DOI QR코드

DOI QR Code

Trip Assignment for Transport Card Based Seoul Metropolitan Subway Using Monte Carlo Method

Monte Carlo 기법을 이용한 교통카드기반 수도권 지하철 통행배정

  • Meeyoung Lee (National Economic Advisory Council) ;
  • Doohee Nam (School of Social Science, Hansung University)
  • Received : 2023.03.13
  • Accepted : 2023.04.25
  • Published : 2023.04.30

Abstract

This study reviewed the process of applying the Monte Carlo simulation technique to the traffic allocation problem of metropolitan subways. The analysis applied the assumption of a normal distribution in which the travel time information of the inter-station sample is the basis of the probit model. From this, the average and standard deviation are calculated by separating the traffic between stations. A plan was proposed to apply the simulation with the weights of the in-vehicle time of individual links and the walking and dispatch interval of transfer. Long-distance traffic with a low number of samples of 50 or fewer was evaluated as a way to analyze the characteristics of similar traffic. The research results were reviewed in two directions by applying them to the Seoul Metropolitan Subway Network. The travel time between single stations on the Seolleung-Seongsu route was verified by applying random sampling to the in-vehicle time and transfer time. The assumption of a normal distribution was accepted for sample sizes of more than 50 stations according to the inter-station traffic sample of the entire Seoul Metropolitan Subway. For long-distance traffic with samples numbering less than 50, the minimum distance between stations was 122Km. Therefore, it was judged that the sample deviation equality was achieved and the inter-station mean and standard deviation of the transport card data for stations at this distance could be applied.

본 연구는 Monte Carlo 기법을 교통카드기반의 수도권 지하철의 통행배정 문제에 적용하는 과정을 검토하였다. 연구는 우선 교통카드에서 역 간 표본의 통행에서 나타나는 통행시간에 대하여 프로빗 모형의 기반이 되는 정규분포의 가정을 적용하였다. Monte Carlo 통행배정은 역 간 통행에 대하여 평균과 표준편차를 산정하고 이를 개별 링크의 차내시간과 환승의 보행 및 배차간격의 가중치로 적용하는 방안을 제안하였다. 샘플 수가 50 이하로 낮게 나타나는 장거리 통행은 유사 통행의 특성을 이전하는 방안으로 적용하였다. 수도권 지하철 네트워크에 대하여 두 가지 방향에서 연구 결과를 검토하였다. 하나는 선릉-성수의 단일 역 간 통행에 대하여 차내시간 및 환승시간에 랜덤샘플링을 적용하는 방안으로 검증하였다. 다음으로 수도권 지하철 전체에 대해서는 역 간 통행 샘플수에 따라서 50 이상은 역 간 정규분포의 가정을 그대로 수용하였다. 샘플수가 50 이하의 장거리 통행은 역 간 최소거리가 122 (Km)에서 표본의 균등성이 확보되는 상황으로 판단하고 이 거리에서 나타나는 카드자료의 역 간 평균과 표준편차를 적용하였다. 사례연구로서 교통카드자료로 구축된 수도권 지하철을 네트워크를 대상으로 단일OD 및 전체 OD의 통행배정의 결과를 도출하였다. 한편 통행에 대한 샘플링이 부족한 상황에서 추가적인 연구가 필요한 것으로 나타났다.

Keywords

References

  1. Clark, C. E.(1961), "The Greatest of A Finite Set of Random Variables", Operations Research, vol. 9, no. 2, pp.145-162. https://doi.org/10.1287/opre.9.2.145
  2. Dial, R. B.(1971), "A Probabilistic Multipath Traffic Assignment Algorithms Which Obviates Path Enumeration", Transportation Research, vol. 5, no. 2, pp.83-111. https://doi.org/10.1016/0041-1647(71)90012-8
  3. Dijkstra, E. W.(1959), "A Note on Two Problems in Connexion with Graphs", Numerishe Matematilk, vol. 1, pp.269-271. https://doi.org/10.1007/BF01386390
  4. Kroese, D. P., Brereton, T., Taimre, T. and Botev, Z. I.(2014), "Why the Monte Carlo method is so important today", WIREs Comput Stat, vol. 6, no. 6, pp.386-392, doi: 10.1002/wics.1314
  5. Lee, M.(2004), Transportation Network Models and Algorithms Considering Directional Delay and Prohibitions for Intersection Movement, Doctoral Dissertation, University of Wisconsin at Madison.
  6. Lee, M.(2017), "Transportation Card Based Optimal M-Similar Paths Searching for Estimating Passengers' Route Choice in Seoul Metropolitan Railway Network", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 16, no.2, pp.1-12. https://doi.org/10.12815/kits.2017.16.2.01
  7. Lee, M.(2022), "Generalized K Path Searching in Seoul Metropolitan Railway Network Considering Entry-Exit Toll", The Journal of the Korea Institute of Intelligent Transport Systems, vol. 21, no. 6, pp.1-20. https://doi.org/10.12815/kits.2022.21.6.1
  8. Moore, E. F.(1957), The Shortest Path through A Maze, Harvard University Press, Cambridge.
  9. Sheffi, Y.(1985), Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods, Prentice-Hall, Englewood Cliffs, NJ.
  10. Shin, H.(2022), Estimating Revenues of Integrated Fare System for Seoul Metropolitan Public Transportation using Smartcard Data, Doctoral Dissertation, Graduated School of Engineering, Seoul National University Civil & Environmental Engineering Major.