基于模型预测控制的智能网联车辆主动避障方法

A Model Predictive Control-based Approach to Active Obstacle Avoidance for Intelligent Connected Vehicle

主动避障作为智能网联车辆的关键技术之一,与智能网联车辆的行车安全、通行效率、舒适性紧密相关.本文以智能网联车辆主动避障技术为研究对象,设计了基于模型预测控制的主动避障算法,在四种不同工况下通过Carsim和MATLAB联合仿真实验.结果表明,基于模型预测控制的主动避障算法在四种工况下均能实现智能网联车辆的主动避障,且车速稳定,乘坐舒适度高,避障效果良好,验证了该方法的实用性和有效性.

As one of the key technologies of intelligent connected vehicle,active obstacle avoidance is closely related to the driving safety,passing efficiency and comfort of intelligent connected vehicle.In this paper,an active obstacle avoidance algorithm based on model predictive control is designed for intelligent connected vehicle,and the simulation tests of the obstacle avoidance algorithm are carried out under four different working conditions through the joint simulation of Carsim and MATLAB,and the simulation results meet the expectations.The results show that the model predictive control-based obstacle avoidance algorithm can realize the active obstacle avoidance of the intelligent connected vehicle under all four working conditions,and the vehicle speed is stable;the ride comfort is high and the obstacle avoidance effect is good,which proves the practicality and effectiveness of the method.