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International Conference on Computational Science and Its Applications

ICCSA 2017: Computational Science and Its Applications – ICCSA 2017 pp 183–198Cite as

Estimation of an Urban OD Matrix Using Different Information Sources

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10405))

Abstract

An Origin Destination matrix for urban trips is more difficult to develop than for interurban long and medium distance trips. The socio-economic characteristics are valuable parameters to estimate trip attractions and destinations, but often the distance does not have a significant effect on the distribution of urban trips. Since the 1980s methods are developed to estimate the trip matrix from traffic volumes. The problem is underdetermined: the information in the OD matrix is more than the information contained in the traffic volumes. Nowadays there are more information sources like probe vehicles, Automated Number Plate Recognition cameras, mobile phone data etc. This article discusses the possibilities and limitations of these additional information sources. Use is made of traffic data collected in Changsha, a town in middle-south China.

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Author information

Authors and Affiliations

  1. Faculty of Science, Ibn Zohr University, Agadir, Morocco

    Asma Sbaï & Fattehallah Ghadi

  2. Delft University of Technology, Delft, The Netherlands

    Henk J. van Zuylen

  3. South West Jiaotong University, Chengdu, China

    Henk J. van Zuylen & Fangfang Zheng

  4. Hunan University, Changsha, China

    Henk J. van Zuylen & Jie Li

Authors
  1. Asma Sbaï
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  2. Henk J. van Zuylen
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  3. Jie Li
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  4. Fangfang Zheng
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  5. Fattehallah Ghadi
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Corresponding author

Correspondence to Jie Li .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Trieste, Trieste, Italy

    Giuseppe Borruso

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  9. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  10. University of Trieste, Trieste, Italy

    Alfredo Cuzzocrea

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Sbaï, A., van Zuylen, H.J., Li, J., Zheng, F., Ghadi, F. (2017). Estimation of an Urban OD Matrix Using Different Information Sources. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10405. Springer, Cham. https://doi.org/10.1007/978-3-319-62395-5_14

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  • DOI: https://doi.org/10.1007/978-3-319-62395-5_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62394-8

  • Online ISBN: 978-3-319-62395-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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