@inproceedings{454ca7ece9dd422f97a6fec33798fadb,
title = "Evacuation Time Model of Large Passenger Flow in Rail Transit",
abstract = "With the acceleration of urbanization, the rapid increase of rail transit passenger flow has brought great pressure on the operation and management of rail transit stations. In this paper, the Xizhimen subway station in Beijing is a research object. The survey and research focus on the large passenger flow at the A1 entrance, A1 exit, and Line 2 in the Xizhimen subway station during the morning peak hour. Based on the field data of passenger flow in various parts of the railway station, the spatial-temporal distribution characteristics of large passenger flow during the morning peak hour were obtained. In addition, based on these characteristics, the corresponding evacuation time models in each part of the railway station established in accordance with the three directions of passengers. The research results can provide the basis for the design of the subway station and the organization and management of rail transit.",
keywords = "Rail transit, evacuation time model, large passenger flow",
author = "Liya Yao and Shuoyang Zhang and Huiya Xiao and Zhaoqi Wang",
note = "Publisher Copyright: {\textcopyright} 2024 SPIE.; 2023 International Conference on Smart Transportation and City Engineering, STCE 2023 ; Conference date: 16-12-2023 Through 18-12-2023",
year = "2024",
doi = "10.1117/12.3024085",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Miroslava Mikusova",
booktitle = "International Conference on Smart Transportation and City Engineering, STCE 2023",
address = "United States",
}