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Estimation of dynamic origin-destination trip tables for a general network

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  • Sherali, Hanif D.
  • Park, Taehyung

Abstract

In this paper, we propose a parametric optimization approach to estimate time-dependent path flows, or origin-destination (OD) trip tables, using available data on link traffic volumes for a general road network. Our model assumes knowledge of certain time-dependent link flow contribution factors that are a dynamic generalization of the path-link incidence matrix for the static case. A least squares model is accordingly formulated to determine the time-dependent trip tables. We develop a column generation approach that uses a sequence of dynamic shortest path subproblems in order to solve this problem. Computational results are presented on several variants of two sample test networks from the literature.

Suggested Citation

  • Sherali, Hanif D. & Park, Taehyung, 2001. "Estimation of dynamic origin-destination trip tables for a general network," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 217-235, March.
    • Handle: RePEc:eee:transb:v:35:y:2001:i:3:p:217-235
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    References listed on IDEAS

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    1. Nancy L. Nihan & Gary A. Davis, 1989. "Application of Prediction-Error Minimization and Maximum Likelihood to Estimate Intersection O-D Matrices from Traffic Counts," Transportation Science, INFORMS, vol. 23(2), pages 77-90, May.
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    4. Sherali, Hanif D. & Arora, Namita & Hobeika, Antoine G., 1997. "Parameter optimization methods for estimating dynamic origin-destination trip-tables," Transportation Research Part B: Methodological, Elsevier, vol. 31(2), pages 141-157, April.
    5. Bell, Michael G. H., 1991. "The real time estimation of origin-destination flows in the presence of platoon dispersion," Transportation Research Part B: Methodological, Elsevier, vol. 25(2-3), pages 115-125.
    6. Sherali, Hanif D. & Sivanandan, R. & Hobeika, Antoine G., 1994. "A linear programming approach for synthesizing origin-destination trip tables from link traffic volumes," Transportation Research Part B: Methodological, Elsevier, vol. 28(3), pages 213-233, June.
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    Citations

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    Cited by:

    1. Anselmo Ramalho Pitombeira-Neto & Carlos Felipe Grangeiro Loureiro & Luis Eduardo Carvalho, 2020. "A Dynamic Hierarchical Bayesian Model for the Estimation of day-to-day Origin-destination Flows in Transportation Networks," Networks and Spatial Economics, Springer, vol. 20(2), pages 499-527, June.
    2. Lin, Pei-Wei & Chang, Gang-Len, 2007. "A generalized model and solution algorithm for estimation of the dynamic freeway origin-destination matrix," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 554-572, June.
    3. Zhao, Miyuan & Chow, Joseph Y.J. & Ritchie, Stephen G., 2015. "An inventory-based simulation model for annual-to-daily temporal freight assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 83-101.
    4. Nie, Yu (Marco) & Zhang, H.M., 2008. "A variational inequality formulation for inferring dynamic origin-destination travel demands," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 635-662, August.
    5. Kumarage, Sakitha & Yildirimoglu, Mehmet & Zheng, Zuduo, 2023. "A hybrid modelling framework for the estimation of dynamic origin–destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
    6. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    7. Kumar, Anshuman Anjani & Kang, Jee Eun & Kwon, Changhyun & Nikolaev, Alexander, 2016. "Inferring origin-destination pairs and utility-based travel preferences of shared mobility system users in a multi-modal environment," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 270-291.
    8. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
    9. repec:cdl:itsrrp:qt95k1q411 is not listed on IDEAS
    10. Hazelton, Martin L., 2008. "Statistical inference for time varying origin-destination matrices," Transportation Research Part B: Methodological, Elsevier, vol. 42(6), pages 542-552, July.
    11. Chow, Joseph Y.J. & Ritchie, Stephen G. & Jeong, Kyungsoo, 2014. "Nonlinear inverse optimization for parameter estimation of commodity-vehicle-decoupled freight assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 71-91.
    12. Yu Nie & H. Zhang, 2010. "A Relaxation Approach for Estimating Origin–Destination Trip Tables," Networks and Spatial Economics, Springer, vol. 10(1), pages 147-172, March.
    13. Gunnar Flötteröd & Michel Bierlaire & Kai Nagel, 2011. "Bayesian Demand Calibration for Dynamic Traffic Simulations," Transportation Science, INFORMS, vol. 45(4), pages 541-561, November.
    14. Lundgren, Jan T. & Peterson, Anders, 2008. "A heuristic for the bilevel origin-destination-matrix estimation problem," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 339-354, May.
    15. repec:cdl:itsrrp:qt3nr033sc is not listed on IDEAS
    16. Felipe Zúñiga & Juan Carlos Muñoz & Ricardo Giesen, 2021. "Estimation and prediction of dynamic matrix travel on a public transport corridor using historical data and real-time information," Public Transport, Springer, vol. 13(1), pages 59-80, March.
    17. repec:cdl:itsrrp:qt3hh8f7nz is not listed on IDEAS

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