IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v32y1998i2p109-126.html
   My bibliography  Save this article

Optimal traffic counting locations for origin-destination matrix estimation

Author

Listed:
  • Yang, Hai
  • Zhou, Jing

Abstract

There has been substantial interest in development and application of methodology for estimating origin-destination (O-D) trip matrices from traffic counts. Generally, the quality of an estimated O-D matrix depends much on the reliability of the input data, and the number and locations of traffic counting points in the road network. The former has been investigated extensively, while the latter has received very limited attention. This paper addresses the problem of how to determine the optimal number and locations of traffic counting points in a road network for a given prior O-D distribution pattern. Four location rules: O-D covering rule, maximal flow fraction rule, maximal flow-intercepting rule and link independence rule are proposed, and integer linear programming models and heuristic algorithms are developed to determine the counting links satisfying these rules. The models and algorithms are illustrated with numerical examples.

Suggested Citation

  • Yang, Hai & Zhou, Jing, 1998. "Optimal traffic counting locations for origin-destination matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 32(2), pages 109-126, February.
    • Handle: RePEc:eee:transb:v:32:y:1998:i:2:p:109-126
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(97)00016-7
    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. Yang, Hai & Sasaki, Tsuna & Iida, Yasunori & Asakura, Yasuo, 1992. "Estimation of origin-destination matrices from link traffic counts on congested networks," Transportation Research Part B: Methodological, Elsevier, vol. 26(6), pages 417-434, December.
    2. Yang, Hai, 1995. "Heuristic algorithms for the bilevel origin-destination matrix estimation problem," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 231-242, August.
    3. Oded Berman & Dmitry Krass & Chen Wei Xu, 1995. "Locating Discretionary Service Facilities Based on Probabilistic Customer Flows," Transportation Science, INFORMS, vol. 29(3), pages 276-290, August.
    4. Yang, Hai & Iida, Yasunori & Sasaki, Tsuna, 1991. "An analysis of the reliability of an origin-destination trip matrix estimated from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 25(5), pages 351-363, October.
    5. Yang, Hai & Iida, Yasunori & Sasaki, Tsuna, 1994. "The equilibrium-based origin-destination matrix estimation problem," Transportation Research Part B: Methodological, Elsevier, vol. 28(1), pages 23-33, February.
    6. A. Hordijk & L. C. M. Kallenberg, 1979. "Linear Programming and Markov Decision Chains," Management Science, INFORMS, vol. 25(4), pages 352-362, April.
    7. Oded Berman & Richard C. Larson & Nikoletta Fouska, 1992. "Optimal Location of Discretionary Service Facilities," Transportation Science, INFORMS, vol. 26(3), pages 201-211, August.
    Full references (including those not matched with items on IDEAS)

    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. Bera, Sharminda & Rao, K. V. Krishna, 2011. "Estimation of origin-destination matrix from traffic counts: the state of the art," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 49, pages 2-23.
    2. Shen, Wei & Wynter, Laura, 2012. "A new one-level convex optimization approach for estimating origin–destination demand," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1535-1555.
    3. 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.
    4. Hai Yang & Qiang Meng & Michael G. H. Bell, 2001. "Simultaneous Estimation of the Origin-Destination Matrices and Travel-Cost Coefficient for Congested Networks in a Stochastic User Equilibrium," Transportation Science, INFORMS, vol. 35(2), pages 107-123, May.
    5. Sherali, Hanif D. & Narayanan, Arvind & Sivanandan, R., 2003. "Estimation of origin-destination trip-tables based on a partial set of traffic link volumes," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 815-836, November.
    6. Louis Grange & Felipe González & Shlomo Bekhor, 2017. "Path Flow and Trip Matrix Estimation Using Link Flow Density," Networks and Spatial Economics, Springer, vol. 17(1), pages 173-195, March.
    7. 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.
    8. 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.
    9. Abdullah Alshehri & Mahmoud Owais & Jayadev Gyani & Mishal H. Aljarbou & Saleh Alsulamy, 2023. "Residual Neural Networks for Origin–Destination Trip Matrix Estimation from Traffic Sensor Information," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    10. 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.
    11. Yang, Hai, 1995. "Heuristic algorithms for the bilevel origin-destination matrix estimation problem," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 231-242, August.
    12. Z. Wu & W. Lam, 2006. "Transit passenger origin-destination estimation in congested transit networks with elastic line frequencies," Annals of Operations Research, Springer, vol. 144(1), pages 363-378, April.
    13. Fu, Hao & Lam, William H.K. & Shao, Hu & Kattan, Lina & Salari, Mostafa, 2022. "Optimization of multi-type traffic sensor locations for estimation of multi-period origin-destination demands with covariance effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    14. Li, Anna C.Y. & Nozick, Linda & Xu, Ningxiong & Davidson, Rachel, 2012. "Shelter location and transportation planning under hurricane conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 715-729.
    15. Fu, Hao & Lam, William H.K. & Shao, Hu & Ma, Wei & Chen, Bi Yu & Ho, H.W., 2022. "Optimization of multi-type sensor locations for simultaneous estimation of origin-destination demands and link travel times with covariance effects," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 19-47.
    16. Wu, Tai-Hsi & Lin, Jen-Nan, 2003. "Solving the competitive discretionary service facility location problem," European Journal of Operational Research, Elsevier, vol. 144(2), pages 366-378, January.
    17. S. Travis Waller & Sai Chand & Aleksa Zlojutro & Divya Nair & Chence Niu & Jason Wang & Xiang Zhang & Vinayak V. Dixit, 2021. "Rapidex: A Novel Tool to Estimate Origin–Destination Trips Using Pervasive Traffic Data," Sustainability, MDPI, vol. 13(20), pages 1-27, October.
    18. 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.
    19. Patriksson, Michael, 2008. "On the applicability and solution of bilevel optimization models in transportation science: A study on the existence, stability and computation of optimal solutions to stochastic mathematical programs," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 843-860, December.
    20. Tao Li, 2017. "A Demand Estimator Based on a Nested Logit Model," Transportation Science, INFORMS, vol. 51(3), pages 918-930, August.

    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:transb:v:32:y:1998:i:2:p:109-126. 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/548/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.