计算机工程与应用 ›› 2020, Vol. 56 ›› Issue (20): 20-27.DOI: 10.3778/j.issn.1002-8331.2002-0038

• 热点与综述 • 上一篇    下一篇

无人机-智能车队协同路径实时规划研究

谢博宇,李茂青,岳丽丽,陈启香   

  1. 1.兰州交通大学 自动化与电气工程学院,兰州 730070
    2.宝鸡文理学院 电子电气工程学院,陕西 宝鸡 721000
  • 出版日期:2020-10-15 发布日期:2020-10-13

Research on Route Real-Time Planning of UAV-Intelligent Platoons Cooperative Systems

XIE Boyu, LI Maoqing, YUE Lili, CHEN Qixiang   

  1. 1.School of Automation & Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
    2.School of Electronic & Electrical Engineering, Baoji University of Arts and Sciences, Baoji, Shaanxi 721000, China
  • Online:2020-10-15 Published:2020-10-13

摘要:

在智能交通系统下的路径实时决策方法中,由于智能车队因路旁检测器未设置、故障或者通信信号中断等情况而导致接收不到道路信息的问题,引入无人机,使智能车队和无人机协同工作,称之为机测工作模式。该模式是根据车道上不同信号显示下的行驶时间以及在交叉口的延误时间,动态计算行驶时间并得到一条用时最少的路径。通过4种场景,利用Matlab仿真得到的结果和理论分析一致,验证了算法的有效性。

关键词: 智能交通, 路径规划, 无人机-智能车队协同系统, Dijkstra算法, 车辆导航系统

Abstract:

In the real-time path decision method under intelligent transportation system, intelligent platoons may not receive road information, the reason is the failure of road detector or the interruption of communication signal. To solve this problem, the UAV is introduced to work together with the intelligent platoons, which is called the UAV mode. In this mode, according to the driving time displayed in different signals on the lane and the delay time at the intersection, the driving time is calculated dynamically and a path with the least time is obtained. Finally, the results of MATLAB simulation are consistent with the theoretical analysis in four scenarios, which verifies the effectiveness of the algorithm.

Key words: intelligent transport, path planning, Unmanned Aerial Vehicle(UAV)-intelligent platoons cooperative system, Dijkstra algorithm, vehicle navigation system