| 基于数据驱动的人机混驾多车协同控制算法 |
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| 引用本文： | 王会鲜,李波,郑洪江,陈伟.基于数据驱动的人机混驾多车协同控制算法[J].交通信息与安全,2021,39(1):76-86. |
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| 作者姓名： | 王会鲜 李波 郑洪江 陈伟 |
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| 作者单位： | 1.上海立信会计金融学院信息管理学院 上海 201209 |
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| 基金项目： | 国家重点研发计划项目;湖北省技术创新重大项目 |
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| 摘 要： | 针对多车协同控制系统中，传统控制算法需要准确获取系统中与驾驶员驾驶行为相关的参数以及与车辆系统动力学相关参数等问题，提出基于数据驱动的自适应动态规划控制算法。以有人与无人驾驶车辆混行的多车协同控制系统为研究对象，通过分析系统的横纵向控制模型，推导出系统状态方程，采用递推数值方法在线逼近最优解，并通过对最优反馈控制矩阵进行优化求解，得到最优控制输入。该算法简化了系统的控制输入参数，仅仅利用V2X通信获得的车辆的前轮转角以及车辆期望的纵向加速度作为控制输入，即可实现无人驾驶车辆的优化控制。基于Carsim和Simulink进行联合仿真测试验证，结果表明，该算法控制参数简单、收敛速度快、控制精度高、适应性强，能够控制无人驾驶车辆在多车系统中保持期望的车速并且与前车保持期望的车间距，同时在任意曲率道路上行驶时与车道中心线之间的横向误差趋于0。
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| 关 键 词： | 智能交通 多车协同控制 数据驱动控制 自适应动态规划算法 V2X通信 人机混驾 |
| 收稿时间： | 2020-07-23 |
A Multi-vehicle Cooperative Control Algorithm Based on Data-Driven Adaptive Control Strategy for Heterogeneous Human-driven and Autonomous Vehicles |
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| WANG Huixian,LI Bo,ZHENG Hongjiang,CHEN Wei.A Multi-vehicle Cooperative Control Algorithm Based on Data-Driven Adaptive Control Strategy for Heterogeneous Human-driven and Autonomous Vehicles[J].Journal of Transport Information and Safety,2021,39(1):76-86. |
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| Authors: | WANG Huixian LI Bo ZHENG Hongjiang CHEN Wei |
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| Affiliation: | 1.School of Information Management, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China2.Department of Technology, Shanghai Engineering Technology Research Center for Intelligent and Connected Vehicle Terminals, Shanghai 200030, China3.Department of Technology, Shanghai PATEO Electronic Equipment Manufacturing Limited Company, Shanghai 200030, China4.School of Automation, Wuhan University of Technology, Wuhan 430070, China |
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| Abstract: | Traditional model-based control methods need to obtain parameters of driving behaviors of drivers and system dynamics of vehicles in a multi-vehicle cooperative control system. However, these parameters cannot be obtained accurately in actual transport systems. A data-driven adaptive dynamic programming control algorithm is proposed to solve the problem. Under the environment of mixed manned and unmanned vehicles, the horizontal and vertical control models of the multi-vehicle cooperative control system are analyzed to derive its state equation. A recursive numerical method is used to approximate an optimal solution. Optimal control inputs are obtained by optimizing a feedback control matrix. The proposed algorithm simplifies control input parameters of the system. Besides, the optimal control of unmanned vehicles can be realized only using two parameters of basic safety messages of vehicles in real-time as the controller's inputs: steering the angel of the fore wheel and expected longitudinal acceleration. A co-simulation is conducted based on CarSim and Simulink. The results show that the proposed algorithm has simple control parameters, fast convergence speed, high control accuracy, and strong adaptability. It ensures the stability of the multi-vehicle cooperative control system and controls unmanned vehicles in platooning to maintain the desired velocity and desired heading. Moreover, its lateral error between the actual trajectory and expected trajectory tends to zero during driving on the road with arbitrary curvature. |
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