Does crowding affect the path choice of metro passengers?

Kim, Kyung Min; Hong, Sung-Pil; Ko, Suk-Joon; Kim, Dowon

doi:10.1016/j.tra.2015.04.023

Cited by 66 publications

(45 citation statements)

References 14 publications

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“…The substantial body of research concerned with pedestrian flow modelling has largely been concerned with avoiding dangerous bunching and bottlenecks or efficient evacuation in emergency situations (Seyfried et al, 2006;Smith et al, 2009;Parisi et al, 2009;Qiu & Hu, 2010;Still, 2013;Kim et al, 2015;Liu et al, 2016).…”

Section: Crowd Movementmentioning

confidence: 99%

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Factors influencing experience in crowds – The participant perspective

et al. 2017

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Humans encounter crowd situations on a daily basis, resulting in both negative and positive experiences. Understanding how to optimise the participant experience of crowds is important. In the study presented in this paper, 5 focus groups were conducted (35 participants, age range: 21-71 years) and 55 crowd situations observed (e.g. transport hubs, sport events, retail situations). Influences on participant experience in crowds identified by the focus groups and observations included: physical design of crowd space and facilities (layout, queuing strategies), crowd movement (monitoring capacity, pedestrian flow), communication and information (signage, wayfinding), comfort and welfare (provision of facilities, environmental comfort), and public order. It was found that important aspects affecting participant experience are often not considered systematically in the planning of events or crowd situations. The findings point to human factors aspects of crowds being overlooked, with the experiences of participants often poor.

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Section: Crowd Movementmentioning

confidence: 99%

“…This has included pedestrian flow and its modelling (Smith et al, 2009;Still, 2013;Kim et al, 2015;Liu et al, 2016) and public order policing (Reicher et al, 2004;Stott et al, 2008;Drury & Stott, 2011). This research emphasis has followed on from major crowd incidents, e.g.…”

Section: Introductionmentioning

confidence: 99%

Factors influencing experience in crowds – The participant perspective

et al. 2017

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“…Other research studies have investigated the crowdedness problem in metro systems [16][17][18]. For example, Kim et al [17] investigated how the problem of crowdedness affects the passengers' choice for transportation, and found that the problem reduces the overall satisfaction of metro passengers.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Kim et al [17] investigated how the problem of crowdedness affects the passengers' choice for transportation, and found that the problem reduces the overall satisfaction of metro passengers. Some other researchers focus on the crowdedness problem from the perspective of other forms of public transportation, such as rail systems [19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Measuring Crowdedness between Adjacent Stations in an Urban Metro System: a Chinese Case Study

et al. 2017

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Abstract:The urban metro system has been widely appreciated as the most important component in urban infrastructures. It plays a critical role in promoting urban social and economic development, and particularly in reducing the urban traffic congestion. However, there are various inherent problems with operating metro systems, which typically involve the crowdedness both at stations and inside vehicles. Both policymakers and academic researchers in China have paid little attention to the crowdedness between metro stations. In order to solve the problem of crowdedness, it is necessary to develop a method to evaluate the level of crowdedness. This work establishes a model to measure the crowdedness between adjacent stations in a metro system based on the load factor principle, passenger standing density, and other factors such as the metro operation schedule and estimations of passenger flows. The Chongqing Metro Line 3 in China is used as a case study to demonstrate the application of the evaluation model. The case study reveals that the model introduced in this study can assist with assessing the crowdedness level between adjacent stations in a metro line. The model is an effective tool for helping the metro management and administration understand the level of crowdedness, apply proper methods to mitigate the crowdedness, and thus improve the quality of the service for those utilizing the metro system.

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“…Kim et al (2015) tambeḿ utilizaram dados de bilhetagem eletrônica em Seul, Coreía do Sul, tendo como resultado que os usuários de metrô de fato utilizam outras rotas que não a mais rápida para evitar a lotação em si e os atrasos causados pela lotação. Os impactos da lotaçaõ, causados à saúde e bem-estar dos usuários, conforme apresentados em Tirachini et al (2013), vão desde aumento de ansiedade, estresse e sentimentos de exaustão, percepção de risco e insegurança, sentimentos de invasaõ de privacidade e maior propensão a atrasos em compromissos, causando impacto tambeḿ na saúde organizacional.…”

Section: Introductionunclassified

Estimação da matriz origem-destino e da distribuição espacial da lotação em um sistema de transporte sobre trilhos a partir de dados de bilhetagem eletrônica

Arbex

Cunha

2017

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RESUMOEste artigo apresenta os resultados de uma análise para estimar a lotação por trechos entre estações de um sistema metroferroviário, ao longo do dia, utilizando dados de bilhetagem eletrônica. É proposta uma adaptação da metodologia baseada no encadeamento de embarques no sistema de transportes, que infere o destino dos usuários, uma vez que não há bilhetagem nas estações de destino. Isso permitiu obter, de maneira rápida e eficiente, sem pesquisas de campo custosas, uma estimativa da matriz de origem-destino no sistema de transporte de passageiros sobre trilhos da Região Metropolitana de São Paulo (RMSP). A metodologia proposta também possibilitou obter o padrão espaço-temporal dos níveis de lotação para todas as linhas e sentidos da rede, assim como os volumes de transferências nas estações através da alocação da matriz ao longo de todo o período de operação e não apenas para os horários de pico, como usualmente feito a partir de pesquisas de campo com base em entrevistas com usuários. ABSTRACTThis paper presents the results of an analysis to estimate station-to-station occupation levels of a metro and urban rail system throughout the day using electronic ticketing data. An adaptation of the trip chaining methodology is proposed, which infers users destination since there is no transaction at the final destination stations. This allowed us to obtain an estimate of the origin-destination matrix quickly and efficiently, without costly field surveys, for the rail passenger transport system of the São Paulo Metropolitan Area (SPMA). The proposed methodology also made it possible to obtain the spatiotemporal pattern of the crowding levels for all lines and directions of the network, as well as the transfer volumes in the stations through the assignment of the matrix throughout the operation period and not only for the peak times, as usually done from field surveys based on user interviews. Palavras-chaves:Lotação, Transporte Público, Sistema Metroferroviário, Bilhetagem Eletrônica. Keywords:Bus, Public transportation, System Metroferroviário, Electronic Ticketing. DOI:10.14295/transportes.v25i3.1347 INTRODUÇÃOIncremento do uso de transporte individual (carros e motos) para os deslocamentos diários, em detrimento ao transporte coletivo, acarretando congestionamentos crescentes, maiores tempos de viagem e maior poluição são alguns dos desafios atuais da mobilidade nos grandes centros urbanos. Nesse contexto, entender como ocorrem os deslocamentos das pessoas é um dos aspectos importantes a fim de que possam ser propostas novas soluções que contribuam para aprimorar os sistemas de transporte coletivo e a qualidade dos serviços, de forma a atrair mais usuários e diminuir o uso de automóveis, contribuindo assim para melhorar a qualidade de vida nas metrópoles.

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Does crowding affect the path choice of metro passengers?

Cited by 66 publications

References 14 publications

Factors influencing experience in crowds – The participant perspective

Factors influencing experience in crowds – The participant perspective

Measuring Crowdedness between Adjacent Stations in an Urban Metro System: a Chinese Case Study

Estimação da matriz origem-destino e da distribuição espacial da lotação em um sistema de transporte sobre trilhos a partir de dados de bilhetagem eletrônica

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