Decision-Making Techniques for Autonomous Vehicles 1st Edition

Capture the future of mobility with Decision-Making Techniques for Autonomous Vehicles, 1st Edition by Jorge Villagra and Felipe Jimenez. This authoritative guide distills the theory and practice behind the critical choices that enable safe, reliable autonomous driving across urban streets and highways worldwide.

Explore a clear, structured presentation of decision-making architectures, from rule-based and probabilistic models to learning-based strategies. The book explains behavior planning, motion planning integration, uncertainty handling, multi-agent interactions, and safety verification using real-world examples and case studies. Readers will find practical insights on sensor fusion, prediction, risk assessment, and how decision modules cooperate with perception and control systems to produce robust autonomous behavior.

Ideal for engineers, researchers, graduate students, system architects, and product teams in the autonomous-vehicle ecosystem, this edition balances mathematical rigor with implementation-minded guidance. Whether you’re developing navigation stacks for self-driving cars, working on ADAS enhancements, or shaping regulatory and safety frameworks, you’ll gain tools and frameworks that accelerate development and improve operational reliability.

Written in a concise, accessible style and grounded in contemporary research, this book is a go-to resource for anyone building or evaluating decision systems for vehicle autonomy. Add Decision-Making Techniques for Autonomous Vehicles to your professional library today—equip your team with the knowledge to design smarter, safer autonomous systems for markets across North America, Europe, Asia, and beyond. Order now to advance your projects and stay at the forefront of autonomous driving innovation.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.