About this book:

This book provides a comprehensive technical roadmap for designing, implementing, and maintaining autonomous vehicles and mobile robots. It establishes a structural foundation by detailing the "sense-plan-act" architecture, moving from the physical hardware—specialized compute platforms, sensors like LiDAR and radar, and drive-by-wire actuators—to the sophisticated software stacks that power them. The text emphasizes that autonomy is not a single achievement but a modular hierarchy involving perception, sensor fusion, high-definition mapping, and probabilistic prediction, all coordinated through robust middleware like ROS 2 and high-throughput data pipelines.

Safety is treated as the central engineering constraint rather than a secondary feature. The book explores rigorous functional safety standards such as ISO 26262 and SOTIF, arguing for a "safety-first" culture that incorporates formal hazard analysis, fault-tolerant design, and redundant fail-operational systems. It details a multi-layered validation strategy that transitions from unit testing and Hardware-in-the-Loop (HIL) simulation to the use of digital twins and scenario generation. This ensures that autonomous systems are tested against the "long tail" of rare edge cases in virtual environments before they encounter the unpredictable risks of public roads.

The final chapters address the operational and societal complexities of deploying autonomous fleets at scale. The authors highlight the necessity of "Data Ops"—the continuous cycle of logging, human-in-the-loop labeling, and machine learning retraining—to ensure systems improve over time. Furthermore, the book navigates the intricate landscape of V2X connectivity, teleoperation, and regional regulatory compliance. By blending deep technical requirements with ethical considerations and human factors, the work provides a holistic view of how intelligent machines can be safely integrated into the human environment while earning public trust.

What You'll Find Inside:

• Comprehensive systems architecture covering perception, planning, control, safety mechanisms, and software frameworks like ROS 2 for self-driving vehicles and mobile robots
• Operating Design Domain (ODD) as a foundational concept for defining system capabilities, limitations, and guiding architecture decisions
• Safety frameworks including ISO 26262 for functional safety, SOTIF for performance limitations, hazard analysis techniques, and safety culture principles
• Verification and validation strategies spanning unit testing, integration testing, HIL testing, simulation, scenario generation, digital twins, and field operations
• Data operations and machine learning lifecycle including logging, labeling, model training/deployment, and continuous improvement through real-world data feedback loops

Who's It For:

This book is designed for autonomous vehicle engineers, robotics specialists, safety engineers, and technical managers working on self-driving systems and mobile robots. It provides a practical, system-level foundation suitable for professionals involved in designing, validating, testing, or deploying autonomous vehicles and mobile robots who need to understand the interplay between architecture, safety, testing, data operations, and fleet management. Advanced students and researchers in autonomous systems will also benefit from its comprehensive coverage of both theoretical concepts and implementation details.