AUTONOMOUS VEHICLE KINEMATICS AND DYNAMICS: Mathematical Modeling, State Estimation, and Low-Level Control System Implementation

What turns an autonomous vehicle’s planned trajectory into precise, stable, physically achievable motion?

Autonomous Vehicle Kinematics and Dynamics: Mathematical Modeling, State Estimation, and Low-Level Control System Implementation takes you inside the engineering layer where mathematics meets the road.

Built for automotive engineers, robotics developers, researchers, and advanced students, this practical guide connects vehicle kinematics, dynamic bicycle models, tire mechanics, sensor fusion, Kalman filtering, trajectory tracking, and model predictive control into one coherent autonomous motion-control framework.

Discover how to model vehicle motion, estimate states from IMU, GNSS, and wheel data, understand tire slip and friction limits, implement Pure Pursuit, Stanley, PID, and MPC controllers, and connect algorithms with C++20, ROS 2, actuator dynamics, CAN communication, and closed-loop validation.

From mathematical model to steering, braking, and physical vehicle response, this book gives you the engineering foundation to understand not just how autonomous vehicles decide where to go—but how they actually get there.