Explainable Artificial Intelligence for Intelligent Transportation Systems: Ethics and Applications

✍ Scribed by Loveleen Gaur, Biswa Mohan Sahoo

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 103
• Category: Library

✦ Synopsis

Transportation typically entails crucial “life-death” choices, delegating crucial decisions to an AI algorithm without any explanation poses a serious threat. Hence, explainability and responsible AI is crucial in the context of intelligent transportation. In Intelligence Transportation System (ITS) implementations such as traffic management systems and autonomous driving applications, AI-based control mechanisms are gaining prominence.

Explainable artificial intelligence for intelligent transportation system tackling certain challenges in the field of autonomous vehicle, traffic management system, data integration and analytics and monitor the surrounding environment.

The book discusses and inform researchers on explainable Intelligent Transportation system. It also discusses prospective methods and techniques for enabling the interpretability of transportation systems. The book further focuses on ethical considerations apart from technical considerations.

✦ Table of Contents

Preface
Acknowledgments
Contents
List of Figures
List of Tables
About the Authors
Abbreviations
Chapter 1: Introduction to Explainable AI and Intelligent Transportation
1.1 Introduction
1.2 Intelligent Transportation Systems
1.3 AI and Infrastructure to Support ITS
1.4 Overview of ITS Applications
1.5 XAI in Aviation and Transportation System
1.6 Intelligent Transportation Systems Past, Present, and Future
1.7 Conclusion
References
Chapter 2: Intelligent Transportation Technology Enablers
2.1 Introduction
2.2 Autonomous Vehicles
2.3 HetVNETs
2.4 AVNS
2.5 FIT
2.6 Digital Maps
2.7 Conclusion
References
Chapter 3: Artificial Intelligent Algorithm Based on Energy Efficient Routing for ITS
3.1 Introduction
3.2 Background Study
3.3 Proposed Work: EER-SHO
3.4 Simulation Setting
3.5 Simulation Results
3.6 Conclusion
References
Chapter 4: Intelligent Transportation System: Modern Business Models
4.1 Introduction
4.2 ITS and Economic Growth
4.2.1 COVID-19 and ITS
4.3 Impact of ITS Advances on the Industry
4.4 ITS Business Models: Ticketing as a Service
4.5 Market Trend of ITS
4.6 Societal Impact of ITS
4.7 Conclusion
References
Chapter 5: Explainable AI in ITS: Ethical Concerns
5.1 AI and Sustainability
5.2 Transportation Network Applications
5.2.1 Accidents Detection
5.2.2 AI Predictive Models
5.2.3 AI in the Airline Industry
5.2.4 AI in Security
5.2.5 AI in Automatic Vehicle Location
5.3 Autonomous Driving Levels and Enablers
5.3.1 Level 0: There Is No Automation
5.3.2 Level 1: Driver Assistance
5.3.3 Level 2: Partial Automation
5.3.4 Level 3: Conditional Automation
5.3.5 Level 4: High Level of Automation
5.3.6 Level 5: Full Automation
5.4 Personalised Mobility Services and AI
5.5 Conclusion
References