Administrator by China Associction for Science and Technology
Sponsored by China Society of Automotive Engineers
Published by AUTO FAN Magazine Co. Ltd.

Automotive Engineering ›› 2023, Vol. 45 ›› Issue (7): 1174-1183.doi: 10.19562/j.chinasae.qcgc.2023.07.008

Special Issue: 智能网联汽车技术专题-规划&决策2023年

Previous Articles     Next Articles

Lane Change and Obstacle Avoidance Trajectory Planning of Intelligent Vehicle Based on Adaptive Fitting

Jun Li1,2(),Wei Zhou1,2,Shuang Tang1,2   

  1. 1.School of Mechanical and Vehicle Engineering,Chongqing Jiaotong University,Chongqing 400074
    2.Chongqing Key Laboratory of Rail Vehicle System Integration and Control,Chongqing 400074
  • Received:2022-12-16 Revised:2023-01-17 Online:2023-07-25 Published:2023-07-25
  • Contact: Jun Li E-mail:cqleejun@163.com

Abstract:

In this paper, the predictive trajectory planning of intelligent vehicles of lanes changing and obstacle avoidance in dynamic environment is studied. Firstly, the coordinate system and dynamic lane change and obstacle avoidance scenarios are defined, to determine the driving constraints of vehicle lane change and obstacle avoidance trajectory planning, and the controlled vehicle and obstacle vehicle models are built. Then, an adaptive piecewise Bezier curve-fitting algorithm is designed to fit the discrete point sequence of the lane change and obstacle avoidance trajectory planning. Further, the model predictive control algorithm is used to design the trajectory planning method for intelligent vehicles for lane changing and obstacles avoidance. Finally, the prediction trajectory planning method of the intelligent vehicle lane change and obstacle avoidance model in a dynamic environment is simulated and analyzed. The results show that the trajectory planning scheme of lane change and obstacle avoidance in this paper can enable the controlled vehicle to complete obstacle avoidance and maintain a stable state in dynamic environment. The adaptive piecewise Bezier curve fitting algorithm designed in this paper has a continuous and smooth fitting trajectory, and the fitting residual between the discrete point sequence provided by the lane change and obstacle avoidance trajectory planning and the corresponding point of the Bezier curve is kept within the set threshold.

Key words: intelligent vehicles, Bezier curves, model predictive control, dynamic obstacle avoidance, lane change trajectory planning