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Modeling departure time choice of metro passengers with a smart corrected mixed logit model - A case study in Beijing

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  • Li, Haiying
  • Li, Xian
  • Xu, Xinyue
  • Liu, Jun
  • Ran, Bin

Abstract

It is critical to improve the effectiveness of demand management in metro systems with passenger departure time choice exactly learned during peak hours. In this study, a practical framework is developed to model departure time choice of metro passengers during peak hours. First, various attributes that influence departure time choice of metro passengers are investigated and the technique for order preference by similarity to ideal solutions (TOPSIS) is used to identify these main attributes. Then, a mixed logit (ML) model of departure time choice that accounts for price endogeneity is developed. To calibrate the model, a stated preference (SP) survey based on D-efficient design is conducted in the Beijing metro system. It is proved that the corrected ML model outperforms the uncorrected ML model according to the collected 1152 sample data. An elasticity analysis of these main attributes is further conducted, which indicates that metro fare and departure time change influence passenger departure time choice more than crowdedness in Beijing metro. Knowledge of these preferences assists traffic managers in balancing passenger departure time to mitigate overcrowding during peak hours. Heterogeneity of passenger socioeconomic and trip characteristics is also concerned taking advantage of ML model. Finally, a ML-based fare discount strategy to ease the crowdedness in Batong Line of Beijing metro is presented and evaluated via an existing simulation tool.

Suggested Citation

  • Li, Haiying & Li, Xian & Xu, Xinyue & Liu, Jun & Ran, Bin, 2018. "Modeling departure time choice of metro passengers with a smart corrected mixed logit model - A case study in Beijing," Transport Policy, Elsevier, vol. 69(C), pages 106-121.
  • Handle: RePEc:eee:trapol:v:69:y:2018:i:c:p:106-121
    DOI: 10.1016/j.tranpol.2018.06.005
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    as
    1. Kim, Kyung Min & Hong, Sung-Pil & Ko, Suk-Joon & Kim, Dowon, 2015. "Does crowding affect the path choice of metro passengers?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 292-304.
    2. Guevara, C. Angelo, 2015. "Critical assessment of five methods to correct for endogeneity in discrete-choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 240-254.
    3. Lurkin, Virginie & Garrow, Laurie A. & Higgins, Matthew J. & Newman, Jeffrey P. & Schyns, Michael, 2017. "Accounting for price endogeneity in airline itinerary choice models: An application to Continental U.S. markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 228-246.
    4. Rose, John M. & Bliemer, Michiel C.J. & Hensher, David A. & Collins, Andrew T., 2008. "Designing efficient stated choice experiments in the presence of reference alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 395-406, May.
    5. Nurul Habib, Khandker M. & Day, Nicholas & Miller, Eric J., 2009. "An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(7), pages 639-653, August.
    6. Jou, Rong-Chang, 2001. "Modeling the impact of pre-trip information on commuter departure time and route choice," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 887-902, November.
    7. Xu, Xin-yue & Liu, Jun & Li, Hai-ying & Jiang, Man, 2016. "Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 130-148.
    8. Vij, Akshay & Walker, Joan L., 2014. "Preference endogeneity in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 90-105.
    9. Wei Wang & Li Huang & Zhaoxia Guo, 2017. "Optimization of Emergency Material Dispatch from Multiple Depot Locations to Multiple Disaster Sites," Sustainability, MDPI, vol. 9(11), pages 1-8, October.
    10. Thorhauge, Mikkel & Cherchi, Elisabetta & Rich, Jeppe, 2016. "How flexible is flexible? Accounting for the effect of rescheduling possibilities in choice of departure time for work trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 177-193.
    11. Kou, Weibin & Chen, Xumei & Yu, Lei & Qi, Yi & Wang, Ying, 2017. "Urban commuters’ valuation of travel time reliability based on stated preference survey: A case study of Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 372-380.
    12. He, Sylvia Y., 2013. "Does flexitime affect choice of departure time for morning home-based commuting trips? Evidence from two regions in California," Transport Policy, Elsevier, vol. 25(C), pages 210-221.
    13. Aydin, Nezir, 2017. "A fuzzy-based multi-dimensional and multi-period service quality evaluation outline for rail transit systems," Transport Policy, Elsevier, vol. 55(C), pages 87-98.
    14. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    15. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
    16. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    17. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    18. Saleh, Wafaa & Farrell, Séona, 2005. "Implications of congestion charging for departure time choice: Work and non-work schedule flexibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 773-791.
    19. Walker, Joan L. & Ehlers, Emily & Banerjee, Ipsita & Dugundji, Elenna R., 2011. "Correcting for endogeneity in behavioral choice models with social influence variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 362-374, May.
    20. Hess, Stephane & Daly, Andrew & Rohr, Charlene & Hyman, Geoff, 2007. "On the development of time period and mode choice models for use in large scale modelling forecasting systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 802-826, November.
    21. de Jong, Gerard & Daly, Andrew & Pieters, Marits & Vellay, Carine & Bradley, Mark & Hofman, Frank, 2003. "A model for time of day and mode choice using error components logit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 245-268, May.
    22. Sadhukhan, Shubhajit & Banerjee, Uttam K. & Maitra, Bhargab, 2016. "Commuters’ willingness-to-pay for improvement of transfer facilities in and around metro stations – A case study in Kolkata," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 43-58.
    23. Lemp, Jason D. & Kockelman, Kara M. & Damien, Paul, 2010. "The continuous cross-nested logit model: Formulation and application for departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 646-661, June.
    24. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    25. Kamargianni, Maria & Dubey, Subodh & Polydoropoulou, Amalia & Bhat, Chandra, 2015. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 473-488.
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