OD Estimation Using Probe Vehicle Trajectories

The estimation of origin-destination (OD) matrix is a critical problem in transportation research. For static OD estimation, most existing literature uses link flows and target matrix from surveys as data sources. With the development of connected vehicle technology and the emergence of e-hailing services, a huge amount of vehicle trajectory data are being collected everyday. Connected vehicles and vehicles offering e-hailing services, like mobile sensors, can provide rich information of traffic conditions. There exist some studies estimating OD matrix using data collected from these probe vehicles. However, some of them still reply on traffic assignment models which are usually hard to calibrate and thus are deviated from the travel behaviors in reality. This paper proposes a novel method for OD estimation, with the only assumption that the route choice behaviors of probe vehicles are the same with other regular vehicles. Under this assumption, the proposed method tries to minimize the deviation between the link flows governed by the estimated OD matrix and the observed link flows which could be inferred from probe vehicle trajectories independently. The simplicity of the formulation and the convexity of the corresponding optimization problem enable its efficiency and scalability. Testing results have shown that the proposed model could estimate OD matrix with good quality, even when the penetration rate of probe vehicles is very low.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.
  • Corporate Authors:

    Transportation Research Board

  • Authors:
    • Zhao, Yan
    • Wong, Wai
    • Zheng, Jianfeng
    • Huang, Shihong
    • Liu, Henry X
  • Conference:
  • Date: 2019


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References;
  • Pagination: 7p

Subject/Index Terms

Filing Info

  • Accession Number: 01698257
  • Record Type: Publication
  • Report/Paper Numbers: 19-04145
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 1 2019 3:51PM