Artificial Intelligence (A) is transforming transportation by enabling intelligent, adaptive, and data-driven mobility systems capable of addressing growing urbanization and sustainability challenges. By leveraging machine learning, computer vision, natural language processing, and advanced data analytics, AI enhances traffic prediction, autonomous navigation, safety monitoring, and infrastructure management. These technologies allow transportation networks to respond in real time to changing conditions, reduce congestion and emissions, improve road safety, and optimize resource utilization. AI also plays a central role in integrating vehicles, users, and infrastructure into cohesive smart mobility ecosystems. As transportation systems evolve toward automation, connectivity, and sustainability, AI emerges as a foundational enabler for resilient, efficient, and future-ready transportation networks worldwide.
The book offers a comprehensive and forward-looking examination of AI’s expanding role in modern transportation. The book spans foundational principles and advanced innovations, beginning with intelligent transportation systems and progressing to specialized areas such as AI-driven driving analytics, smart traffic control, and augmented-reality-based safety navigation. It further explores emerging frontiers including autonomous vehicle intelligence, edge-AI frameworks, 6G-enabled mobility, quantum computing, generative AI for infrastructure design, and robust vehicle-to-vehicle communication systems. By integrating theory, applications, and future trends, the book presents a holistic vision of how AI can build safer, smarter, and more sustainable transportation ecosystems while supporting the broader evolution of smart cities.
This book is designed for researchers, engineers, industry professionals, urban planners, policymakers, and advanced students engaged in transportation, artificial intelligence, and smart city development. It serves as both a practical reference and a visionary guide for those seeking to understand, design, and deploy AI-enabled transportation solutions, while supporting informed decision-making and innovation in global mobility systems.
Table of Contents:
Preface. 1. Role of Artificial Intelligence in Transportation Systems. 2. Intelligent Transportation Systems: A Comprehensive Review of Technologies, Applications, and Future Trends. 3. Role of AI in Traffic Safety and Prevention of Accidents. 4. Artificial Intelligence for Measuring Transportation Comfort: A Comprehensive Review. 5. AI-powered Driving Analytics: Understanding Driver Behavior through Data. 6. Smart Vision: Powering Vehicle Detection with Deep Learning. 7. Quantum Computing and Communication for Intelligent Transportation System Networks: Exploring Qubit-based Innovations in Cryptography and Optimization Frontiers. 8. Generative AI-based Framework for Road Infrastructure Design in Intelligent Transportation Systems. 9. Neural Network–driven Driver Wellness Analytics: Predicting Mental Fatigue through Whole-Body Vibration Patterns and Psychosocial Health Monitoring. 10. AR and AI for Driver Assistance and Navigation. 11. The Invisible Highway: Integrating Artificial Intelligence with 6G Next-Generation Mobility. 12. Development of Machine Intelligence for Self-driving Vehicles Through Video Capturing. 13. Harnessing Edge AI for Real-Time Telematics: A Framework for Low-Latency Vehicle Data Analytics. 14. Quantum Machine Learning for Next-Gen Wireless: Fundamentals and Path Ahead. 15. AI Foundations for Reliable V2V Communication.
About the Author :
Dr. Dhanashree Kulkarni is Professor, Head of Department of Computer Science and Engineering and Dean Academics at SAEF’s Angadi Institute of Technology and Management (AITM), Karnataka, India. She has a PhD from the Faculty of Computer and Information Sciences, from Visvesvaraya Technological University (VTU), Belagavi. Her area of interests includes AI, Machine Learning, Natural Language processing, data analytics, intelligent transportation systems and cybersecurity. She has contributed significantly to research, with publications in reputed international journals and conferences, and holds multiple patents to her credit. She is a member of IEEE ITSS (Intelligent Transportation System Society) and ACM member.
Dr. Anand B. Deshpande is currently the Principal and Director of the Suresh Angadi Education Foundation’s, Angadi Institute of Technology and Management (AITM), Belagavi, Karnataka, India. He has a PhD in Electrical and Electronics Engineering Sciences from VTU, Belagavi, India. His research work has been published in reputed journals, conferences, and books, and he has filed patents in several areas. He has edited 2 volumes, Intelligent Designs, Innovations and Sustainability in Agriculture 4.0 and Computational Intelligence Methods for Super-Resolution in Image Processing Applications. His research interests include AI, Image and Video Analytics, Data Analytics, and Machine Vision.
Dr. Vania V. Estrela has a M.Sc. degree in ECE from Northwestern University, USA; and a PhD in ECE from the Illinois Institute of Technology (IIT), Chicago, IL, USA. She works at Universidade Federal Fluminense's (UFF), Brazil, Department of Telecommunications. Research interests include Cyber-Physical Systems, Multimedia, Biomedical Engineering, Neuroscience, Unmanned Aerial Systems, Simulation, Smart Designs, Communications, Artificial Intelligence, and Geoprocessing. She edits and reviews for several prestigious publishers. She is engaged in Humanitarian Engineering, Technology Transfer, STEAM Education, Environmental Issues, Digital Inclusion, and all UN Sustainable Development Goals. She has served as editor of more than 20 books and special issues. She has served on a plethora of Technical and Organizational Committees and is a member of IEEE.
