Waiting Decision Behavior of Commuters for Bus Transits Based on Prospect Theory
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 4
Abstract
Aiming to analyze the waiting decision behavior of commuters for bus transits at a bus station of departure during morning peak hours, this paper builds a bus-waiting decision model based on the prospect theory, with consideration of commuters’ total travel costs comprehensively. Taking the total costs of taxi carpooling for individuals as the reference point for travel costs, the travel prospect value models of commuters choosing bus and bus were established, respectively. The results of the numerical example show that the best choice of commuters is closely related to the bus departure interval and the in-vehicle travel time. This paper constructs a two-variable dynamic selection model to explore the decision-making behavior of commuters, with bus departure intervals and in-vehicle travel times as core variables. The research result can help the public transportation management department adjust departure intervals, as well as improve the commuters’ travel satisfaction and the utilization efficiency of the public transportation system.
Get full access to this article
View all available purchase options and get full access to this article.
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 work was partially supported by Colleges and Universities in Hebei Province through the Science and Technology Research Project (QN2018231), the Natural Science Foundation of Hebei Province (E2019202447), and the Natural Science Foundation of Guangdong Province (2018A030310333).
References
Beesley, M. 1965. “The value of time spent in traveling: Some new evidence.” Economical 32 (126): 174–185. https://doi.org/10.2307/2552547.
Cai, M., Z. Lan, Z. Zhang, and H. B. Wang. 2019. “Evaluation of road traffic noise exposure based on high-resolution population distribution and grid-level noise data.” Build. Environ. 147 (Jan): 211–220. https://doi.org/10.1016/j.buildenv.2018.08.037.
Carrion, C., and D. Levinson. 2012. “Value of travel time reliability: A review of current evidence.” Transp. Res. Part A: Policy Pract. 46 (4): 720–741. https://doi.org/10.1016/j.tra2012.01.003.
Chen, L., L. Feng, and Q. R. Li. 2018. “Bus departure interval model considering on-bus perceived value.” [In Chinese.] J. Harbin Inst. Technol. 50 (3): 150–155. https://doi.org/10.11918/j.issn.0367-6234.201704096.
Fan, W., and R. Machemehl. 2009. “Do transit users just wait for buses or wait with strategies?” Transp. Res. Rec. 2111 (1): 169–176. https://doi.org/10.3141/2111-19.
Fan, W., R. Machemehl, and N. Lownes. 2008. “Carsharing: Dynamic decision-making problem for vehicle allocation.” Transp. Res. Rec. 2063 (1): 97–104. https://doi.org/10.3141/2063-12.
Fujii, S., and R. Kitamura. 2004. “Drivers’ mental representation of travel time and departure time choice in uncertain traffic network conditions.” Networks Spatial Econ. 4 (3): 243–256. https://doi.org/10.1023/b:nets.0000039781.10517.3a.
Gao, K., L. J. Sun, H. Z. Tu, and H. Li. 2018. “Heterogeneity in valuation of travel time reliability and in-vehicle crowding for mode choices in multimodal networks.” Transp. Eng. Part A: Syst. 144 (10): 04018061. https://doi.org/10.1061/JTEPBS.0000187.
Ghader, S., A. Darzi, and L. Zhang. 2019. “Modeling effects of travel time reliability on mode choice using cumulative prospect theory.” Transp. Res. Part C: Emerging Technol. 108 (Nov): 245–254. https://doi.org/10.1016/j.trc.2019.09.014.
Gwilliam, K. M. 1999. The value of time of economic evaluation of transport projects: Lessons from recent research. New York: World Bank.
Han, F., X. M. Zhao, and L. Cheng. 2020. “Traffic assignment problem under tradable credit scheme in a bi-modal stochastic transportation network: A cumulative prospect theory approach.” J. Cent. South Univ. 27 (1): 180–197. https://doi.org/10.1007/s11771-020-4287-0.
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. 43 (12): 119–123.
Huang, C., M. Burris, and W. Douglass Shaw. 2016. “Models of transportation choice with risk: An application to managed lanes.” Transp. Lett. 9 (5): 276–295. https://doi.org/10.1080/19427867.2016.1204811.
Huang, C., M. Burris, and W. Douglass Shaw. 2017. “Models of transportation choice with risk: An application to managed lanes.” Transp. Lett. 9 (5): 276–295. https://doi.org/10.1080/19427867.2016.1204811.
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. 2017 (7): 42–46.
Indriany, S., A. Sjafruddin, A. Kusumawati, and W. Weningtyas. 2018. “Mode choice model for working trip under risk and uncertainty.” Nagoya Jpn. (ICETIA) 1977 (1): 020041. https://doi.org/10.1063/1.5042897.
Jiang, S. C., Y. F. Sun, and Y. C. Du. 2012. “Influence of in-vehicle congestion degree on choice of public transit mode.” [In Chinese.] J. Tongji Univ. (Nat. Sci.) 2012 (12): 89–93. https://doi.org/10.3969/j.issn.0253-374x.2012.12.015.
Kahneman, D., and A. Tversky. 1979. “Prospect theory: An analysis of decisions under risk.” Econometrica 47 (2): 263–291. https://doi.org/10.1142/9789814417358_0006.
Li, T. Y., and M. H. Shao. 2011. “Comparison of value public transport time for passengers considering congestion.” [In Chinese.] J. Transp. Sci. Eng. 27 (3): 85–89. https://doi.org/10.3969/j.issn.1674-599X.2011.03.016.
Lv, S., L. Y. Tao, and Y. K. Mo. 2015. “Level of service classification and quantification for bus waiting time on commuting trip.” [In Chinese.] J. Transp. Syst. Eng. Inform. Technol. 15 (3): 190–195. https://doi.org/10.16097/j.cnki.1009-6744.2015.03.030.
Miralinaghi, M., S. Peeta, X. Z. He, and S. V. Ukkusuri. 2019. “Managing morning commute congestion with a tradable credit scheme under commuter heterogeneity and market loss aversion behavior.” Transportmetrica B: Transp. Dyn. 7 (1): 1780–1808. https://doi.org/10.1080/21680566.2019.1698379.
Psarros, I., K. Kepaptsoglou, and M. G. Karlaftis. 2011. “An empirical investigation of passenger wait time perception.” Transp. Res. Board Meet. 14 (3): 109–122. https://doi.org/10.5038/2375-0901.14.3.6.
Shao, M. H., T. Y. Li, and L. J. Sun. 2012. “Survey method and model of passengers cost perception of crowding level in bus.” [In Chinese.] J. Tongji Univ. (Nat. Sci.) 40 (7): 71–74. https://doi.org/10.3969/j.issn.0253-374x.2012.07.012.
Shi, A., X. W. Hu, and J. Wang. 2014. “A cumulative prospect theory approach to owner mode choice mode choice behavior prediction.” Transp. Sci. Technol. 29 (4): 386–394. https://doi.org/10.3846/16484142.2014.983161.
Tian, L. J., C. R. Lu, and W. B. Huang. 2016. “Modelling carpooling behavior based on cumulative prospect theory.” [In Chinese.] Syst. Eng. Theory Pract. 36 (6): 1576–1584.
Wang, W., and H. J. Sun. 2016. “Cumulative prospect theory-based user equilibrium model with stochastic perception errors.” J. Cent. South Univ. 23 (5): 2465−2474. https://doi.org/10.1007/s11771-016-3305-8.
Wu, Q. B., F. Chen, and Y. X. Gao. 2015. “Computation model of standing-passenger density in urban rail transit carriage.” [In Chinese.] J. Traffic Transp. Eng. 15 (4): 101–109. https://doi.org/10.19818/j.cnki.1671-1637.2015.04.013.
Wu, W. X., and H. J. Huang. 2009. “Model of subway commuters’ departure time choice with in-carriage congestion and arrival early late penalty.” [In Chinese.] J. Transp. Syst. Eng. Inf. Technol. 9 (1): 132–136. https://doi.org/10.3969/j.issn.1009-6744.2009.01.022.
Xia, J. J., Z. C. Jun, and J. X. Gao. 2012. “Travel routing behaviors based on prospect theory.” [In Chinese.] J. Highway Transp. Res. Dev. 29 (4): 126–131. https://doi.org/10.3969/j.issn.1002-0268.2012.04.022.
Xu, T., Z. Lan, D. W. Hu, X. D. Sun, and W. L. Wang. 2013. “Influence of trip cost on trip mode for resident.” [In Chinese.] J. Traffic Transp. Eng. 13 (1): 95–101. https://doi.org/10.3969/j.issn.1671-1637.2013.01.014.
Yang, C., B. B. Liu, L. Y. Zhao, and X. D. Xu. 2017. “An experimental study on cumulative prospect theory learning model of travelers’ dynamic mode choice under uncertainty.” Int. J. Transp. Technol. 6 (2): 143–158. https://doi.org/10.1016/j.ijtst.2017.07.002.
Yang, L. Y., and P. J. Zhao. 2012. “Travel mode choice model accounting for individual preference heterogeneity and correlation among choice alternatives.” [In Chinese.] Acta Scientiarum Naturalium Universitatis Pekinensis 48 (6): 1009–1015. https://doi.org/10.13209/j.0479-8023.2012.130.
Zhang, C., T. L. Liu, H. J. Huang, and J. Chen. 2018. “A cumulative prospect theory approach to commuters’ day-to-day route choice modeling with friends’ travel information.” Transp. Res. Part C 86 (Jan). 527–548. https://doi.org/10.1016/j.trc.2017.12.005.
Zhang, W., and R. C. He. 2014. “Residents travel mode choice based on prospect theory.” [In Chinese.] J. Comput. Appl. 34 (3): 749–753. https://doi.org/10.11772/j.issn.1001-9081.2014.03.0749.
Zong, G., Q. H. Zeng, and S. H. Wei. 2020. “Study on choice behavior of traffic mode based on time value.” [In Chinese.] J. Ind. Eng. Manage. 2020 (3): 15. https://doi.org/10.13587/j.cnki.jieem.2020.03.015.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 4 • April 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Aug 26, 2020
Accepted: Dec 14, 2020
Published online: Feb 4, 2021
Published in print: Apr 1, 2021
Discussion open until: Jul 4, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.