Estimation of emergency evacuation capacity for subway stations

Wu, You; Xu, Jie; Jia, Limin; Qin, Yong

doi:10.1080/19439962.2017.1357059

Cited by 26 publications

(12 citation statements)

References 23 publications

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“…In order to verify the effectiveness of the model and algorithm, he took the capacity estimation of Fuxingmen station of Beijing Metro as an example to simulate the evacuation process, and obtained the optimal evacuation path and reasonable estimation, and selected the evacuation passenger flow per unit time and network congestion as the evaluation indexes of station capacity in emergency. His method is not stable [2]. Yuan Z studied the influence of emergency signs on evacuation dynamics in smoke environment.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

Huang

Cao

2021

Neural Comput & Applic

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Due to safety issues when passengers get on and off the subway and spend a lot of time on the subway, this makes subway station signs very important. Moreover, in case of fire and other dangerous situations and emergency evacuation, the guiding signs must be able to guide passengers to leave the station and dangerous areas efficiently and orderly, so as to protect the personal and property safety of passengers. The purpose of this study was to analyze the decision response of subway evacuation signs using the characteristics of the brain components. In this study, subway model is constructed. When you perform simulation using software, you need to fine tune the parameters to get the best simulation effect. A questionnaire survey was made on the components of the subway sign. The results show that the number of people who think that the standard font of the blackboard logo is the most representative of the emergency exit, accounting for 78.2% of the total number of people, taking the image as the first choice accounted for 52.9% of the total number of people, and the green sulfur powder logo as the first choice accounted for 69.8% of the total number. This study makes an important contribution to the research of subway traffic safety problems.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

Huang

Cao

2021

Neural Comput & Applic

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“…Highly efficient emergency evacuation minimizes economic losses and casualties. The existing studies found that the emergency evacuation of metro stations is mainly influenced by three aspects: (1) people, such as passenger evacuation behavior [13,14]; (2) objects, such as the equipment facility evacuation capacity and layout of equipment and facilities [15,16]; and (3) human-object interactions, such as the evacuation routes of passengers between walking facilities [17,18]. To reduce the emergency evacuation risks generated by the above influences, the existing studies proposed measures for optimization design, such as in terms of passengers, escape plans to reduce the congestion probability, and rescue plans to improve the emergency response efficiency [19,20].…”

Section: Review Of Dfs Application Methods For the Evacuation Of Metro Stationsmentioning

confidence: 99%

BIM-based safety design for emergency evacuation of metro stations

Tang

Xia

et al. 2021

Automation in Construction

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“…Several studies related to metro emergencies have been carried out in recent years. The capacity of evacuating subway stations under emergencies is estimated by using a bi-level programming model, and the performance of a subway station has been calculated [2]. Big data methods are also used in analyzing the resilience and vulnerability of transit networks and provide measures and methodologies in planning and preparing for emergencies [3].…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation of Metro Congestion Propagation Based on Route Choice Behaviors Under Emergency-Caused Delays

2019

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Generally, metro emergencies could lead to delays and seriously affect passengers’ trips. The dynamic congestion propagation process under metro emergency-caused delays could be regarded as the aggregation of passengers’ individual travel choices. This paper aims to simulate the congestion propagation process without intervention measures under the metro emergency-caused delays, which is integrated with passengers’ route choice behaviors. First, using a stated preference survey data collected from Guangzhou Metro (GZM) passengers, route choice models are developed based on random regret minimization (RRM) theory under metro emergency conditions. Then, a simulation environment is established using graph cellular automata (graph-CA) with augmented GZM network structure, where an ASEIR (advanced susceptible-exposed-infectious-recovered) model with time delay is proposed as the evolution rule in graph-CA. Furthermore, considering passengers’ routing preferences, a quantified method for the congestion propagation rate is proposed, and the congestion propagation process on a subnetwork of the GZM network is simulated. The simulation results show that metro congestion during peak periods has a secondary increase after the end of the emergency-caused delays, while the congestion during nonpeak hours has a shorter duration and a smaller influence range. The proposed simulation model could clearly reflect the dynamic process of congestion propagation under metro emergencies.

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Estimation of emergency evacuation capacity for subway stations

Cited by 26 publications

References 23 publications

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

RETRACTED ARTICLE: Decision response of subway evacuation signs based on brain component features

BIM-based safety design for emergency evacuation of metro stations

Simulation of Metro Congestion Propagation Based on Route Choice Behaviors Under Emergency-Caused Delays

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