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A Method for Direct Estimation of Origin/Destination Trip Matrices

Author

Listed:
  • Malachy Carey

    (Carnegie-Mellon University, Pittsburgh, Pennsylvania)

  • Chris Hendrickson

    (Carnegie-Mellon University, Pittsburgh, Pennsylvania)

  • Krishnaswami Siddharthan

    (Carnegie-Mellon University, Pittsburgh, Pennsylvania)

Abstract

Estimates of the volume of travel between zones or locations is often a necessary step in transportation studies. This paper suggests a method of estimating origin/destination volumes, using a direct demand function and incomplete, aggregate data. Most attention is devoted to demand functions which are linear in their parameters. With such demand functions, volume estimates are obtained from a quadratic programming problem, which minimizes the sum of squared errors from a direct demand function, subject to constraints derived from observations of some travel volumes. A decomposition algorithm is suggested for solving the programming problem and is proven to converge. The method may also be used in the trip distribution phase of the conventional urban transportation model systems (UTMS).

Suggested Citation

  • Malachy Carey & Chris Hendrickson & Krishnaswami Siddharthan, 1981. "A Method for Direct Estimation of Origin/Destination Trip Matrices," Transportation Science, INFORMS, vol. 15(1), pages 32-49, February.
    • Handle: RePEc:inm:ortrsc:v:15:y:1981:i:1:p:32-49
    DOI: 10.1287/trsc.15.1.32
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    Cited by:

    1. Andrew Johnson & Yao Zhao & Xin Xu, 2016. "Transportation Planning and Scheduling for the 2014 Special Olympics USA Games," Interfaces, INFORMS, vol. 46(3), pages 218-230, April.
    2. Li, Guoyuan & Chen, Anthony, 2022. "Frequency-based path flow estimator for transit origin-destination trip matrices incorporating automatic passenger count and automatic fare collection data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    3. Kuo, Yong-Hong & Leung, Janny M.Y. & Yan, Yimo, 2023. "Public transport for smart cities: Recent innovations and future challenges," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1001-1026.
    4. Zhaonan Qu & Alfred Galichon & Johan Ugander, 2023. "On Sinkhorn's Algorithm and Choice Modeling," Papers 2310.00260, arXiv.org.
    5. Li, Tao & Wan, Yan, 2019. "Estimating the geographic distribution of originating air travel demand using a bi-level optimization model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 131(C), pages 267-291.

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