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.