IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i7p2951-d342576.html
   My bibliography  Save this article

A Bicycle Origin–Destination Matrix Estimation Based on a Two-Stage Procedure

Author

Listed:
  • Seungkyu Ryu

    (Korea Institute Science Technology Information, Dajeon 34141, Korea)

Abstract

As more people choose to travel by bicycle, transportation planners are beginning to recognize the need to rethink the way they evaluate and plan transportation facilities to meet local mobility needs. A modal shift towards bicycles motivates a change in transportation planning to accommodate more bicycles. However, the current methods to estimate bicycle volumes on a transportation network are limited. The purpose of this research is to address those limitations through the development of a two-stage bicycle origin–destination (O–D) matrix estimation process that would provide a different perspective on bicycle modeling. From the first stage, a primary O–D matrix is produced by a gravity model, and the second stage refines that primary matrix generated in the first stage using a Path Flow Estimator (PFE) to build the finalized O–D demand. After a detailed description of the methodology, the paper demonstrates the capability of the proposed model for a bicycle demand matrix estimation tool with a real network case study.

Suggested Citation

  • Seungkyu Ryu, 2020. "A Bicycle Origin–Destination Matrix Estimation Based on a Two-Stage Procedure," Sustainability, MDPI, vol. 12(7), pages 1-14, April.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2951-:d:342576
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/7/2951/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/7/2951/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Braun, Lindsay M. & Rodriguez, Daniel A. & Cole-Hunter, Tom & Ambros, Albert & Donaire-Gonzalez, David & Jerrett, Michael & Mendez, Michelle A. & Nieuwenhuijsen, Mark J. & de Nazelle, Audrey, 2016. "Short-term planning and policy interventions to promote cycling in urban centers: Findings from a commute mode choice analysis in Barcelona, Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 164-183.
    2. Fisk, Caroline, 1980. "Some developments in equilibrium traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 14(3), pages 243-255, September.
    3. Kager, R. & Bertolini, L. & Te Brömmelstroet, M., 2016. "Characterisation of and reflections on the synergy of bicycles and public transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 208-219.
    4. Menghini, G. & Carrasco, N. & Schüssler, N. & Axhausen, K.W., 2010. "Route choice of cyclists in Zurich," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 754-765, November.
    5. Meghan Winters & Gavin Davidson & Diana Kao & Kay Teschke, 2011. "Motivators and deterrents of bicycling: comparing influences on decisions to ride," Transportation, Springer, vol. 38(1), pages 153-168, January.
    6. Hopkinson, P & Wardman, M, 1996. "Evaluating the demand for new cycle facilities," Transport Policy, Elsevier, vol. 3(4), pages 241-249, October.
    7. 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.
    8. Brenninger-Göthe, Maud & Jörnsten, Kurt O. & Lundgren, Jan T., 1989. "Estimation of origin-destination matrices from traffic counts using multiobjective programming formulations," Transportation Research Part B: Methodological, Elsevier, vol. 23(4), pages 257-269, August.
    9. 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.
    10. J. Hunt & J. Abraham, 2007. "Influences on bicycle use," Transportation, Springer, vol. 34(4), pages 453-470, July.
    11. Tung Tung, Chi & Lin Chew, Kim, 1992. "A multicriteria Pareto-optimal path algorithm," European Journal of Operational Research, Elsevier, vol. 62(2), pages 203-209, October.
    12. 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.
    13. Cascetta, Ennio & Nguyen, Sang, 1988. "A unified framework for estimating or updating origin/destination matrices from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 22(6), pages 437-455, December.
    14. Ehrgott, Matthias & Wang, Judith Y.T. & Raith, Andrea & van Houtte, Chris, 2012. "A bi-objective cyclist route choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 652-663.
    15. 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.
    16. Broach, Joseph & Dill, Jennifer & Gliebe, John, 2012. "Where do cyclists ride? A route choice model developed with revealed preference GPS data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1730-1740.
    17. Ortúzar, Juan de Dios & Iacobelli, Andrés & Valeze, Claudio, 2000. "Estimating demand for a cycle-way network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(5), pages 353-373, June.
    18. 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.
    19. Barbour, Refat & Fricker, Jon D., 1994. "Estimating an origin-destination table using a method based on shortest augmenting paths," Transportation Research Part B: Methodological, Elsevier, vol. 28(2), pages 77-89, April.
    20. Pucher, John & Buehler, Ralph & Seinen, Mark, 2011. "Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 451-475, July.
    21. Martens, Karel, 2007. "Promoting bike-and-ride: The Dutch experience," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 326-338, May.
    22. 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.
    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. Melo, Lucas Eduardo Araújo de & Isler, Cassiano Augusto, 2023. "Integrating link count data for enhanced estimation of deterrence functions: A case study of short-term bicycle network interventions," Journal of Transport Geography, Elsevier, vol. 112(C).

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Melo, Lucas Eduardo Araújo de & Isler, Cassiano Augusto, 2023. "Integrating link count data for enhanced estimation of deterrence functions: A case study of short-term bicycle network interventions," Journal of Transport Geography, Elsevier, vol. 112(C).
    8. 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.
    9. Felipe González & Carlos Melo-Riquelme & Louis Grange, 2016. "A combined destination and route choice model for a bicycle sharing system," Transportation, Springer, vol. 43(3), pages 407-423, May.
    10. Castillo, Enrique & Menéndez, José María & Jiménez, Pilar, 2008. "Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations," Transportation Research Part B: Methodological, Elsevier, vol. 42(5), pages 455-481, June.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. Michel Bierlaire & Frank Crittin, 2006. "Solving Noisy, Large-Scale Fixed-Point Problems and Systems of Nonlinear Equations," Transportation Science, INFORMS, vol. 40(1), pages 44-63, February.
    19. 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.
    20. Lo, H. P. & Zhang, N. & Lam, W. H. K., 1999. "Decomposition algorithm for statistical estimation of OD matrix with random link choice proportions from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 33(5), pages 369-385, June.

    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:gam:jsusta:v:12:y:2020:i:7:p:2951-:d:342576. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.