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.

针对交叉路口不确定车辆运动流的跟踪问题，提出了一种基于多层次图、多角度的方法。首先，通过使用构建的多层图将每个运动流分配到具有不同邻域的不同层。其次，多角度视图下的所有多层图形都映射到选定的主视图。最后通过求解映射主视图运动流的最短路径实现车辆跟踪。通过对路口车辆跟踪的实验和分析，结果表明，该方法可以有效预测路口车辆流量不确定的车辆轨迹，跟踪效果与地面真实情况的误判率小于6%，