Toward an Accurate Microscopic Passenger Train Evacuation Model Using MassMotion

During emergency situations in trains, rapid and safe evacuation is crucial for saving lives of passengers. Computer models such as EvacTrain, STEPS, Pathfinder and FDS+Evac are making use of either a discrete space network or a continuous space network, and allow determining egress times for various emergency passenger train designs and conditions. These models offer insights into potential difficulties and offer possible solutions to evacuation challenges in a short time and at low cost. This paper focuses on the application of MassMotion (a commercial available evacuation software commonly used for evacuation planning in buildings) to passenger train evacuation. Key performance indicators such as mean total evacuation times, standard deviations, maximum evacuation times, minimum evacuation times, and 95th percentile of egress times are determined to evaluate the accuracy and reliability of MassMotion. In the validation test, actual occupant egress rates from a fire drill conducted by the Spanish Railroad Administration in a passenger train are used to measure the reliability of MassMotion for producing accurate egress time predictions. Further, the MassMotion passenger train simulation model is verified and compared to other existing microscopic passenger train evacuation models for a hypothetical case study. The comparison shows that microscopic models with continuous-space representation predict passenger evacuation times more accurately than discrete networks. Also, the force-based model MassMotion provides consistent and reliable egress time predictions. The findings of this study contributes to the field of egress models for passenger train emergencies and can be used by evacuation modellers and authorities to support their decisions.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AR070 Standing Committee on Railroad Operational Safety.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Anvari, Bani
  • Nip, Chi Kin
  • Majumdar, Arnab
• Conference:
  • Transportation Research Board 96th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2017-1-8 to 2017-1-12
• Date: 2017

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 16p
• Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Cellular automata; Computer models; Evacuation; Passenger trains
• Subject Areas: Passenger Transportation; Planning and Forecasting; Railroads; Security and Emergencies;

Filing Info

• Accession Number: 01631519
• Record Type: Publication
• Report/Paper Numbers: 17-05766
• Files: TRIS, TRB, ATRI
• Created Date: Mar 31 2017 9:24AM