Autonomous vehicle; collision avoidance; supervisor; lane change; model predictive control; non-convex optimization; micro-genetic algorithm
Issue Date
2021-06
Publisher
SAGE PUBLICATIONS LTD
Citation
ADVANCES IN MECHANICAL ENGINEERING, v. 13, NO. 6, article no. 16878140211027669, Page. 1-14
Abstract
A planar motion control system is proposed for autonomous vehicles not only to follow the lanes, but also to avoid collisions by braking, accelerating, and steering. The supervisor is designed first to determine the desired speed and the risk of the maneuvering due to road boundaries and obstacles. In order to allow lane changes on multi-lane roads, the model predictive controller is formulated based on the probabilistic non-convex optimization. The micro-genetic algorithm is applied to calculate the target speed and target steering angle in real time. A software-in-the-loop unit is constructed with the Rapid Control Prototyping device in the vehicle communication environment. The performance of the proposed system is verified for various collision avoidance scenarios and the simulation results demonstrate the safe and effective driving performance of autonomous vehicles with no collision on multi-lane road.