04967cam a22005178i 4500 9781003502432 FlBoTFG 20251030122256.0 m o d cr ||||||||||| 240603s2024 flu ob 001 0 eng OCoLC-P eng rda OCoLC-P 9781003502432 (ebook) 1003502431 9781040099292 (electronic bk. : PDF) 1040099297 (electronic bk. : PDF) 9781040099346 (electronic bk. : EPUB) 1040099343 (electronic bk. : EPUB) 9781032655017 (hardback) 9781032819969 (paperback) 10.1201/9781003502432 doi (OCoLC)1439174892 (OCoLC-P)1439174892 TL152.8 COM 059000 bisacsh TJF bicssc Explainable artificial intelligence for autonomous vehicles : concepts, challenges, and applications / edited by Kamal Malik, Moolchand Sharma, Suman Deswal, Deevyankar Agarwal, Yahya Obaid Bakheet Al Shamsi. First edition. Boca Raton, FL : CRC Press, 2024. 1 online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier Explainable AI (XAI) for engineering applications "The book "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 the 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"-- Provided by publisher. OCLC-licensed vendor bibliographic record. Automated vehicles. 95283 Intelligent transportation systems. 58094 COMPUTERS / Computer Engineering bisacsh 64152 Malik, Kamal, editor. 95284 Taylor & Francis https://www.taylorfrancis.com/books/9781003502432 OCLC metadata license agreement http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf E-Books 68027 68027