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http://dx.doi.org/10.12815/kits.2022.21.3.1

Train Crowdedness Analysis Model for the Seoul Metropolitan Subway : Considering Train Scheduling  

Lee, Sangjun (Dept. of Transportation Systems Research, The Seoul Institute)
Yun, Seongjin (Dept. of Transportation Systems Research, The Seoul Institute)
Shin, Seongil (Dept. of Transportation Systems Research, The Seoul Institute)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.21, no.3, 2022 , pp. 1-17 More about this Journal
Abstract
Accurate analysis of the causes of metro rail traffic congestion provides a means of addressing issues arising from metro rail traffic congestion in metropolitan areas. Currently, congestion analysis based on counting, weight detection, CCTVs, and mobile Wi-Fi is limited by poor accuracies or because studies have been restricted to single routes and trains. In this study, a train congestion analysis model was used that includes the transfer and multi-path behavior of metro passengers and train operation plans for metropolitan urban railroads. Analysis accuracy was improved by considering traffic patterns in which passengers must wait for next trains due to overcrowding. The model updates train crowding levels every 10 minutes, provides information to potential passengers, and thus, is expected to increase the social benefits provided by the Seoul metropolitan subway
Keywords
Crowding; Urban railway; Smartcard data; Train Operation plan; Train scheduling;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Transportation Research Board of the National Academies(2013), Transit Capacity and Quality of Service Manual (3rd ed.).
2 Lee, S. J., Shin, S. I., Lee, S. H. and Yun, S. J.(2021), "Estimation of Usable Waiting Areas considering Passenger Behavior on Urban Railway Platforms", Journal of Korean Society of Transportation, vol. 39, no. 6, pp.721-736.   DOI
3 Nguyen, K. A., Wang, Y., Li, G., Luo, Z. and Watkins, C.(2019), "Realtime tracking of passengers on the London underground transport by matching smartphone accelerometer footprints", Sensors, vol. 19, no. 19, 4184.   DOI
4 Shin, S. I., Lee, S. J. and Lee, C. H.(2019), "A Model for Analyzing Time-Varying Passengers' Crowdedness Degree of Subway Platforms Using Smart Card Data", The Korea Institute of Intelligent Transport Systems, vol. 18, no. 5, pp.49-63.   DOI
5 Azevedo, J. A., Costa, M. E. O. S., Madeira, J. J. E. R. S. K. and Martins, E. Q. V.(1993), "An algorithm from the ranking of shortest paths", European Journal of Operation Research, vol. 69, pp.97-106.   DOI
6 Cho, S. K. and Chung, I. B.(2015), "A Study on the Solution of Train Delay and Congestion on Seoul Subway Line 2", Seoul City Research, pp.123-135.
7 Eom, J. K., Song, J. Y. and Lee, K. S.(2014), "Load factor decrease in the Seoul metro circle line through analyzing passenger OD demand", Journal of the Korean Society for Railway, vol. 17, no. 6, pp.457-465.   DOI
8 Jiao, L., Shen, L., Shuai, C., Tan, Y. and He, B.(2017), "Measuring crowdedness between adjacent stations in an urban metro system: A Chinese case study", Sustainability, vol. 9, no. 12, 2325.   DOI
9 Lee, S. J. and Shin, S. I.(2020), "A Study on Improving Subway Crowding Based on Smart Card Data: A Focus on Early Bird Policy Alternative", Journal of Information Technology Services, vol. 19, no. 2, pp.125-138.   DOI
10 Ministry of Land, Infrastructure and Transport(2013), Highway Capacity Manual, South Korea.
11 Ministry of Land, Infrastructure and Transport(2018), Urban Railway Station and Transfer and Convenience Facilities Design Guidelines.
12 Seoul Institute(2016), "Policy utilization for crowdedness costs for subway in Seoul", Policy Report, vol. 208, p.3.
13 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", The Korean Society for Railway, vol. 19, no. 5, pp.663-671.   DOI
14 Hong, S. P., Min, Y. H., Park, M. J., Kim, K. M. and Oh, S. M.(2015), "Precise estimation of connections of metro passengers from Smart Card data", Transportation, vol. 43, no. 5, pp.749-769.   DOI
15 Seoul Open Data Portal, http://stat.seoul.go.kr, 2021.11.22.
16 Tirachini, A., Hensher, D. A. and Rose, J. M.(2013), "Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand", Transportation Research Part A: Policy and Practice, vol. 53, pp.36-52.   DOI
17 Transportation For London(2017), Review of the TfL WiFi pilot, London, pp.4-45.