Estimation of Transfer Time Distribution Parameters with Automatic Fare Collection Data: Stochastic Frontier Model
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 7
Abstract
The uncertainty in walking and waiting transfer times at transit stops depends on the environmental conditions, vehicle schedule punctuality, and variations among individuals. Relying only on the mean values ignores such uncertainty and leads to improper transfer coordination. This paper provides a general framework to estimate the time distribution parameters of walking and waiting based on automatic-fare-collection data under the assumption that the distribution function is known. The proposed methodology contributes to the existing literature by providing a stochastic frontier model (SFM) that is adaptable to transit assignment models. The normal/exponential SFM is utilized to estimate distribution parameters based on the maximum-likelihood method. The methodology was applied to smart-card data from Japan to estimate the transfer walking- and waiting-time distributions between bus stops and rail stations. The results indicate a low disturbance in the observed data for walking time and that our assumptions regarding walking-time estimation were reliable. Furthermore, we quantified how the waiting time at a bus stop depends on variations in the service headway. These findings are expected to help in making more informed decisions to optimize transit schedules.
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 used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments (raw data distribution copyrights belong to Shizuoka Railway Co., Ltd). Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors express their gratitude to Shizuoka Railway Co., Ltd. for providing the data required for this research. We also thank the audience and reviewers at the 14th International Conference on Advanced Systems in Public Transport (CASPT) for valuable comments on an earlier draft of this paper.
References
Chowdhury, M. S., and S. I. J. Chien. 2001. “Dynamic vehicle dispatching at the intermodal transfer station.” Transp. Res. Rec. 1753 (1): 61–68. https://doi.org/10.3141/1753-08.
Chung, E. H., and A. Shalaby. 2007. “Development of control strategy for intermodal connection protection of timed-transfer transit routes.” Transp. Res. Rec. 2006 (1): 3–10. https://doi.org/10.3141/2006-01.
Dessouky, M., R. Hall, A. Nowroozi, and K. Mourikas. 1999. “Bus dispatching at timed transfer transit stations using bus tracking technology.” Transp. Res. Part C: Emerging Technol. 7 (4): 187–208. https://doi.org/10.1016/S0968-090X(99)00019-4.
Dessouky, M., R. Hall, L. Zhang, and A. Singh. 2003. “Real-time control of buses for schedule coordination at a terminal.” Transp. Res. Part A: Policy Pract. 37 (2): 145–164. https://doi.org/10.1016/S0965-8564(02)00010-1.
Fan, Y., A. Guthrie, and D. Levinson. 2016. “Waiting time perceptions at transit stops and stations: Effects of basic amenities, gender, and security.” Transp. Res. Part A: Policy Pract. 88 (Jun): 251–264. https://doi.org/10.1016/j.tra.2016.04.012.
Fu, Q., R. Liu, and S. Hess. 2012. “A review on transit assignment modelling approaches to congested networks: A new perspective.” Procedia-Social Behav. Sci. 54 (Oct): 1145–1155. https://doi.org/10.1016/j.sbspro.2012.09.829.
Greene, W. H. 2008. “The econometric approach to efficiency analysis.” In The measurement of productive efficiency and productivity change. New York: Oxford University Press.
Ingvardson, J. B., O. A. Nielsen, S. Raveau, and B. F. Nielsen. 2018. “Passenger arrival and waiting time distributions dependent on train service frequency and station characteristics: A smart card data analysis.” Transp. Res. Part C: Emerging Technol. 90 (May): 292–306. https://doi.org/10.1016/j.trc.2018.03.006.
Jang, W. 2010. “Travel time and transfer analysis using transit smart card data.” Transp. Res. Rec. 2144 (1): 142–149. https://doi.org/10.3141/2144-16.
Jondrow, J., C. A. Knox Lovell, I. S. Materov, and P. Schmidt. 1982. “On the estimation of technical inefficiency in the stochastic frontier production function model.” J. Econom. 19 (2–3): 233–238. https://doi.org/10.1016/0304-4076(82)90004-5.
Kieu, L. M., A. Bhaskar, P. E. Almeida, N. R. Sabar, and E. Chung. 2016. “Transfer demand prediction for timed transfer coordination in public transport operational control.” J. Adv. Transp. 50 (8): 1972–1989. https://doi.org/10.1002/atr.1440.
Kittelson and Associates, KFH Group, Parsons Brinckerhoff Quade and Douglass, and K. Hunter-Zaworski. 2003. Transit capacity and quality of service manual. Washington, DC: Transportation Research Board.
Knoppers, P., and T. Muller. 1995. “Optimized transfer opportunities in public transport.” Transp. Sci. 29 (1): 101–105. https://doi.org/10.1287/trsc.29.1.101.
Kurauchi, F., and J. D. Schmöcker. 2017. Public transport planning with smart card data. London: CRC Press.
Kusakabe, T., T. Iryo, and Y. Asakura. 2010. “Estimation method for railway passengers’ train choice behavior with smart card transaction data.” Transportation 37 (5): 731–749. https://doi.org/10.1007/s11116-010-9290-0.
Lee, M., and K. Sohn. 2015. “Inferring the route-use patterns of metro passengers based only on travel-time data within a Bayesian framework using a reversible-jump Markov chain Monte Carlo (MCMC) simulation.” Transp. Res. Part B Methodol. 81 (Part 1): 1–17. https://doi.org/10.1016/j.trb.2015.08.008.
Liu, R., R. M. Pendyala, and S. Polzin. 1997. “Assessment of intermodal transfer penalties using stated preference data.” Transp. Res. Rec. 1607 (1): 74–80. https://doi.org/10.3141/1607-11.
Nakamura, T., N. Uno, J. D. Schmöcker, and T. Iwamoto. 2017. “Multipurpose smart card data: Case study of Shizuoka, Japan.” In Public transport planning with smart card data, 113–131. London: CRC Press. https://doi.org/10.1201/9781315370408-10.
Nielsen, O. A. 2004. “Behavioral responses to road pricing schemes description of the Danish AKTA experiment.” J. Intell. Transp. Syst. Technol. Plann. Oper. 8 (4): 233–251. https://doi.org/10.1080/15472450490495579.
StataCorp. 2015. Stata statistical software: Release 14. College Station, TX: StataCorp LP.
Sun, L., Y. Lu, J. G. Jin, D. H. Lee, and K. W. Axhausen. 2015. “An integrated Bayesian approach for passenger flow assignment in metro networks.” Transp. Res. Part C: Emerging Technol. 52 (Mar): 116–131. https://doi.org/10.1016/j.trc.2015.01.001.
Sun, Y., and R. Xu. 2012. “Rail transit travel time reliability and estimation of passenger route choice behavior: Analysis using automatic fare collection data.” Transp. Res. Rec. 2275 (1): 58–67. https://doi.org/10.3141/2275-07.
Wahaballa, A. M., F. Kurauchi, T. Yamamoto, and J. D. Schmöcker. 2017. “Estimation of platform waiting time distribution considering service reliability based on smart card data and performance reports.” Transp. Res. Rec. 2652 (1): 30–38. https://doi.org/10.3141/2652-04.
Wardman, M., J. Hine, and S. Stradling. 2001. Interchange and travel choice volume 1. Edinburgh, UK: Scottish Executive Central Research Unit.
Yu, B., S. Wu, B. Yao, Z. Yang, and J. Sun. 2012. “Dynamic vehicle dispatching at a transfer station in public transportation system.” J. Transp. Eng. 138 (2): 191–201. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000311.
Zhang, Y. S., and E. J. Yao. 2015. “Splitting travel time based on AFC data: Estimating walking, waiting, transfer, and in-vehicle travel times in metro system.” Discrete Dyn. Nature Soc. 2015 (1): 1–11. https://doi.org/10.1155/2015/539756.
Zhou, F., J. G. Shi, and R. H. Xu. 2015. “Estimation method of path-selecting proportion for urban rail transit based on AFC data.” Math. Problems Eng. 2015 (6): 1–9. https://doi.org/10.1155/2015/350397.
Information & Authors
Information
Published In
Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 7 • July 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Sep 15, 2020
Accepted: Feb 4, 2021
Published online: Apr 29, 2021
Published in print: Jul 1, 2021
Discussion open until: Sep 29, 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.