Skip to main content
Log in

Use of repeated cross-sectional travel surveys for developing meta models of activity-travel scheduling processes

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

The paper presents an investigation of the temporal transferability of activity scheduling process models and a Meta model of activity scheduling processed by using repeated cross-sectional datasets. Three repeated cross-sectional household travel survey datasets collected in the greater Toronto and Hamilton Area in the years 2001, 2006, and 2011 are used for the investigation. A random utility maximization based dynamic activity scheduling model is utilized to develop activity-travel scheduling models for non-workers and workers separately. Individual year-specific models are compared to identify the temporal stability of the effects of different variables in the model. Results are used to define temporal evolution components in the Meta models. Estimated models are tested for temporal transferability. Different transferability measures are used to test the temporal transferability of cross-sectional year-specific and the Meta models. Results demonstrate an approach of effectively using multiple repeated cross-sectional datasets as pseudo panel data to develop Meta models to improve the temporal transferability of activity scheduling models.

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.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Aptech: GAUSS User Manual. Maple Valley, CA (2014)

  • Auld, J., Mohammadian, A.: Activity planning processes in the agent-based dynamic activity planning and travel scheduling (ADAPTS) model. Transp. Res. Part A 46(8), 1386–1403 (2012). https://doi.org/10.1016/j.tra.2012.05.017

    Google Scholar 

  • Ben-Akiva, M.E., Lerman, S.R.: Discrete choice analysis: theory and application to travel demand MIT Press series in transportation studies, vol. 9. MIT Press, Cambridge (1985)

    Google Scholar 

  • Bhat, C.R.: A multiple discrete–continuous extreme value model: formulation and application to discretionary time-use decisions. Transp. Res. Part B Methodol. 39(8), 679–707 (2005). https://doi.org/10.1016/j.trb.2004.08.003

    Article  Google Scholar 

  • Bhat, C.R.: The multiple discrete-continuous extreme value (MDCEV) model: role of utility function parameters, identification considerations, and model extensions. Transp. Res. Part B Methodol. 42(3), 274–303 (2008). https://doi.org/10.1016/j.trb.2007.06.002

    Article  Google Scholar 

  • Bowman, J. L., Bradley, M., Castiglione, J., Yoder, S. L.: Making advanced travel forecasting models affordable through model transferability. Paper presented at the 2014 Annual Meeting of Transportation Research Board, Washington DC, January 2014 (2014)

  • Davidson, W., Vovsha, P., Freedman, J., Donnelly, R.: CT-RAMP family of activity-based models. The paper presented at Autralian Transport Research Forum. Sept 29-Oct 1, 2010, Canbverra, Australia (2010)

  • DMG: Transportation Tomorrow Survey. dmg.utoronto.ca (2012)

  • Fox, J., Hess, S.: Review of evidence for temporal transferability of mode-destination models. Transp. Res. Rec. J. Transp. Res. Board 2175, 74–83 (2010)

    Article  Google Scholar 

  • Habib, K.M.N.: A comprehensive utility-based system of travel options modelling (CUSTOM) considering dynamic time-budget constrained Potential Path Area (PPA) in activity scheduling process: application in modelling worker’s daily activity-travel schedules. Transp. A Transp. Sci. 14(4), 292–315 (2018)

    Google Scholar 

  • Habib, K.M.N.: Modelling Activity Generation Process. University of Toronto (2007)

  • Habib, K.M.N., Swait, J., Salem, S.: Using repeated cross-sectional travel surveys to enhance forecasting robustness: accounting for changing mode preferences. Transp. Res. Part A Policy Pract. 67, 110–126 (2014). https://doi.org/10.1016/j.tra.2014.06.004

    Article  Google Scholar 

  • Habib, K.M.N., Sasic, A., Weis, C., Axhausen, K.: Investigating the nonlinear relationship between transportation system performance and daily activity–travel scheduling behaviour. Transp. Res. Part A Policy Pract. 49, 342–357 (2013). https://doi.org/10.1016/j.tra.2013.01.016

    Article  Google Scholar 

  • Habib, K.M.N.: A random utility maximization (RUM) based dynamic activity scheduling model: application in weekend activity scheduling. Transportation 38(1), 123–151 (2011). https://doi.org/10.1007/s11116-010-9294-9

    Article  Google Scholar 

  • Jin, X., Wu, J., Horowitz, A.J.: Transferability of time-of-day choice modeling for long-distance trips (2009)

  • Koppelman, F.S., Wilmot, C.G.: Transferability analysis of disaggregate choice models. Transp. Res. Rec. J. Transp. Res. Board 895, 18–24 (1982)

    Google Scholar 

  • Lee, L.-F.: Generalized econometric models of selectivity. Econometrica 51, 507–512 (1983)

    Article  Google Scholar 

  • Miller, E.: A travel demand modelling system for the greater toronto area. In: Toronto: Joint Program in Transportation. University of Toronto (2007)

  • Miller, E., Roorda, M.: Prototype model of household activity-travel scheduling. Transp. Res. Rec. J. Transp. Res. Board 1831, 114–121 (2003). https://doi.org/10.3141/1831-13

    Article  Google Scholar 

  • Pendyala, R., Kitamura, R., Kikuchi, A., Yamamato, T., Fuji, S.: Florida activity mobility simulator: overview and preliminary validation results. Transp. Res. Rec. 1921, 123–130 (2005)

    Article  Google Scholar 

  • Pollak, R.A., Wales, T.J.: Demand System Specification and Estimation. Oxford University Press, New York (1992)

    Google Scholar 

  • Sikder, S., Augustin, B., Pinjari, A.R., Eluru, N.: Spatial transferability of tour-based time-of-day choice models: an empirical assessment. Proc. Soc. Behav. Sci. 104, 640–649 (2013). https://doi.org/10.1016/j.sbspro.2013.11.158

    Article  Google Scholar 

  • Sikder, S., Pinjari, A.R.: Spatial transferability of person-level daily activity generation and time use models: empirical assessment. Transp. Res. Rec. J. Transp. Res. Board 2343, 95–104 (2013)

    Article  Google Scholar 

  • Swait, J., Bernardino, A.: Distinguishing taste variation from error structure in discrete choice data. Transp. Res. Part B Methodol. 34(1), 1–15 (2000). https://doi.org/10.1016/S0191-2615(99)00009-0

    Article  Google Scholar 

  • Thomas, T., Tutert, S.I.A.: An empirical model for trip distribution of commuters in The Netherlands: transferability in time and space reconsidered. J. Transp. Geogr. 26, 158–165 (2013). https://doi.org/10.1016/j.jtrangeo.2012.09.005

    Article  Google Scholar 

Download references

Acknowledgements

The study was funded by an NSERC Discovery Grant and an Early Researcher Award from Ontario Ministry of Economic Development and Innovation. Authors acknowledge the comments and suggestion of the reviewer as well as participants of the 2015 IATBR conference. However, the views expressed in the paper belong only to the authors of the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Khandker M. Nurul Habib.

Ethics declarations

Conflict of interest

There is no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Salem, S., Habib, K.M.N. Use of repeated cross-sectional travel surveys for developing meta models of activity-travel scheduling processes. Transportation 46, 395–423 (2019). https://doi.org/10.1007/s11116-018-9954-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-018-9954-8

Keywords

Navigation