The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
권호 표지
DOI QR코드

DOI QR Code

An Analysis on Evacuation Scenario at Metro-stations using Pedestrian Movement-based Simulation Model

보행류 기반 도시철도역사 평가 시뮬레이터를 활용한 대피 시나리오 분석

  • 유소영 (한국철도기술연구원 녹색교통물류시스템공학연구소 교통체계분석연구팀) ;
  • 정래혁 (정도 UIT) ;
  • 정진혁 (연세대학교 도시공학과)
  • Received : 2016.02.02
  • Accepted : 2016.03.31
  • Published : 2016.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

A subway system is one of the major transportation modes at a metropolitan area. When it meets the other lines, the metro station, so-called transferring station, is usually threatened by severe pedestrian congestion and safety issue of transit users including the transportation vulnerable. Although transportation planners forecast travel demand at the beginning, it is not easy to predict pedestrian flows precisely for a long term if land use plans have dramatically changed. Due to expensive costs, structural extension of metro stations is limited. Therefore, it requires efficient and technical improvements as meeting the demand of pedestrian and physical characteristics. In this study, the core mechanism of pedestrian movement-based simulation model was introduced and evacuation scenarios were analyzed with the developed model. As a result, the multiple optimal routes for unexpected events at the solid space of the multiple stories are easily searched through the simulator and in the case of Sadang Station, travel time can be reduced by 60% when the evacuation information and intuitive design are provided.

도시 철도는 도시 광역권 교통수단으로, 주요 노선들이 만나는 환승역사의 경우, 역사내 보행 통행시 극심한 혼잡을 야기하며, 승강장 내 교통약자를 포함한 이용객들의 안전사고 위험이 높게 나타난다. 반영구적 도시교통 기반시설로의 도시철도역사는 초기 건설 당시 장기 이용 수요 예측을 실시하지만, 향후 신설 노선 및 환승(예정)역을 정확히 파악할 수 없고 건설완료 이후 토지이용계획이 급변할 경우, 예측 수요와 실제 수요는 상이하게 나타날 수 있으며, 확장이 제한적이고 대규모 추가공사 비용이 요구되기 때문에 도시철도 역사가 지닌 물리적 특성 및 이용자 요구에 따라 효율적인 개선이 필요하다. 본 연구에서는 도시철도역사 구조, 이동 동선 등 물리적 요소와 시시각각 변하는 도시철도 내 이용수요 등 변수를 고려하여 다양한 시나리오에 대한 효과분석이 가능한 도시철도역사 평가용 시뮬레이터 핵심 모형을 소개하고, 해당 시뮬레이터를 활용하여, 사당역 대피 시나리오를 분석하였다. 분석결과, 시뮬레이터 활용하여 유사상황 발생시 입체 공간 상에서 다양한 조건을 고려한 다수의 대피 경로 탐색이 용이하였으며, 사당역의 경우, 대피경로 정보제공을 통해 기존 대비 약 60% 대피시간을 절감할 수 있는 것으로 분석되었다.

Keywords

References

  1. Lee J., Kim T. and You S.(2015), "Improvement of Pedestrian Convenience and Mobility by Applying the Walking Guidance System in Subway Stations," Journal of Korean Society of Transportation, vol. 33, no. 2, pp.204-214. https://doi.org/10.7470/jkst.2015.33.2.204
  2. Jung R. and Chung J.(2015), "Analysis of Route Choice Behavior in Subway Stations," Seoul Studies, vol. 16, no. 2, pp.203-214.
  3. Helbing D. and Molnar P.(1995), "Social Force Model for Pedestrian Dynamics," Physical Review, vol. 51, pp.4282-4286.
  4. Still K.(2000), Crowd Dynamics, University of Warwick, Coventry United Kingdom.
  5. SudK A., Andersen E., Curtis S., Lin M. and Manocha D.(2007), Real-Time Path Planning for Virtual Agents in Dynamic Environments, IEEE Virtual Reality, Charlotte, N.C.
  6. Han M., Choi D., Jeong G. and Lee Y.(2010), "Overview of the Development of Microscopic Pedestrian Simulation (P-Sim)," Journal of Transportation Technology and Policy, vol. 7, no. 2, pp.15-29.
  7. Han M.(2015), "Analytic Program of Pedestrian Space Considering Pedestrian Behavior," Railway Journal, vol. 18, no. 4, pp.104-108.
  8. Abdelghany A., Abdelghany A., Mahmassi H.S. and Al-Zahrani A.(2012), "Dynamic Simulation Assignment Model for Pedestrian Movements in Crowded Networks," Transportation Research Record, vol. 2416, pp.95-105.
  9. Fruin J.J. (1971), Pedestrian Planning and Design, Metropolitan Association of Urban Designers and Environmental Planner, Inc. N.Y.
  10. Ministry of Land, Infrastructure, and Transport (2014), Design Guideline for Metro-Station and Transferring Facilities (New Edition).
  11. Transportation Research Board(2014), Transit Capacity and Quality of Service Manual (4th Edition), TCRP Report 165.
  12. Kim J., Oh Y., Son Y. and Park W.(2002), "A Study on Estimating LOS for Pedestrian Facilities," portation, vol. 20, no. 1, pp.149-156.
  13. Lim J., Shin H. and Kim H.(2004), "New Pedestrian LOS by Trip Purpose and Walkway Function," Journal of the Korean Society of Civil Engineers, vol. 24, no. 5, pp.724-728.
  14. Bruce W.(2001), Modeling the Roadside Walking Environment: A Pedestrian Level of Service, Transportation Research Board, 01-0511.
  15. Transportation Research Board(2010), Highway Capacity Manual 2010 (5th Edition).
  16. Ministry of Land, Transport and Maritime Affairs(2014), Korea Highway Capacity Manual.
  17. Yoon T. and Lee Y.(2010), "A Study on the Evaluation Method of Level of Service in Transfer Walking Facilities," Journal of Korean Society of Transportation, vol. 28, no. 1, pp.15-29.
  18. Shin S., Lee K. and Hong W.(2015), "Strategies for Vitalizing Mega Complex and Transportation Facilities," Railway Journal, vol. 18, no. 4, pp.72-79.
  19. Shin S. and Lee K.(2014), Walkability Improvement Strategies for Large Scaled Transportation Complex, The Seoul Institute, 2014-PR-47, pp.1-96.
  20. Industry-Academic Cooperation Foundation at Ajou Univeristy(2014), Behavior Survey of Transferring Facilities for Public Transit and LOS Analysis, TS Korea Transportation Safety Authority.
  21. Ministry of Land, Infrastructure, and Transport (2015), Development of Trip and Transfer Technology for Passengers in the Metro Station.
  22. Jung R., Chung J. and You S.(2016), "Analysis of Route Choice Behavior in Subway Station Focus on Walking Distance," The Korea Spatial Planning Review, Vol. 88, pp.81-100. https://doi.org/10.15793/kspr.2016.88..005
  23. Lee J., Kim T. Chung J. and Kim J.(2016), "Modeling Lane Formation in Pedestrian Counter Flow and Its Effect on Capacity," Journal of Civil Engineering, vol. 20, no. 3, pp.1099-1108.
  24. Lee J.(2016), "Analysis on LOS Criteria of Pedestrian Flow by Simulating a Pedestrian Flow Model," Korean Society of Transportation, Vol. 34, no. 2, In press.

Cited by

  1. Identifying the Indoor Space Characteristics of an Urban Railway Station Based on Pedestrian Trajectory Data vol.2019, pp.None, 2016, https://doi.org/10.1155/2019/8401318