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Factors affecting temporal changes in mode choice model parameters

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  • Nobuhiro Sanko

Abstract

In travel demand forecasting models, parameters are often assumed to be stable over time. The stability of these parameters, however, has been questioned. This study investigates the factors affecting temporal changes in mode choice model parameters using a method proposed by the author that jointly utilises repeated cross-sectional data. In this method, the parameters are assumed to follow functional forms and the parameter changes are modelled endogenously. While the author’s previous studies assumed that all parameters are the same function of the same variable, this study assumes that different parameters are different functions of different variables, including time (year) and macro-economic variables. The paper describes a case study of a journey-to-work mode choice analysis for Nagoya, Japan, that examines 288 combinations of the functional forms and variables. The analysis found that the functions of time had serious over-fitting problems and that parameter changes are more closely related to economic factors.

Suggested Citation

  • Nobuhiro Sanko, 2016. "Factors affecting temporal changes in mode choice model parameters," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(7), pages 641-652, October.
    • Handle: RePEc:taf:transp:v:39:y:2016:i:7:p:641-652
    DOI: 10.1080/03081060.2016.1204088
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    Cited by:

    1. Nobuhiro Sanko, 2018. "Travel demand forecasts improved by using cross-sectional data from multiple time points: enhancing their quality by linkage to gross domestic product," Transportation, Springer, vol. 45(3), pages 905-918, May.

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