A Dynamic Collaborative Planning Method for Multi-vehicles in the Autonomous Driving Platform of the DeepRacer
A Dynamic Collaborative Planning Method for Multi-vehicles in the Autonomous Driving Platform of the DeepRacer
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DeepRacer自动驾驶平台中多车动态协同规划方法
DOI：
10.23919/ccc55666.2022.9902120
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Chunrun Du
中科院分区：
文献类型：
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作者：
Haikuo Du;Moyan Zhu;Wenjie Zhu;Yanbo Liu;Anbei Zhao;Wenchao Xu;Weiqi Sun;Chunrun Du
本文的主要研究内容是车辆的纵向和横向控制以及车队的复杂调度问题。对于单车控制的导航模块，采用Gazebo模拟真实的环境，利用二维激光雷达、双目摄像机和标签码进行车辆定位和导航。对于多车辆调度部分，本文主要关注队列状态的切换。一种是车队从编队到解散的反复切换，采用了解散状态控制策略和排状态控制策略。为了实现两种状态之间的无缝切换，提出了一种新的上层算法。二是车队上下立交桥时，可以切换控制方式，保证车辆正确导航。第三种情况是队列中的跟随者超过汽车，成为队列中间的领导者或跟随者，然后后退成为队列后面的跟随者。模拟是在Gazebo使用DeepRacer在亚马逊的平台。
The main research content of this paper is vehicle longitudinal and lateral control and complex scheduling problem of vehicle platoon. For the navigation module of single vehicle control, Gazebo is used to simulate the real environment, and 2D lidar, binocular camera and tag codes are used to carry out vehicle localization and navigation. For the multi-vehicle scheduling part, this paper mainly pays attention to switching of platoon states. One is the repeated switch of the convoy from formation to disbandment, and two control strategies are adopted, namely, disbandment state control strategy and platoon state control strategy. In order to achieve seamless switching between two states, a new upper layer algorithm is proposed. Second, when the fleet is on and off the overpass, the control methods can be switched to ensure the correct navigation of the vehicles. The third is the situation that the follower of the platoon overtakes the car and becomes the leader or follower in the middle of the platoon fall back to become a follower at the back of the line. The simulation is in Gazebo using DeepRacer in the Amazon's platform.