针对交叉路口附近道路几何分布较为复杂的实际特点,提出基于道路精简滤波(RRF)原理的地图匹配算法。研究了基于D-S证据理论的多规则数据融合技术在二路段地图匹配中的应用。建立了最短欧氏距离和最小航向差两条判决规则。引入相关性模糊决策理论,将多路段匹配问题简化为二路段匹配问题,使D-S证据判决规则的概率分配函数能根据实际路网分布作适应性调整,提高了算法的鲁棒性。对实际跑车数据的仿真处理结果表明,应用该算法可以较好地解决城市交叉路口地图匹配问题。

A Map Matching Algorithm Based on Road Reduction Filter(RRF) is proposed in this paper, which pays particular attention to the matching problems that arise at intersections. Application of credibilist multi-criteria association using belief theory and Dempster-Shafer's rule in only two roads map matching problem is studied. Two criteria, the shortest Euclidean distance and the smallest angle difference between road segment and vehicle heading are presented. Moreover, the correlation theory is introduced to simplified MM problems from multiread segments to only double road segments. As a result, the probability assignment function in criteria can be adjusted adaptively in accordance with actual road network. Simulation results with actual field experimental data show that RRF can perfectly solve the MM problem at urban intersections.