Technical Papers
Oct 13, 2015

Schedule-Based Rail Transit Path-Choice Estimation using Automatic Fare Collection Data

Publication: Journal of Transportation Engineering
Volume 142, Issue 1

Abstract

This paper presents a schedule-based passenger’s path-choice estimation model for a multioperator rail transit network, using automatic fare collection (AFC) data from both entry and exit stations. By introducing the train schedule connection network (TSCN), the path-choice estimation is converted into a set generation and weighted assignment problem for feasible TSCN paths (i.e., passenger trajectories). A major factor in path choice, the fail-to-board (FtB) phenomenon because of overcrowding in peak periods, is explicitly modeled. A method for estimating the FtB parameters is described and a weighted assignment function based on FtB parameters is provided. The case of a typical commuting origin-destination pair in the Beijing Subway is analyzed to demonstrate the capability of the proposed model. Results show that: (1) there can be multiple feasible trajectories for one pair of entry and exit records because of the FtB probability, especially in peak periods; and (2) the transfer penalty is more influential during offpeak periods when the in-vehicle times are similar for different paths. The model has potential for locating network capacity bottlenecks at the train run level and for evaluating the effects of adjusting train timetables on the passengers’ path choice.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors appreciate the data support from both Beijing Subway and Tongji University.

References

Chan, J. (2007). “Rail transit OD matrix estimation and journey time reliability metrics using automated fare data.” M.S. thesis, Massachusetts Institute of Technology, Cambridge, MA.
Cui, A. (2006). “Bus passenger origin-destination matrix estimation using automated data collection systems.” M.S. thesis, Massachusetts Institute of Technology, Cambridge, MA.
Dijkstra, E. W. (1959). “A note on two problems in connexion with graphs.” Numerische Math., 1(1), 269–271.
Guo, Z. (2011). “Mind the map! The impact of transit maps on path choice in public transit.” Transp. Res. Part A, 45(7), 625–639.
Hagberg, A. A., Schult, D. A., and Swart, P. J. (2008). “Exploring network structure, dynamics, and function using NetworkX”. Proc., 7th Python in Science Conf., G. Varoquaux, T. Vaught, and J. Millman, eds., SciPy2008, Pasadena, CA, 11–15.
Hickman, M. D., and Bernstein, D. H. (1997). “Transit service and path choice models in stochastic and time-dependent networks.” Transp. Sci., 31(2), 129–146.
Jang, W. (2010). “Travel time and transfer analysis using transit smart card data.” J. Transp. Res. Board, 2144, 142–149.
Kusakabe, T., Iryo, T., and Asakura, Y. (2010). “Estimation method for railway passengers’ train choice behavior with smart card transaction data.” Transportation, 37(5), 731–749.
Schmöcker, J. (2006). “Dynamic capacity constrained transit assignment.” Ph.D. thesis, Imperial College London, London.
Seaborne, C. W. (2008). “Application of smart card fare payment data to bus network planning in London, U.K.” M.S. thesis, Massachusetts Institute of Technology, Cambridge, MA.
Sun, Y., and Xu, R. (2012). “Rail transit travel time reliability and estimation of passenger route choice behavior.” J. Transp. Res. Board, 2275, 58–67.
Wang, W. (2010). “Bus passenger origin-destination estimation and travel behavior using automated data collection system in London, U.K.” M.S. thesis, Massachusetts Institute of Technology, Cambridge.
Wikipedia. (2013a). “Beijing subway.” 〈http://en.wikipedia.org/wiki/Beijing_Subway〉 (Jun. 11, 2013).
Wikipedia. (2013b). “Metro systems by annual passenger rides.” 〈http://en.wikipedia.org/wiki/Metro_systems_by_annual_passenger_rides〉 (Jun. 11, 2013).
Wilson, N. H., Zhao, J., and Rahbee, A. (2009). “The potential impact of automated data collection systems on urban public transport planning.” Schedule-based modeling of transportation networks, Springer, New York, 1–25.
Wilson, N. H. M., and Nuzzolo, A. (2004). Schedule-based dynamic transit modeling: Theory and applications, Kluwer Academic, Norwell, MA.
Zhao, J., Rahbee, A., and Wilson, N. H. M. (2007). “Estimating a rail passenger trip origin-destination matrix using automatic data collection systems.” Comput. -Aided Civ. Infrastruct. Eng., 22(5), 376–387.
Zhou, F., and Xu, R. (2012). “Model of passenger flow assignment for urban rail transit based on entry and exit time constraints.” J. Transp. Res. Board, 2284, 57–61.

Information & Authors

Information

Published In

Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 142Issue 1January 2016

History

Received: Dec 8, 2013
Accepted: Aug 24, 2015
Published online: Oct 13, 2015
Published in print: Jan 1, 2016
Discussion open until: Mar 13, 2016

Permissions

Request permissions for this article.

Authors

Affiliations

Yanshuo Sun, S.M.ASCE [email protected]
Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742. E-mail: [email protected]
Paul M. Schonfeld, F.ASCE [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742 (corresponding author). E-mail: [email protected]

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.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share