The Future of Intelligent Transport Systems

The Future of Intelligent Transport Systems

ISBN-10:
0128182814
ISBN-13:
9780128182819
Pub. Date:
02/24/2020
Publisher:
Elsevier Science
ISBN-10:
0128182814
ISBN-13:
9780128182819
Pub. Date:
02/24/2020
Publisher:
Elsevier Science
The Future of Intelligent Transport Systems

The Future of Intelligent Transport Systems

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Overview

The Future of Intelligent Transport Systems considers ITS from three perspectives: users, business models and regulation/policy. Topics cover in-vehicle applications, such as autonomous driving, vehicle-to-vehicle/vehicle-to-infrastructure communication, and related applications, such as personalized mobility. The book also examines ITS technology enablers, such as sensing technologies, wireless communication, computational technology, user behavior as part of the transportation chain, financial models that influence ITS, regulations, policies and standards affecting ITS, and the future of ITS applications. Users will find a holistic approach to the most recent technological advances and the future spectrum of mobility.


Product Details

ISBN-13: 9780128182819
Publisher: Elsevier Science
Publication date: 02/24/2020
Pages: 272
Product dimensions: 6.00(w) x 9.00(h) x (d)

About the Author

George Dimitrakopoulos is Assistant Professor at the Department of Informatics and Telematics of Harokopio University of Athens. His research interests include optimization and performance evaluation of wireless systems, applications of wireless networks, intelligent transport systems, autonomous driving and smart radio systems. He has authored more than 150 articles and is involved in research and development projects in transportation and urban mobility.

Lorna Uden is Professor Emeritus in the Department of Computing at Staffordshire University in UK. Her research interests include learning technology, web engineering and technology, big data, knowledge management, and the Internet of Things. She has authored more than 200 papers and is on the editorial board of several international journals, including as the founder and editor-in-chief for the International Journal of Web Engineering and Technology, and the International Journal of Learning Technology. She has been invited as keynote speaker at many international conferences and visiting professor at many universities internationally. She is the conference chair for both KMO and LTEC. She also travels widely to give workshop on Problem Based Learning.

Iraklis Varlamis is Associate Professor of Data Management at the Department of Informatics and Telematics at the Harokopio University of Athens. His research interests span data-mining and knowledge extraction from social media, to intelligent systems and machine learning with application in recommender systems and personalization. He has co-authored three books and more than 130 papers concerning graph and text mining, data analytics, intelligent systems and personalization and has more than 2000 citations on his work. He holds a patent from the Greek Patent Office and an application pending from the US patent office. He is been involved on several EU funded projects concerning intelligent systems, machine learning, and data mining on the industrial and automotive domain.

Table of Contents

PART ONE: ITS Technology enablers1. Sensing and perception systems for ITS2. Communication advances and ITS3. Computing technologies: platforms, processors and controllers

PART TWO: ITS users4. User requirements and preferences for ITS5. Co-creation of value for user experiences6. ITS and their users: classification and behavior7. User acceptance and ethics of ITS

PART THREE: ITS business models8. ITS and economic growth9. Impact of ITS advances on the industry10. ITS business and revenue models11. ITS and marketing12. Societal impact of ITS

PART FOUR: ITS regulations, policies and standards13. ITS and sustainability14. ITS standardization bodies and standards15. ITS programs and strategies worldwide

PART FIVE: The future of ITS applications16. Transportation network applications17. Autonomous Driving levels and enablers18. Intelligent Transport Systems and Smart Mobility19. Big Data Analytics for Intelligent Transportation Systems20. Personalized Mobility Services and AI21. Integrated mobility for smart cities22. ITS and blockchain23. Conclusions and way forward

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Takes a holistic approach to the most recent technological advances, addressing the entire spectrum of future mobility

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