Explainable Artificial Intelligence for Autonomous Vehicles: Concepts, Challenges, and Applications

Explainable AI for Autonomous Vehicles: Concepts, Challenges, and Applications is a comprehensive guide to developing and applying explainable artificial intelligence (XAI) in the context of autonomous vehicles. It begins with an introduction to XAI and its importance in developing autonomous vehicles. It also provides an overview of the challenges and limitations of traditional black-box AI models and how XAI can help address these challenges by providing transparency and interpretability in the decision-making process of autonomous vehicles. The book then covers the state-of-the-art techniques and methods for XAI in autonomous vehicles, including model-agnostic approaches, post-hoc explanations, and local and global interpretability techniques. It also discusses the challenges and applications of XAI in autonomous vehicles, such as enhancing safety and reliability, improving user trust and acceptance, and enhancing overall system performance. Ethical and social considerations are also addressed in the book, such as the impact of XAI on user privacy and autonomy and the potential for bias and discrimination in XAI-based systems. Furthermore, the book provides insights into future directions and emerging trends in XAI for autonomous vehicles, such as integrating XAI with other advanced technologies like machine learning and blockchain and the potential for XAI to enable new applications and services in the autonomous vehicle industry. Overall, the book aims to provide a comprehensive understanding of XAI and its applications in autonomous vehicles to help readers develop effective XAI solutions that can enhance autonomous vehicle systems’ safety, reliability, and performance while improving user trust and acceptance.

This book:

• Discusses authentication mechanisms for camera access, encryption protocols for data protection, and access control measures for camera systems.
• Showcases challenges such as integration with existing systems, privacy, and security concerns while implementing explainable artificial intelligence in autonomous vehicles.
• Covers explainable artificial intelligence for resource management, optimization, adaptive control, and decision-making.
• Explains important topics such as vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, remote monitoring, and control.
• Emphasizes enhancing safety, reliability, overall system performance, and improving user trust in autonomous vehicles.

The book is intended to provide researchers, engineers, and practitioners with a comprehensive understanding of XAI’s key concepts, challenges, and applications in the context of autonomous vehicles. It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, information technology, and automotive engineering.

Dr. Kamal Malik is currently working as a Professor in CSE in the School of Engineering and Technology at CTU Ludhiana, Punjab, India. She has published Scientific Research Publications in reputed International Journals, including SCI and Scopus indexed Journals such as Adhoc and senior Wireless Networks, 50, Engineering, Technology and Applied Sciences Research, Journals of Advanced Research in Engineering, Research Journal of Applied Sciences of Engineering & Technology(RJASET- Maxwell Sciences), SSRN-Electronic Journal, Design Engineering, Indian Journal of Science and Technology(IJST), International Journal of Computer Applications(IJCA), and many more. She has also attended many National and International Conferences of repute like Springer, and Elsevier in India. Her major research areas are Artificial Intelligence, Machine Learning and Deep Learning, Data Analytics, Computational Neurosciences, and bio-inspired computing. She has more than 13 years of rich Academic and Research experience. She has guided 3 research scholars and currently guiding 8 research Scholars at CT University, Ludhiana. She has worked in renowned Institutes and Universities like RIMT Mandigobindgarh, Maharishi Markandeshwar University, Mullana, GNA University, Phagwara. She has also chaired various sessions in Springer and Elsevier. She has also been awarded with the preeminent researcher award from Green Thinkerz society at CII, Chandigarh. She has completed her Doctor of Philosophy in Computer Science from IKGPTU Kapurthala in 2017, her Masters and Graduation from Kurukshetra University, Kurukshetra in 2009 and 2006 respectively.

Mr. Moolchand Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, GGSIPU Delhi. He has published scientific research publications in reputed international journals and conferences, including SCI-indexed and Scopus-indexed journals such as Expert Systems (Wiley), Cognitive Systems Research (Elsevier), Physical Communication(Elsevier), Journal of Electronic Imaging (SPIE ), Intelligent Decision Technologies: An International Journal, Cyber-Physical Systems (Taylor & Francis Group), International Journal of Image & Graphics (World Scientific), International Journal of Innovative Computing and Applications (Inderscience) and Innovative Computing and Communication Journal (Scientific Peer-reviewed Journal). He has authored/co-authored chapters with international publishers like Elsevier, Wiley, and De Gruyter. He has authored/edited four books with a National/International level publisher (CRC Press, Bhavya publications). His research areas include Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is associated with various professional bodies like IEEE, ISTE, IAENG, ICSES, UACEE, Internet Society, and life membership of the Universal Inovators research lab, etc. He possesses teaching experience more than nine years. He is the co-convener of the ICICC, DOSCI, ICDAM & ICCCN springer Scopus Indexed conference series and ICCRDA-2020 Scopus Indexed IOP Material Science & Engineering conference series. He is also the organizer and co-convener of the International Conference on Innovations and Ideas towards Patents (ICIIP) series. He is also the advisory and TPC committee member of the ICCIDS-2022 Elsevier SSRN Conference. He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group, IJEECS and World Scientific Journal, and many springer conferences. He is also served as a session chair in many international springer conferences. He is a doctoral researcher at DCR University of Science & Technology, Haryana. He completed his Post Graduation in 2012 from SRM UNIVERSITY, NCR CAMPUS, GHAZIABAD, and Graduated in 2010 from KNGD MODI ENGG. COLLEGE, GBTU.

Prof. Suman Deswal holds a Ph.D. from DCR University of Science & Technology, Murthal, India. She completed her M. Tech (CSE) from Kurukshetra University, Kurukshetra, India, and B. Tech (Computer Science & Engg.) from CR State College of Engg., Murthal, India, in 2009 and 1998, respectively. She has 18 years of teaching experience and works as a Professor in the Department of Computer Science and Engineering at DCR University of Science and Technology, Murthal, India. Her research area includes wireless networks, heterogeneous networks, distributed systems, Machine Learning and Bioinformatics. She has many research papers to her credit in reputed journals, including SCI-indexed and Scopus-indexed Journals and conferences. She is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, and International IEEE & Springer Conferences.

Dr. Umesh Gupta is currently an Associate Professor at the School of Computer Science Engineering and Technology at Bennett University, Times of India Group, Greater Noida, Uttar Pradesh, India. He received a Doctor of Philosophy (Ph.D.) (Machine Learning) from the National Institute of Technology, Arunachal Pradesh, India. He has awarded a gold medal for his Master of Engineering (M.E.) from the National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India, and Bachelor of Technology (B.Tech.) from Dr. APJ, Abdul Kalam Technical University, Lucknow, India. His research interests include SVM, ELM, RVFL, machine learning, and deep learning approaches. He has published over 35 referred journal and conference papers of international repute. His scientific research has been published in reputable international journals and conferences, including SCI-indexed and Scopus-indexed journals like Applied soft computing (Elsevier) and Applied Intelligence (Springer), each of which is a peer-reviewed journal. His publications have more than 158 citations with an h-index of 8 and an i10-index of 8 on Google Scholar as of March 1, 2023. He is a senior Member of IEEE (SMIEEE) and an active member of ACM, CSTA, and other scientific societies. He also reviewed papers for many scientific journals and conferences in the US and abroad. He led sessions at the 6th International conference (ICICC-2023), 3rd International Conference on Data Analytics and Management (ICDAM 2023), the 3rd International Conference on Computing and Communication Networks (ICCCN 2022), and other international conferences like Springer ETTIS 2022 and 2023. He is currently supervising two Ph.D. students. He is the co-principal investigator (co-PI) of TWO major research projects. He published three patents in the years 2021-2023. He also published four book chapters with Springer, CRC.

Mr. Deevyankar Agarwal is a lecturer at the University of Technology and Applied Sciences in Muscat, Oman. He works in the Engineering Department, EEE Section (Computer Engineering), . He has 22 years of teaching and research experience. He is currently a doctoral researcher at the University of Valladolid, Spain. He has written several research papers that have been published in Springer, Elsevier, and Taylor & Francis international journals. Also, he has published various papers in IEEE international conferences and national conferences. He is a reviewer for Springer’s Journal as well as for many IEEE conferences. He is also served as a session chair in many international springer conferences. His research areas include optimization of algorithms in Artificial Intelligence, Deep Learning, Machine Learning for healthcare sector.

Dr. Yahya Obaid Al Shamsi is working as the Dean of Engineering at the University of Technology and Applied Sciences in Muscat, Oman. He has 25 years of teaching and research experience. He got his PhD from the University of Bath, Department of Architecture and Civil Engineering, UK. He has published various research papers in the international journals of Springer and Elsevier. He is a reviewer for Springer’s Journal as well as for many IEEE conferences. He is also served as a session chair in many international springer conferences.