一种基于浮动车优化地图匹配方法

Optimized map-matching method for floating car

地图匹配方法,对于浮动车技术有着重要的意义。由于浮动车数据自身的特点,传统的地图匹配算法难以直接应用在城市道路浮动车数据匹配上。针对目前浮动车地图匹配算法应用于城市复杂路网时只考虑单一车辆位置数据,联动性研究较少,导致产生匹配精度不高的问题,考虑车辆运行特征与道路路网的连通信息,同时结合动态GPS数据,把模糊逻辑推理思想引入到网格地图匹配方法中,提出一种优化的地图匹配方法,并对其有效性进行了验证。研究表明,优化浮动车地图匹配方法在保持网格地图匹配实时性优点的同时,提高了算法的匹配精度。

Map-matching method has great significance for floating car technology. It is hard for the traditional map-matching algorithm to be directly applied to floating car data matching of city road due to the characteristics of floating car data. Currently, since the floating car map-matching algorithm used in city complex road network considers the single vehicle location data only, and the research on co-movement is less,it results in low matching precision. Considering the vehicle operating characteristics and the intercommunication information of road network,the optimized map-matching method is proposed with the dynamic GPS data,in which the fuzzy logic theory is introduced into the grid map-matching method. The effectiveness of the method was veri-fied. The research results show that the optimized map-matching method for floating car can improve the matching precision of the algorithm while keeping the advantage of real-time performance of grid map-matching.