Introduction to Autonomous Driving

This book offers an accessible introduction to the fast-moving world of autonomous driving. Aimed at students, researchers, and professionals, it provides both a comprehensive overview and a hands-on guide to the core concepts and practical tools used to build self-driving cars.
Autonomous driving stands at the intersection of artificial intelligence, robotics, embedded systems, and transportation engineering. Over the past two decades, the field has advanced from speculative prototypes to road-tested systems with significant industrial and societal impact. This textbook reflects that evolution, offering readers a structured yet flexible entry point into the autonomous vehicle (AV) ecosystem.
Key topics include how autonomous vehicles perceive their surroundings, determine their location, plan routes, and make driving decisions. Each chapter bridges foundational concepts with real-world applications using open-source platforms such as ROS2, CARLA, BlueICE, and Autoware.Universe. Readers will gain hands-on experience through simulation environments, real-world datasets, and modular development tools.
A unique emphasis on experiential learning encourages active engagement with the complexities of AV development. From simulating sensor fusion to implementing planning strategies and security protocols, learners interact directly with the technical and design challenges inherent in the field. Reflection exercises throughout the book emphasize ethical considerations and the societal implications of AV technology underscoring the importance of responsible innovation alongside technical fluency.
While some background in programming and mathematics is helpful, the content is designed to be approachable and engaging for a broad audience interested in the future of mobility. The organization of the text from foundational chapters on perception and localization to advanced discussions of full-stack systems and industry trends mirrors the layered architecture of an actual autonomous vehicle.
Introduction to Autonomous Driving equips readers not only with the skills needed to contribute to AV projects today, but also with the conceptual clarity and critical perspective required for leadership in this transformative domain.

Sommario

Chapter 1 Introduction to Autonomous Driving.- Chapter 2 Simulation Playground.- Chapter 3 Sensor Technologies.- Chapter 4 V2X Communications.- Chapter 5 Perception Algorithms.- Chapter 6 Localization Algorithms.- Chapter 7 Path Planning and Decision-Making.- Chapter 8 Drive-by-Wire and Vehicle Control Systems.- Chapter 9 Computing Systems.- Chapter 10 End-to-End Solutions.- Chapter 11 Security and Privacy.- Chapter 12 Simulation and Testing Techniques.- Chapter 13 Industry Landscape.- Chapter 14 Conclusion.

Info autore

Sidi Lu is an assistant professor of Computer Science at William & Mary. Her research interests broadly encompass edge computing, emerging mobility, and applied AI and data science, aimed at enhancing the reliability, scalability, security, and efficiency of networked, distributed, and autonomous systems. Her contributions have gained significant visibility within the university and the broader community. She has received prestigious awards, including the Ralph E. Kummler Award for Distinguished Achievement in Research and the Michael E. Conrad Research Award. Her work in vehicle computing has been highlighted in the Global Auto Mobility weekly newsletter, and her disk failure prediction software, along with the associated dataset, has been downloaded by researchers from over 200 institutions globally. Furthermore, she has established close collaborations with industry leaders, and her findings have been published in a range of top-tier conferences and journals.

Weisong Shi is an Alumni Distinguished Professor and Chair of the Department of Computer and Information Sciences at the University of Delaware (UD), where he leads the Connected and Autonomous Research (CAR) Laboratory. He is an internationally renowned expert in edge computing, autonomous driving, and connected health. His pioneer paper, "Edge Computing: Vision and Challenges," has been cited more than 7000 times. Before joining UD, he was a professor at Wayne State University (2002-2022). He served in multiple administrative roles, including Associate Dean for Research and Graduate Studies at the College of Engineering and Interim Chair of the Computer Science Department. Dr. Shi also served as a National Science Foundation (NSF) program director (2013-2015). Dr. Shi is the Editor-in-Chief of IEEE Internet Computing Magazine and Elsevier Smart Health. He is the founding steering committee chair of three conferences, including the ACM/IEEE Symposium on Edge Computing (SEC), the IEEE/ACM International Conference on Connected Health (CHASE), and the IEEE International Conference on Mobility (MOST). He is a fellow of IEEE and a distinguished scientist of ACM.

Riassunto

This book offers an accessible introduction to the fast-moving world of autonomous driving. Aimed at students, researchers, and professionals, it provides both a comprehensive overview and a hands-on guide to the core concepts and practical tools used to build self-driving cars.
Autonomous driving stands at the intersection of artificial intelligence, robotics, embedded systems, and transportation engineering. Over the past two decades, the field has advanced from speculative prototypes to road-tested systems with significant industrial and societal impact. This textbook reflects that evolution, offering readers a structured yet flexible entry point into the autonomous vehicle (AV) ecosystem.
Key topics include how autonomous vehicles perceive their surroundings, determine their location, plan routes, and make driving decisions. Each chapter bridges foundational concepts with real-world applications using open-source platforms such as ROS2, CARLA, BlueICE, and Autoware.Universe. Readers will gain hands-on experience through simulation environments, real-world datasets, and modular development tools.
A unique emphasis on experiential learning encourages active engagement with the complexities of AV development. From simulating sensor fusion to implementing planning strategies and security protocols, learners interact directly with the technical and design challenges inherent in the field. Reflection exercises throughout the book emphasize ethical considerations and the societal implications of AV technology—underscoring the importance of responsible innovation alongside technical fluency.
While some background in programming and mathematics is helpful, the content is designed to be approachable and engaging for a broad audience interested in the future of mobility. The organization of the text—from foundational chapters on perception and localization to advanced discussions of full-stack systems and industry trends—mirrors the layered architecture of an actual autonomous vehicle.
Introduction to Autonomous Driving equips readers not only with the skills needed to contribute to AV projects today, but also with the conceptual clarity and critical perspective required for leadership in this transformative domain.

Dettagli sul prodotto

• Autori: Yuankai He, Weisong Shi
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Copertina rigida
• Pubblicazione: 02.10.2025
• EAN: 9783031994845
• ISBN: 978-3-0-3199484-5
• Pagine: 251
• Illustrazioni: XII, 251 p. 31 illus., 30 illus. in color.
• Categorie: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica; Elektronik, Fahrzeugbau, Regelungstechnik, Slam, Verkehrsingenieurwesen, Verkehrsplanung, Kybernetik und Systemtheorie, LiDAR, Transportation Technology and Traffic Engineering, Automotive Engineering, Cyber-Physical Systems, Control, Robotics, Automation, Multiagent Systems, Vehicle Control, path planning, autonomous vehicles, Perception algorithms, simulation tools, Drive-by-Wire Control Systems, Localization Algorithms