{"title":"A study on passenger flow model and simulation in aspect of COVID-19 spreading on public transport bus stops","authors":"Rafał Burdzik , Wongelawit Chema , Ireneusz Celiński","doi":"10.1016/j.jpubtr.2023.100063","DOIUrl":null,"url":null,"abstract":"<div><p>Public transport during COVID-19 has been crucial in ensuring the safety and health of both passengers and staff while maintaining essential public transport services. Currently public transport is gradually resuming its operations, the pandemic's influence is expected to persist for a long time. The vast majority of studies in this aspect concern the likelihood of spreading the virus inside the means of transport during travel. Nevertheless, there exists a substantial body of articles addressing the manner in which passenger movement within public transport systems has been impacted by the safety concerns and altered satisfaction levels following the propagation of the pandemic. This paper presents a model that accurately represents how passengers move through different parts of a public transport system, such as a bus or train station and stops. This model takes into account factors like how long it takes for passengers to board and exit a vehicle, how they move through different parts of the stops, and how their movements are affected by factors like crowding and delays. To reduce the risk of transmission on public transport focused on bus stops areas, the research paper formulated a passenger flow model using simulation programs like PTV Vissim and FlexSim with assumptions on minimum distance and concept of area cross sections. These programs were used to simulate passenger exchange scenarios, using data collected from real data. The paper aimed to develop a passenger exchange model that could reduce the risk of infection. By understanding the passenger flow model and how passengers interact with the public transport system, we can implement effective measures to minimize the spread of COVID-19 and other infectious diseases.</p></div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077291X23000243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 1
Abstract
Public transport during COVID-19 has been crucial in ensuring the safety and health of both passengers and staff while maintaining essential public transport services. Currently public transport is gradually resuming its operations, the pandemic's influence is expected to persist for a long time. The vast majority of studies in this aspect concern the likelihood of spreading the virus inside the means of transport during travel. Nevertheless, there exists a substantial body of articles addressing the manner in which passenger movement within public transport systems has been impacted by the safety concerns and altered satisfaction levels following the propagation of the pandemic. This paper presents a model that accurately represents how passengers move through different parts of a public transport system, such as a bus or train station and stops. This model takes into account factors like how long it takes for passengers to board and exit a vehicle, how they move through different parts of the stops, and how their movements are affected by factors like crowding and delays. To reduce the risk of transmission on public transport focused on bus stops areas, the research paper formulated a passenger flow model using simulation programs like PTV Vissim and FlexSim with assumptions on minimum distance and concept of area cross sections. These programs were used to simulate passenger exchange scenarios, using data collected from real data. The paper aimed to develop a passenger exchange model that could reduce the risk of infection. By understanding the passenger flow model and how passengers interact with the public transport system, we can implement effective measures to minimize the spread of COVID-19 and other infectious diseases.