doi:10.16186/j.cnki.1673-9787.2020.5.14

Received:2019/12/15

Revised:2020/02/28

Published:2020/09/15

Study on the optimal speed control strategy and algorithm for intelligent vehicle

ZHANG Li, XU Haiqin, WANG Ziwen, WANG Fuzhong, ZHANG Tao

School of Electrical Engineering and Automation， Henan Polytechnic University， Jiaozuo 454000 ， Henan，China

Abstract:In the national college student smart car competition，the key to achieve excellent results in the photoelectric four-wheel cycle racing project is to maximize the speed，yet because of many diversified track elements such as rings，loop islands and other elements，simple track image processing and traditional PID control algorithm can not enable the smart car to accelerate and decelerate in the shortest possible time. The cascade control method related to image and velocity， proposed in the paper，could realize process optimization and center calculation of the track image through reverse perspective transformation，and could achieve cascade control on speed loop and steering loop. By artificial bee colony algorithm imposing real-time tuning control on PID parameters，the velocity of the vehicle could be maintain in its best state.Experimental results showed that the algorithm could not only improve the speed and speed control stability of intelligent vehicle，but also enhance the adaptability of intelligent vehicle to light environment.

Key words:intelligent vehicle;speed control;artificial bee colony algorithm;PID control;reverse perspective transtormation

智能车车速最优控制策略与算法研究_张丽.pdf