IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v19y2016icp1-23.html
   My bibliography  Save this article

Revisiting the route choice problem: A modeling framework based on mental representations

Author

Listed:
  • Kazagli, Evanthia
  • Bierlaire, Michel
  • Flötteröd, Gunnar

Abstract

We present a new approach for modeling and analyzing route choice behavior. It is motivated by the need to reduce the complexity of the state-of-the-art choice models. It is inspired by the simplifications done by the travelers, using representations of their surrounding space. The proposed framework is based on elements designed to mimic the mental representations used by travelers, denoted as Mental Representation Items (MRIs). It allows the modeler to adjust the level of complexity according to the needs of the specific application. This paper describes how operational models based on MRIs can be derived and discusses the applications of these models to traffic assignment and route guidance systems. We report estimation results using revealed preference data to demonstrate the applicability and validity of the approach.

Suggested Citation

  • Kazagli, Evanthia & Bierlaire, Michel & Flötteröd, Gunnar, 2016. "Revisiting the route choice problem: A modeling framework based on mental representations," Journal of choice modelling, Elsevier, vol. 19(C), pages 1-23.
    • Handle: RePEc:eee:eejocm:v:19:y:2016:i:c:p:1-23
    DOI: 10.1016/j.jocm.2016.06.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534515300518
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jocm.2016.06.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. van der Zijpp, N.J. & Fiorenzo Catalano, S., 2005. "Path enumeration by finding the constrained K-shortest paths," Transportation Research Part B: Methodological, Elsevier, vol. 39(6), pages 545-563, July.
    2. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
    3. Shlomo Bekhor & Moshe Ben-Akiva & M. Ramming, 2006. "Evaluation of choice set generation algorithms for route choice models," Annals of Operations Research, Springer, vol. 144(1), pages 235-247, April.
    4. Lai, Xinjun & Bierlaire, Michel, 2015. "Specification of the cross-nested logit model with sampling of alternatives for route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 220-234.
    5. Flötteröd, Gunnar & Bierlaire, Michel, 2013. "Metropolis–Hastings sampling of paths," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 53-66.
    6. Mai, Tien & Fosgerau, Mogens & Frejinger, Emma, 2015. "A nested recursive logit model for route choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 100-112.
    7. Fosgerau, Mogens & McFadden, Daniel & Bierlaire, Michel, 2010. "Choice probability generating functions," MPRA Paper 24214, University Library of Munich, Germany.
    8. Azevedo, JoseAugusto & Santos Costa, Maria Emilia O. & Silvestre Madeira, Joaquim Joao E. R. & Vieira Martins, Ernesto Q., 1993. "An algorithm for the ranking of shortest paths," European Journal of Operational Research, Elsevier, vol. 69(1), pages 97-106, August.
    9. T. Arentze & H. Timmermans, 2005. "Representing mental maps and cognitive learning in micro-simulation models of activity-travel choice dynamics," Transportation, Springer, vol. 32(4), pages 321-340, July.
    10. Piet Bovy & Sascha Hoogendoorn-Lanser, 2005. "Modelling route choice behaviour in multi-modal transport networks," Transportation, Springer, vol. 32(4), pages 341-368, July.
    11. Carlos F. Daganzo & Yosef Sheffi, 1977. "On Stochastic Models of Traffic Assignment," Transportation Science, INFORMS, vol. 11(3), pages 253-274, August.
    12. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
    13. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    14. Golledge, Reginald G & Garling, Tommy, 2003. "Cognitive Maps and Urban Travel," University of California Transportation Center, Working Papers qt1bp9f7wc, University of California Transportation Center.
    15. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Multivariate Extreme Value (MEV) models," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 31-52.
    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. Jun Li & Xinjun Lai, 2019. "Modelling travellers’ route choice behaviours with the concept of equivalent impedance," Transportation, Springer, vol. 46(1), pages 233-262, February.
    2. Kurmankhojayev, Daniyar & Li, Guoyuan & Chen, Anthony, 2024. "Link criticality index: Refinement, framework extension, and a case study," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Evanthia Kazagli & Michel Bierlaire & Matthieu de Lapparent, 2020. "Operational route choice methodologies for practical applications," Transportation, Springer, vol. 47(1), pages 43-74, February.

    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. Evanthia Kazagli & Michel Bierlaire & Matthieu de Lapparent, 2020. "Operational route choice methodologies for practical applications," Transportation, Springer, vol. 47(1), pages 43-74, February.
    2. Yao, Rui & Bekhor, Shlomo, 2022. "A variational autoencoder approach for choice set generation and implicit perception of alternatives in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 273-294.
    3. Papola, Andrea & Tinessa, Fiore & Marzano, Vittorio, 2018. "Application of the Combination of Random Utility Models (CoRUM) to route choice," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 304-326.
    4. Hamzeh Alizadeh & Bilal Farooq & Catherine Morency & Nicolas Saunier, 2018. "On the role of bridges as anchor points in route choice modeling," Transportation, Springer, vol. 45(5), pages 1181-1206, September.
    5. Ding-Mastera, Jing & Gao, Song & Jenelius, Erik & Rahmani, Mahmood & Ben-Akiva, Moshe, 2019. "A latent-class adaptive routing choice model in stochastic time-dependent networks," Transportation Research Part B: Methodological, Elsevier, vol. 124(C), pages 1-17.
    6. Lai, Xinjun & Bierlaire, Michel, 2015. "Specification of the cross-nested logit model with sampling of alternatives for route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 220-234.
    7. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    8. Mai, Tien & Yu, Xinlian & Gao, Song & Frejinger, Emma, 2021. "Routing policy choice prediction in a stochastic network: Recursive model and solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 151(C), pages 42-58.
    9. Li, Dawei & Feng, Siqi & Song, Yuchen & Lai, Xinjun & Bekhor, Shlomo, 2023. "Asymmetric closed-form route choice models: Formulations and comparative applications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    10. S. F. A. Batista & Ludovic Leclercq, 2019. "Regional Dynamic Traffic Assignment Framework for Macroscopic Fundamental Diagram Multi-regions Models," Transportation Science, INFORMS, vol. 53(6), pages 1563-1590, November.
    11. Hess, Stephane & Quddus, Mohammed & Rieser-Schüssler, Nadine & Daly, Andrew, 2015. "Developing advanced route choice models for heavy goods vehicles using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 29-44.
    12. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.
    13. Carlo Prato & Shlomo Bekhor & Cristina Pronello, 2012. "Latent variables and route choice behavior," Transportation, Springer, vol. 39(2), pages 299-319, March.
    14. Selin Damla Ahipaşaoğlu & Uğur Arıkan & Karthik Natarajan, 2019. "Distributionally Robust Markovian Traffic Equilibrium," Transportation Science, INFORMS, vol. 53(6), pages 1546-1562, November.
    15. Mai, Tien & Fosgerau, Mogens & Frejinger, Emma, 2015. "A nested recursive logit model for route choice analysis," Transportation Research Part B: Methodological, Elsevier, vol. 75(C), pages 100-112.
    16. Tien Mai & Fabian Bastin & Emma Frejinger, 2018. "A decomposition method for estimating recursive logit based route choice models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 253-275, September.
    17. Mohammad Nurul Hassan & Taha Hossein Rashidi & Neema Nassir, 2021. "Consideration of different travel strategies and choice set sizes in transit path choice modelling," Transportation, Springer, vol. 48(2), pages 723-746, April.
    18. Dieter, Peter & Caron, Matthew & Schryen, Guido, 2023. "Integrating driver behavior into last-mile delivery routing: Combining machine learning and optimization in a hybrid decision support framework," European Journal of Operational Research, Elsevier, vol. 311(1), pages 283-300.
    19. Moshe Ben-Akiva & Song Gao & Lu Lu & Yang Wen, 2015. "DTA2012 Symposium: Combining Disaggregate Route Choice Estimation with Aggregate Calibration of a Dynamic Traffic Assignment Model," Networks and Spatial Economics, Springer, vol. 15(3), pages 559-581, September.
    20. Rasmussen, Thomas Kjær & Watling, David Paul & Prato, Carlo Giacomo & Nielsen, Otto Anker, 2015. "Stochastic user equilibrium with equilibrated choice sets: Part II – Solving the restricted SUE for the logit family," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 146-165.

    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:eejocm:v:19:y:2016:i:c:p:1-23. 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.journals.elsevier.com/journal-of-choice-modelling .

    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.