A map-matching algorithm with low-frequency floating car data based on matching path

A map-matching algorithm with low-frequency floating car data based on matching path
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一种基于路径匹配的低频浮动车数据地图匹配算法

DOI:
10.1186/s13638-018-1154-x
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发表时间:
2018-06
影响因子:
2.6
通讯作者:
Song Hu
Song Hu
中科院分区:
计算机科学4区
文献类型:
--
作者:
Ling Yuan;Dan Li;Song Hu

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With the wide application and rapid development of Intelligent Transportation System (ITS), the floating car has been widely used in the collection of traffic information, which is also very important in the application of the wireless sensor networks. In addition to the high-frequency floating car, energy-saving low-frequency floating car has attracted great attention, but the low-frequency GPS data have a poor effect on map matching. Taking consideration of the distance, direction, speed, and topology of road and vehicle, we propose a global map matching algorithm with low-frequency floating car data based on the matching path. The proposed algorithm preprocesses the floating car data and road network data to determine the potential points and sections by constructing the error region. Then, we calculate the potential matching path graph with the analysis of time and space. Finally, we can obtain the matching result by parallel computing with section division methodology. The experiment results demonstrate that the proposed map-matching algorithm can improve the running time and matching accuracy compared with the existing methods.
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