Technical Papers
Jan 20, 2023

Allowing for Psychological Comprehensive Perception Value in Transfer Decision of Public Transit

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 4

Abstract

To explore traveler transfer decisions for different purposes, a transfer decision model allowing psychological comprehensive perception value is built based on cumulative prospect theory. Combined with the value function of the arrival time and time value model, the cost function of psychological comprehensive perception is established, and the reference point of psychological comprehensive perception is set. Travel cumulative prospect models of bus interchanges and bus transfers to subways chosen by commuters and noncommuters are established, and the two-dimensional (departure time and travel mode) optimal travel decisions of commuters and noncommuters are obtained based on the calculation results. The results show that traveler cumulative prospect value first increases and then decreases with the delay of departure time, and the peak value’s occurrence time of a bus transfer to a subway is later than that of a bus interchange. Cumulative prospect value decreases as the transfer time increases when travelers’ arrive at the destination at the same time. Commuters obtain higher gains when they choose late departure time and bus transfer to the subway with determined transfer time, while noncommuters obtain higher gains with the opposite choice. The results show that traveler comprehensive psychological perception not only depends on arrival time but also depends on departure time, travel time in different stages, and cost. Travelers have different risk preferences for different travel purposes, and commuters’ time value is high, which determines whether they tend to pursue risk. Noncommuters tend to avoid risk. This conclusion can provide a theoretical basis for transfer decisions to improve satisfaction with public transit.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This paper was financially supported by The National Natural Science Foundation of China (51908187).

References

Cascajo, R., A. Garcia-Martinez, and A. Monzon. 2017. “Stated preference survey for estimating passenger transfer penalties: Design and application to Madrid.” Eur. Transport Res. Rev. 9 (3): 1–11. https://doi.org/10.1007/s12544-017-0260-x.
Chi, D., and B. Wang. 2020. “Research on influencing factors of rail transit transfer choice behavior based on logistic model.” [In Chinese.] Sci. Technol. Innovation 2020 (17): 13–14. https://doi.org/CNKI:SUN:HLKX.0.2020-17-005.
Connors, R. D., and A. Sumalee. 2009. “Network equilibrium model with travelers’ perception of stochastic travel times.” Transp. Res. Part B: Methodol. 43 (6): 614–624. https://doi.org/10.1016/j.trb.2008.12.002.
Hu, X. W., J. Wang, and G. L. Sun. 2011. “Traveler’s mode choice behavior analysis under bounded rational.” [In Chinese.] J. Harbin Inst. Technol. 42 (12): 114–118. https://doi.org/CNKI:SUN:HEBX.0.2011-12-024.
Huang, X. J., and X. L. Shi. 2017. “Modeling and analysis of path selection with two dimensional condition based on prospect theory.” [In Chinese.] China Transp. Rev. 39 (7): 42–46. https://doi.org/CNKI:SUN:YSZH.0.2017-07-010.
Jiang, H., and X. H. Ren. 2018. “Passenger choice behavior model and empirical study under flight delay information.” [In Chinese.] J. Transp. Syst. Eng. Inf. Technol. 18 (4): 188–193. https://doi.org/10.16097/j.cnki.1009-6744.2018.04.028.
Jin, F. L., A. B. Kun, and E. J. Yao. 2020. “Mode choice analysis in urban transport with shared battery electric vehicles: A stated-preference case study in Beijing, China.” Transp. Res. Part A: Policy Pract. 133 (3): 95–108. https://doi.org/10.1016/j.tra.2020.01.009.
Kahneman, D., and A. Tversky. 1979. “Prospect theory: An analysis of decision under risk.” Econimetrica 47 (2): 263–291. https://doi.org/10.2307/1914185.
Li, X., and L. Liu. 2015. “Route choice model for commuters based on cumulative prospect theory.” [In Chinese.] Transp. Syst. Eng. Inf. 15 (1): 173–178. https://doi.org/10.16097/j.cnki.1009-6744.2015.01.027.
Li, Y., C. Shi, and Z. J. Zhou. 2021. “Decision-making factor analysis of urban rail transit transfer flow.” [In Chinese.] Urban Transport China 19 (2): 121–127. https://doi.org/10.13813/j.cn11-5141/u.2021.0005.
Liang, C. Y., and Y. Kong. 2018. “Analysis of influencing factors on transfer mode selection of Changchun rail transit.” [In Chinese.] Technol. Econ. Areas Commun. 20 (3): 6–10. https://doi.org/10.19348/j.cnki.issn1008-5696.2018.03.002.
Lyu, Z. X., X. Yang, S. Z. Tao, and J. Ma. 2017. “A decision method for route selection of ships based on prospect theory and TOPSIS.” [In Chinese.] J. Transp. Inf. Saf. 35 (6): 18–84. https://doi.org/10.3963/j.issn.1674-4861.2017.06.011.
Ma, S. H., Y. Li, and M. Yue. 2020. “Study on intercity passenger transfer mode choice based on travel chain.” [In Chinese.] J. Beijing Jiao Tong Univ. 44 (6): 74–81. https://doi.org/10.11860/j.issn.1673-0291.20200070.
Ma, S. T., Y. C. Zhou, and Y. Zhang. 2019. “Study on travel mode selection prediction model based on NL cumulative prospect theory.” [In Chinese.] Transp. Syst. Eng. Inf. 19 (4): 135–142. https://doi.org/10.16097/j.cnki.1009-6744.2019.04.020.
Manley, E. J., S. W. Orr, and T. Cheng. 2015. “A heuristic model of bounded route choice in urban areas.” Transp. Res. Part C: Emerging Technol. 56 (Jul): 195–209. https://doi.org/10.1016/j.trc.2015.03.020.
Oostendorp, R., and L. Gebhardt. 2018. “Combining means of transport as a users’ strategy to optimize traveling in an urban context: Empirical results on intermodal travel behavior from a survey in Berlin.” J. Transp. Geogr. 71 (Jul): 72–83. https://doi.org/10.1016/j.jtrangeo.2018.07.006.
Pnevmatikou, A. M., M. G. Karlaftis, and K. Kepaptsoglou. 2015. “Metro service disruptions: How do people choose to travel?” Transportation 42 (6): 933–949. https://doi.org/10.1007/s11116-015-9656-4.
Prabhat, S., and O. Margaret. 2006. “A model for development of optimized feeder routes and coordinated schedules—A genetic algorithms approach.” Transport Policy 13 (5): 413–425. https://doi.org/10.1016/j.tranpol.2006.03.002.
Qian, K., Y. Chen, and B. Mao. 2015. “Route choice behavior for urban rail transit considering transfer time.” [In Chinese.] Transp. Syst. Eng. Inf. 15 (2): 116–121. https://doi.org/10.16097/j.cnki.1009-6744.2015.02.018.
Qin, S. H. 2013. Research on joint choice behavior of travel mode and route based on prospect theory. [In Chinese.] Harbin, China: Harbin Institute of Technology. https://doi.org/10.7666/d.D420455.
Schmidt, U., C. Starmer, and R. Sugden. 2008. “Third-generation prospect theory.” J. Risk Uncertainty 36 (3): 203–223. https://doi.org/10.1007/s11166-008-9040-2.
Schwanen, T., and D. F. Ettema. 2009. “Coping with unreliable transportation when collecting children: Examining parents’ behavior with cumulative prospect theory.” Transp. Res. Part A 43 (5): 511–525. https://doi.org/10.1016/j.tra.2009.01.002.
Sepeher, G., D. Aref, and Z. Lei. 2019. “Modeling effects of travel time reliability on mode choice using cumulative prospect theory.” Transp. Res. Part C: Emerging Technol. 108 (10): 245–254. https://doi.org/10.1016/j.trc.2019.09.014.
Shi, A., X. W. Hu, and J. Wang. 2014. “A cumulative prospect theory approach to car owner mode choice behaviour prediction.” Transport 29 (4): 386–394. https://doi.org/10.3846/16484142.2014.983161.
Si, B. F., B. Mao, and Z. L. Liu. 2007. “Passenger flow assignment model and algorithm for urban railway traffic network under the condition of seamless transfer.” J. China Railway Soc. 29 (6): 12–18. https://doi.org/10.3321/j.issn:1001-8360.2007.06.003.
Tian, L. J., Q. Yang, H. J. Huang, and C. Lyu. 2016. “The cumulative prospect theory-based travel mode choice model and its empirical verification.” [In Chinese.] Syst. Eng. Theory Pract. 36 (7): 1778–1785. https://doi.org/10.12011/1000-6788(2016)07-1778-08.
Tversky, A., and D. Kahneman. 1992. “Advances in prospect theory: Cumulative representation of uncertainty.” J. Risk Uncertainty 5 (4): 297–323. https://doi.org/10.1007/BF00122574.
Wang, H. Q., H. Chen, W. Feng, and W. W. Liu. 2017. “Multi-dimensional travel decision model of heterogeneous commuters based on cumulative prospect theory.” [In Chinese.] J. Zhejiang Univ. (Eng. Sci.) 51 (2): 297–303. https://doi.org/10.3785/j.issn.1008-973X.2017.02.010.
Wang, J. Y., T. T. Zhou, and J. W. Peng. 2021. “Simulation evaluation of high-speed rail passenger transfer to urban rail transit: Based on modeling skills and implementation of Anylogic.” Technol. Econ. Areas Commun. 23 (5): 14–22. https://doi.org/10.19348/j.cnki.issn1008-5696.2021.05.003.
Wei, H., R. G. Ma, and Y. F. Zhao. 2014. “Split model in urban comprehensive passenger hub.” [In Chinese.] J. Chang’an Univ. (Nat. Sci. Ed.) 34 (2): 94–98. https://doi.org/10.19721/j.cnki.1671-8879.2014.02.015.
Yang, Q. F., W. D. Qu, and T. Sun. 2018. “Research on dynamic path selection model considering risk aversion.” [In Chinese.] Technol. Highway Transport 14 (8): 300–304. https://doi.org/CNKI:SUN:GLJJ.0.2018-08-100.
Yao, L. 2020. “Commuter travel mode selection based on cumulative prospect theory.” [In Chinese.] Technol. Econ. Areas Commun. 22 (5): 33–38. https://doi.org/10.19348/j.cnki.issn1008-5696.2020.05.008.
Zhang, W., and R. C. He. 2014. “Dynamic route choice based on prospect theory.” Soc. Behav. Sci. 138 (Jul): 159–167. https://doi.org/10.1016/j.sbspro.2014.07.191.
Zhang, Z., and Z. H. Huang. 2020. “Walking time distribution of transfer passengers based on proportional hazard model.” IOP Conf. Ser.: Earth Environ. Sci. 474 (7): 072033. https://doi.org/10.1088/1755-1315/474/7/072033.
Zhou, L. Z., S. Q. Zhong, S. F. Ma, and N. Jia. 2014. “Prospect theory based estimation of drivers’ risk attitudes in route choice behaviors.” Accid. Anal. Prev. 73 (Dec): 1–11. https://doi.org/10.1016/j.aap.2014.08.004.

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 149Issue 4April 2023

History

Received: Mar 2, 2022
Accepted: Jul 26, 2022
Published online: Jan 20, 2023
Published in print: Apr 1, 2023
Discussion open until: Jun 20, 2023

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Associate Professor, College of Civil Engineering and Transportation, Hebei Univ. of Technology, Tianjin 300401, China. Email: [email protected]
Postgraduate, College of Civil Engineering and Transportation, Hebei Univ. of Technology, Tianjin 300401, China. Email: [email protected]
Shengyu Liu [email protected]
Postgraduate, College of Civil Engineering and Transportation, Hebei Univ. of Technology, Tianjin 300401, China. Email: [email protected]
Associate Professor, College of Civil Engineering and Transportation, Hebei Univ. of Technology, Tianjin 300401, China (corresponding author). Email: [email protected]

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