Autonomous Vehicles, Volume 1: Using Machine Intelligence 1st Edition

Autonomous Vehicles, Volume 1: Using Machine Intelligence (1st Edition) by Romil Rawat, Mary Sowjanya Alamanda, Syed Imran Patel, Varshali Jaiswal, Imran Khan, and Allam Balaram delivers a contemporary, practical guide to the algorithms powering self-driving cars and intelligent mobility systems.

Start here if you want a clear, up-to-date introduction to machine intelligence for autonomous systems. The book opens with accessible explanations of perception, sensor fusion (LiDAR, radar, camera), and localization techniques, then progresses to planning, control, and decision-making frameworks used in real-world autonomous vehicles. Each chapter balances theory with applied examples, helping readers connect computer vision, deep learning, and robotics concepts to on-road behavior.

Engineers, graduate students, researchers, and industry practitioners across India, Europe, North America, and Asia will find the volume particularly valuable for its focus on deployment challenges—safety, scalability, regulatory considerations, and urban mobility integration. Practical diagrams, comparative analyses, and case studies make complex topics approachable without sacrificing technical rigor.

Whether you’re preparing for a career in autonomous systems, contributing to intelligent transport projects, or researching next-generation ADAS and self-driving stacks, this book equips you with the foundational knowledge and industry perspective needed to innovate. Its global relevance and regional context make it useful for smart-city planners and automotive teams working in diverse markets.

Claim your copy of Autonomous Vehicles, Volume 1: Using Machine Intelligence today to stay ahead in the fast-evolving fields of autonomous mobility and machine intelligence.

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