steiler, 2012 [online]). Moreover, Ernst & Young’s study showed (Fuß & Forst, 2012 [online]) that people in general (50%), but those aged 18-35 in particular (58%), can imagine using carsharing if it was sufficiently available. One reason why commercial schemes may attract especially young customers is the nature of these schemes. Cars can be parked anywhere within the business areas of the respective scheme and not only at fixed stations like in traditional carsharing programmes. This means that customers need to find a car first before they can start their journey and the easiest way to locate the next car is by using a smartphone application that leads customers to the vehicle (Daimler, 2012b [online]; DriveNow, 2012b [online]). However, to some extent this discriminates all those customers that do not possess a smartphone. Therefore Kramper (2012a [online]) and Finanztest (2012 [online]) note that the commercial carsharing schemes of BMW and Daimler are especially made for the internet generation. Taking Ernst & Young’s survey among car owners, 52% of all 18-35 year-olds possess a smartphone, compared to 29% of the total interviewees (Fuß & Forst, 2012 [online]). BMW even stated that 80% of its DriveNow customers possess a smartphone (DriveNow, 2012b [online]). Besides offering the internet generation a native access to their schemes, BMW and Daimler offer additional degrees of flexibility to their customers. On the one hand, the new commercial schemes do not require any particular commitments to certain environmental behaviours (Kramper, 2012a [online]) and are characterised by the absence of monthly fees compared to traditional carsharing schemes (Firnkorn & Müller, 2012 [online]). The possibility to rent cars in a more flexible way, on the other hand, seems to be important to customers as well. 80% of the rentals have been made spontaneously (Solberg, 2009 [online]) and 90% were one-way

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journeys where the destination differed from the starting point (Daimler, 2010 [online]). This is not only advantageous compared to traditional carsharing, where cars have to be returned to specific stations, but it also allows to use commercial carsharing schemes as an additional option to fulfil individual mobility demands. As Corinna Ballweg and Wiebke Ebbing (2011 [online]) from the news magazine Die Zeit note, new technologies are needed to reach the destination cheapest and fastest by using a mix of different systems and transport modes. This so-called multimodality, Kramper (2012c [online]) and Ballweg and Ebbing

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(2011 [online]) believe, is needed to break the dominance of private car ownership. In this regard Daimler (2012a [online]; 2012b [online]) believes that today’s urban populations combine different transport modes such as public transport, taxis, car rental and car2go to create a multimodal service that simplifies urban mobility and increases the quality of life in cities. Henrich, thus, advertises the car2go Smarts as the first ‘own’ public transport (Bund, 2011 [online]) and announced that car2go wants to become part of a connected traffic chain (Daimler, 2012a [online]). Whereas many transport modes are still to some degree island solutions where customers have to pay individually for each service (Ballweg & Ebbing, 2011 [online]; Kramper, 2012a [online]), politicians (Schlesiger, 2011 [online]), nongovernmental organisations (Breitinger, 2010 [online]; Duhr, 2010 [online]) and companies (Daimler, 2011b [online]; Seiwert & Schlesiger, 2012 [online]) work on systems that allow to use all transport modes, for example, with a single customer card. It can thus be assumed that a functioning multimodal transport system will further reduce the need for private cars because customers can choose how to reach the destination cheapest and fastest (Ballweg & Ebbing, 2011 [online]). 1.4.2 Carmaker or Mobility Provider The initial success and the continuous expansion of car2go and DriveNow makes it obvious that there is a market for commercial carsharing. Experts, however, worry that carsharing may sustainably damage carmakers core business, the selling of cars. David Zhao (2010 [online]), automotive expert for the business consultancy Frost and Sullivan believes that carsharing is a double-edged sword to carmakers, because “On [the] one hand, it means sales opportunities… On the other hand, as carsharing vehicles replace personal vehicles, a … decline in new vehicles sales is expected.” Zhao (2010 [online]) believes that this “WILL happen, and vehicle manufacturers need to carefully gauge the potential impact on their total sales.”

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BMW and Daimler are confident that the impact on total sales will be positive. Henrich believes (Bund, 2011 [online]) that car2go is no competition to Daimler’s traditional business because, as he highlights, the average buyer of a new car is older than 50 years compared to car2og where 90% of customers are below 50 years. He rather hopes to attract and bind young people to the brand so when they move to rural areas and decide to have a family, for example, they will purchase a Mercedes. Ian Robertson, Chief Marketing Officer of BMW, also wants to lead potential customers to the brand (Magenheim, 2011 [online]). Only Tony

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Douglas, who markets newly developed mobility services for BMW, acknowledges that companies may not only offer carsharing by choice but also because they want to retain a competitive advantage. His statement reads like ‘If we don’t do it, someone else will do it. If it is not done by big companies, small will do it’ (Schlesiger, 2011 [online]). 1.4.3 Sustainability Concerns Carsharing, traditional and commercial schemes, primarily responds to sustainability concerns in three ways. First, by reducing car ownership. Several studies, which cover traditional carsharing schemes if not mentioned otherwise, have shown that on average several dozens of users share one carsharing vehicle in Germany (Der Blaue Engel, 2010 [online]; Loose, 2011 [online]). Frost & Sullivan estimates “that, on average, each shared vehicle replaced 15 personally owned vehicles” (Zhao, 2010 [online]). In a study among North American carsharing users, Elliot Martin, Susan A. Shaheen and Jeffrey Lidicker (2010, p. 15 [online]) from Berkeley University, California, calculated that each carsharing vehicle has removed 9 to 13 private vehicles and that “the vehicle holding population exhibited a dramatic shift towards a carless lifestyle.” In an evaluation on the impact of carsharing on Swiss customers, the study has shown that car ownership among carsharing users has declined from 40% before joining to 24% after joining a carsharing programme (BFE, 2006 [online]). In Bremen, one of three city states in Germany, a study found that each carsharing vehicle of a traditional scheme substituted nine cars (Der Senator für Bau, Umwelt und Verkehr, 2005 [online]) and have led to a reduction of 1,000 vehicles up until now (Mobil.Punkt, n.d. [online]). In a rare study of commercial carsharing users, Firnkorn and Müller (2012 [online]) found that each car2go vehicle in Ulm had reduced car ownership by 2.3 to 10.3 cars, but has a potential to take 19.2 vehicles off the street in the long term. Second, carsharing responds to sustainability concerns because customers reduce travelled Copyright © 2013. Diplomica Verlag. All rights reserved.

kilometres in cars and increase the usage of public transport. A car owner, for example, will make use of the own car as often as possible because first, he or she already pays high fixed costs and other transport modes will only cause additional variable costs, and second, because drivers tend to neglect other variable costs than those for petrol (Loose, 2011 [online]). In contrast, customers of carsharing schemes have a strong incentive to drive as little as possible because they have to pay directly for each single journey and kilometre (Rodt et al, 2010 [online]). Willi Loose (2011 [online]), CEO of the Bundesverband Carsharing (BCS, Federal

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Association of Carsharing), speaks of the learning curve of carsharing users which leads, after some experience with this transport mode, to the bundling of several trips into fewer because costs are seen as variable costs which can be reduced, for example, by using public transport. Carsharing providers have recognized this connection and started offering discounts for customers of public transport (Daimler, 2012a [online]; DriveNow, 2012c [online]; Finanztest, 2012 [online]). In Switzerland, the above mentioned study has shown that the number of households taking part in traditional carsharing programmes and holding public transport passes, has increased by one quarter after one year (BFE, 2006 [online]). Michael Specht (2010 [online]) from Stern reminds, however, that carsharing can only be beneficial for the environment when customers sell their cars but not when carsharing is used instead of a bike or public transport. And indeed, studies have shown that the availability of carsharing has led to journeys that would not have been made otherwise (BFE, 2006 [online]). Martin and Shaheen (2011 [online]) found the same effect in their study among carless households but note, however, that this increase is relatively small. The average travelled distance among formerly carless households reached the same level to which other formerly car owner households reduced theirs, so that the annually driven kilometres were reduced on average by 1,740 kilometres or 8% per customer (U.S. Department of Transport, 2011 [online]). This reduction benefits the environment. Considering that the average German car drove 14,200 km in 2010 (Kuhnert & Radke, 2011 [online]) and emitted 144 g CO2 per kilometre (Rodt et al, 2010 [online]), the environmental CO2 emissions of each car are slightly more than 2 tonnes. Calculations of CO2 emission savings are rare, but in Switzerland a study concluded that each carsharing customer saved 290 kg of CO2 per year (BFE, 2006 [online]). Considering the Northern American and Swiss studies mentioned above, this would correspond to 8-14% CO2 savings in Germany or 1,140-2,013 kilometres travelled less per customer. Loose worries, however, that this effect may not be achieved in commercial Copyright © 2013. Diplomica Verlag. All rights reserved.

schemes because the price calculation which is based on time units, gives, from his point of view, an incentive to use cars even for small trips (Lamparter, 2010 [online]). The third way how carsharing responds to sustainability concerns is by providing cars that are more environmentally friendly than the average car in terms of their CO2 emissions. By emitting fewer CO2 emissions, carsharing can directly affect the climate positively and help to lower emission levels in German cities. The latter is a persistent problem (UBA, 2012

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[online]) despite the fact that the general fuel consumption in Germany has decreased consistently, reaching 7.5 litres per 100 km in 2009 (BMVBS, 2011 [online]) and thus lowered the average CO2 emissions of a German car to 144g per kilometre (Rodt et al, 2010 [online]). Because carsharing programmes use small cars which they replace after as early as 18 months (Finanztest, 2012 [online]), the average car fleet of carsharing organisations emits only 132.4 g CO2/km (Loose, 2011 [online]). The fleet of Smarts in Daimler’s car2go programme, however, tops this by emitting a mere 97 g CO2/km (car2go, n.d. [online]); BMW has not released official figures of its fleet. While Daimler’s figures are certainly impressive, assessing the full CO2 impact of carsharing vehicles “require a complex analysis using … lifecycle assessments … and well-to-wheels balances“ (Firnkorn & Müller, 2012, p. 277 [online]), an assessment which has not been carried out yet (Firnkorn & Müller, 2012 [online]). There seems to be a consensus in the literature, though, that carsharing vehicles reduce CO2 emissions either by reducing the travelled kilometres or by increasing the usage of the even more environmentally-friendly public transport. Further reductions, moreover, can be achieved by using electric vehicles (EVs) which use electricity produced from renewables, such as in Daimler’s case (Daimler, 2012e [online]). Daimler’s electric Smarts are offered at the same price as petrol Smarts despite that they cause increased costs for battery, charging times and maintenance (Daimler, 2012e [online]). One seventh of car2go’s fleet is already electric (Daimler, 2012e [online]) and Frost & Sullivan estimates that “EVs will be increasingly leveraged by … carsharing programs [so that] By 2016, one in five new shared vehicles … is expected to be an EV” (Zhao, 2010 [online]). Zhao (2010 [online]), among others, believes that this “means huge business opportunities for EV manufacturers.” Ferdinand Dudenhöffer, head of the CAR Center of the University Duisburg-Essen, expects that increased demand will not only come from carsharing programmes itself but that the use of electric vehicles in carsharing schemes may be a key factor to promote this new technology (Herz, 2011 [online]). In a study, where people tested

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electric vehicles and were asked about whether they liked the tested vehicles, 71% stated they would consider electric vehicles for their next purchase (Herz, 2011 [online]). And indeed, Johan Jansson (2011 [online]) from the Umeå School of Business, Sweden, supports this notion that the use of this new technology may subsequently lead to an increased demand. His study found that consumers in general become accustomed more easily to innovative products, when they can test them first and have a positive experience (Jansson, 2011 [online]). This effect is not only useful for introduction of electric vehicles, but as this study

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will suggest in part three, it could also be used for the introduction of driverless vehicle technologies as a way to benefit vehicle sales Regarding the use of electric vehicles in carsharing schemes and its possible effects on sustainable mobility, however, another aspect needs to be highlighted. The current lack of sufficiently available charging stations is seen as one the biggest obstacles for the introduction of electric vehicles (Fuß, 2011 [online]). The increased use of electric vehicles in carsharing schemes will help to build up the necessary infrastructure and thereby accelerate, Daimler (2011b [online]) believes, the introduction of EVs in general. 1.5 Limitations of Carsharing This section will look at two main limitations of current commercial carsharing business models. Both, it will be shown in part three, could partially be offset by the suggested concept of integrating driverless cars in carsharing schemes. 1.5.1 Parking Customers of commercial carsharing schemes benefit from the possibility to park their cars not only at specific stations such as reserved spaces on private areas or in public streets as in traditional carsharing schemes, but also alongside public roads (Lawinczak & Heinrichs, 2008 [online]). Because carsharing is just one of several stakeholders with an interest in using public spaces (Firnkorn & Müller, 2012 [online]), communities have to decide how to increase the attractiveness of carsharing without risking displeasing local residents. This leaves them with two problems. First, in order to offer their customers short waiting and seeking times at the individual destinations, carsharing schemes need an oversupply of parking spaces (Specht, 2010 [online]) which fulfil the requirements of customers, such as that the parking lot is close to their residence, directly accessible and easy to find (Lawinczak & Heinrichs, 2008 [online]).

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Moreover, the community is also interested in avoiding ‘parking-slot seeking traffic,’ which not only costs time and is stressful for the individual but also increases noise and exhaust emissions for the community (Senatsverwaltung für Stadtentwicklung, 2006 [online]). The problem is, according to Lawinczak and Heinrichs (2008 [online]) that there are at best few parking spaces available in densely populated city areas, which makes it often impossible for carsharing companies and their customers to rent and find, respectively, suitable parking spaces in close proximity to their customers.

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Second, communities that want to create parking spaces for carsharing schemes cannot easily do so. A lacking uniform federal regulation makes currently every created carsharing parking lot legally contestable because according to sec. 41 in combination with sec. 283 of the Straßenverkehrsordnung (StVO, Highway Code), parking spaces can only be reserved for taxis, disabled people or residents (Bundesministerium der Justiz, 2010 [online]; Lawinczak & Heinrichs, 2008 [online]). Several attempts to pass a law which would equate carsharing with the abovementioned stakeholders, however, failed so far because of the fear, carsharing could be put at an advantage over hire car (Brenner, 2011b [online]). Communities which do not want to wait for legal certainty found two ways to bypass existing legislation: granting, like Bremen, special usage (Sondernutzung) to carsharing companies, or partially confiscate public spaces (Teileinziehung), like Berlin did (Lawinczak & Heinrichs, 2008 [online]). Despite the fact that both solutions are legally contestable, Bremen and Berlin are the only communities that were able to increase carsharing parking lots significantly (Brenner, 2011b [online]). However, even in Berlin the proceedings to apply for parking spaces take between 6-9 months which is seen as too long by respective companies (Lawinczak & Heinrichs, 2008 [online]). Another issue arises, once the parking spaces are established. A study by Lawinczak and Heinrichs (2008 [online]) observed unauthorised parking in 44% of all cases where no carsharing vehicle was parked. It comes thus to no surprise that customers desire more parking spaces (Solberg, 2009 [online]) and companies are in a competition for each slot that has been established by communities (Schlesiger, 2011 [online]). Henrich even stated in an interview that the refusal of local governments to establish parking lots is a major obstacle to the expansion of car2go (Specht, 2010 [online]). 1.5.2 Availability The availability of vehicles in carsharing schemes is limited by three aspects.

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First, the number of parking spaces is low which limits the number of vehicles. While at the moment the slowly increasing number of supplied carsharing vehicles meets the demand, it remains questionable whether carsharing providers can offer enough parking lots to meet future demand of their vehicles in the middle to long term. A corresponding law could have the potential to mitigate, but not entirely resolve this problem.

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Second, the business area of carsharing programmes is limited. This means that several suburbs can be reached by cars but vehicles cannot be left there (Kramper, 2012a [online]). Customers that live in residential areas outside of urban centres can therefore not make use of carsharing schemes to drive home and leave the car in their respective neighbourhood. Third, the willingness of people to walk to the next available car is limited. A study by BCS has shown that on average people do not want to walk further than 700 metres to find a car. This, however, can increase the costs for companies in terms of having to provide more cars and parking lots. The current part has shown that traditional carsharing persistently grew over the past two decades and that commercial carsharing schemes grew especially fast in the past years. While beneficial for the environment, carsharing can be expected to grow even further in the future due to observable social and business change. Some of the limitations of current carsharing programmes might pose obstacles to further growth, but could be offset by the use of driver-

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less vehicles (see below).

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Part2:DriverlessVehicles The fact that you’re still driving is a bug, not a feature. Anthony Levandowski Business Lead on Google’s Self-Driving Car Project 2.1 Introduction The part at hand is going to assess the second component which is required for the proposed concept, driverless vehicles. The background section gives an historical overview of past and current developments. It shows that this technology has seen major advances within the last eight years and indicates the feasibility of reaching marketability eventually. The following section concerns itself with traffic accidents, a major societal issue that can be tackled by the widespread use of driverless vehicles, for example, in carsharing schemes. Because the vast majority of car-related traffic accidents are caused by respective drivers, this section will first look at the main causes for such accidents, which are [1] distractions, [2] deliberate non-compliance with traffic regulations, and [3] physical deficits in the elderly. Afterwards, the study continues to give an overview of traffic accidents in Germany, i.e. the consequences of the aforementioned deficits, and the economic costs caused by traffic accidents. Besides looking at the general population, this section will, as in part one, especially focus on young people because it is them who demand new mobility services and who make use of carsharing the most. However, because of a slow demographic change towards an aging society in Germany, which could eventually increase the use of carsharing among the elderly, the analysis will also include this age group. The subsequent section analyses automation in passenger vehicles as a response to car-related traffic accidents. It starts by introducing first, driver assistance systems and second, advanced Copyright © 2013. Diplomica Verlag. All rights reserved.

driver assistance systems, to show that these technologies were developed in order to tackle certain deficits of drivers and investigates how these systems are accepted by users and what, especially German customers, expect of these systems. The last section of this part will investigate the current developmental state of driverless vehicle technologies in order to understand problems, which have to be overcome before the

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introduction, limitations it may encounter due to its system limitations, as well as its potential to improve traffic safety. 2.2 Background Shortly after the introduction of the first motor car at the turn of the 20th century (Bird, 1960), driver assistance systems such as speed indicators were introduced to support drivers with their driving task (Becker, 2012 [online]). General Motors presented the idea of an autonomous vehicle for the first time to a wider public at the 1939 World’s Fair exhibition (Vanderbilt, 2012b [online]). In 1953, GM and the Radio Cooperation of America developed a scale model automated highway system (AHS) which was supposed to control cars by wires in roads (Wetmore, 2003 [online]). Since then “a few isolated systems have been built” (Wetmore, p. 18, 2003 [online]) but turned out to require extensive control and never worked reliably (Wetmore, 2003 [online]). In the 1960s and 1970s a team of Stanford University equipped a buggy with a video camera and image processing capabilities which in 1978 eventually “crossed a chair-filled room without human intervention in about five hours” (Vanderbilt, 2012b [online]). In the 1980s and 1990s Ernst Dickmanns achieved great distinction with his experiments in Germany and is since then regarded as pioneer of autonomous cars (Vanderbilt, 2012b [online]). His vehicles, usually transporters fully packed with computers and sensors, were capable of driving autonomously in real-world traffic on German motorways (Vanderbilt, 2012b [online]). Despite the success, limited processing power soon emerged as one of the biggest obstacles (Davis, 2006 [online]). Dickmanns referred to Moore’s Law in 1996, proclaiming that it would take another decade until sufficient processors were available and, as Joshua Davis (2006 [online])), author from Wired magazine notes, “He was right, and everyone knew it.” In order to achieve the U.S. congressional goal that “by 2015, one-third of the operational ground combat vehicles are unmanned” (National Defence Authorization, 2000 [online]), the

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Defense Advanced Research Projects Agency (DARPA) decided in 2004 to spur innovation in the field of autonomous vehicle technologies by offering “$1 million to anyone who could build a self-driving vehicle capable of navigating 300 miles of desert” (Davis, 2006 [online]). The “prize [for the event dubbed Grand Challenge 2004] went unclaimed as no vehicles were able to complete the … route,” with the best team completing 7.3 miles (DARPA, 2007 [online]). One year later, DARPA doubled the prize money and 5 teams out of 23 completed the Grand Challenge 2005, a 132-mile race through the Mojave Desert (DARPA, 2005

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[online]). In 2007, DARPA hold the last event of this kind, the so-called Urban Challenge which “represented the first full-scale demonstration of autonomous vehicles operating together in traffic” (DARPA, p. 4, 2008 [online]). Cars had to drive on unknown roads, consider traffic signs, park independently, filter into the traffic, overtake other cars (Bartels, Ruchatz & Brosig, n.d. [online]) and share the road with more than thirty professional human drivers (Stewart, 2007 [online]). Six out of eleven cars finished the competition successfully, with Stanford’s team finishing second (DARPA, 2008 [online]). Whereas German carmakers such as Audi (Squatriglia, 2010a [online]), BMW (Boeriu, 2011 [online]) and Volkswagen (Bartels, Ruchatz & Brosig, n.d. [online]), suppliers such as Continental (2012 [online]) and research projects such as the European Highly Automated Vehicles for Intelligent Transport (HAVEit, 2011 [online]) are explicitly working on driverless vehicle technologies, it is the search engine provider Google who has announced the biggest advancements. In October 2010, Sebastian Thrun, formerly team leader of the Stanford Racing Team which won DARPA’s Grand Challenge 2005 and became second in DARPA’s Urban Grand Challenge, announced for his new employer Google that its fleet of autonomous vehicles had already travelled more than 225,000 km on public roads (Thrun, 2010 [online]). In August 2012, this number had more than doubled, while “there hasn’t been a single accident” (Urmson, 2012 [online]). The different technologies of autonomous systems work very similar and have been improved since DARPA’s Grand Challenge competitions. In general, Nidhi Kalra, James Anderson & Martin Wachs (2009 [online]) from the RAND corporation note, autonomous driving is based on functions categorised as sensing, planning, and acting. After a system has gathered information about the external environment (sensing), it applies specific algorithms (planning) to “create a set of actions that bring the system closer to its objective” (Kalra, Anderson & Wachs, p. 7, 2009 [online]) and executes these plans subsequently (acting) (Kalra, Ander-

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son & Wachs, 2009 [online]). However, it is important to acknowledge that there is a continuum between a purely humandriven and completely autonomously-driven vehicle which has implications for the further study. Several, very similar, suggestions have been made to distinguish the different levels of automation, though no uniform definition, let alone any standard, exists. The project group Automation: Legal Consequences of Increasing Vehicle Automation of the Bundesanstalt für Straßenwesen (BASt, Federal Road Research Institute) proposes the stages [1] driver only,

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[2] assisted [3] semi-automated, [4] highly automated, and [5] fully automated (Rauch et al, 2009 [online]), with Bryant Walker Smith (2012e [online]) noting that these distinctions “are not absolute.” Table 2 shows the results of the project group. Each stage, beginning from [2] assisted, is supposed to support the driver with the driving task to make driving saver, either by mitigating the worst outcomes of accidents or by preventing them at all. The next section will continue to analyse reasons for and results of traffic accidents. 2.3 Social Issue Traffic Accidents 2.3.1 Background Road safety is seen as a major societal issue (European Commission, 2012c [online]). According to the United Nations Economic Commission for Europe (UNECE, 2012 [online]), 1.3 million people die and up to 50 million more are injured in traffic accidents each year. Despite the fact that over 90% of global fatalities (WHO, 2009 [online]) and around 80% of global injuries in traffic accidents occur in low and middle-income countries, which possess less than half of all registered vehicles (UNECE, 2012 [online]), high-income countries are not spared from the problem. For example, in 2010 1,473,443 people were injured and 31,029 lost their lives in 1,114,980 traffic accidents in the European Union (European Commission, 2012a [online]). With 49 road deaths per 1 million inhabitants, Germany had to suffer a considerably higher number of traffic deaths than the worldwide best-performing country Sweden (33 road deaths), but still less than the European average of 61 (European Commission, 2012b [online]). Before more detailed statistics for Germany will

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be presented, the following section will now turn to main causes of traffic accidents. Nomen clature

Descriptionwithdegreeofautomationand expectationofthedriver

Exampleofasystem characteristic

 Driveronly

 Driverdrivespermanently(duringthewhole journey),controllingthelongitudinal(accelerat ing/decelerating)andtransverseguiding (steering)

 Nosystemthatintervenesin neitherlongitudinalnortrans verseguiding







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Assisted

DrivercontrolspermanentlyEITHERlongitudinal ORtransverseguiding.Therespectiveother taskisassistedbythesystemwhich[1]the driverhastomonitorPERMANENTLYand[2] wherethedriverneedstobecapableof overwritingthesystemcompletelyatanytime

AdaptiveCruiseControl(ACC): longitudinalguidingwithadaptive headwaycontrolandspeed regulation;Parkingassistant: transverseguidingbyparking assistant,automaticsteeringinto theparkingslot,drivercontrols longitudinalguiding







Partly automated

ThesystemcontrolslongitudinalANDtrans verseguiding(foracertaintimeperiodand/or inaspecificsituation)which[1]thedriverhas tomonitorPERMANENTLYand[2]wherethe driverneedstobecapableofoverwritingthe systemcompletelyatanytime

TrafficJamAssistant:automatic longitudinalandtransverse guidinguptoacertainvelocity whichthedriverhastomonitor permanentlyandwhichrequires himtobecapableofresuming controlatanytime







Highly automated

Thesystemcontrolslongitudinalandtransverse guidingforacertaintimeperiodinspecific situations,which[1]thedriverdoesNOThave tomonitorpermanentlybutwhere[2]the drivercanresumecontrolafterhavingbeen askedbythesystemandafterasufficienttime, while[3]thesystemisawareofitslimitations andisnotcapabletoencompasstheminimum riskstateoutofeveryinitialsituation.

TrafficJamChauffeur:automatic longitudinalandtransverse guidinguptoacertainvelocity whichthedriverdoesnothaveto monitorpermanentlyandwhich requireshimtobecapableof resumingcontrolafterasufficient timereserve





Fully automated

Thesystemcompletelycontrolslongitudinal andtransverseguidinginadefinedusecase. Thedriverisnotrequiredtomonitorthe system.Beforeleavingtheusecase,thesystem asksthedrivertoresumecontrolaftera sufficienttime,and,incasenocontrolistaken, thesystemswitchesintotheminimumrisk state.Thesystemknowsofallofitslimitations andcanswitch,ineverysituation,intothe minimalriskstate.

MotorwayPilot:automatic longitudinalandtransverse guidinguptoacertainvelocity whichthedriverdoesnothaveto monitorandwhich,incasethe driverdoesnottakecontrolafter beingaskedbythesystem,brings thevehicletoahalt







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Table2.Proposeddefinitionsfordifferentstagesoftheautomationofthedrivingtask AccordingtoNadjaRauchetal(2009[online])

2.3.2 The Role of the Driver in Car-related Traffic Accidents Because technical defects and external factors such as defect roads play a minor role in causing traffic accidents (Statistisches Bundesamt, 2012a [online]), this section will concentrate on the role of drivers in car-related traffic accidents. In this regard, the literature distinguishes in general between three major sources of human-caused accidents: [1] distractions,

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[2] the deliberate non-compliance with traffic regulations such as driving at unsuitable velocities or under the influence of alcohol or drugs, and [3] physical deficits that increase with age and negatively impact the driving task (Kubitzki, 2011 [online]). Because distractions are widely believed to cause 90% of all accidents (Kubitzki, 2011 [online]), this study will now continue to investigate this aspect of traffic accidents before looking at the other two causes of traffic accidents. 2.3.2.1 Distractions In general, every distraction is suboptimal for a driver because a new task shifts part of the attention away from the original driving task (Kubitzki, 2011 [online]). If several tasks compete for the attention of a person, however, one task will be put into the centre of attention and all others will receive fewer capacities due to the functioning of the human brain (Kubitzki, 2011 [online]). According to a study of the insurance company Allianz, the author Jörg Kubitzki (2011 [online]) summarises the literature and writes that one way to categorize distractions is by distinguishing their source, which can be localised [1] spatially (does the distraction lie inside the car, such as a conversation with a passenger, or outside of the car, such as a billboard at the roadside), [2] mentally (is the cause of the distraction internal, for example, is the driver angry, or is the distraction caused externally, for example, by an argument with another passenger) and [3] technologically (is the distraction device-related, such as using a mobile phone, or is it non-device related, such as smoking a cigarette). These categorizations help to understand where, how and why traffic accidents are linked to distractions and what can be done to mitigate risks. For example, when considering the spatial occurrence of accidents, Mc Evoy et al. (2007, cited in Kubitzki, 2011 [online]) found that more than 90% of accidents were caused by distractions within the car, such as drinking, eating or smoking. A study of BASt (2012a [online]) found that 80% of drivers acknowledged that they would engage in non-driving related activities. The Allianz, too, asked drivers

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how often they would engage in non-driving related activities, the results of which can be found in the following table.





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Activities,cardriverssaidtheywould engageinwhiledrivingin%  Sneeze,cough,feelitchyorblowtheirnose Smoke Eat Listentomusicexcitedly Listentointerestingradiofeatures Havestrongemotionsduetointense conversationsorthoughts  

Never

Rarely

Occa sionally

Often

Very often

 21 84 43 26 14 52

 39 3 30 24 19 33

 33 4 20 24 31 11

 6 6 6 18 29 3

 1 3 0 8 6 0









Table3.Activitiescardriverssaidtheywouldengageinwhiledriving AccordingtoresearchoftheAllianz(Kubitzki,2011[online])

Although these results need to be treated with caution because of their non-representative character and the subjective assessments of the interviewees, they indicate that distractions are ubiquitous. Despite their potential risk, however, only one quarter of drivers in the BASt study believed that their activities were distracting and less than 10% of drivers thought that distractions outside of the car are dangerous (BASt, 2012a [online]). Because these figures are subjective, traffic researchers create risk rankings to objectively evaluate which activities and distractions pose what risks. The following table shows the Risk Ranking New Zealand Focus Group Research, the Risk Ranking Regan, and the Allianz Risk Ranking. These risk rankings have in common that distractions were often linked to mobile phones or smartphones, either caused by making or answering phone calls, sending text messages or emails, or using the internet. As Kubitzki (2011 [online]) notes, it may be easy for a person to handle a phone call and the driving task at the same time, but when the traffic situation changes suddenly, it may require the full attention of the driver. For this reason, German legislation prohibited phone calls without a hands-free set in 2001 (DEKRA, 2012 [online]) and also prohibited to use a smartphone or similar devices while driving, regardless of the Copyright © 2013. Diplomica Verlag. All rights reserved.

function which was used (Kubitzki, 2011 [online]). Nonetheless, offences against these regulations almost doubled from 284,000 in 2005 to 450,000 between in 2011, with more

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

RiskRankingNewZealandFocus GroupResearch

RiskRankingRegan2005

RiskRankingAllianz

1.Email/internet(when available/used)

1.Takeacall







2.Texting,cellphone– longcall, answeringhandheld,rolling cigarettes,selectingaCD, reachingforitemunderseat

2.Mobilephone– textmessag ing

2.Callsomeone

 1.Disruptivepassengers,sober driverwithdrunkteens,reading amap,petsunrestrained, changingclothes,readingand writing







3.Answeringhandsfree,eating drinking,cellphone–shortcall

3.Mobilephone–conversa tion/talking(handsfreeand handheld)

3.Behaviourofotherroadusers







4.Reachingforitemnextto driver,nondisruptivepassengers

4.DVDPlayer(ifportableand poorlylocated)

4.Peopleoreventsoutsidethe car,nontrafficrelated



5.Adjustingclimatecontrol, 5.Conversationwithpassengers restrainedpets,doingmakeupor (ifdriverisyoungorold) shaving

5.Intensivetalkwithpassenger









6.Routenavigation(ifpoorly designed)

6.Takecareofchildren/babies









7.Cassetteplayer/CDplayer

7.Excitingfeelings/experiences









8.Radio

8.Signs/billboards,nontraffic related

9.Climatecontrols

9.Countryside,buildings, landmarks



 







10.Eating/drinking

10.Writingatextmessageor email









11.Smokingrelated

11.Lookingforitems(seeking, grasping,bendingdown)





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12.Listeningtomusicexcitedly











13.Beingimmersedinthoughts











14.Smoking







Table4.RiskRankings AccordingtoCraigGordon(2005[online]),Kubitzki(2011[online])andReagon(citedinKubitzki,2011 [online])



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than 40% of these offences committed by people younger than 35 years (KBA, 2012a [online]). Whereas the increase of offences may merely reflect the current strong shift on the telecommunication market towards mobile and smartphones (Bundesnetzagentur, 2012 [online]), this trend is especially problematic in regard to accidents. Studies have shown that the mental, cognitive and emotional distraction of a phone call in a car cannot be compared to real life conversations, whether a hands-free set is used or not, and consumes more brain capacity than conversations to physically present passengers (Kubitzki, 2011 [online]). How prevalent the use of mobile phones in cars is, shows the result of the Allianz survey in the following table.



Cardrivers

 notpossessingahandsfreesetand answeringphonecalls(in%) makingphonecalls(in%)  possessingahandsfreesetand answeringphonecalls(in%) makingphonecalls(in%) 

Never

Rarely

Occa sionally

Often

Very often

 68 72

16 22

22 19

6 5

3 3

0 1

19 23

 31 31

21 18

13 6 

Table5.Howmanycardriversanswerandmakephonecallswhiledriving AccordingtoresearchoftheAllianz(Kubitzki,2011[online]) Note:shareofnewcarsequippedwithahandsfreeincreasedfrom24%in2008to30%in2012 (DAT,2012[online]).

 Another trend linked to the proliferation of mobile devices is sending text messages and emails. The amount of sent text messages have risen since 2005 by almost 300% to 55 billion Copyright © 2013. Diplomica Verlag. All rights reserved.

in 2011, and the share of frequent internet users, defined as having used the internet at least once in the last three months, increased in the same time period by nearly 1,200% to 28.6 million (Bundesnetzagentur, 2012 [online]). A representative study of the Allianz (Kubitzki, 2011 [online]) shows that these trends affect behaviour of car drivers: 20% of drivers admit to write and 33% admit to read SMS or emails while driving, with young drivers (18-24 years) writing (25%) and reading (40%) messages above average.

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

The recent technological upgrade of cars has also led to new sources of distractions, for example, from satellite navigation systems or board computers. The equipment rate of new .

cars with satellite navigation and board computers has increased within the last four years from 33% to 42% and 59% to 68% respectively (DAT, 2012 [online]). The Allianz survey (Kubitzki, 2011 [online]) shows again that these devices are commonly used while driving as well.

 

Cardrivers  admittingtosetupthesatellitenavigation whiledrivingin%













Never

Rarely

Occa Often sionally

Very often

 43

 25

 18

 13

 1











admittingtotakeareadingfromthesatellite 25 16 30 22 7 navigationwhiledrivingin%  Table6.Howmanycardriverssetupandtakeareadingfromtheirsatellitenavigationwhile driving AccordingtoresearchoftheAllianz(Kubitzki,2011[online])

In general, Kubitzki (2011 [online]) notes, it needs to be highlighted that speech recognition will not be an answer to the information overflow because each new task, no matter whether it is operated by hand or speech, requires certain mental processes and still has the potential to distract the driver. 2.3.2.2 Deliberate Non-Compliance with Traffic Regulations The problem of non-compliance is problematic insofar because only if road users abide by traffic regulations and laws, behaviour of single participants becomes predictable for other road users (BMVBS, 2011 [online]; KBA, 2012a [online]). The two most common offences Copyright © 2013. Diplomica Verlag. All rights reserved.

against existing regulations are driving too fast and driving under the influence of alcohol or drugs (Kubitzki, 2011 [online]). Regarding the former, the WHO (2009, p. 18 [online]) point out that a “5% increase in average speed leads to an approximately 10% increase in crashes that cause injuries, and a 20% increase in fatal crashes.” In general, “for a properly restrained motor vehicle occupant the critical impact speed is 50km/h (for side impact crashes) and 70 km/h (for head-on

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39

crashes)” (OECD & ITF, p. 15, 2008 [online]). For pedestrians, however, “the chances of survival diminish rapidly at speeds greater than 30km/h” (OECD & ITF, p. 15, 2008 [online]). In this regard it is important to note that especially young people are prone to drive at inappropriately high velocities. In general, the reasons for this behaviour is linked to certain motives related to young age, such as the readiness to assume risk (DEKRA, 2012 [online]) or the desire to impress peers (Kubitzki, 2011 [online]), but also the deficit of driving experience (Heißing et al, 2011 [online]). The second common way of non-compliance with traffic regulations is by driving under alcohol or illicit drugs. In Germany it is, according to section 24a of the Straßenverkehrsgesetz (StVG, road traffic act), not allowed to drive with blood alcohol concentrations (BAC) of more than 0.5‰ (Bundesministerium der Justiz, 2011 [online]), nor is it allowed, according to section 315c and 316 of the Strafgesetzbuch (StGB, criminal code), to drive under the influence of any other illicit drug (Bundesministerium der Justiz, 2012b [online]). In a study for the European research project Driving under the Influence of Drugs, Alcohol and Medicines (DRUID), Sjoerd Houwing, Marjan Hagenzieker and René Mathijssen (2011 [online]) sought to find how prevalent certain drugs in drivers were. Although not containing German participants due to legal regulations, their study showed that drink and drug-driving is not uncommon among the driving population. Observed prevalence rates of BACs over 0.1‰, for example, were as high as 8.59% in Italy. A dangerous finding by another DRUID study is that “Drunk drivers often think that alcohol does not impair their performance… [while] Drug consumers believe that drugs may improve their driving” (Heißing et al, p. 13, 2011 [online]). However, when evaluating the driver’s risk of being involved in an accident with road deaths in France for the DRUID project, Blandine Gadegbeku et al (2010 [online]) found that positive detection of cannabis was associated with an odds rate of 1.89, meaning that car drivers having consumed cannabis were 1.89 as likely as sober drivers to be involved Copyright © 2013. Diplomica Verlag. All rights reserved.

in an accident with road deaths. The odds rate was found to be 8.39 and 13 for BACs below 0.1 ‰ and between 0.8-1.2 ‰ respectively. When alcohol was combined with other drugs, the ratio increased to 47.7, for a drug-drug combination the odds rate was 35. These results imply that drink and drug-driving significantly increase the risk to be involved in an accident with road fatalities. However, the study also found that “The odds ratios … for amphetamines, cocaine and opiates are not significantly different from 1 which indicates that the

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

probability of being responsible for a fatal crash is not increased” (Heißing et al, p. 12, 2011 [online]). 2.3.2.3 Physical Deficits in the Elderly Another main cause of human-caused traffic accidents can be seen, admittedly to varying degrees, in the aging process of the human body which eventually leads to the natural degradation of physical abilities needed for the driving task (DEKRA, 2012 [online]). This degradation is not directly linked to the calendric age but to the bio-functional age of a person, which depends upon individual living conditions and the everyday life (DEKRA, 2012 [online]). A report by the German insurer DEKRA (2012 [online]) notes, that the elderly suffers from decreasing acuity of seeing and hearing, but are also affected on the psychofunctional level, i.e., on aspects of attention and memory. The selective attention, i.e. filtering relevant information, as well as the parted attention, i.e. processing several parallel information, requires more time and can lead to exhaustion more easily for the elderly. Moreover, the speed of processing information and the reaction and orientation time can be negatively affected. Considering that the German people in general are aging (Statistisches Bundesamt, 2012f [online]; see table 7), this may become an increasingly significant factor for traffic safety in the future. 2.3.3 Traffic Accidents in Germany 2.3.3.1 General Overview After having looked at reasons for traffic accidents, this section will now look at statistics for Germany. The problem is, however, that the police which is registering traffic accidents is not required to note down whether the respective accident had been caused by a distraction, despite the fact that distractions are thought to be the major source of traffic accidents. This makes it impossible to link some of the aforementioned reasons, which cause traffic accidents, directly to the result, the actual traffic accidents. However, it can be doubted whether Copyright © 2013. Diplomica Verlag. All rights reserved.

drivers would respond truthfully when asked whether they were distracted because, for example, they could risk losing their insurance coverage. Thus the statistics in this section will represent the results of traffic accidents rather than the distraction causes which may have led to them. In general, the number of traffic accidents in Germany, which does only include those accidents that were reported to the police (Kubitzki, 2011 [online]; Statistisches Bundesamt,

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2012 [online]), is quite stable. However, while 505,535 people were injured and 11,300 lost their lives in 2,311,466 traffic accidents in 1991 and despite the fact that the number of traffic accidents stayed pretty stable (2,361,457 traffic accidents in 2011), the number of injured people declined by more than a fifth to 392,365 and the number of road casualties by almost two thirds to 4,009 deaths (Statistisches Bundesamt, 2012g [online]). According to the Statistisches Bundesamt (StBA, federal statistical office) (Statistisches Bundesamt, 2012 [online]), the police reported that on average 1.3 errors had been made in each traffic accident and that the largest share of errors (65.5% or 254,120 errors) had been made by car drivers. This figure reflects that cars are still the predominant transport mode, which is also reflected by figures showing that 49.5% of traffic deaths and 54.9% of injured people were a driver of or a passenger in a car (Statistisches Bundesamt, 2012 [online]). The following section focusses on statistics on urban roads, because the proposed concept in part three suggests to alter commercial carsharing schemes for urban areas. 2.3.3.2 German Urban Areas in General The majority of traffic accidents (70%) in which people were injured in 2011 was caused by car drivers, who caused 83% of all accidents with motor scooters and motorbikes, and 75% and 76% with bicyclists and pedestrians respectively (Statistisches Bundesamt, 2012a [online]). Two thirds of accidents were caused by erratic behaviour in regard to right of way (21.6%), distance (13.9%), turning (13.73%), pedestrians (7.9%) and velocity (7.8%) (Statistisches Bundesamt, 2012a [online]). Figure 1 (Statistisches Bundesamt, 2012a [online]) shows how many accidents with traffic injuries were caused by car drivers and how many people died comparatively to total road deaths, presenting categories which represent 95% of total accidents. Reflecting the high safety standards of cars, it shows that even though car vs. car accidents make up more than 40% of all accidents were people were injured, they only caused 12.5% of the total deaths Copyright © 2013. Diplomica Verlag. All rights reserved.

that occurred. Compared to that, the most vulnerable road users are pedestrians. While accidents in this category only represent 13.4% of total accidents, almost every second death (48%) occurred in this category. 



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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

Figure1.Howoencarscausedaccidentswithotherroadusersandhowmanypeopledied comparavely

60% 50% 40%

shareof traffic accidents

30% 20% 10% 0%

 Whereas the chart shows that car drivers had to suffer only a relatively small share of traffic deaths compared to the absolute number of accidents, it is important for this study in regard to current and possible future target groups of carsharing that most road fatalities and seriously-injured car drivers, the latter is defined as a person who is treated in a hospital for more than 24 hours (BMVBS, 2011 [online]), were male and either young (aged 18-24) or old (above 64), see figure 2 (Statistisches Bundesamt, 2012 [online]).

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Figure2.Shareofseriouslyinjuredcardriversintotalpopulation

90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

shareofcarsoftotalaccidents male





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Figure 3 shows (Statistisches Bundesamt, 2012a [online]) that the reason for this result is that most accidents are caused by the young and elderly. Accidents caused by inappropriately high velocities as well as too short distances between cars decrease significantly with age which can be explained by the increasing maturity of drivers (DEKRA, 2012 [online]). Traffic accidents that occurred in complex situations, however, such as applying right of way rules, turning at diversions or looking out for pedestrians, i.e. situations that require to keep an overview of many road users and react quickly to changing conditions, increased significantly with age, which could be linked to the increasing physical deficits of the elderly (DEKRA, 2012 [online]). Figure3.Accidentsper1,000populationanderraticbehaviourcausingthem 250 200 150 100 50 0

mistakerelatedtorightofway

wrongdistancetopreviouscar

mistakerelatedtoturning

wrongbehaviourtowardspedestrians

inappropriatevelocity





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These figures indicate that there is a huge potential do increase road safety. As shown in the next section, the proposed concept may have the potential to contribute to an increased road safety not only for the car drivers and passengers themselves but also for other road users such as pedestrians or bicyclists.

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

2.3.3.3 German Urban Areas in Regard to Carsharing Despite the fact that no official figures regarding accidents of carsharing customers are available, some other aspects apart from age and sex of carsharing customers may also be specifically important for the risk of carsharing customers of being involved in an accident. First, figure 4 shows that many accidents in urban areas occur when carsharing is used the most: in the commuter traffic in the evening (Daimler, 2010 [online]). Second, in a study of Swedish car drivers Jim Langford, Rob Methorst and Liisa HakamiesBlomqvist (2006 [online]) found that with a lower annual distance driven, crashes per million have increased significantly. This could mean that with increasing customer numbers who mainly rely on carsharing vehicles, accident numbers may be on the rise due to decreasing experience. Figure4.Distributionofaccidentsinwhichpeoplewereinjured(withincitylimits)overaweek

3500 3000 2500 2000 1500 1000 500

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0

Monday Friday

Tuesday Saturday

Wednesday Sunday

Thursday

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Third, while it is prohibited to use carsharing vehicles under the influence of alcohol or illicit drugs, it should not be neglected that 3.6% and 0.3% of all accidents are caused by drunk drivers and drivers under the influence of illicit drugs respectively (Statistisches Bundesamt, 2012 [online]). Interesting in this regard is that a DRUID project among drug users in Germany has shown that the probability of driving under influence of drugs rises for larger cities (Heißing et al, 2011 [online]) while carsharing is only available in the largest cities. Forth, Kubitzki (2011 [online]) notes that studies have shown that the probability to use technology is higher in dense traffic, which could also increase the risk of traffic accidents due to distractions. Fifth, again Kubitzki (2011 [online]) notes, drivers that have to get used to new cars, for example, in car hire or carsharing schemes, are at increased risk of distractions because they may not be familiar with the interior and settings of these vehicles. These points highlight that with rising numbers of carsharing customers the risk to be involved in traffic accidents will inevitably rise. Using driverless vehicles in carsharing schemes, as suggested in the proposed concept of this study, has the potential to mitigate this trend substantially. 2.3.4 Economic Costs of Traffic Accidents Deaths, disabilities and injuries cause not only great emotional stress to millions of families (OECD & ITF, 2008 [online]), but the United Nations (n.d. [online]) also estimates “that global losses due to road traffic injuries total $518 billion and cost Governments between 1 and 3 per cent of their gross national product [GDP].” In Germany the economic costs of traffic accidents were an estimated €30.52bn in 2009 (Straube, 2011 [online]). According to Martina Straube (2011 [online]) from BASt, costs for physical damage were at €17.23 billion and costs for people who were injured at €13.29 billion. Statistically, each person that died in a traffic accident cost the German society €996,412, each seriously injured person cost Copyright © 2013. Diplomica Verlag. All rights reserved.

€110,571, and each lightly injured person cost €4,416 on average. According to Straube (2011 [online]), the total economic costs sank in the last years mainly because physical damages are on average much cheaper and because fewer people died in traffic accidents. Considering the GDP of 2009 (Statistisches Bundesamt, 2010 [online]), traffic accidents in Germany caused economic costs of approximately 1.27% of Germany’s total GDP. As DEKRA (2012 [online]) notes, however, these figures may not reflect the total costs because

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

light injuries are often not accurately diagnosed at the outset and can become chronic in the long term. These figures highlight that an increased road safety is beneficial not only for affected individuals but the economy and thus the society of a country as well. 2.4 Automation in Passenger Vehicles as a Response to Traffic Accidents 2.4.1 Driver Assistance Systems As the aforementioned statistics show, there is still room for improvement to increase the safety of car drivers and other road users. One way to achieve higher safety is by using passive safety systems, such as seatbelts or airbags. Other systems like the anti-lock brake system (ABS) or the electronic stability programme (ESP) help stabilizing the car when certain physical parameters reach specific thresholds, and have greatly increased the safety of car passengers. Recent systems assist the driver with additional information, such as speed alert, which tells the driver whether a maximum pre-set speed is being exceeded (EuroRAP & Euro NCAP, 2011 [online]) or night vision, which displays distant obstacles in the head-up display, and by trying to keep up the attention of drivers through systems such as the attention assistant, which detects and warns the driver of drowsiness. However, as Ekkehard Brühning and Andre Seeck from the Deutscher Verkehrssicherheitsrat (DVR, German Traffic Safety Association) note, purely informative systems cannot prevent all accidents (DVR, 2006 [online]). They estimate that approximately one third of all accidents would require an active intervention of ADAS (DVR, 2006 [online]), for example, through systems introduced in the next section. 2.4.2 Advanced Driver Assistance Systems This sections concerns itself with ADAS, categorized as assisting, semi-automated, highlyautomated and fully-automated systems (see table 2).

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One system of the category assisted driving is the adaptive cruise control (ACC). Drivers can set a certain speed and the car automatically regulates the speed of the car and the distance to the vehicles in front by accelerating and decelerating automatically (EuroRAP & Euro NCAP, 2011 [online]). The driver is left with steering and, as in all other currently available systems, is required to monitor and control the correct functioning of the system. With more cars being equipped with ACC, this technology is expected to increase fuel efficiency and thus reduce some negative environmental effects of driving (Kalra, Anderson & Wachs, 2009 [online]).

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Another system which assists the driver is called lane support. It “reads lane markings and the position of the vehicle within the road lane [and issues] a … warning if the vehicle crosses the lane markings” (EuroRAP & Euro NCAP, p. 15, 2011 [online]). Some systems, however, go one step further and can keep the car, if requested, automatically in the lane (Audi, 2012 [online]). It is estimated that lane support could reduce traffic fatalities by around 5% and even further when combined with other assistance systems (EuroRAP & Euro NCAP, 2011 [online]). The main limitations of lane support, however, are everything that may prevent the system from recognizing the lane markings, such as mud, heavy rain, snow or old markings (EuroRAP & Euro NCAP, 2011 [online]). The autonomous emergency brake (AEB) is one system which belongs to the third category of partly-automated assistance systems. Because drivers almost always brake too late, too little or not at all (Bloch, 2012 [online]), AEBs are “warning the driver and supporting his braking response and/or [apply] the brakes independently” in an emergency (Euro NCAP, 2012 [online]). When the magazine auto motor und sport (Bloch, 2012 [online]) tested AEBs of various cars in urban environments, all systems scored at least satisfactory results. The not yet available but currently developed traffic jam assistant is an ADAS of the category highly-automated systems. It combines ACC and lane support, which means the car steers, accelerates and decelerates fully automatically in traffic jams up to 60 km/h. Audi (2012b [online]) claims that its system will even work on roads without proper markings and will also react to other road users and the environment. BMW’s electric car i3, which is scheduled to be released in 2013 (Kilimann, 2011a [online]) and will be used in its carsharing scheme DriveNow (Magenheim, 2011 [online]), will reportedly make use of a traffic jam assistant (Boeriu, 2011 [online]). The also not yet available assistance system piloted parking would be fully-automated. Here the driver can leave the car which then parks either in a parking slot or a multi-story car park,

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and later comes back to the driver fully automatically (Audi, 2012b [online]). BMW’s i3 will provide a similar system where the driver has to remain in the car though (Boeriu, 2011 [online]). 2.4.3 Car Drivers, Customers, and Advanced Driver Assistant Systems Recommended by insurers (see, for example, Kubitzki, 2011 [online]) and due to increasing popularity (DVR, 2010 [online]), equipment rates of cars with ADAS slowly increase beyond marginal numbers (DAT, 2012 [online]). According to the DVR (2010 [online]), 35%, 25%

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Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

and 18% of interviewees knew ACC, AEB and lane assist respectively, with 5% of new cars being equipped with these systems (DAT, 2012 [online]). The discrepancy between popularity and equipment rates can be explained by another study conducted by Puls, which found that one third of customers would be willing to pay up to €500 for such systems (Lanzinger, 2011 [online]). However, as Alexander Bloch (2012 [online]) from the magazine auto motor und sport notes, a single system can easily cost more than what customers are willing to pay for all systems combined. Only for the AEB assistant of Volvo, for example, customers have to pay €1,980. Bloch (2012 [online]) therefore believes that high costs are the reason for observable low equipment rates, with negative effects on the overall traffic safety. Those customers that opt for ADAS, however, may also negatively affect traffic safety, as Berthold Färber, Head of the Institut für Arbeitswissenschaft (Institute for Industrial Science) notes (DVR, 2006 [online]). Whereas, for example, Japanese car drivers shrug off malfunctions and are pleased with systems which work ‘in general,’ Germans expect cars which they regard as ‘engineering prototypes labelled Made in Germany’ to work 100%. This means, according to Färber (DVR, 2006 [online]), that German drivers demand systems to work reliably and predictably, and fulfil all expectations. Whereas systems such as ABS and ESP, for example, are nowadays completely accepted by users because they work reliably and as expected (DVR, 2006 [online]), modern ADAS work within certain limitations and may malfunction beyond certain thresholds. The problem is that systems cannot interpret and see the real world as humans do, so expectations of drivers may sometimes not be met (DVR, 2006 [online]). According to a study conducted by Heike Sacher (2008 [online]), the majority of 72 drivers did indeed neither understand nor was aware of the limitations of ADAS. This misinformation and misbelief may lead to dangerous situations, for example, when drivers rely on systems, feel safe and engage in other activities where the traffic situation would actually require full attention because of ADAS’ system limitations (DVR, 2006 [online]); Kubitzki, 2011 [online]).

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2.5 Fully-Automated Vehicles At the moment driverless vehicles are neither sold nor ready to be marketed to the public. Huge developments over the past years, however, indicate that this technology is not a mere future vision, but the future of driving (HAVEit, 2011b [online]). Whereas the timeframe for a possible introduction will be discussed in the third part, this section will now look at

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technological aspects to understand the technology, its limitations and possible future pathways. Going back to Kalra, Anderson and Wachs’ overview (2009 [online]), driverless vehicles have to manage three functions: sensing, planning and acting. Whereas acting, i.e. accelerating, decelerating and steering is already achieved in ADAS systems such as ACC or lane support, the other two functions need further explanations. In regard to sensing, it is important to know that premium automobiles already employ numerous sensors for current ADAS (see, for example, Audi, 2012 [online]). Sensor technologies such as radar (Bosch, 2012 [online]), laser (Euro NCAP, 2012 [online]), sonar (Scheider, 2011 [online]) and video cameras (EuroRAP & Euro NCAP, 2011 [online]) monitor the environment around a vehicle from various angles and with different methods. These sensors are disadvantaged over the human eye because a single sensor does not have the same perception capabilities. To ensure that observations are consistent with the actual environment nonetheless, “at least two different measurement methods [are] used in every direction” (Boeriu, 2011 [online]). This way, the “potential weakness in one method is counterbalanced by the strength of the other method” (Boeriu, 2011 [online]). Moreover, some sensors outperform the human eye in certain disciplines, for example, by seeing further or in the dark (Audi, 2012 [online]). The increasing availability and cost effectiveness of various and ever new sensors, Bartels, Ruchatz and Brosig (n.d. [online]) from Volkswagen believe, will allow the reliable sensing of the environment and eventually enable autonomous driving. The second function, planning, uses the generated data from sensors and, with the help of algorithms, processes those into a model of the real world which then enables the system to make decisions regarding the driving task (Kalra, Anderson & Wachs, 2009 [online]). Since DARPA’s first Grand Challenge, it became clear that rule-based thinking, which means to program every possible situation into the software of a driverless vehicle, was impossible, but that algorithms are required “equivalent of self-awareness” (Davies, 2006 [online]). Systems Copyright © 2013. Diplomica Verlag. All rights reserved.

now, and with the help of new and more sensors, question data which allows them to discard information they had previously accepted, like shadows or malfunctioning sensors (Davies, 2006 [online]). DARPA’s Grand Challenge 2005 winning car, for example, had incorrectly identified objects 6,000 out of 50,000 before, but only 1 out of 50,000 times after adapting the new approach (Davies, 2006 [online]). According to Justin Rattner, Intel’s R&D director in 2006, “The new paradigm is based on probabilities [and the] statistical analysis of patterns, [which] is a better reflection of how our minds work” (Davies, 2006 [online]). While sensors

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collect the data, Google, for example, lets “its algorithms figure out the rules on their own” (Vanderbilt, 2012a [online]). Because of the complexity of the driving task, however, these algorithms need to be trained with input (Vanderbilt, 2012a [online]). Despite that Google has travelled more than 500,000 km with its driverless vehicle fleet, the company acknowledges that training the algorithms will take more time (Urmson, 2012 [online]). Compared to Google’s approach, carmakers are seeking to continually improve existing technologies and implement those in future cars. Considering, for example, the capabilities of adaptive cruise control, lane support and autonomous emergency brake systems, it becomes apparent that the next step will consist of combining these already available and functioning technologies into a single system which controls the speed, distance to other road users, steers and brakes when necessary. The abovementioned limitations of these currently available systems, however, indicate that this step will be more complicated than it sounds. Volkswagen, for example, developed a temporary auto pilot (TAP) for the HAVEit project which can steer, accelerate and decelerate the car automatically (HAVEit, 2011 [online]). The carmaker highlights, however, that TAP does only work in specific situations and still requires that the driver monitors the system and is able to intervene at any given time (HAVEit, 2011 [online]). TAP is therefore representing “a link between today’s assistance systems and the vision of fully automatic driving” (HAVEit, 2011 [online]). Approaches of both Google and carmakers promise to increase road safety for drivers, passengers but also for pedestrians, cyclists and other road users, significantly. With the potential to reach more customers in the future, the influence of carsharing on road safety will increase gradually. A relatively recent trend which needs to be considered in terms of driverless vehicles is called car-to-x communication. This concept proposes that cars communicate with each other and the surrounding infrastructure in order to being able to base decisions on more information.

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At the moment neither communication standards have been formulated nor who would pay for the introduction and maintenance of these complex and expensive systems (IRM WG, 2010 [online]). Some experts, such as Stefan Liske, auto industry consultant at business consultancy PCH, believe that autonomous driving will not be realised without car-to-x technology (Vanderbilt, 2012d [online]). Test vehicles of Google and other carmakers, however, have made no use of, but manage to perform without this technology. It thus remains questionable why driverless vehicle technologies would not be marketed until car-to-

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x communication, an expensive technology in its infancy, is sufficiently available. As has been shown in this part, the majority of accidents are due to human erratic behaviour and at the moment it is widely believed that fully-automated vehicles alone deliver additional safety compared to human drivers without car-to-x communication.

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Part3:PrefeasibilityStudy Think of the impact that computers have had on offices, they have totally transformed them, and the same thing is going to happen on the roads. Prof Paul Newman Project Leader for the Autonomous Car ‘Wildcat’ at Oxford University 3.1 Introduction The third part will now engage in analysing the feasibility of the proposed concept. By outlining the concept in the following section, it will be shown how the new concept alters current schemes and that besides changing the primary service of renting the car, new secondary services will be created. These new and improved services offer new advantages to customers and may make carsharing schemes more attractive to a broader range of customers. The following section analysis the micro environment of carmakers. Both components of the concept, carsharing and driverless vehicle technologies, will be analysed by the four components of the SWOT analysis: strengths, weaknesses, opportunities and threats. It will be shown that carmakers could benefit from their brand name and financial resources of the core business, while the new technology requires new competences. The external analysis indicates that the concept could attract more customers because of the newly created services, whereas competing industries may emerge as potentially dangerous opponents in terms of lobbying against and delaying pivotal legislation or creating direct competition with own schemes. In the subsequent section, the study will analyse the macro environment of carmakers in

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regard to the proposed concept. Out of the STEEPLED analysis, all components but economics will be investigated, because economic factors such as interest rates or the unemployment rate can first, hardly be expected to prevent the realisation of the concept in the long term, and second, impossibly be predicted for the time when the concept may be realised. This leaves the study with an ad hoc tool which is called STEPLED in this study, analysing the seven macro-environmental components society, technology, environment, politics, legislation, ethics and demographics. The analysis will indicate the large market potential of the

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proposed concept, and where companies can and should act in order to facilitate the realisation of this concept. 3.2 The Concept The general idea of this study is the integration of driverless vehicles in commercial carsharing schemes in Germany. The carsharing programmes DriveNow from BMW and car2go from Daimler were chosen because they allow their customers an increased flexibility compared to traditional carsharing schemes in regard to rental times and car return options. This flexibility is in line with the proposed concept and would further be extended due to new time saving opportunities for customers offered by driverless technologies. Moreover, the necessary infrastructure in terms of internet and smartphone applications has been laid and could be used for the concept after minor adjustments. The integration of driverless vehicle technologies will change the actual car drive, the primary service, and will also create new services for the customer before and after the car drive, the secondary services. The change in regard to the primary service will allow the enabling of a fully-automated driving mode so that the complete driving task will be conducted by the system without requiring the driver to monitor or engage in any driving-related activities. The driver, on the other hand, is free to use the travel time for other purposes. The newly created secondary services will be pre-cardrive and post-car-drive related. The former regards a new service before the actual car drive. At the moment, customers are required to find an available car, for example, with their smartphone applications. In the future, however, the nearest vehicle could be called via the same, slightly modified application, and drive completely autonomously to pick up the customer. In terms of the post-car-drive service, the integration of driverless vehicle technologies would allow customers to leave the car right at the desired destination, without having to park the car. The vehicle, on the other hand, would take off by itself, either looking for a parking slot or driving to the next customer.

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3.3 Micro-Environmental Analysis: SWOT The following section analysis the micro environment of carmakers, first the internal perspective considering carmakers‘ strengths and weaknesses, followed by the external perspective looking at possible opportunities and threats posed by the proposed concept. It will be shown that carmakers are in a good position to incorporate driverless vehicle technologies into their carsharing schemes and that the opportunities offered by this new technology are manifold.

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55 However, a major threat could be posed by possible competition, which would increase with the availability of driverless vehicle technologies. 3.3.1 Strengths Currently both carmakers develop strength by constantly extending their carsharing programmes and making experiences in terms of the administration. The schemes attract steadily more customers and BMW and Daimler are about to become established providers in the field of carsharing. Three other strengths, moreover, stem from their core business of developing, manufacturing and selling cars. First, BMW’s and Daimler’s core business provides both companies with a certain degree of financial strength compared to entirely new entrants or small providers in the carsharing business. This allows offering more service, expanding faster to other cities, and initially charging less for the service by offsetting losses with profits from other business areas. The financial strength gives thus a competitive advantage in this field, which is especially highlighted by the fact that the significantly larger of both schemes, car2go, is planned to operate at a loss over a total time period of five years. Second, another strength of carmakers is based on their respective brand name and image. Both brands, it can be argued, are well established and known for manufacturing premium automobiles. This means that BMW and Daimler, compared to small or local providers, can transfer the brand name and image to new services, such as carsharing. BMW even tries to incorporate new mobility services into the overall business strategy and announced that it does not only want to become the most successful carmaker but also the leading provider of services for individual mobility (BMW, 2008 [online]). The third strength which is based on the core business of carmakers concerns driverless vehicle technologies. The long experience of making and designing cars may constitute a strength in the future compared to other providers, such as Google. Carmakers understand the Copyright © 2013. Diplomica Verlag. All rights reserved.

complete car and have full control, even if sometimes only in collaboration with suppliers, over the design of each single component. Especially when comparing the different driverless vehicle systems of carmakers and Google in regard to their visual appearance, it becomes clear that Google is more interested in the software and functioning of the system. It simply attaches sensors all around their cars, with the biggest one sitting on the roof being as wide as the complete width of the car, approximately thirty centimetres long and a good half a meter tall. This approach may be more visible and actually help the marketing of its product to

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some extent. It may even be easily attachable to other cars so that it could be sold separately, as Google itself suggests (Lavrinc, 2012a [online]). However, carmakers are already forced to consider customer requirements in regard to the overall design of the vehicle and they try to integrate sensors invisibly into the car design. Knowing how to do that and being capable of doing this may be an important advantage to distinguish oneself from the competition in the future. 3.3.2 Weaknesses Despite the advantage over small and local providers to transfer brand name and image to carsharing services, BMW and Daimler are known as premium carmakers and could thus be attacked by medium and low cost carmakers which enter the carsharing market. It will be important to provide cars according to customer requirements in the long term in order to stay ahead of competition. This means, for example, if surveys would indicate that customers are more concerned about the mobility per se and a low price to increase flexibility, then the premium carmakers BMW and Daimler may be compromised to some extent. In regard to driverless vehicle technologies it needs to be highlighted that even though the actual making of cars is still in the domain of expertise of carmakers, and despite the fact that carmakers have gained significant information about and experience in the making of ADAS, driverless technologies require completely new competences linked to sensors and software for autonomous driving. The former is currently developed alone or in collaboration with supplying companies such as Bosch (2012 [online]) or Continental (2012 [online]), the latter, a software which processes huge amount of data in real time and makes decision regarding the driving task, lies in a new domain for traditional carmakers. On the one hand, carmakers are familiar with the development of software. As Manfred Broy, a professor of informatics at the Technical University of Munich and a leading expert on software in cars, points out, an F35 Joint Strike Fighter requires 5.7 million lines of software code, the 787 Dreamliner of

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Boing runs on 6.5 million lines of software code, but a premium-class automobile “probably contains close to 100 million lines of software code” (Charette, 2009 [online]). The fact, however, that the radio and navigation system of the Mercedes S-Class alone requires over 20 million lines of code (Charette, 2009 [online]), for example, indicates that significant parts of the code are not used specifically for the driving task. “The auto industry is still learning,” as Tom Vanderbilt (2012d [online]), author of mobility books and for Wired magazine, puts it. Due to its core business model, however, Google is already very good at dealing with huge

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57 amounts of data as well as with writing complex algorithms (Vanderbilt, 2012d [online]). Carmakers will have to pick up new skills, recruit experts, and test new technologies extensively to compensate for these weaknesses. 3.3.3 Opportunities The proposed concept offers a wide range of opportunities to carmakers, from increasing their profits by accommodating rising demand for their schemes, to lowering costs by making use of new driverless technologies, and using their schemes as an opportunity to market the new technologies for their core business. First, car2go’s and DriveNow’s constantly increasing customer base, the expansion to new cities and the enlarging of business areas combined with social trends investigated in part one, indicate that commercial carsharing has the potential to grow further in the near to midterm future. Moreover, BMW and Daimler could benefit from a generally worsening public transport service. According to Michael Reidenbacher et al. (2008 [online]) of the German institute for urban studies, public transport will have to face increasing passenger numbers in already overstrained urban agglomerations while insufficient investments are planned to help meeting future requirements. Moreover, the attractiveness of the mobility services taxis and rental cars may decline as well. Hartmut Knaack, chairman of the Bundes-Zentralverband Personenverkehr – Taxi und Mietwagen (BZP, federal association personal transport – taxi and hire car) and member of the BZP committee Traffic and Business Policies, believes that both sectors are very likely to face staff shortages (BZP, 2011 [online]) whereas taxi services could additionally become more expensive due to constantly increasing insurance rates (BZP, 2011 [online]). Carsharing schemes could benefit from these weaknesses and increase their customer base. Second, apart from the flexibility offered by commercial carsharing, the integration of driverless vehicle technologies would create further benefits for customers. Regarding the

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primary service, the driving task, customers would presumably reduce the overall risk of having an accident while being able to relax and engage in other activities at the same time. One such activity, which already makes it to cars but is currently prohibited by law because of the risk to cause accidents, is the use of mobile phones and smartphones. Not only would this risk be eliminated when cars drive autonomously, but the opportunity to spent the journey time with their mobile phones may become another selling point for people that want to be available all around the clock. This share of people is quite high, as a survey conducted

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by Ernst & Young (Fuß & Forst, 2012 [online]) shows: 70% of the total interviewees and 82% of people under 25 think it is important or very important to be available 24/7. These people could not only talk and message risk free, but also engage in other activities such as reading or surfing the internet when the proposed concept was realised. The possibility to work or prepare business meetings may attract a completely new group of customers as well. Regarding the newly created pre-car-drive service where the car can be called to the customer’s location and drives there autonomously, customers would not have to search available cars anymore, thereby tackling one of current carsharing programmes’ limitations (see 1.5.2). Such service may be welcomed especially by those people that prefer spending their time on other activities, those people that are physically impaired or whose poor health negatively affects their walking, those people that may feel unsafe looking for cars at certain times or in specific areas, but also by those people that can do without walking, either in bad weather or traffic conditions or because of other personal reasons. When arriving at the desired destination, on the other hand, customers would not be required to seek a parking slot for their vehicle anymore because of the new post-car-drive service (see limitation of carsharing, 1.5.2). At the moment finding a parking spot exactly at the desired destination is rare, especially where many businesses, shops and resident apartments are seen alongside comparably few parking slots, like it is common in many city centres (Senatsverwaltung für Stadtentwicklung, 2006 [online]). This means that customers may regularly be required to seek an available parking slot which means spending more time in the car. This time could not only be spent on other activities (see above), but it also creates additional costs for each single minute. The integration of driverless vehicle technologies would allow customers to just leave the car at the desired destination and immediately start engaging in new activities. This post-car-drive service, moreover, has the potential to turn a current disadvantage into a selling point (see carsharing’s limitations 1.5.2). Providers could provide their customers with the opportunity to use their carsharing vehicles beyond the currently Copyright © 2013. Diplomica Verlag. All rights reserved.

limited business areas, because driverless vehicles could autonomously return after the passenger has reached its destination. This increases the potential customer base significantly and could, in the long term, even be used as a basis to offer city-to-city or even country-tocountry connections. These new secondary services will increase the mobility of and the flexibility for customers and would certainly attract a whole range of new customers for the respective carsharing

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59 provider. A survey by Ernst & Young (Fuß & Forst, 2012 [online]), which found that 75% of the general population and 85% of the people under 25 think that unrestricted mobility is important or very important, supports this view (Fuß & Forst, 2012 [online]). The proposed concept would thus respond to these demands by offering a very flexible service. This could in turn potentially attract many customers which use other mobility providers or options at the moment. Third, integrating driverless technologies in carsharing schemes can potentially reduce the costs of providers. While the renting time will be decreased due to the loss of parking-slot seeking traffic and thus the turnover may be negatively affected (Vogt, J., personal communication [email], 17/7/2012), the availability of vehicles will increase for other customers (see limitation of carsharing, 1.5.2). Moreover, because it can be assumed that cars will be generally driving faster to customers than customers could walk to cars, the availability of cars will also be increased. This may even result in requiring fewer vehicles in total for the scheme, however, considering that high peak rental times may occur, this effect may not completely offset the lost in turnover. Nonetheless, other factors have the potential to reduce overall costs: autonomous vehicles could plan routes better; fuel efficiency will be increased; fewer accidents will likely result in lower insurance costs (Kalra, Anderson & Wachs, 2009 [online]); cars could be called for maintenance services instead of sending teams to them (Daimler, 2010 [online]); in off-peak times vehicles could drive to locations that offer free parking (Nagel, T., personal communication [email], 17/7/2012); and a smart software could analyse historic rental patterns to predict future demand and sent cars to respective areas in advance. Moreover, in-car advertising could be offered due to the fact that it does not pose a risk for distractions anymore. This could generate turnover either from advertising companies or from customers willing to pay a premium to switch off adverts. Forth, using driverless vehicles in carsharing schemes has the potential to make customers familiar with this new technology and can thus help support the sales of the respective Copyright © 2013. Diplomica Verlag. All rights reserved.

company. As mentioned above, customers become more easily accustomed to innovative products when they have the opportunity to test them (Jansson, 2011 [online]). What is already used for electric vehicles would therefore also be an important instrument for driverless vehicle technologies because this approach has the potential to strengthen a possibly becoming weaker core business.

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3.3.4 Threats The proposed concept, however, does also pose several threats to BMW and Daimler, primarily regarding direct competition for their carsharing schemes as well as indirect competition for their own core businesses. First, with carsharing currently emerging as a potentially profitable new business area, BMW and Daimler may not be the sole providers of highly flexible schemes in the long term. Both companies can expect to increasingly face new competition from carmakers, highlighted by recent market entrants Peugeot and Volkswagen, and have to be aware that existing traditional programmes could turn their business and pricing models into similarly flexible schemes. The number of competitors may increase even further if Google or other developers would provide a system which could be attached to cars afterwards (Lavrinc, 2012a [online]). Taxi and hire car companies as well as traditional carsharing providers may make use of this option. Above all it should not be forgotten, Joachim Vogt (personal communication [email], 17/7/2012) from Confitech, an automotive supplier developing and selling ADAS, reminds that the first provider to offer such a technology would have a first-mover advantage and others would need to follow shortly after. In this regard it will be essential whether one approach, Google’s or the automotive industry’s, will come up with a workable solution faster than the competition. If the time period between the marketability of both solutions is very long, it could mean a competitive advantage for several years, if not decades, when considering that customers might be bound to one provider after they have signed up to a scheme which offers the first marketable solution. Second, another threat regarding direct competition may also come from efforts of mobility providers that plan to offer its customers access to various services in a single application. For example, the Deutsche Bahn (DB, German Railways) is already planning an application that helps customers to find the best and fastest offer among different schemes and services

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(Kramper, 2012c [online]). While beneficial for customers, providers could not only lose their customers to other services but also risk being reduced to comparable factors such as availability and price. With potentially numerous providers competing in each city in the long run, this situation may require to further develop unique selling points. BMW, for example, has already announced it would distinguish itself from its competition by offering premium cars (Sixt, 2011 [online]). Whether this may result in premium prices and lower demand in the long term remains an open question.

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61 Third, carsharing providers need to be aware that other providers of mobility services may not only not support but also actively try to prevent any further developments of carsharing schemes, for example, due to lobbying (see 3.4.4). The reason is that the proposed concept has the potential to sustainably change the mobility industry and might pose a threat to other companies. Thus, collaborating with other stakeholders may be required from carsharing providers to achieve results which are accepted by a wide range of stakeholders. Fourth, despite the fact that carsharing is currently a small business for and rather seems to complement than substitute the core business of carmakers, Schlesinger (2011 [online]) believes that mobility services such as carsharing have the potential to become the most important business area for carmakers and may thus pose a threat to the core business. First of all, car ownership may decline in the long term, as shown in part one. One reason could be that possessing an own car conflicts with the demand for higher flexibility, because even though a car may offer flexibility in terms of mobility, it requires a long-term commitment and causes high fixed costs (Loose, 2011 [online]). On the other hand, each single carsharing customer will increasingly rely on and become familiar with carsharing but also with other services such as hire car or public transport. This could mean that purchase intentions for new cars may be reduced even further. Moreover, each customer who does not possess a car is also a potential customer of other services such as DB, hire car or local transport, which implies that these companies will also compete for those customers who seek the highest flexibility possible (Seiwert & Schlesiger, 2012 [online]). The planned smartphone application of DB is an example for this (Kramper, 2012c [online]). Fifth, one threat is related to the complexity of the software which controls driverless vehicles. The example of Toyota, which tried to figure out what caused an unintended acceleration in some of its vehicles and subsequently accidents, serves as a good case to show that with more software and more electronic components, the search for failures and malfunctions will not become easier. After Toyota had recalled more than seven million cars without Copyright © 2013. Diplomica Verlag. All rights reserved.

having a clue what caused the problem, it asked experts to investigate the problem, first from the U.S. National Highway Traffic Safety Administration (NHTSA) and later from the National Aeronautics and Space Administration (NASA) (NHTSA, 2011 [online]). The result of the extensive investigation was that no electronic cause could be identified but that it was believed “that those incidents are most likely the result of pedal entrapment by a floor mat that holds the accelerator pedal in an open throttle position” (NHTSA, 2011 [online]). When a few faulty lines of software code would cause accidents consistently and the problem cannot

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be found even by many experts over a longer time period, thousands or millions of customers, either car buyers or carsharing customers, may be required to do without their own or the carsharing car for an indefinite time period. Considering that software will become more complex in the future and taking into account that the same basic software is most likely used in each single model sold by a carmaker, malfunctioning systems may pose an existential threat to a company. 3.4 Macro-Environmental Analysis: STEPLED The following section will analyse macro-environmental components regarding the proposed concept. The sub-sections will, if possible, refer to both components of the concept, starting by carsharing and followed by driverless vehicle technologies. Both will consider current developments to draw some conclusions about possible future developments. It will be found that many factors are working towards the realisation of the proposed concept, however, a few others, such as the legislation, require swift actions from carmakers soon. 3.4.1 Society The trends mentioned in part one indicate that the German mobility behaviour may be about to change and it has been shown how carsharing offers an alternative transport mode for these changing requirements. Whether these changes reflect a truly changing society or whether they represent a mere delay, the ADAC (personal communiation [email] 17/7/2012) notes, will be key to determine the possible success. The ADAC, representing more than 17 million customers who own two thirds of all registered vehicles in Germany (Dervisevic, 2012 [online]), believes nonetheless that carsharing will be an important transport mode in the future. Regarding driverless vehicles, several aspects need to be looked at. First, Vanderbilt (2012a [online]) thinks that “The most slippery territory … may be social and cultural” and that one question determining the success of driverless vehicles will be whether customers “want to Copyright © 2013. Diplomica Verlag. All rights reserved.

give up the wheel [because a] car represents freedom” (Vanderbilt, 2012a [online]). For the case study Germany, the ADAC (personal communication [email] 17/7/2012) believes, car drivers would prefer driving themselves because of the fear to be at a machine’s mercy. Christian Lauw (personal communication [email], 16/7/2012), CEO of a Munich limousine service, believes that those who already prefer being driven by professionals, demand human services which cannot be substituted by a ‘dead computer.’ When in March 2012, however, 17,400 U.S. American vehicle owners were asked by J.D. Power and Associates (2012

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63 [online]), a global marketing information services company, 37% said they definitely would or probably would purchase this technology for their next car. When told the estimated market price was US$ 3,000, this number declined to 20%, but among buyers aged 18-37 and also for those living in urban areas, still 30% were willing to pay this premium (J.D. Power and Associates, 2012 [online]). Even though these figures represent purchase intentions of North American buyers and despite the fact that the market price for driverless vehicle technologies will probably much higher at the outset (see 3.4.2), it gives a strong indication that car drivers may already be willing to give up the wheel during times of “boring driving” (J.D. Power and Associates, 2012 [online]). This also indicates that especially the target group of carsharing, young people living in cities, may be especially willingly to accept and adapt to this form of mobility. Second, in regard to “public authorities and users of the product … safety is a basic requirement” (van der Heijden & van Wees, p. 322, 2001 [online]). Not only companies (Audi, 2012a [online]; Boeriu, 2011 [online]; Bosch, 2012 [online]; Continental, 2012 [online]; Urmson, 2012 [online]) but also politicians (DEKRA, 2012 [online]; European Commission, 2010 [online]) believe that these technologies will make driving safer. This optimism can be explained by a few simple assumptions. New (advanced) driver assistance systems have always increased the safety and/or mitigated some of the worst outcomes of accidents. It seems reasonable to assume that this trend will continue because carmakers will hardly release any new systems which could actually decrease traffic safety. Human drivers, on the other hand, “are forever stuck in version 1.0 [without any] hope of an upgrade in evolutionary sight” (Vanderbilt, 2012e [online]). This means that it can be assumed that systems have the potential to eventually drive safer than humans, and could thus get the necessary political and social support for the introduction and proliferation. Third, it can be assumed that carmakers will only release technologies which they believe do not lead to product liability claims (see 3.4.5 Legislation) or the risk of being exposed to bad Copyright © 2013. Diplomica Verlag. All rights reserved.

press. This social and economic pressure may thus help preventing the introduction of any premature technology. Tyler Cowen (2011 [online]) from the New York Times, however, warns that this pressure could also lead to a delayed introduction. Driverless vehicles which drive better than humans but still cause accidents may be seen as too risky for an introduction, despite the fact that they would actually save lives (Cowen, 2011 [online]).

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Forth, a fear has been expressed in the literature that driverless technologies could alter the behaviour of other road users (DEKRA, 2012 [online]; Kalra, Anderson & Wachs, 2009 [online]; RAND, cited in Vanderbilt, 2012c [online]). A few pedestrians, for example, which expect cars to brake autonomously, may develop behaviours to cross streets without looking for any traffic. While it would be fatal in case the approaching vehicle is a ‘traditional’ car (DEKRA, 2012 [online]), it can be doubted whether a rationally thinking pedestrian would assume this property from each car in the introduction period of driverless vehicles. 3.4.2 Technology Technological components of carsharing such as the signing up procedure, locating a car via internet and smartphone applications, as well as the procedures to rent and pay for a car, have been successfully established by BMW and Daimler. Connecting the car with social networks, like BMW does with its fleet (DriveNow, 2012a [online]), and enable further functions and internet applications, however, poses a trade-off between customer demands and safety, because it will almost necessarily create new sources of distraction which may potentially cause accidents. In regard to the second component of the proposed concept, the driverless vehicle technology, several aspects need to be considered. First, the technology regarding future development challenges, followed by the possible date of introduction and risks related to the technology. First, after driverless vehicles can currently be termed as being capable of managing regular situations, the current challenge is teaching software how to cope with irregular situations, such as driving in bad weather conditions or reacting to road users who do not follow regulations. Regarding the former, Google’s Chris Urmson (2012 [online]) states, for example, that their cars will need “to master snow-covered roadways, interpret temporary construction signals and handle other tricky situations that many drivers encounter.” In terms of the latter, Kalra, Anderson and Wachs (2009, p. 10 [online]) note that “While it is possible to

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design autonomous vehicles that obey all traffic rules, they … must share the road with other drivers who do not do so.” Algorithms, therefore, need to encompass as many eventualities as possible to be not only prepared for each situation in which road users obey the rules, but also those in which they may not. Vanderbilt (2012a [online]) believes that driverless vehicles will eventually think faster than mortal drivers, attend more information and react quicker to emergencies while never panicking or getting angry. In this regard, it is believed that “Human beings in moderately

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65 stressful environments such as driving can be expected to have an error rate of around 1 in 500 decisions” (Euro RAP & Euro NCAP, 2011, p. 5 [online]). Therefore, Bryant Walker Smith, working on legal aspects of robotics and especially autonomous driving at Stanford Law School’s Center for Internet and Society, believes that one question determining the introduction will be “…how safe do these vehicles need to be, and how should that safety be measured” (Walker Smith, B., personal communication [email] 12/7/2012). With two different approaches, Google’s driverless vehicle fleet and the evolutionary improvement of ADAS of most carmakers, this question can be answered in two ways. Regarding Google’s approach, Walker Smith (2012h [online]) suggests that “Rather than asserting that computers are perfect drivers, we might ask whether they actually drive better than humans.” In a calculation for the United States, Walker Smith (2012h [online]) sought to sought to estimate how many representative kilometres a driverless vehicle must travel without incident to establish at the 99 percent confidence level that the vehicle crashes no more frequently than the average human-driven vehicle. Following his calculation (Walker Smith, B., personal communication [email] 12/7/2012), this would mean that in Germany driverless vehicles would have to drive, without being involved in any accident, representative 820,611 km to statistically suggest that they have no more accidents than human drivers, around 6.5 million km to prove that they have fewer accidents with personal injuries, and almost 500 million km to prove that fewer people will die in traffic accidents. At a time when Google had close to 300,000 km in total (Vanderbilt, 2012a [online]) in October 2011, the driverless fleet had completed less than 2,000 km in fully autonomous mode, according to a statement by Sergei Brin, co-founder of Google (Hachmann, 2011 [online]). This means that attempting to actually drive 500 million km, which constitutes 0.056% of Germany’s annual motorised individual traffic (DLR, 2007 [online]), will be a major challenge. Most likely, this will not be achieved by testing a fleet of a few driverless cars so that Google and companies using similar approaches will have a hard time proving the safety of their product before it is

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released to the public. In regard to the evolutionary approach used by many carmakers, it is interesting that the third largest car insurer in Germany, R+V, has not recorded a single accident caused by existing ADAS (Richter, R., personal communication [email] 24/7/2012). While this may not reflect the reality completely and some accidents may not be recognized as having been caused by malfunctioning ADAS (Richter, R., personal communication [email] 25/7/2012), it is a strong indication that carmakers carefully design and test new systems before introducing them.

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Nonetheless, the first highly and fully-automated systems may be released soon in the near future (see 2.4.2) and carmakers will have to make sure that those as well are as safe as current ADAS, which are in most instances relatively simple. One measure to achieve highest possible safety could be what Rauch et al (2009 [online]) term a system switching into the minimum-risk state. This could be done, for example, by extending the function of already available autonomous emergency braking systems and thereby applying article 13 of the United Nations Convention on Road Traffic (see 3.2.5 Legislation) to autonomous vehicles. This article states that a driver shall “be able to stop his vehicle within his … vision and short of any foreseeable obstruction” (United Nations, 1968a [online]). If a vehicle was acting according to this wording when it encounters a situation beyond its restrictions, systems such as AEB could safely decelerate the car or even bring it to a halt, in case the driver does not want or cannot take control fast enough. In the beginning, this emergency braking could, though working under certain restrictions as well, minimize the fear of both politicians authorizing the use of and customers buying driverless vehicles, while at the same time enabling higher road safety. This could be based on the fact that driving slower would cause fewer and less severe accidents, especially in urban environments where cars would drive relatively slow in the first place. Second, because it is an essential part of the proposed concept, the possible timeframe for the introduction of driverless vehicle technologies is an important question. However, because this question aims at the future and will remain unanswered till the first driverless vehicle is sold to a customer, the following paragraphs summarize and analyse statements of experts working in the field in terms of the technological feasibility (legal aspects will be discussed below). Johann Gwehenberger, back in 2006 head of the Allianz Centre for Technology (DVR, 2006 [online]), was holding a comparatively extreme view because he believed that autonomous driving would not be realised before the year 2055. The opposite extreme view is marked by Alan Taub, retired vice president of GM’s global research and development,

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who “predicts that self-driving cars will be on the road by the decade’s end” (Vanderbilt, 2012a [online]), or by Vogt who points at Google’s fleet of driverless vehicles indicating it was already technologically feasible (Vogt, J., personal communication [email] 17/7/2012). The majority of experts, however, takes the view that driverless vehicles will be realised somewhere in the middle of the next decade, such as Matthias Knobloch, Head of Department for Traffic Policy of the ACE Auto Club Europa (ACE, automobile club Europe) (Knobloch, M., personal communication [email] 17/7/2012), Ekkehard Brühning, BASt

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67 (DVR, 2006 [online]); or Frank Flemisch, scientist at DLR (Gaub, 2010 [online]). Providing more than just a release date, Bernd Bohr, chairman of the Bosch Group Automotive Technology business sector, expects a gradual shift towards autonomous systems that “will first become established in relatively discrete situations … [but will] expand … over successive vehicle generations to embrace higher speeds and more complex situations” (Bohr, 2011 [online]). In his opinion, this will lead to autonomous driving over the next two decades (Bohr, 2011 [online]). This opinion is shared by Knobloch, who thinks extrapolating the slow evolutionary development of the automobile industry’s past would be the most reliable (Knobloch, M., personal communication [email] 17/7/2012). Results of HAVEit match these cautious estimates, because the highly-automated systems developed in the project could potentially be marketed within the next three to ten years (HAVEit, 2011b [online]; Hoeger et al, 2011 [online]), with a few more years required for fully-automated systems. Supporting the view that driverless vehicles will not be on the road all too soon is further indicated when considering the costs of this technology. Vogt (personal communication [email] 17/7/2012) calculates that equipping a premium car with only those ADAS which were available today would cost as much as a compact car. Adding the functionalities of Google’s technology, he estimates, would lead to costs of a second compact car (Vogt, J., personal communication [email] 17/7/2012). However, because a rising availability and manufacturing of sensors will lead to increasing cost effectiveness, the technology will become much cheaper over time (Bartels, Ruchatz & Brosig, n.d. [online]; Squatriglia, 2010a [online]). It should be mentioned, however, that some experts such as Stefan Liske, auto industry consultant at PCH, believe that it will be impossible within the next 10-15 years “to come up with a budget [for car-to-x communication] that would be needed in order to turn cities into environments for autonomous driving” (Vanderbilt, 2012d [online]). Whether these technologies will actually be prerequisites of driverless vehicle technologies remains unclear, though.

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With a whole industry expecting driverless vehicles hitting the roads eventually, such as Clifford Nass, director of Stanford’s Revs Program, stating “Everyone thinks this is coming” (Vanderbilt, 2012a [online]), all predictions need to be viewed cautiously nonetheless. As Jameson M. Wetmore (2003, p. 14 [online]) in an article for the Automotive History Review reminds, automated traffic systems as well “have been ‘only 20 years away’ for over 60 years.”

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Third, another aspect of driverless vehicle technologies is the trend towards increasing connectivity of cars with the internet or via car-to-x communication with other cars and the infrastructure, and has led to the fear that cars could be prone to computer viruses and hacking attacks (Taylor, 2012 [online]; Vogt, J., personal communication [email] 17/7/2012). Vogt (personal communication [email] 17/7/2012) believes that this situation may pose a real threat in the future and suggests that hacked cars could be used for purposeful accidents or attacks directed at certain people. Brian Contos, a security strategist with McAfee, notes that “Cars have essentially become smart phones that can go 100 miles an hour (Taylor, 2012 [online]). He believes that “while a hacked phone may be a big personal inconvenience, just one hacked car creates a huge risk for everyone else on the road” (Taylor, 2012 [online]). To overcome this problem, Contos suggests that this “issue … must be solved by auto manufacturers in the factory” (Taylor, 2012 [online]). Considering, however, that thousands of military specialists are employed in the field of cyberwar, Vogt notes, solving this problem may not be as straightforward as it sounds (Vogt, J., personal communication [email] 17/7/2012). Carmakers and providers of driverless vehicles will thus have to consider this trade-off between networked cars and safety. 3.4.3 Environment Whether the environment will or will not benefit from the proposed concept, can hardly be predicted at the moment. At the moment, carsharing schemes have beneficial effects on the environment in terms of declining car ownership, increased use of public transport and by making use of environmentally-friendly vehicles which get exchanged and updated within very short time periods. When integrating driverless vehicle technologies, schemes could become even more attractive for a larger number of customers and these two effects could increase even further. Parking-slot seeking traffic would disappear and so would noise and exhaust emissions

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caused by it. The environment, however, may also be negatively affected. While customers currently have to walk to the next available car, the car would drive to the customer in the proposed concept, creating additional traffic. Moreover, the Jevons Paradox suggests that making something more efficient will consequently lead to an increased use which offsets the initial savings (Owen, 2010 [online]). The Jevons Paradox may apply to the realised concept, but there is also a chance it may not, depending on various aspects ranging from the overall success of

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69 such a programme, the impact on public transport and car ownership, to the emissions of carsharing fleets or whether electricity for electric cars comes from renewables. Therefore it may need attention in the future to develop counter-strategies in due time. 3.4.4 Politics While communal politicians have recognised the potential of carsharing to reduce car ownership, emissions and traffic in their communities (Der Senator für Bau, Umwelt und Verkehr, 2005 [online]; Senatsverwaltung für Stadtentwicklung, 2006 [online]), politicians on the national level struggle to reflect these advantages in required legislation (Lühmann, 2010 [online]). Draft laws which sought to increase the number of available parking spaces, for example, failed to pass the parliament several times (Brenner, 2011b [online]). This was due to lobbying of hire car companies which feared to lose out against carsharing providers (Brenner, 2011b [online]). On another occasion, public transport companies successfully lobbied against the establishment of more parking spaces for carsharing vehicles in Berlin out of the fear to lose customers (Schlesiger, 2011 [online]). These lobbying activities cannot only be observed against carsharing providers, but also in general in the industry. The taxi association BZP, for example, lobbied successfully against a new law which, if it had been agreed on, would liberate customers of hire car companies from the obligation to return a car (BZP, 2011 [online]). This lobbyism can take the form of a business war (“Gewerbekrieg”) (BZP, 2011 [online]) and thus needs to be considered by carsharing providers when proposing a concept which could potentially affect vast parts of hire car and taxi companies’ businesses. Using multi-stakeholder approaches to alter existing carsharing schemes in collaboration with instead of in competition to hire car and taxi companies, may be key for fast business growth. BMW’s and Daimler’s joint venture with SIXT (SIXT, 2011 [online]) and Europcar (Daimler, 2011 [online]) respectively, is certainly a first step towards this approach. The strong German taxi industry, with more than 22,000 taxi companies transporting 414 million customers and earning almost €4 billion annually (BZP, 2011 [online]), should be considered Copyright © 2013. Diplomica Verlag. All rights reserved.

in the future as well, in order to facilitate a smooth transition of the market. Considering driverless technologies and German politics, it is also essential to look at the BMVBS, because it creates required legal provisions as well as the required infrastructure for the regular inspection of driverless vehicles. At the moment, the BMVBS takes the view that people should stay responsible for driving at all times (BMVBS, 2011 [online]; DEKRA, 2012 [online]). No developments towards explicitly allowing driverless vehicles, like those in

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the United States (see 3.4.5), can be observed. This indicates that any process which aims at legalising driverless vehicles will have to start at the beginning, from public debates to draft laws and passing final bills. New legislation which would explicitly allow driverless vehicles in other countries, on the other hand, could speed up processes in Germany nonetheless. The experiences and regulations of other countries could be used as a basis to create own legislation which would, according to aims of the BMVBS, strengthen the competitiveness of the German automobile industry in a global environment (BMVBS, 2011 [online]). In the absence of such developments, however, anticipated beneficiaries of this legislation should not expect any fast decisions. Second, German politics will be required to legally initiate a setting up of an infrastructure which is capable of inspecting driverless vehicles in order to check “whether the computers in driverless cars are in good working order” (Cowen, 2011 [online]). Two figures highlight this need: [1] in 41.2% of all break-downs where the ADAC (2012a [online]) had to assist one of its customers, the break-down was caused by an electrical defect. [2] The number of product recalls in the automobile industry has been increasing steadily, from 55 in 1998 to 186 in 2011 (KBA, 2012a [online]). Both figures indicate that break-downs, under certain circumstances even leading to accidents (Kalra, Anderson & Wachs, 2009 [online]), may be increasing with cars which are more dependent on ever new and more systems. Thus it is required to set up a respective infrastructure to inspect driverless vehicles regularly. 3.4.5 Legislation Considering the legislative environment for the proposed concept, carsharing can be and is realised within the existing framework. The only legislative struggle, the establishment of more parking spaces for providers, moreover, would become obsolete with the integration of driverless vehicles. Considering the legislation in regard to driverless vehicles, however, Kalra, Anderson and Wachs (2009, p. ix [online]) formulate the main question: “Who will be

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responsible when the inevitable crash occurs, and to what extent?” The following paragraphs will discuss the legal status quo in Germany and challenges in order to change legislation, as well as latest developments in the United States. First, the current legislative framework needs to be analysed for legal aspects regarding the driver of a car, the certification of a driverless vehicle, as well as the liability of carmakers. In regard to the former, the German legislation is in line with the United Nations Convention on Road Traffic, which Germany acceded in 1973 (United Nations, 1968b [online]). In article 8

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71 section 1, the convention states that “Every moving vehicle … shall have a driver” (United Nations, 1968a [online]), with article 1 (v) defining a driver as a person (United Nations, 1968a [online]). Accordingly, the German legislation implies a considerable human involvement of car drivers (Gasser, n.d. [online]), such as in sec. 3 (1) of the StVO, which states that the driver of a car shall be able to control the vehicle at all times (Bundesministerium der Justiz, 2010 [online]). This means that current partly-automated systems are legal, because the driver has to monitor the system and is able to intervene at any given time (Gasser, n.d. [online]). Also currently planned ADAS will be specifically allowed because developers highlight that drivers will always be in control (Boeriu, 2011 [online]; HAVEit, 2011 [online]; HAVEit, 2011b [online]; Hoeger et al, 2011 [online]). The project group Automation: Legal Consequences of Increasing Vehicle Automation of the BASt, however, believes that highly and fully-automated systems would be prohibited by the StVO because the driver would act illegally at times when he or she does not monitor the system and thus omit acting in traffic (Gasser, n.d. [online]). Because Germany is currently bound to the convention, authorizing driverless vehicles would imply breaching the convention. It would be possible, according to article 49 though, to change sections of the convention with the support of at least two-thirds of all parties (United Nations, 1968a [online]) or, in case of being in dispute over the interpretation or application of parts of the convention, to declare that one does not consider oneself bound to the convention according to article 52 (United Nations, 1968a [online]). Article 60 (d) Annex 1 states, for example, that “Contracting Parties may grant exemptions … in respect of … vehicles of a special form or type.” Such interpretive disputes could be used in the short term until a final decision with at least two-thirds of the contracting parties has been agreed on. In regard to the certification of driverless vehicles, the German certifying organisation KBA (2012b [online]) grants certificates according to three standards: [1] national standards in accordance with sec. 20, 22 and 22a of the Straßenverkehrs-Zulassungs-Ordnung (StVZO,

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National vehicle safety standard); [2] European standards from the European Community (EC), which are suggested by the European Commission and passed by the European Parliament; and [3] international standards by the United Nations’ Economic Commission for Europe (ECE). The latter determines standards for the national and European level, which are worked out by the United Nations Working Party 29 (WP 29), the so-called World Forum for Harmonization of Vehicle Regulations (UNECE, n.d. [online]). Through agreements of the WP 29, which are “updated on a regular basis in line with technical progress … countries

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incorporate innovations in vehicle technology [but can also] prohibit … products from entering their markets” (UNECE, p. 18, 2012 [online]). Considering the different technological approaches from Google and the automobile industry, reaching consensus so that cars can be certified for different markets may be subject to a long process in which different views concerning safety considerations but also economic interests have to be overcome. As a European country, on the other side, Germany could at least benefit by the European Council Directive 70/156/EEC, article 7, which states that “a whole vehicle or vehicle components, certified in one of the European states … cannot be excluded from markets of other states” (European Union, 1970 [online]). Was the European legislation to change in favour of driverless vehicles in the future, it would mean that once a system has been certified, it could be used in and sold to other European states immediately. This would benefit carsharing providers with schemes in other European countries by making use of driverless vehicles in those programmes as well. Concerning the product liability, the project group Automation: Legal Consequences of Increasing Vehicle Automation assumes that any damage caused by a driverless car would lead to a case of product liability (Gasser, n.d. [online]) under the Produkthaftungsgesetz (ProdHaftG, product liability act) in combination with section 823 (1) of the Bundesgesetzbuch (BGB, Civil Code). This is due to the fact that, because the car driver would neither be required to monitor the system at all times nor to intervene suddenly, resulting damage from an accident can by definition only be caused by a defective system (Gasser, n.d. [online]). This poses one major, if not the biggest obstacle to the introduction of driverless vehicles. Current regulations would shift the entire responsibility for traffic accidents caused by cars to manufacturers (Kalra, Anderson & Wachs, 2009 [online]). Considering that malfunctioning systems could lead to huge financial regresses, Kalra, Anderson and Wachs (2009, p. 22 [online]) note that “manufacturers may be reluctant to introduce technology that will increase their liability.” Because this delay, however, may be inefficient from an econom-

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ic perspective (Kalra, Anderson & Wachs, 2009 [online]), policy makers are required to change the legislative framework. As early as 2006, Brühning noted that German legislation needs to adapt to new technological possibilities and that, if carmakers were not putting any pressure on policy-makers, new laws are unlikely to be discussed and passed (DVR, 2006 [online]). Six years later, the situation has remained the same with German politicians such as Steffen Bilger, member of the traffic commission in the German Bundestag, showing interest

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73 in the topic but negating the importance to act anytime soon (Eichhorn, J., personal communication [email] 16/7/2012). The legislation in the United States, on the other hand, is in some instances ahead of the German one. In a general debate whether autonomous driving is allowed because it is not explicitly illegal (Calo, 2011a [online]), Nevada, host of DARPA’s Grand Challenges, was the first state that officially adopted a driverless vehicle regulation allowing to test drive autonomous vehicles on 1 March 2012 (Walker Smith, 2012g [online]), with other states already working towards similar regulations (Walker Smith, 2012b,c,f [online]). Nevada’s adopted regulation LCB File No. R084-11 allows the testing of driverless vehicles (Nevada DMV, 2012c [online]) according to Article 60 (c) of the UN Convention on Road Traffic which allows granting exemptions to “Vehicles used for experiments whose purpose is to keep up with technical progress and improve road safety.” The new legislation, Nevada believes, puts it “at the forefront of autonomous vehicle development” (Nevada DMV, 2012a [online]). It allows companies to test driverless vehicles on public roads under certain restrictions, such as having proved that the technology has already successfully travelled for at least 10,000 miles in autonomous mode (sec. 8. 3. (b), ensuring that at least two persons are physically present when driving in autonomous mode (sec. 10. 1.), and depositing a surety bond of at least $1,000,000 for any claims that could result from accidents caused by driverless vehicles (sec. 8. 4.) (Nevada DMV, 2012c [online]). Sec. 16. 1., moreover, describes under which conditions “an autonomous vehicle may be offered for sale by a licensed vehicle dealer in this State” (Nevada DMV, p. 13, 2012c [online]). The DMV, however, does currently only accept applications for testing (Nevada DMV, n.d. [online]) and in May 2012, Google’s self-driving vehicles were the first to receive a licence by Nevada’s DMV (Nevada DMV, 2012a [online]). In regard to Nevada’s regulatory approach, Walker Smith (personal communication [email] 12/7/2012) notes that “Nevada is largely betting that corporate reputation rather than government regulation will be key to ensuring that these systems are safe.” Whether this “debat-

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able approach” (Walker Smith, B., personal communication [email] 12/7/2012) will succeed, can hardly be said at this point. However, it allows companies, Google as well as carmakers such as BMW and Daimler, to test their technologies and, in case of accident-free tests, will likely increase society’s willingness to accept and/or adapt this new technology. These developments have not yet impacted on European or German legislation, but as mentioned above, they may form a foundation which allows quick adaptation in the future. 3.4.6 Ethics

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The classical ethical quandary primarily revolves around fictive situations in which a driverless car would not be able to prevent an accident anymore, with each option left leading to a different accident (Walker Smith, 2012h [online]). When the car can decide, for example, whether to strike a motorcyclist or being crushed by a truck, “how should [it] balance the welfare of its occupants with the welfare of others“ (Walker Smith, 2012h [online]). Such debates, it can be argued, are likely to arise with the introduction of and also after the first accidents had been caused by driverless vehicles. However, the occurrence of such incidents is presumably marginal and, from an overall road safety point of view, rather insignificant. Considering previous debates on injuries and road fatalities which had been caused by airbags and making use of seatbelts, the overall safety gain of driverless vehicles can be expected, as seatbelts and airbags proved for these technologies, to offset disadvantages considerably, leaving little argument to the debate in the long run. 3.4.7 Demographics expects that the currently 81.2 million inhabitants of Germany will decrease to somewhere between 69.4 to 73.6 million inhabitants by 2050 (Statistisches Bundesamt, 2012f [online]). At the same time, the share of young people is expected to decline while the share of older people is expected to increase, as shown in table 7. It is remarkable that the number of people aged 79 years and older will be larger for both the lower and upper threshold predictions, than the share of people who are younger than 18. Moreover, the share of people aged above 65 years will almost be as large as the share of people aged below 40 (30.5-31.8% vs. 36-36.6%), which implies that almost two thirds of the German population will be older than 40 by 2050. This group is currently termed the young generation, the very same group that shows signs of changed mobility behaviour. This is a considerable development and will certainly impact on the chances of the proposed concept. The increasing share of the elderly among the total population will require increased

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efforts to ensure their mobility (BMVBS, 2011 [online]). Carsharing has the potential to provide this group with mobility which is more flexible and easier to use than public transport and cheaper than using a taxi. By making use of driverless vehicles, moreover, the physical deficits of the elderly which could be a factor in causing accidents would be negligible. The proposed concept would thus not only offer a new form of flexible mobility to the elder German society, but also offer a relatively new target group for carsharing providers compared to the majority of current customers.

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75  Age

 Year

 017

 2009 2050lowerestimation 2050upperestimation





1825

2009 2050lowerestimation 2050upperestimation





2639

2009 2050lowerestimation 2050upperestimation





4065

2009 2050lowerestimation 2050upperestimation





6679

2009 2050lowerestimation 2050upperestimation





79and older

2009 2050lowerestimation 2050upperestimation





Total populaon

2009 2050lower 2050upper 





 Population

Shareof populationin%

 Relativechange comparedto 2009in% 

13,470,000 9,521,000 10,217,000

16.5 13.7 13.9

 16.8 15.8







7,740,000 5,089,000 5,450,000

9.5 7.3 7.4

 22.6 21.8

13,980,000 10,348,000 11,265,000

17.1 14.9 15.3

 12.8 10.5

30,587,000 22,394,000 24,211,000

37.4 32.3 32.9

 13.8 12.1

11,818,000 11,841,000 12,169,000

14.5 17.1 16.5

 +18.0 +14.3

4,133,000 10,225,000 10,291,000

5.1 14.7 14.0

 +191.3 +176.5









 15.1 9.9

81,735,000 69,412,000 73,608,000



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Table7.ExpecteddemographicchangeinGermanyby2050 AccordingtodataoftheStasschesBundesamt(2012f[online])



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Conclusion The study at hand proposes to integrate driverless vehicles in commercial carsharing schemes in Germany. Whereas one component, commercial carsharing, has been realised by the German carmakers BMW and Daimler for the case study of Germany, the second component, driverless vehicles, is in development and is expected to be marketable within the next two decades. By analysing current social developments and societal issues in regard to both components, the study found that driverless vehicles integrated in carsharing schemes have the potential to do both responding to social change by offering a new and flexible mode of transport, and tackling the societal issue of traffic accidents by improving the safety of passengers and other road users significantly. In terms of carsharing, the study found that the proposed concept can tackle some of the current limitations very well. The issue drawing currently the biggest attention, limited parking spaces, would disappear because vehicles could drive either to the next customer, a petrol or charging station, the maintenance or an available, free-of-charge parking space. Limitations of carsharing in regard to the availability of vehicles would also be reduced, because neither would customers have to walk to vehicles anymore nor would the scheme be needed to be limited to a certain business area. Only one limitation explored in part one, the total number of available cars, depends on providers’ willingness to offer a sufficient number of vehicles, and can thus not directly be influenced by the concept. With a sufficiently large demand, however, there would be no reason why providers could not operate as many cars as they want, because the issue of parking spaces, the initial reason which may limit the number of available cars in the current legislative environment, would become obsolete. Regarding traffic accidents, the study has shown that most traffic accidents are caused by erratic behaviour of human drivers. Whether it is distractions, deliberate non-compliance with traffic regulations or physical deficits in the elderly, which lead to accidents, by making use

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of driverless vehicles these accidents are expected to decline significantly, if not disappear almost completely. Ethical questions surrounding the question how driverless vehicles should react in case of an inevitable accident, it has been shown, are important in the public debate to highlight system limitations and for carmakers to come up with smart solutions. However, it is neither likely that this very marginal number of traffic accidents will delay the introduction of driverless vehicles, nor should the introduction of a technology be delayed which is expected to benefit the overall road safety significantly. Driverless vehicles will never be

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77 perfect (Walker Smith, 2012h [online]) and carmakers and politicians would be wise to not claim anything else. Rather should they remind their opponents that software can be improved incrementally (Vanderbilt, 2012e [online]) while “To err is human” (Euro RAP & Euro NCAP, 2011, p. 5 [online]). By showing in the analysis that the proposed concept offers many new features which will likely attract new and more customers, the study indicates that with an increasing availability and penetration of carsharing schemes, the positive effect of driverless vehicles on road safety could become more and more significant. For carmakers, on the other hand, the proposed concept offers a chance to face some of the biggest challenges in the automobile industry since the invention of the motorcar (BMW, 2008 [online]). On the one hand, it is highlighted that driving has remained essentially unchanged in the past century but “has been completely transformed [by driverless vehicle technologies] in just the past half decade” (Vanderbilt, 2012a [online]). This means that the importance to distinguish one from competitors through the driving task or even by the safety equipment and systems will eventually diminish steeply. On the other hand, social change leading to new mobility behaviour might negatively affect private car ownership and thus the main business of carmakers. The study has shown that the decision of carmakers to become active in other mobility markets can be considered wise. Not only does it seem unlikely that the observed social change will be completely reserved, but growing customer numbers also show that there is demand for new forms of mobility. The successful expansion of schemes to other cities, countries and continents indicates that there is a profitable global market potential of carsharing which may be able to offset losses in the core business in the long term. The proposed concept analysed the logical step in the future, to combine driverless vehicle technologies in such carsharing schemes. The current technological status quo indicates that autonomous systems will be available eventually, and the legislative environment to allow such vehicles is already about to change, if only in the United States at this moment. Because of the strong standing of the automobile industry in Germany, however, it can be expected Copyright © 2013. Diplomica Verlag. All rights reserved.

that similar laws and regulations will follow, the more urgent and pressing the issue becomes. Moreover, studies in the United States show that a significant number of customers could already imagine buying and making use of cars with driverless vehicle technologies. Because of the currently high costs of such systems, however, it has also been shown that making customers familiar with innovative technologies in carsharing schemes might be the first step which leads to a widespread adaptation. So is it possible that the ultimate introduction of driverless vehicles may be accompanied by a brief period of resistance in the population,

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however, it can be expected that it would fade quickly when the system begins to feel natural (Vanderbilt, 2012a [online]). Much like “it would feel strange to be in an elevator run by a human operator,” Vanderbilt (2012a [online]) notes, “it’s the absence of technology that begins to feel uncomfortable.” This research concentrated on the perspective of carmakers and thereby had to neglect other issues that require further research. Consequences for the society overall, for example, need further assessment. A realisation of the proposed concept could constitute a very attractive mode of transport for many people that use public transport, walk or ride a bicycle at the moment, which means that traffic density could increase despite lower car ownership. Moreover, companies but also individuals may make use of such schemes by transporting documents, medicine, tools, groceries or any products, putting further pressure on traffic infrastructures. On the other hand, employment in mobility and transport industries could be destroyed. More research will also be required to investigate the feasibility of the proposed concept in other countries than Germany. Especially in urban agglomerations in countries with developing or emerging economies, where the population and the share of the urban population increase steadily, a realisation of the proposed concept would certainly require adjustments to meet local demands.

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Recommendaons The analysis has shown that a few factors, such as the changing mobility behaviour of the German society, can hardly be influenced by carmakers. However, carmakers could become active in a few fields and they should not hesitate to do so. First, the study has found that driverless vehicles cannot be operated under current laws. For one, Germany is a member to the United Nations Convention on Road Traffic which states that cars need to be driven by humans. On the other hand, current product liability regulations would shift the complete responsibility and thus the complete financial regress of each single accident to carmakers. Because both provisions prevent the legal operation of driverless vehicles in Germany and could, in the long term and if unchanged, damage the competitiveness of the German automobile industry, carmakers should advocate the new technology actively. In the United States, for example, a lively debate started about whether or under which circumstances driverless vehicles should be legal, only after Google announced in 2010 its tests which came as a “terrestrial Sputnik shock“ (Vanderbilt, 2012a [online]). It took two years until the first state passed a bill to allow the testing of such vehicles. Moreover, studies have shown that a third of people living in the United States would purchase cars with driverless vehicle technologies. Not only are there no similar figures for Germany available, but the whole debate is basically non-existent in the German society, even for ADAS (IRM WG, 2010 [online]), despite the fact that driverless vehicle technologies have the potential to benefit the society as a whole. Not only the government but also the society would benefit from fewer traffic accidents and their costly consequences. The result from the combination of driverless vehicles and carsharing schemes, moreover, offers additional advantages. While the young generation could make use from more flexible and less time consuming transport, the elderly would be enabled to travel more easily. In the long term, the fuel efficiency and traffic flow can be expected to increase, while noise and exhaust emissions would be reduced due to sophisticated anticipatory driving. These aspects need to be highlighted as potential Copyright © 2013. Diplomica Verlag. All rights reserved.

benefits of driverless vehicles in carsharing schemes in any debate, but can also be used individually for either one. Moreover, taking the fear from politicians and potential customers by developing a safety system which could bring the car to a halt as described in 3.4.2 could further increase the acceptance among the population. Therefore it is strongly recommended that carmakers help initiating this debate very soon.

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Second, instead of letting the debate taking its own course, carmakers should try to channel the debate in a way that is beneficial to their own business. Especially when considering the competition, it means that any action should be wisely coordinated and done in collaboration with potential competitors. The analysis has shown that carsharing providers could easily be involved in business wars and that heavy lobbying of other mobility sectors against beneficial legislation for carsharing schemes can be expected. Any delay, however, could eventually also mean a disadvantage for the German car industry overall. In case carmakers are forced to shift their facilities and research entities to other countries, competences and human capital would leave as well. It is thus important to facilitate some kind of cooperation with other competitors in order to not only enable a smooth introduction of the proposed concept but also in order to take advantage of the strengths of other providers. Third, considering the technology for driverless vehicle technologies, carmakers should make intensive use of the opportunity to test their systems in Nevada and other states where testing will be allowed in the future. While it may prove impossible to drive 500 million km and more (see 3.4.2), every additional autonomously driven kilometre will strengthen the faith of the public in this new technology. Moreover, test kilometres can be used initially to distinguish one from competitors when introducing the technology. Considering that Google has already travelled half a million kilometres, BMW and Daimler should use their already existing systems and test them more extensively. Fourth, because the driverless car will neither be available tomorrow nor is it likely that a fully-autonomous car journey will be the first automated technology that customers experience, carmakers need to develop long-term strategies of how to incorporate these technologies so that customers will accept them. BMW’s TrackTrainer, an autonomous technology for race courses which the company uses in “driver training sessions to give participants a genuine feel [as if they were sitting] behind the wheel and not [on] the passenger seat” (Boeriu, 2011 [online]), is one way to communicate the possibilities of this new technology. Copyright © 2013. Diplomica Verlag. All rights reserved.

Another will be the directed use of automated technologies in carsharing schemes, such as the traffic jam assistant or piloted parking as planned for the BMW i3. An increased use of these technologies will help customers to become familiar and feel safe with these technologies, despite high costs and the possible negative effect on profits. Fifth, with an evolving technology, carmakers will hardly be able to distinguish themselves from competitors in terms of the driving experience and the safety technology. While this can

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81 be offset when selling cars, for example, through design or equipment with premium interior, distinguishing oneself sustainably and successfully from other carsharing competitors may be more challenging. Carmakers should begin to explore innovative concepts to offer a unique travel experience to different target groups so that they will not be reduced to the price of their offer. Sixth, with Google taking another approach than German carmakers, a big question is which system will be marketable first. Carmakers should be prepared for the case that Google’s system goes on sale first and what consequences a product, which could theoretically be attached to any vehicle, might have. Cooperation such as suggested above with other competitors like taxi or hire car companies, for example, could prove beneficial to convince those partners that waiting for own systems will be beneficial. Even a cooperation with Google should not be ruled out entirely because it might offer benefits in the short term. These recommendations constitute some of the most pressing points. While the concept will not be realised without a functioning technology, it is important to prepare customers, politicians and competitors alike that the mobility as we know it is about to change fundamentally. Driverless vehicles are likely to play a major role in future traffic systems, and

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carsharing would be a smart way to make use of this technology.

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Copyright © 2013. Diplomica Verlag. All rights reserved. Kowalski, Daniel. The Integration of Driverless Vehicles in Commercial Carsharing Schemes in Germany: A Prefeasibility Study : A Prefeasibility Study, Diplomica Verlag, 2013.

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