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An Improved Map Matching Algorithm Based on Dynamic Programming Approach

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Information Technology for Management: Towards Business Excellence (ISM 2020, FedCSIS-IST 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 413))

Abstract

GPS sensors embedded in almost all mobile devices and vehicles generate a large amount of data that can be used in both practical applications and transportation research. Despite the high accuracy of location measurements in 3–5 m on average, this data can not be used for practical use without preprocessing. The preprocessing step that is needed to identify the correct path as a sequence of road segments by a series of location measurements and road network data is called map matching. In this paper, we consider the offline map matching problem in which the whole trajectory is processed after it has been collected. We propose a map matching algorithm based on a dynamic programming approach. To enhance the quality of the map matching algorithm, we propose a modification of the algorithm aimed at enhancing the accuracy of the map matching procedure. The modification of the algorithms consists in dividing the GPS trajectory into sections and step-by-step running the base map matching algorithm for each section. The experimental studies were conducted on the dataset collected in Samara, Russia, and the publicly available large-scale dataset for testing, benchmarking, and offline learning of map matching algorithms. Experiments showed that the proposed algorithm outperforms other comparable algorithms in terms of accuracy.

The work was partially supported by RFBR research projects no. 18-29-03135-mk.

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Authors and Affiliations

  1. Samara National Research University, 34, Moskovskoye shosse, Samara, 443086, Russia

    Alexander Yumaganov, Anton Agafonov & Vladislav Myasnikov

Authors
  1. Alexander Yumaganov
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  2. Anton Agafonov
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  3. Vladislav Myasnikov
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Correspondence to Anton Agafonov .

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Editors and Affiliations

  1. University of Economics in Katowice, Katowice, Poland

    Ewa Ziemba

  2. University of Warsaw, Warsaw, Poland

    Witold Chmielarz

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Yumaganov, A., Agafonov, A., Myasnikov, V. (2021). An Improved Map Matching Algorithm Based on Dynamic Programming Approach. In: Ziemba, E., Chmielarz, W. (eds) Information Technology for Management: Towards Business Excellence. ISM FedCSIS-IST 2020 2020. Lecture Notes in Business Information Processing, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-030-71846-6_5

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  • DOI: https://doi.org/10.1007/978-3-030-71846-6_5

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