基于短时预测的地图匹配算法

Map matching algorithm based on short-term prediction

地图匹配算法的有效性和可靠性对于车载导航系统而言非常重要,而目前存在的地图匹配算法在一些复杂环境下(如道路交叉口)仍然不能提供合理的输出。因此,为了提高道路网络中的地图匹配精度,提出了基于短时预测的地图匹配算法。该算法首先使用待匹配定位点的历史信息建立短时预测模型,从而获取到待匹配时刻未来一段时间内的位置预测点;然后使用待匹配定位点和短时预测点与道路之间的平均距离替换待匹配定位点与道路之间的距离;最后采用Dempster-Shafer证据理论融合车辆与道路之间的距离信息和方向信息,有效地扩大了待匹配道路之间的差异,从而提高了算法的鲁棒性。仿真和实验表明,新算法在复杂环境下具有较强的有效性和可靠性。

Efficient and reliable map matching algorithms are essential for vehicle navigation systems, while most existing solutions cannot provide trustworthy outputs when the situation is ambiguous （such as at road intersections）. In order to improve the precision of map matching, a new map matching algorithm based short-term prediction was proposed. Firstly, the algorithm employed the history positioning information to set up the model of short-term prediction. Accordingly, the future positions would be obtained after the current matching time; secondly, the distance comparability between vehicle and route was defined by the modified average distance, and it replaced the projecting distance between current matching position and route; finally, the Dempster-Shafer evidence was adopted to fuse the modified average distance and direction information between vehicle and route. It could effectively expand the credibility differences of the candidate routes and enhance the robustness of the algorithm. The results of simulation and experiments demonstrate the better efficiency and reliability of the estimates even for ambiguous environment.