Skip to main content
Log in

Mode choice analysis with imprecise location information

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

Several large-scale person trip surveys include the information of the origin and destination of the trip only at the TAZ (traffic analysis zone) level, so the accuracy of location information is not enough to examine the effect of access and egress conditions on mode choice. Two approaches are applied in this study to complement the imprecise information; one for access to public transit from home, and the other for egress from public transit to destination. Home-based trip data with the destinations as university, governmental office, and hospitals are used in this study. About the information of the egress, the precise location of the destination are identified within TAZ from GIS database using the purpose of the trip and the type of the destination reported by the respondent, and the distance from the nearest train station and bus stop are calculated. About the access to the public transit form home, the distance from home to the public transit is treated as a probabilistic variable in estimating the mode choice model in this study. The model has the same structure as the latent class model. Census data which contain the population distribution within TAZ at city block level is used for the distribution of origin. The results of empirical analysis show that the proposed model has a better log-likelihood at convergence than those with TAZ centroids as the ends of the trip. The results suggest that the proposed model has the same effect as obtaining the precise location information, and that it enables to better represent mode choice behavior than using TAZ centroid. The results also suggest that imprecise location information provides smaller coefficient estimates for the effect of access and egress conditions, resulting the underestimate on the elasticity of the access and egress conditions for promoting public transit.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Asakura, Y., Hato, E.: Tracking survey for individual travel behaviour using mobile communication instruments. Transp. Res. Part C 12, 273–291 (2004)

    Article  Google Scholar 

  • Bhat, C.R.: Imputing a continuous income variable from grouped and missing income observations. Econ. Lett. 46, 311–319 (1994a)

    Article  Google Scholar 

  • Bhat, C.R.: Estimation of travel demand models with grouped and missing income data. Transp. Res. Rec. 1443, 45–53 (1994b)

    Google Scholar 

  • Chalasani, V.S., Denstadli, J.M., Engebretsen, Ø., Axhausen, K.W.: Precision of geocoded locations and network distance estimates. J. Transp. Stat. 8, 1–15 (2005)

    Google Scholar 

  • Geene, W.H., Hensher, D.A.: A latent class model for discrete choice analysis: contrast with mixed logit. Transp. Res. Part B 37, 681–698 (2003)

    Article  Google Scholar 

  • Gómez-Ibáñez, J.A., Fauth, G.R.: Using demand elasticities from disaggregate mode choice models. Transportation 9, 105–124 (1980)

    Article  Google Scholar 

  • Hensher, D.A., Rose, J.M.: Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: a case study. Transp. Res. Part A 41, 428–443 (2007)

    Google Scholar 

  • Newman, P., Kenworthy, J.: Sustainability and Cities: Overcoming Automobile Dependence. Island Press, Washington (1999)

    Google Scholar 

  • Papola, A.: Some developments on the cross-nested logit model. Transp. Res. Part B 38, 833–851 (2004)

    Article  Google Scholar 

  • Steimetz, S.S.C., Brownstone, D.: Estimating commuters’ “value of time” with noisy data: a multiple imputation approach. Transp. Res. Part B 39, 865–889 (2005)

    Article  Google Scholar 

  • Talvitie, A., Dehghani, Y.: Comparison of the observed and coded network travel time and cost measurements. Transp. Res. Rec. 723, 46–51 (1979)

    Google Scholar 

  • Train, K.E.: The sensitivity of parameter estimates to data specification in mode choice models. Transportation 7, 301–309 (1978)

    Article  Google Scholar 

  • Train, K.E.: Discrete Choice Methods with Simulation. Cambridge University Press, Cambridge (2003)

    Google Scholar 

Download references

Acknowledgments

The authors acknowledge the constructive comments given by anonymous reviewers which significantly aided in improving the quality of the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Toshiyuki Yamamoto.

Additional information

Ryosuke Komori was at the Department of Geotechnical and Environmental Engineering, Nagoya University at the time this work was undertaken.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yamamoto, T., Komori, R. Mode choice analysis with imprecise location information. Transportation 37, 491–503 (2010). https://doi.org/10.1007/s11116-009-9254-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-009-9254-4

Keywords

Navigation