IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v37y2003i10p811-822.html
   My bibliography  Save this article

Some comments on origin-destination matrix estimation

Author

Listed:
  • Hazelton, Martin L.

Abstract

Estimation of origin-destination (O-D) matrices from link count data is considered. This problem is challenging because the number of parameters to be estimated is typically larger than the number of network links. As a result, it is (usually) impossible to identify a unique optimal estimate of the O-D matrix from mean link traffic counts. However, information from the covariance matrix of link count data collected over a sequence of days can relieve this problem of indeterminacy. This fact is illustrated through a simple example. The use of second-order statistical properties of the data in O-D matrix estimation is then explored, and a class of estimators proposed. Practical problems of model mis-specification are discussed and some avenues for future research outlined.

Suggested Citation

  • Hazelton, Martin L., 2003. "Some comments on origin-destination matrix estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 811-822, December.
    • Handle: RePEc:eee:transa:v:37:y:2003:i:10:p:811-822
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965-8564(03)00044-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Xiaoyan & Maher, Mike J., 1998. "The evaluation and application of a fully disaggregate method for trip matrix estimation with platoon dispersion," Transportation Research Part B: Methodological, Elsevier, vol. 32(4), pages 261-276, May.
    2. Hazelton, Martin L., 2000. "Estimation of origin-destination matrices from link flows on uncongested networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(7), pages 549-566, September.
    3. Kurt Jörnsten & Stein W. Wallace, 1993. "Overcoming the (Apparent) Problem of Inconsistency in Origin-Destination Matrix Estimations," Transportation Science, INFORMS, vol. 27(4), pages 374-380, November.
    4. Maher, M. J., 1983. "Inferences on trip matrices from observations on link volumes: A Bayesian statistical approach," Transportation Research Part B: Methodological, Elsevier, vol. 17(6), pages 435-447, December.
    5. Spiess, Heinz, 1987. "A maximum likelihood model for estimating origin-destination matrices," Transportation Research Part B: Methodological, Elsevier, vol. 21(5), pages 395-412, October.
    6. Cremer, M. & Keller, H., 1987. "A new class of dynamic methods for the identification of origin-destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 117-132, April.
    7. Lo, H. P. & Zhang, N. & Lam, W. H. K., 1996. "Estimation of an origin-destination matrix with random link choice proportions: A statistical approach," Transportation Research Part B: Methodological, Elsevier, vol. 30(4), pages 309-324, August.
    8. Van Zuylen, Henk J. & Willumsen, Luis G., 1980. "The most likely trip matrix estimated from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 14(3), pages 281-293, September.
    9. Martin L. Hazelton, 2001. "Estimation of origin–destination trip rates in Leicester," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(4), pages 423-433.
    10. Cascetta, Ennio, 1984. "Estimation of trip matrices from traffic counts and survey data: A generalized least squares estimator," Transportation Research Part B: Methodological, Elsevier, vol. 18(4-5), pages 289-299.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Flurin S. Hänseler & Nicholas A. Molyneaux & Michel Bierlaire, 2017. "Estimation of Pedestrian Origin-Destination Demand in Train Stations," Transportation Science, INFORMS, vol. 51(3), pages 981-997, August.
    3. Enrique Castillo & Pilar Jiménez & José Menéndez & María Nogal, 2013. "A Bayesian method for estimating traffic flows based on plate scanning," Transportation, Springer, vol. 40(1), pages 173-201, January.
    4. Wu, Zhiyou & Tian, Jing & Quan, Jing & Ugon, Julien, 2014. "Optimality conditions and optimization methods for quartic polynomial optimization," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 968-982.
    5. Yang, Yudi & Fan, Yueyue, 2015. "Data dependent input control for origin–destination demand estimation using observability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 385-403.
    6. Barroso, Joana Maia Fernandes & Albuquerque-Oliveira, João Lucas & Oliveira-Neto, Francisco Moraes, 2020. "Correlation analysis of day-to-day origin-destination flows and traffic volumes in urban networks," Journal of Transport Geography, Elsevier, vol. 89(C).
    7. 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.
    8. Yang, Yudi & Fan, Yueyue & Royset, Johannes O., 2019. "Estimating probability distributions of travel demand on a congested network," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 265-286.
    9. Yang, Yudi & Fan, Yueyue & Wets, Roger J.B., 2018. "Stochastic travel demand estimation: Improving network identifiability using multi-day observation sets," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 192-211.
    10. Hazelton, Martin L., 2010. "Bayesian inference for network-based models with a linear inverse structure," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 674-685, June.
    11. Shao, Hu & Lam, William H.K. & Sumalee, Agachai & Chen, Anthony & Hazelton, Martin L., 2014. "Estimation of mean and covariance of peak hour origin–destination demands from day-to-day traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 52-75.
    12. Simonelli, Fulvio & Marzano, Vittorio & Papola, Andrea & Vitiello, Iolanda, 2012. "A network sensor location procedure accounting for o–d matrix estimate variability," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1624-1638.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blume, Steffen O.P. & Corman, Francesco & Sansavini, Giovanni, 2022. "Bayesian origin-destination estimation in networked transit systems using nodal in- and outflow counts," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 60-94.
    2. Shao, Hu & Lam, William H.K. & Sumalee, Agachai & Chen, Anthony & Hazelton, Martin L., 2014. "Estimation of mean and covariance of peak hour origin–destination demands from day-to-day traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 52-75.
    3. 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.
    4. Seungkyu Ryu, 2020. "A Bicycle Origin–Destination Matrix Estimation Based on a Two-Stage Procedure," Sustainability, MDPI, vol. 12(7), pages 1-14, April.
    5. Guo, Jianhua & Liu, Yu & Li, Xiugang & Huang, Wei & Cao, Jinde & Wei, Yun, 2019. "Enhanced least square based dynamic OD matrix estimation using Radio Frequency Identification data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 27-40.
    6. Hazelton, Martin L., 2000. "Estimation of origin-destination matrices from link flows on uncongested networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(7), pages 549-566, September.
    7. Yang, Yudi & Fan, Yueyue & Wets, Roger J.B., 2018. "Stochastic travel demand estimation: Improving network identifiability using multi-day observation sets," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 192-211.
    8. Castillo, Enrique & Menéndez, José María & Sánchez-Cambronero, Santos, 2008. "Predicting traffic flow using Bayesian networks," Transportation Research Part B: Methodological, Elsevier, vol. 42(5), pages 482-509, June.
    9. Hazelton, Martin L., 2001. "Inference for origin-destination matrices: estimation, prediction and reconstruction," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 667-676, August.
    10. Doblas, Javier & Benitez, Francisco G., 2005. "An approach to estimating and updating origin-destination matrices based upon traffic counts preserving the prior structure of a survey matrix," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 565-591, August.
    11. Xie, Chi & Kockelman, Kara M. & Waller, S. Travis, 2011. "A maximum entropy-least squares estimator for elastic origin–destination trip matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1465-1482.
    12. 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.
    13. Yang, Yudi & Fan, Yueyue & Royset, Johannes O., 2019. "Estimating probability distributions of travel demand on a congested network," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 265-286.
    14. Bierlaire, Michel, 2002. "The total demand scale: a new measure of quality for static and dynamic origin-destination trip tables," Transportation Research Part B: Methodological, Elsevier, vol. 36(9), pages 837-850, November.
    15. 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.
    16. Lo, Hing-Po & Chan, Chi-Pak, 2003. "Simultaneous estimation of an origin-destination matrix and link choice proportions using traffic counts," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(9), pages 771-788, November.
    17. Hazelton, Martin L., 2010. "Bayesian inference for network-based models with a linear inverse structure," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 674-685, June.
    18. Menon, Aditya Krishna & Cai, Chen & Wang, Weihong & Wen, Tao & Chen, Fang, 2015. "Fine-grained OD estimation with automated zoning and sparsity regularisation," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 150-172.
    19. Bielli, Maurizio & Reverberi, Pierfrancesco, 1996. "New operations research and artificial intelligence approaches to traffic engineering problems," European Journal of Operational Research, Elsevier, vol. 92(3), pages 550-572, August.
    20. Bierlaire, M. & Toint, Ph. L., 1995. "Meuse: An origin-destination matrix estimator that exploits structure," Transportation Research Part B: Methodological, Elsevier, vol. 29(1), pages 47-60, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:37:y:2003:i:10:p:811-822. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.