A map matching algorithm for intersections based on Floating Car Data

Wenjie Liao, Weifeng Lv, T. Zhu, Dongdong Wu
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引用次数: 8

Abstract

The traditional map matching algorithms consider little about the complicated structure of the road network, and regard all roads as the same. However, in the transportation information system using the floating car data (FCD), the GPS sampling rate is low, and it is probable to figure out the incorrect result when the vehicle is in the intersection area. To solve this problem, this paper proposes a bidirectional heuristic map matching algorithm for intersections based on a data structure for intersections. This algorithm apply the data structure of intersections to separates the intersection part from common map matching, decreases the FCD map matching mistakes that caused by the complicated road network and the GPS errors, and increases the accuracy of map matching.
基于浮动车辆数据的交叉口地图匹配算法
传统的地图匹配算法很少考虑路网的复杂结构,认为所有道路都是相同的。然而,在使用浮车数据(FCD)的交通信息系统中,GPS采样率较低,当车辆处于交叉口区域时,很可能得出不正确的结果。为了解决这一问题,本文提出了一种基于交叉口数据结构的双向启发式交叉口映射匹配算法。该算法利用交叉口的数据结构,将交叉口部分从普通地图匹配中分离出来,减少了路网复杂和GPS误差造成的FCD地图匹配错误,提高了地图匹配的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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