Active vehicle obstacle avoidance based on integrated horizontal and vertical control strategy - Xu Li; Yibo Yang; Jianchun Wang (Automatika, 2020)
In this paper, an integrated control method is proposed which is based on a planning of vehicle’s path and speed with respect to obstacles and a model predictive control for tracking this path. The planning layer builds a model predictive control framework based on the vehicle kinematics model; based on the potential field theory, comprehensively considers the vehicle’s state information and the relative position and velocity information of the obstacles, establishes the potential field function, introduces the optimization objective function, and optimizes vehicle’s path and speed. The tracking layer builds a model predictive control framework based on the vehicle dynamics model, establishes an optimized objective function that takes the optimal front wheel rotation angle and optimal longitudinal acceleration as inputs, and constrains the lateral acceleration and yaw angular velocity to achieve the vehicle’s obstacle avoidance path track. A co-simulation platform of CarSim and Matlab/Simulink was built to analyse the performance of the vehicle under static and dynamic obstacles under different initial speed conditions. The results show that the vehicle can track the reference path and reference speed smoothly, realize the horizontal and vertical comprehensive control of active obstacle avoidance, and verify the effectiveness of the proposed control method.