Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Tran
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English Pages 286 Year 2023
Table of contents :
Cover
Half Title
Title Page
Copyright Page
Contents
Preface
Contributors
SECTION I: Toward Explainable ITS
CHAPTER 1: Explainable Artificial Intelligence for Intelligent Transportation Systems: Are We There Yet?
SECTION II: Interpretable Methods for ITS Applications
CHAPTER 2: Towards Safe, Explainable, and Regulated Autonomous Driving
CHAPTER 3: Explainable Machine Learning Method for Predicting Road-Traffic Accident Injury Severity in Addis Ababa City Based on a New Graph Feature Selection Technique
CHAPTER 4: COVID-19 Pandemic Effects on Traffic Crash Patterns and Injuries in Barcelona, Spain: An Interpretable Approach
CHAPTER 5: Advances in Explainable Reinforcement Learning: An Intelligent Transportation Systems Perspective
CHAPTER 6: Road-Traffic Data Collection: Handling Missing Data
CHAPTER 7: Explainability of Surrogate Models for Traffic Signal Control
CHAPTER 8: Intelligent Techniques and Explainable Artificial Intelligence for Vessel Traffic Service: A Survey
CHAPTER 9: An Explainable Model for Detection and Recognition of Traffic Road Signs
CHAPTER 10: An Interpretable Detection of Transportation Mode Considering GPS, Spatial, and Contextual Data Based on Ensemble Machine Learning
CHAPTER 11: Blockchain and Explainable AI for Trustworthy Autonomous Vehicles
SECTION III: Ethical, Social, and Legal Implications of XAI in ITS
CHAPTER 12: Ethical Decision-Making under Different Perspective-Taking Scenarios and Demographic Characteristics: The Case of Autonomous Vehicles
Index