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http://dx.doi.org/10.12815/kits.2021.20.5.1

Estimation of Mass Rapid Transit Passenger's Train Choice Using a Mixture Distribution Analysis  

Jang, Jinwon (Dept. of Transportation Engineering & Dept. of Smart Cities)
Yoon, Hosang (Dept. of Transportation Engineering & Dept. of Urban Big Data Convergence)
Park, Dongjoo (Dept. of Transportation Engineering & Dept. of Urban Big Data Convergence)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.20, no.5, 2021 , pp. 1-17 More about this Journal
Abstract
Identifying the exact train and the type of train boarded by passengers is practically cumbersome. Previous studies identified the trains boarded by each passenger by matching the Automated Fare Collection (AFC) data and the train schedule diagram. However, this approach has been shown to be inefficient as the exact train boarded by a considerable number of passengers cannot be accurately determined. In this study, we demonstrate that the AFC data - diagram matching technique could not estimate 28% of the train type selected by passengers using the Seoul Metro line no.9. To obtain more accurate results, this paper developed a two-step method for estimating the train type boarded by passengers by applying the AFC data - diagram matching method followed by a mixture distribution analysis. As a result of the analysis, we derived reasonable express train use/non-use passenger classification points based on 298 origin-destination pairs that satisfied the verification criteria of this study.
Keywords
Subway; Express train; Train type; Travel time distribution; AFC data;
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1 Cheng G., Zhao S. and Xu S.(2019), "Estimation of passenger route choices for urban rail transit system based on automatic fare collection mined data," Transactions of the Institute of Measurement and Control, vol. 41, no. 11, pp.3092-3102.   DOI
2 Katori T., Takahashi Y. and Izumi T.(2004), "Determination of stations where rapid trains stop or pass to local ones using a genetic algorithm to shorten total trip time," Computers in Railways, vol. 9, pp.113-121.
3 Lee H. J., Zhang D., He T. and Son S. H.(2017), "Metro Time: Travel Time Decomposition under Stochastic Time Table for Metro Networks," 2017 IEEE International Conference on Smart Computing, Hong Kong, pp.1-8.
4 Othman N. B., Legara E. F., Selvam V. and Monterola C.(2015), "A data-driven agent-based model of congestion and scaling dynamics of rapid transit systems," Journal of Computational Science, vol. 10, pp.338-350.   DOI
5 Sun Y. and Schonfeld P. M.(2016), "Schedule-Based Rail Transit Path-Choice Estimation using Automatic Fare Collection Data," Journal of Transportation Engineering, vol. 142, no. 1.
6 Hong S. P., Min Y. H., Park M. J. and Kim K. M. et al.(2016), "Precise estimation of connections of metro passengers from Smart Card data," Transportation, vol. 43, pp.749-769.   DOI
7 Baek J. H. and Sohn K. M.(2016), "An investigation into passenger preference for express trains during peak hours," Transportation, vol. 43, pp.623-641.   DOI
8 Hong L., Li W. and Zhu W.(2017), "Assigning Passenger Flows on a Metro Network Based on Automatic Fare Collection Data and Timetable," Discrete Dynamics in Nature and Society, vol. 2017, pp.1-10.
9 Kim K. M., Oh S. M., Hong S. P. and Ko S. J.(2015), "Tracing a Logical Path of Passengers: A Case study of Seoul Metro Line 9," Journal of the Korean Society for Railway, vol. 18, no. 6, pp.586-595.   DOI
10 Kim M. S., Kim J. T., Kim T. S. and Park S. S. et al.(2013), "Study of the Metropolitan Rapid Transport System to Minimize Sidetrack Construction," Journal of the Korean Society for Railway, vol. 16, no. 5, pp.402-409.   DOI
11 Kim K. M., Hong S. P., Ko S. J. and Kim D. W.(2015), "Does crowding affect the path choice of metro passengers?," Transportation Research Part A, vol. 77, pp.292-304.   DOI
12 Kim K. M., Oh S. M. and Rho H. L.(2016), "Express Train Choice and Load Factor Analysis as Line Extension in Seoul Metro 9," Journal of the Korean Society for Railway, vol. 19, no. 5, pp.663-671.   DOI
13 Kusakabe T., Iryo T. and Asakura Y.(2010), "Estimation method for railway passengers' train choice behavior with smart card transaction data," Transportation, vol. 37, pp.731-749.   DOI
14 Lee K. H., Lee T. G., Kim H. G. and Lee H. Y.(2018), "A Study on Expres Train Operation for Reducing Travel Time of Urban Railway," Journal of the Korean Society for Urban Railway, vol. 6, no. 2, pp.103-110.   DOI
15 Luo Q., Hou Y., Li W. and Zhang X.(2012), "Stop Plan of Express and Local Train for Regional Rail Transit Line," Journal of Advanced Transportation, vol. 2018, 3179321.
16 Soo P. J., Hee L. H. and Mu W. J.(2006), "A Development of Optimum Operation Models for Express-Rail Systems," Journal of the Korean Society for Civil Engineers D, vol. 26, no. 4D, pp.679-686.
17 Wu J., Qu Y., Sun H. and Yin H.(2019), "Data-driven model for passenger route choice in urban metro network," Physica A, vol. 524, pp.787-798.   DOI
18 Zhou F., Shi J. and Xu R.(2015), "Estimation Method of Path-Selecting Proportion for Urban Rail Transit Based on AFC Data," Mathematical Problems in Engineering, vol. 2015, pp.1-9.
19 Sohn K. M.(2007), "Mixed Operation with Express Train for Urban Railways in Seoul Metropolitan Area," Journal of Korean Society of Transportation, vol. 25, no. 5, pp.195-207.
20 Sun Y. and Xu R.(2012), "Rail Transit Travel Time Reliability and Estimation of Passenger Route Choice Behavior," Transportation Research Record: Journal of the Transportation Research Board, vol. 2275, pp.58-67.   DOI
21 Zhu W. and Xu R.(2016), "Generating route choice sets with operation information on metro networks," Journal of Traffic and Transportation Engineering(English Edition), vol. 3, no. 3, pp.243-252.   DOI
22 Zhu W., Wang W. and Huang Z.(2017), "Estimating train choices of rail transit passengers with real timetable and automatic fare collection data," Journal of Advanced Transportation, vol. 2017, 5824051.