Artificial Intelligence for Autonomous Vehicles 1st Edition

Capture the future of mobility with Artificial Intelligence for Autonomous Vehicles, 1st Edition by Sathiyaraj Rajendran. This authoritative guide cuts through complexity to deliver practical, state-of-the-art approaches that power self-driving systems—from perception and sensor fusion to decision-making and safe path planning.

Explore clear, example-driven chapters that explain core AI techniques—deep learning, computer vision, reinforcement learning—and how they integrate with LiDAR, radar, and camera data for robust vehicle autonomy. Real-world scenarios and algorithmic insights make complex topics accessible for engineers, researchers, product managers, and graduate students building vehicles for urban streets, highways, and mixed-traffic environments across North America, Europe, and Asia.

You’ll gain actionable knowledge on model training, validation, simulation workflows, and safety-critical considerations that help reduce deployment risk in city traffic and varied geographic conditions. Emphasis on explainability, real-time constraints, and regulatory-aware design prepares teams to meet both technical and operational challenges.

Whether you’re upgrading an existing stack or starting a development program, this edition is a practical roadmap to accelerate R&D and commercial projects in autonomous mobility. The balanced blend of theory and application offers immediate value for development, testing, and deployment phases.

Stay ahead in the rapidly evolving autonomous-vehicle landscape—add Artificial Intelligence for Autonomous Vehicles by Sathiyaraj Rajendran to your library today and turn cutting-edge AI concepts into real-world driving intelligence.

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