基于多准则融合的信任理论地图匹配算法

A map-matching algorithm based on multi-criteria fusion using belief theory

本文提出了一种基于多准则融合的地图匹配算法,该算法运用信任理论融合了多种评价准则并对匹配过程中的道路选择进行了综合评价。首先,利用车辆定位的当前和历史信息建立了邻近准则、夹角准则和历史轨迹邻近准则。然后,运用D-S证据组合规则,将三种评价准则进行融合应用于道路选择过程中。最后,借助连通性准则对融合的最终结果进行修正,提高了算法的精度。仿真结果表明,对于简单和复杂路网,该算法都能提供较高的匹配精度,识别出车辆行驶的道路。

In this paper, a novel map-matching algorithm based on multi-criteria fusion using belief theory was proposed, which provided a synthetic evaluation for the results of road selection in road matching. Firstly, a proximity criterion and an angular criterion were established on current information in vehicle navigation, and a historical trajectory proximity criterion was put forward according to historical information. The road selection strategy then was employed based on multi-criteria fusion by using D-S evidence theory. Fi- nally, the accuracy of matching results was improved by taking account of connection criterion. Simulation results demonstrate that the proposed algorithm is effective and can recognize the road on which the vehicle is running in simple and complicated road network.