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Methodological transferability in route choice modeling

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  • Bekhor, Shlomo
  • Prato, Carlo Giacomo

Abstract

The search for the shortest path constitutes the common practice in actual traffic studies, as this simplistic route choice model enables the universal implementation of traffic assignment and simulation procedures to every network configuration. The literature illustrates the large efforts in trying to move forward from this simplistic approach, the limited attempts in modeling route choice behavior from revealed preference data, and the nonexistent endeavor in investigating the transferability of more realistic path generation techniques and route choice models. This paper introduces a test to analyze the transferability of path generation techniques that is based on a newly defined efficiency index for the evaluation of their "cost-effectiveness". Then, equality of model estimates is tested to examine the transferability of route choice models, based on a methodology normally used in the estimation of models with mixed data (typically revealed and stated preference data) and on an existing transferability test statistic commonly used in mode choice modeling. Lastly, an experiment is presented to illustrate the implementation of the transferability tests, based on revealed preference data from two different case studies. Experiment results show that path generation techniques are totally transferable at the model specification level and partially transferable at the model parameter level, and that transferability is generally verified when parameters optimized for a larger network are successfully applied to a smaller network. Experiment results also show that not all route choice models are transferable at the model specification level, and none are transferable at the model parameter level.

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  • Bekhor, Shlomo & Prato, Carlo Giacomo, 2009. "Methodological transferability in route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(4), pages 422-437, May.
  • Handle: RePEc:eee:transb:v:43:y:2009:i:4:p:422-437
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    3. Anders F. Jensen & Thomas K. Rasmussen & Carlo G. Prato, 2020. "A Route Choice Model for Capturing Driver Preferences When Driving Electric and Conventional Vehicles," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    4. Quattrone, Agata & Vitetta, Antonino, 2011. "Random and fuzzy utility models for road route choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1126-1139.
    5. Mai, Tien & Frejinger, Emma & Bastin, Fabian, 2015. "A misspecification test for logit based route choice models," Economics of Transportation, Elsevier, vol. 4(4), pages 215-226.
    6. 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.
    7. Di Gangi, Massimo & Vitetta, Antonino, 2021. "Quantum utility and random utility model for path choice modelling: Specification and aggregate calibration from traffic counts," Journal of choice modelling, Elsevier, vol. 40(C).

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