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Origin-destination missing data estimation for freight transportation planning: a gravity model-based regression approach

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  • Guoqiang Shen
  • Saniye Gizem Aydin

Abstract

This paper develops a log-linear regression approach to estimate missing data in a sparse origin-destination (O-D) matrix assuming the sampled or observed O-D trips follow a good gravity pattern. The approach is tested with randomly selected samples from the known portions of 1997, 2002, and 2007 US Commodity Flow Survey (CFS) O-D value and tonnage matrices and validated with 2007 US O-D tonnage matrix at the state level. The missing data are also estimated for the 2007 CFS tonnage matrix with the best intercept and coefficients obtained using all known entries of the matrix. The concept of the approach can be extended beyond the gravity model to any strong mathematical pattern embedded in the known set of a sparse O-D matrix to estimate its missing cells.

Suggested Citation

  • Guoqiang Shen & Saniye Gizem Aydin, 2014. "Origin-destination missing data estimation for freight transportation planning: a gravity model-based regression approach," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(6), pages 505-524, August.
    • Handle: RePEc:taf:transp:v:37:y:2014:i:6:p:505-524
    DOI: 10.1080/03081060.2014.927665
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    Cited by:

    1. Abderrahman Ait-Ali & Jonas Eliasson, 2022. "The value of additional data for public transport origin–destination matrix estimation," Public Transport, Springer, vol. 14(2), pages 419-439, June.
    2. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Chen, Yan & Song, Dongdong & Zhi, Danyue & Wang, Yiyun & Gao, Ziyou, 2023. "Estimating intercity heavy truck mobility flows using the deep gravity framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    3. Thompson, C.A. & Saxberg, K. & Lega, J. & Tong, D. & Brown, H.E., 2019. "A cumulative gravity model for inter-urban spatial interaction at different scales," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    4. Shen, Guoqiang & Zhou, Long & Aydin, Saniye Gizem, 2020. "A multi-level spatial-temporal model for freight movement: The case of manufactured goods flows on the U.S. highway networks," Journal of Transport Geography, Elsevier, vol. 88(C).

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