Map-matching is essential for almost all intelligent transportation systems, including context and personalized services. To support real-time intelligent transportation services, online map-matching is usually a prerequisite. Although many map-matching methods have been proposed, they often fail to balance the two conflicting objectives, i.e., matching quality and computation time. To alleviate the contradiction, in this paper, we propose a three-stage online map-matching algorithm, named as SD-Matching, to fully exploit a new dimension of collected GPS trajectory data (i.e., vehicle heading direction) in a provably smart way. In the first stage, heading direction is first used to enhance the probability computation of candidate edges for a given GPS point. In the second stage, heading direction is also employed to narrow down the searching space and serve as a cost-effective guider in the shortest path computation for two consecutive GPS points. In the third stage, heading direction is further utilized to refine the vehicle travelling path for a sequence of GPS points, together with the topology of the road network. Finally, we evaluate the SD-Matching algorithm using the real-world taxi data and road network data in the city of Beijing, China, to demonstrate its effectiveness and efficiency.
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Chao Chen and Yan Ding contributed equally on this work. The work was supported by the National Key R&D Project of China (No. 2017YFB1002000), the National Science Foundation of China (No. 61602067 and No. 71601024), the Fundamental Research Funds for the Central Universities (No. 106112017cdjxy180001), Chongqing Basic and Frontier Research Program (No. cstc2015jcyjA00016), Open Research Fund Program of Shenzhen Key Laboratory of Spatial Smart Sensing and Services (Shenzhen University), Research Project of Graduate Students in Chongqing (CYS188), and Ministry of Education in China Humanities and Social Sciences Youth Foundation (No. 16yjc630169). Chao Chen and Xuefeng Xie are the corresponding authors.
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Chen, C., Ding, Y., Xie, X. et al. A three-stage online map-matching algorithm by fully using vehicle heading direction. J Ambient Intell Human Comput 9, 1623–1633 (2018). https://doi.org/10.1007/s12652-018-0760-0