计算机工程与应用 ›› 2022, Vol. 58 ›› Issue (17): 263-269.DOI: 10.3778/j.issn.1002-8331.2101-0195

• 工程与应用 • 上一篇    下一篇

基于多层图多角度的道路交叉口车辆跟踪

刘向前,闫娟,杨慧斌,贾茜伟   

  1. 上海工程技术大学 机械与汽车工程学院,上海 201620
  • 出版日期:2022-09-01 发布日期:2022-09-01

Road Intersections Vehicle Tracking Based on Multi-Layer Graphs and Multi-Angle

LIU Xiangqian, YAN Juan, YANG Huibin, JIA Xiwei   

  1. School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
  • Online:2022-09-01 Published:2022-09-01

摘要: 针对交叉路口下不确定运动流车辆跟踪问题,提出一种基于多层图多角度对车辆进行跟踪的方法。构建多层图形将各运动流分配到具有不同邻域的不同层;将多角度视图下所有多层图形映射到所选定主视图中;通过求解映射主视图下运动流最短路径,实现对车辆轨迹的跟踪。由跟踪实验及分析,结果表明,该方法对交叉路口不确定运动流的车辆运行轨迹可有效预测并进行跟踪,且跟踪效果与地面真实情况基本一致,误判率维持6%以下,具有实际应用价值,可为智能交通中车辆的跟踪提供新的方法。

关键词: 车辆跟踪, 多层图, 视频流, 多角度, 最短路径

Abstract: Aiming at the problem of tracking uncertain vehicle motion flow at intersections, a method based on multi-level graphs and multi-angle is proposed. Firstly, each motion flow is assigned to different layers with diverse neighborhoods by using the constructed multi-layer graphs; secondly, all multi-layer graphics under multi-angle views are mapped to the selected main view; finally, the vehicle tracking is realized by solving the shortest path of the mapping main view motion flow. Through the experiment and analysis of vehicle tracking at intersections, the results show that this method can effectively predict vehicle trajectory for uncertain vehicle flow at intersections, and the misjudgment rate between tracking effect and the real situation on the ground is less than 6%, which can provide a new method for vehicle tracking in intelligent transportation.

Key words: vehicle tracking, multi-layer graphs, video stream, multi-angle, shortest path