Path Planning and Predictive Control of Autonomous Vehicles for Obstacle Avoidance

Abstract

This paper investigates path planning/trajectory generation algorithms and Model Predictive Control (MPC) of autonomous vehicles for obstacle avoidance. Two path planning approaches are designed in this work. To demonstrate obstacle avoidance of autonomous vehicles, Prescan and Matlab/Simulink are used to build an integrated model consisting of algorithms, an ego vehicle model, an MPC controller, and obstacle avoidance scenarios. Simulation tests are performed to validate the developed algorithms and compare the performance of two motion planning approaches for two scenarios. The performance comparison is presented in the paper with respect to the smoothness of the reference path/trajectory and the ego vehicle steering angle change while it performs an obstacle avoidance maneuver.