Skip to main content
SpringerLink
Log in

Evaluation of choice set generation algorithms for route choice models

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

This paper discusses choice set generation and route choice model estimation for large-scale urban networks. Evaluating the effectiveness of Advanced Traveler Information Systems (ATIS) requires accurate models of how drivers choose routes based on their awareness of the roadway network and their perceptions of travel time. Many of the route choice models presented in the literature pay little attention to empirical estimation and validation procedures. In this paper, a route choice data set collected in Boston is described and the ability of several different route generation algorithms to produce paths similar to those observed in the survey is analyzed. The paper also presents estimation results of some route choice models recently developed using the data set collected.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Bekhor, S., Ben-Akiva, and M.S. Ramming (2002). “Adaptation of Logit Kernel to Route Choice Situation.” Transportation Research Record, 1805, 78–85.

    Article  Google Scholar 

  • Bekhor, S. and J. Prashker (2001). “Stochastic User Equilibrium Formulation for the Generalized Nested Logit Model.” Transportation Research Record, 1752, 84–90.

    Article  Google Scholar 

  • Ben-Akiva, M., M.J. Bergman, A.J. Daly, and R. Ramaswamy (1984). “Modelling Inter Urban Route Choice Behaviour.” In J. Volmuller and R. Hamerslag (eds.), Proceedings of the 9th International Symposium on Transportation and Traffic Theory, VNU Press, Utrecht, pp. 299–330.

  • Ben-Akiva, M. and M. Bierlaire (1999). “Discrete Choice Methods and Their Applications to Short Term Travel Decisions.” In R.W. Hall (ed.), Handbook of Transportation Science.

  • Ben-Akiva, M. and D. Bolduc (1996). “Multinomial Probit with a Logit Kernel and a General Parametric Specification of the Covariance Structure.” Working Paper, 1996.

  • Ben-Akiva, M. and S.R. Lerman (1985). Discrete Choice Analysis: Theory and Application to Travel Demand, Cambridge, MA: MIT Press.

  • Cascetta, E., A. Nuzzolo, F. Russo, and A. Vitetta (1996). “A Modified Logit Route Choice Model Overcoming Path Overlapping Problems: Specification and Some Calibration Results for Interurban Networks.” In J.B. Lesort (ed.), Transportation and Traffic Theory. Proceedings from the Thirteenth International Symposium on Transportation and Traffic Theory, Lyon, France, Pergamon pp. 697–711.

  • Chu, C. (1989). “A Paired Combinatorial Logit Model for Travel Demand Analysis.” In Proceedings of the 5th World Conference on Transportation Research, 4, Ventura, CA, pp. 295–309.

  • Daganzo, C.F. and Y. Sheffi (1977). “On Stochastic Models of Traffic Assignment.” Transportation Science, 11, 253–274.

    Google Scholar 

  • De la Barra, T., B. Perez, and J. Anez (1993). “Multidimensional Path Search and Assignment.” In Proceedings of the 21st PTRC Summer Meeting, pp. 307–319.

  • Gliebe, J.P., F.S. Koppelman, and A. Ziliaskopoulos (1999). Route Choice Using a Paired Combinatorial Logit Model, presented at the 78th TRB Meeting, Washington D.C.

  • Horowitz, J.L. (1983). “Statistical Comparison of Non-Nested Probabilistic Discrete Choice Models.” Transportation Science, 17, 319–350.

    Article  Google Scholar 

  • McFadden, D. (1978). “Modeling the Choice of Residential Location.” In A. Karlqvist et al. (eds.), Spatial Interaction Theory and Residential Location, North Holland, Amsterdam pp. 75–96.

  • McFadden, D. and K. Train (2000). “Mixed MNL Models for Discrete Response.” Journal of Applied Econometrics, 15(5), 447–470.

    Article  Google Scholar 

  • Papola A. (2000). “Some Development of the Cross-Nested Logit Model.” In Proceedings of the 9th IATBR Conference. Gold Coast, Australia.

  • Prashker, J.N. and S. Bekhor (1998). “Investigation of Stochastic Network Loading Procedures.” Transportation Research Record, 1645, 94–102.

    Article  Google Scholar 

  • Ramming, M.S. (2001). “Network Knowledge and Route Choice.” Unpublished Ph.D. Thesis, Massachusetts Institute of Technology.

  • Vovsha, P. (1997). “The Cross-Nested Logit Model: Application to Mode Choice in the Tel-Aviv Metropolitan Area.” Transportation Research Record, 1607, 6–15.

    Article  Google Scholar 

  • Wen, C. and F. Koppelman (2001). “The Generalized Nested Logit Model.” Transportation Research Part B: Methodological, 35(7), 627–641.

  • Yai, T., S. Iwakura, and S. Morichi (1997). “Multinomial Probit with Structured Covariance for Route Choice Behavior.” Transportation Research Part B, 31, 195–207.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Civil and Environmental Engineering, Technion—Israel Institute of Technology, Technion Campus, Haifa, 32000, Israel

    Shlomo Bekhor

  2. Massachusetts Institute of Technology, Cambridge, MA, USA

    Moshe E. Ben-Akiva

  3. J.F. Sato and Associates, Littleton, CO, USA

    M. Scott Ramming

Authors
  1. Shlomo Bekhor
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Moshe E. Ben-Akiva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Scott Ramming
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shlomo Bekhor.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bekhor, S., Ben-Akiva, M.E. & Ramming, M.S. Evaluation of choice set generation algorithms for route choice models. Ann Oper Res 144, 235–247 (2006). https://doi.org/10.1007/s10479-006-0009-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-006-0009-8

Keywords

Search

Navigation