Modeling and Sensitivity Analysis for Railway Passengers’ Public Transit Mode Choice

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Comprehensive terminal integrates different modes of transport and sharing rates of different traffic modes influence its planning greatly. To determine the sharing rates, it’s necessary to study mode choice probability of passengers. Based on the theory of disaggregate choice, with the survey of mode choices of passengers arriving by rail in Nanjing south railway station, this paper establishes multinomial logit (MNL) model and nest logit (NL) model, considering three types of modes of transport including the subway, regular bus, and taxi. Models are calibrated with SPSS and validated through statistical indicators. Therefore, important factors influencing choice are obtained. The accuracy test results of two kinds of models show that NL model has higher prediction accuracy, and can overcome the shortcomings of traditional logit model’s independent and irrelevant alternatives (IIA). Finally, this paper develops the sensitivity analysis using the NL upper model as an example, and gives the sensitivity physical meaning, namely the development level of taxi.

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Edited by:

Xun Wu, Weizhen Chen, Weijun Yang and Jianguo Liang

Pages:

678-684

Citation:

J. Zhang et al., "Modeling and Sensitivity Analysis for Railway Passengers’ Public Transit Mode Choice", Applied Mechanics and Materials, Vols. 641-642, pp. 678-684, 2014

Online since:

September 2014

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$41.00

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[1] D. McFadden, S. Daniel, Conditional logit analysis of qualitative choice behavior, in: P. Zarembka (Eds. ), Frontiers in Econometrics, Academic Press, 1974, pp.105-142.

[2] M. Ben-Akiva, R. L. Steven, Discrete choice analysis: The theory and application to travel demand, The MIT Press, Cambridge Massachusetts, (1985).

[3] A. Thomas, M. Ben-Akiva, A theoretical and empirical model of trip chaining behavior. Transportation Research Part B, 13 (1979) 243-257.

DOI: https://doi.org/10.1016/0191-2615(79)90016-x

[4] H. G. William and D. A. Hensher, A latent class model for discrete choice analysis: contrasts with mixed logit. Transportation Research Part B, 37 (2003) 681-698.

DOI: https://doi.org/10.1016/s0191-2615(02)00046-2

[5] M. Tang, Research on pedestrian traffic behavior model and simulation algorithm in passenger transfer hub, Ph.D. Thesis, Jilin University, Jilin, China, (2010).

[6] J. Tang, Z. Juan. Travel space and mode combined choice model for urban travelers, Journal of highway and transportation research and development. l27 (2010) 84-99.