重庆理工大学学报(自然科学) ›› 2023, Vol. 37 ›› Issue (7): 34-43.

• 车辆工程 • 上一篇    下一篇

融合车道线势场的模型预测车道保持方法

卢 兵,黄文艺,王 博   

  1. (1.北京理工大学电动车辆国家工程实验室,北京 100081; 2.北京理工大学深圳汽车研究院(电动车辆国家工程实验室深圳研究院),广东 深圳 518118; 3.广州汽车集团股份有限公司汽车工程研究院,广州 511434)
  • 出版日期:2023-08-15 发布日期:2023-08-15
  • 作者简介:卢兵,男,博士,主要从事自动驾驶路径规划及控制研究,Email:lubingev@sina.com;通信作者 黄文艺,男,博士, 主要从事自动驾驶感知目标识别及跟踪研究,Email:huangwenyi@szari.ac.cn。

Lane potential field-based lane keeping strategy with model predictive control

  • Online:2023-08-15 Published:2023-08-15

摘要: 车道保持作为先进辅助驾驶(ADAS)的重要组成部分,对缓解驾驶疲劳和提升驾 驶安全性意义重大。基于车道线势场设计与模型预测控制,提出了一种融合车道线势场的模型 预测车道保持控制方法,以优化车道保持过程中的行驶稳定性与安全性。在 Carsim&Simulink 的联合仿真环境下,仿真结果表明,基于模型预测控制的车道保持算法对比 PID控制,在跟踪精 度与车辆稳定性方面都具有明显的优势,横向跟踪精度与车辆稳定性都有显著的提升;此外,与 无融合车道线势场的车道保持模型预测控制对比,具有更好的车辆稳定性和通行效率(27.8 km/hvs26.6km/h),其最大横摆角速度与最大横向加速度均下降了 10%左右。仿真结果验证 了所提出算法的有效性和优越性,具备良好的工程指导价值。

关键词: 车道线势场, 车道保持, 模型预测控制

Abstract: As an important part of advanced assisted (ADAS) driving, lane keeping control is significant to reduce driving fatigue and improve driving safety. Based on lane line potential field design and model predictive control, this paper proposes a model predictive lane keeping control method that integrates lane line potential field to optimize driving stability and safety during lane keeping. The co-simulation of the proposed algorithm is carried out under Carsim&Simulink. The simulation results show that, compared with PID control, the lane keeping algorithm based on model predictive control has obvious advantages in both tracking accuracy and vehicle stability, and the lateral tracking accuracy and vehicle stability are significantly improved. Furthermore, compared with the lane keeping MPC without the fusion of the lane line potential field, the proposed method has better vehicle stability and traffic efficiency (27.8 km/h vs 26.6 km/h), and its maximum yaw rate and maximum lateral acceleration decrease by almost 10%. The simulation results show the effectiveness and superiority of the proposed algorithm, which has good engineering guiding significance.

中图分类号: 

  • U461.99