首页> 外文期刊>IEEE Transactions on Intelligent Transportation Systems >Path Planning and Cooperative Control for Automated Vehicle Platoon Using Hybrid Automata
【24h】

Path Planning and Cooperative Control for Automated Vehicle Platoon Using Hybrid Automata

机译:混合自动机的车辆自动排路径规划与协同控制

获取原文
获取原文并翻译 | 示例
       

摘要

Cooperative driving systems may increase the utilization of road infrastructure resources through coordinated control and platooning of individual vehicles with the potential of enhancing both traffic safety and efficiency. Vehicle cooperative driving is essentially a hybrid system that is a combination of discrete events, i.e., the transition of discrete cooperative maneuvering modes, such as vehicle merging and platoon splitting, as well as continuous vehicle dynamics. In this paper, a novel hybrid system consisting of the discrete cooperative maneuver switch and the continuous vehicle motion control is introduced into a multi-vehicle cooperative control system with a distributed control structure, leading each automated vehicle to conduct path planning and motion control separately. The primary novelty of this paper lies in that it presents a control algorithm combining artificial potential field (APF) approach with model predictive control (MPC), and using the optimizer of the MPC controller to replace the gradient-descending method in the traditional APF approach. Such a method can accomplish both path planning and motion control synchronously. Second, based on hybrid automata, a cooperative maneuver switching model consisting of a system state set and a discrete maneuver transition rule is established for two discrete maneuvers in the cooperative driving system, i.e., single-vehicle cruising and multiple-vehicle platooning. Simulations in several typical traffic scenarios demonstrate the effectiveness of the proposed method.
机译:协同驾驶系统可以通过对单个车辆进行协调控制和排练来提高道路基础设施资源的利用率,从而有可能提高交通安全性和效率。车辆协同驾驶本质上是一种混合系统,该系统是离散事件的组合,即离散协同操纵模式(例如车辆合并和排分裂)的过渡以及连续的车辆动力学。本文将由离散协同操纵开关和车辆连续运动控制组成的新型混合动力系统引入具有分布式控制结构的多车协同控制系统中,使每辆自动驾驶汽车分别进行路径规划和运动控制。本文的主要新颖之处在于,提出了一种将人工势场(APF)方法与模型预测控制(MPC)相结合的控制算法,并使用MPC控制器的优化器替代了传统APF方法中的梯度下降方法。这种方法可以同时完成路径规划和运动控制。其次,基于混合自动机,建立了一种由系统状态集和离散机动过渡规则组成的协同机动切换模型,用于协同驾驶系统中的两种离散机动,即单车巡航和多车排。在几种典型交通场景中的仿真证明了该方法的有效性。

著录项

  • 来源
  • 作者单位

    Minist Transport, Res Inst Highway, Beijing 100088, Peoples R China|Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Wuhan 430063, Hubei, Peoples R China;

    Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Wuhan 430063, Hubei, Peoples R China|Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China;

    Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Wuhan 430063, Hubei, Peoples R China|Minist Educ, Engn Res Ctr Transportat Safety, Wuhan 430063, Hubei, Peoples R China;

    Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Wuhan 430063, Hubei, Peoples R China|Minist Educ, Engn Res Ctr Transportat Safety, Wuhan 430063, Hubei, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Automated vehicle platoon; path planning and tracking; model predictive control; artificial potential field;

    机译:自动化车辆排;路径规划和跟踪;模型预测控制;人工势场;
  • 入库时间 2022-08-18 04:11:52

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号