Crowd Evacuation Analysis and Modeling of Rail Transit Hub Stations Based on a Simulation Method

The Metro is a significant part of a transit system as it provides service to millions of people every day. During peak hours, rail transit hub stations are packed with commuters; therefore, it is extremely important to evacuate all occupants safely and rapidly when a catastrophe occurs. In this study, the authors focused on a typical urban rail transit hub in Shanghai: the Caobao Road Metro Station. Spatial data and population parameters are collected to set up a geometric model. The authors conducted dozens of evacuation simulations for different scenarios and established a ranking standard to assess the level of service of a station. The analysis combines evacuation time, pedestrian density, exit efficiency, and potential risks. The results show that the hub has an imbalance on efficiency of exits. This research can help understand the potential dangers and provide scientific suggestions for metro administration and supervision authorities.

• Record URL:
  • https://doi.org/10.1061/9780784482292.105
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784482292
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Hu, Miaoqing
  • Lu, Linjun
  • Ni, Anning
  • Zhang, Wenying
  • Yang, Jun
• Conference:
  • 19th COTA International Conference of Transportation Professionals
  • Location: Nanjing , China
  • Date: 2019-7-6 to 2019-7-8
• Publication Date: 2019-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Monograph Title: CICTP 2019: Transportation in China—Connecting the World

Subject/Index Terms

• TRT Terms: Crowds; Emergency exits; Evacuation; Hubs; Pedestrian density; Rail transit; Simulation
• Geographic Terms: Shanghai (China)
• Subject Areas: Operations and Traffic Management; Passenger Transportation; Public Transportation; Safety and Human Factors;

Filing Info

• Accession Number: 01735995
• Record Type: Publication
• ISBN: 9780784482292
• Files: TRIS, ASCE
• Created Date: Apr 9 2020 9:00AM