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Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data

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  • Hyunmyung Kim
  • Daisik Nam
  • Wonho Suh
  • Seung Hoon Cheon

Abstract

Identifying accurate origin-destination (O-D) travel demand is one of the most important and challenging tasks in the transportation planning field. Recently, a wide range of traffic data has been made available. This paper proposes an O-D estimation model using multiple field data. This study takes advantage of emerging technologies – car navigation systems, highway toll collecting systems and link traffic counts – to determine O-D demand. The proposed method is unique since these multiple data are combined to improve the accuracy of O-D estimation for an entire network. We tested our model on a sample network and found great potential for using multiple data as a means of O-D estimation. The errors of a single input data source do not critically affect the model’s overall accuracy, meaning that combining multiple data provides resilience to these errors. It is suggested that the model is a feasible means for more reliable O-D estimation.

Suggested Citation

  • Hyunmyung Kim & Daisik Nam & Wonho Suh & Seung Hoon Cheon, 2018. "Origin-destination trip table estimation based on subarea network OD flow and vehicle trajectory data," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(3), pages 265-285, April.
    • Handle: RePEc:taf:transp:v:41:y:2018:i:3:p:265-285
    DOI: 10.1080/03081060.2018.1435437
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    Cited by:

    1. Wei Yu & Xiaofei Ye & Jun Chen & Xingchen Yan & Tao Wang, 2020. "Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method," Sustainability, MDPI, vol. 12(3), pages 1-21, February.

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