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汽车安全与节能学报

汽车安全与节能学报 ›› 2022, Vol. 13 ›› Issue (4): 686-696.DOI: 10.3969/j.issn.1674-8484.2022.04.010

• 智能驾驶与智慧交通 • 上一篇    下一篇

人机共驾车辆路径跟踪集成控制策略

张新荣1(), 许权宁1, 宫新乐2,*(), 李学鋆3, 黄晋2,*()   

  1. 1.长安大学 道路施工技术与装备教育部重点实验室，西安 710064，中国
    2.清华大学 车辆与运载学院，北京 100084，中国
    3.武汉理工大学 汽车工程学院，武汉 430070，中国
  • 收稿日期:2022-03-28 修回日期:2022-08-24 出版日期:2022-12-31 发布日期:2023-01-01
  • 通讯作者: 宫新乐,黄晋
  • 作者简介:黄晋(1984—)，男(汉)，山东，副教授；E-mail：huangjin@tsinghua.edu.cn。
    *宫新乐(1990—)，男(汉)，黑龙江，博士后研究员；E-mail：xinlegong@gmail.com。
    张新荣(1968—)，男(汉)，陕西，教授。E-mail：zxrong@chd.edu.cn。
  • 基金资助:
    中央高校基本科研业务费专项资金(300102259306);国家自然科学基金(52122217);国家自然科学基金(52102438)

Integrated control strategy for path tracking of human-machineco-driving vehicle

ZHANG Xinrong1(), XU Quanning1, GONG Xinle2,*(), LI Xueyun3, HUANG Jin2,*()   

  1. 1. Chang’an University, Key Laboratory of Road Construction Technology and Equipment of MOE, Xi’an 710064, China
    2. School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
    3. School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China
  • Received:2022-03-28 Revised:2022-08-24 Online:2022-12-31 Published:2023-01-01
  • Contact: GONG Xinle,HUANG Jin

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摘要：

针对人机共驾车辆路径跟踪控制精度和车辆稳定性难以有效保障的问题，提出一种集成控制策略，包括主动前轮转向系统（AFS）可变传动比曲线和基于模型预测控制（MPC）的路径跟踪控制器。针对稳定性控制，构建考虑路面附着条件和车速的AFS可变传动比函数，用于保证车辆路径跟踪过程中的安全性和横向稳定性；针对路径跟踪控制，设计基于MPC的路径跟踪控制器，用于跟踪目标路径；搭建了基于Carsim/Matlab的联合仿真平台并进行仿真验证。结果表明：集成控制策略可以有效改善人机共驾车辆的操作稳定性，显著提高了车辆的跟踪性能，削弱了驾驶员驾驶状态波动对车辆行驶安全的影响。

关键词: 人机共驾, 横摆稳定性, 路径跟踪, 集成控制

Abstract:

Aiming at the problems of human-machine co-driving vehicle path tracking control accuracy and vehicle stability that were difficult to guarantee effectively, an integrated control framework was proposed, mainly including active front wheel steering system (AFS) variable ratio curve and path tracking controller based on model predictive control (MPC). In terms of stability control, the AFS variable ratio function considering road adhesion conditions and vehicle speed was constructed to ensure the safety and lateral stability during vehicle path tracking; in terms of path tracking control, the MPC-based path tracking controller was designed to track the target path. Finally, a joint simulation platform based on Carsim / Matlab was built and simulated for verification. The results show that the integrated control strategy can effectively improve the operational stability of the human-machine co-driving vehicle, significantly improve the tracking performance of the vehicle, and weaken the impact of driver driving state fluctuations on vehicle driving safety.

Key words: human-machine co-driving, yaw stability, path tracking, integrated control

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