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    杨祺, 刘士荣. 多自主车辆队列跟随控制器设计[J]. 华东理工大学学报(自然科学版), 2020, 46(2): 250-258. DOI: 10.14135/j.cnki.1006-3080.20190118001
    引用本文: 杨祺, 刘士荣. 多自主车辆队列跟随控制器设计[J]. 华东理工大学学报(自然科学版), 2020, 46(2): 250-258. DOI: 10.14135/j.cnki.1006-3080.20190118001
    YANG Qi, LIU Shirong. Following Controller for Multi-autonomous Vehicle Platooning[J]. Journal of East China University of Science and Technology, 2020, 46(2): 250-258. DOI: 10.14135/j.cnki.1006-3080.20190118001
    Citation: YANG Qi, LIU Shirong. Following Controller for Multi-autonomous Vehicle Platooning[J]. Journal of East China University of Science and Technology, 2020, 46(2): 250-258. DOI: 10.14135/j.cnki.1006-3080.20190118001

    多自主车辆队列跟随控制器设计

    Following Controller for Multi-autonomous Vehicle Platooning

    • 摘要: 针对自主车辆队列行驶过程中,车辆间具有通信正常或通信中断两类情况,分别设计了两类队列跟随控制器。选用激光测距仪和单目摄像机作为车载传感器,从激光测距传感器数据中提取环境障碍物的物理特征信息,从视觉传感器数据中获取领航车辆的相对角度信息,然后对两种传感器的信息进行融合。根据跟随车辆和领航车辆之间是否存在通信的问题,分别提出了基于李雅普诺夫稳定性和模糊控制策略在通信正常和无通信两种情况下的控制器设计。最后在ROS仿真环境中对本文设计的控制器进行了验证。

       

      Abstract: In this paper, two types of vehicle platoon following controllers are designed, respectively, according to the situation that the communication between vehicles is normal or interrupted in the driving process. Laser range finder and monocular camera are used as vehicle sensors. Firstly, the physical characteristic information of obstacles in the environment is collected from the laser sensor and the obtained data is clustered by means of the DBSCAN algorithm. The clustering result of obstacles in the environment is fitted to the physical shape with a minimum circumscribed rectangle, whose center point is taken as the center of each obstacle. Secondly, the angle of the leader vehicle is obtained from visual sensor. The color distribution information of the preceding vehicle is pre-defined. The Camshift algorithm is used for calculating the relative angle between the preceding and the following vehicle in each frame of picture. Thirdly, the information collected by two kinds of sensors is fused for designing controller. According to whether there exists the communication between the leader and the follower or not, this paper proposes two different controllers based on Lyapunov function and fuzzy control logic, respectively. When the communication between vehicles is normal, the Lyapunov-based controller design will be used. When there doesn’t exist the communication between vehicles, the fuzzy control strategy will be selected. If the vehicle does not resume communication within a certain period of time, it would move to a safety area to wait for repairing. Finally, the proposed algorithm is verified via the theoretical derivation and the simulation in robot operating system (ROS).

       

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