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Map Matching Algorithms: An Experimental Evaluation

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Web and Big Data (APWeb-WAIM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10988))

Abstract

Map matching is an important operation of location-based services, which matches raw GPS trajectories onto real road networks, and facilitates tasks of urban computing, such as intelligent traffic systems, etc. More than ten algorithms have been proposed to address this problem in the recent decade. However, existing algorithms have not been thoroughly compared under the same experimental framework. For example, some algorithms are tested only on specific datasets. This makes it rather difficult for practitioners to decide which algorithms should be used for various scenarios. To address this problem, in this paper we provide a survey on a wide spectrum of existing map matching algorithms, classify them into different categories based on their main techniques, and compare them through extensive experiments on a variety of real-world and synthetic datasets with different characteristics. We also report comprehensive findings obtained from the experiments and provide new insights about the strengths and weaknesses of existing map matching algorithms which can guide practitioners to select appropriate algorithms for various scenarios.

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Notes

  1. 1.

    In this paper we use ‘trajectory’ to represent any raw GPS trajecotry for simplicity.

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Acknowledgement

This research is supported in part by the Key Grant Project on Humanities and Social Sciences of MOE of China (16JJD860008), the 2018 RUC Special Fund for First-Class Universities (Majors) of Central Universites, and RUC Start-up Fund (2018030119).

Author information

Authors and Affiliations

  1. School of Journalism and Communication, Renmin University of China, Beijing, 100872, China

    Na Ta

  2. College of Software, Beihang University, Beijing, 100191, China

    Jiuqi Wang

  3. Department of Computer Science, Tsinghua University, Beijing, 100084, China

    Guoliang Li

Authors
  1. Na Ta
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  2. Jiuqi Wang
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  3. Guoliang Li
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Correspondence to Na Ta .

Editor information

Editors and Affiliations

  1. South China University of Technology, Guangzhou, China

    Yi Cai

  2. Nagoya University, Nagoya, Japan

    Yoshiharu Ishikawa

  3. Hong Kong Baptist University, Kowloon Tong, Hong Kong, China

    Jianliang Xu

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Ta, N., Wang, J., Li, G. (2018). Map Matching Algorithms: An Experimental Evaluation. In: Cai, Y., Ishikawa, Y., Xu, J. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 10988. Springer, Cham. https://doi.org/10.1007/978-3-319-96893-3_14

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  • DOI: https://doi.org/10.1007/978-3-319-96893-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96892-6

  • Online ISBN: 978-3-319-96893-3

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