Optimum Capacity of the Metro Station with the Aim of Reducing the Incidence of Infectious Respiratory Diseases (Case Study: Imam Khomeini Metro Station in Tehran)

Document Type : Scientific - Research

Authors
1 Ph.D. student, Department of Civil Engineering - Transportation, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 Associate Professor, Department of Civil – Transportation Planning, Imam Khomeini International University, Qazvin, Iran
3 Professor, Department of Civil-Transportation Engineering, Tarbiat Modares University, Tehran, Iran
Abstract
The main goal of the present study is to provide the basis factor model to determine the optimal capacity of the metro station with the aim of minimizing the incidence of infectious diseases. In this research, the study area, namely Imam Khomeini metro station in Tehran, was investigated. After collecting the information, some indicators affecting the demand and capacity and the statistics obtained in the years before Corona, as well as structural observations during the Corona outbreak, were examined and the information was analyzed. After confirming reliability and validity, factor analysis was evaluated and categorized and prioritized in the conditions of Corona. According to the results of the factor analysis in order to categorize and reduce the variables related to the model for determining the optimal capacity of the Imam Khomeini subway station in the conditions of Covid, the most important of them are, in order: the percentage of employees in the sample per day, the perception of people's access to the subway by taxi, the percentage of the number of car owners, the percentage of commercial and service trips, the average income, the percentage of office trips, and the congestion index on footpaths with respect to social distance are among the seven variables with the most important priority in factor modeling, which are further shown in the proposed regression model. In measuring the optimal capacity of Imam Khomeini metro station, they were measured.

Keywords


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Volume 15, Issue 3 - Serial Number 60
Winter 2024
Pages 3865-3879

  • Receive Date 07 November 2022
  • Revise Date 19 December 2022
  • Accept Date 24 December 2022