Map Matching Based on Conditional Random Fields and Route Preference Mining for Uncertain Trajectories

Ming Xu, Yiman Du, Jianping Wu and Yang Zhou

Mathematical Problems in Engineering, 2015, vol. 2015, 1-13

Abstract:

In order to improve offline map matching accuracy of uncertain GPS trajectories, a map matching algorithm based on conditional random fields (CRF) and route preference mining is proposed. In this algorithm, road offset distance and the temporal-spatial relationship between the sampling points are used as features of GPS trajectory in a CRF model, which integrates the temporal-spatial context information flexibly. The driver route preference is also used to bolster the temporal-spatial context when a low GPS sampling rate impairs the resolving power of temporal-spatial context in CRF, allowing the map matching accuracy of uncertain GPS trajectories to get improved significantly. The experimental results show that our proposed algorithm is more accurate than existing methods, especially in the case of a low-sampling-rate.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:717095

DOI: 10.1155/2015/717095

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