Modelling and Analysis on Emergency Evacuation from Metro Stations

Chen, Shaokuan; Di, Yue; Liu, Shuang; Wang, Baoshan

doi:10.1155/2017/2623684

Cited by 16 publications

(19 citation statements)

References 25 publications

(34 reference statements)

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“…A multiagent-based model was developed based on meta model for pedestrian simulation in metro stations and the model includes the three-level pedestrian agent model, the station environment abstraction model, and interactive rule base [28]. e evacuation time for a given number of evacuees was calculated with a multiagent-based simulation approach, while the evacuation bottlenecks in metro stations were also identified [29]. A theoretical framework for safety analysis of underground space was established based on previously reported fire accidents and empirical research into underground stations [30].…”

Section: Literature Reviewmentioning

confidence: 99%

Emergency Evacuation Simulation and Optimization for a Complex Rail Transit Station: A Perspective of Promoting Transportation Safety

Tian

2020

Journal of Advanced Transportation

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Rail transit stations with multifloor structures have been built in many cities to intensively utilize land resources and facilitate lives of community. However, being overcrowded with passengers results in high risks during daily operation. In response, this study conducted an emergency evacuation simulation and optimization in the three-dimensional (3D) space of “complex rail transit stations” (CRTSs). The aim of the paper is to provide a methodology to determine effective emergency evacuation strategies for CRTSs. The Lianglukou Rail Transit Station in Chongqing, China, was used as a case study and the AnyLogic simulation platform employed for simulating emergency evacuations. An emergency evacuation theoretical framework was established. The emergency evacuation strategies, including evacuation routes and evacuation times, were determined based on the theoretical demonstration. Simulation and optimization of emergency evacuation in the Lianglukou station were conducted. Accordingly, four main simulation results were obtained: (1) Escalators/stairs and turnstiles are key facilities in the evacuation; (2) Effective guidance for the evacuation is necessary in the public space of the station; (3) Passenger aggregation nodes should be guided for balanced evacuation; (4) Removing metal barriers is a useful evacuation optimization measure. The proposed research method and framework can be used by other CRTSs in the establishment of emergency evacuation strategies and effective optimization strategies to promote safety of transportation system. The research findings are beneficial to passengers in helping them provide valuable emergency evacuation guidance.

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Section: Literature Reviewmentioning

confidence: 99%

Emergency Evacuation Simulation and Optimization for a Complex Rail Transit Station: A Perspective of Promoting Transportation Safety

Tian

2020

Journal of Advanced Transportation

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“…e impact of the merging ratio on pedestrian ows and evacuation times was calculated for each oor in congested situations [13,25]. Important conditions of these models was that the steady state conditions of pedestrian ows were considered, and the staircase was lled with pedestrians at the same density as the constant conditions at the start [32,39]. In this paper, the entire stairs evacuation process was simulated to analyze the impact of pedestrian merging.…”

Section: Analysis Of Stairs Evacuation Capacitymentioning

confidence: 99%

“…is model does not fully express the dynamic change process of the floor pedestrian flow and stairs pedestrian flow in a stairs evacuation. An essential assumption of this model is that the pedestrian flow of stairs is in the steady-state, in which the staircase is filled with pedestrians and has the same density for each floor at the start; this assumption disregards the initial/final stage of a stairs evacuation [32]. erefore, the development of a stairs evacuation model that fully considers pedestrian merging flows and appropriately describes the entire process of stairs evacuation has theoretical significance and practical value.…”

Section: Introductionmentioning

confidence: 99%

A Stairs Evacuation Model Considering the Pedestrian Merging Flows

Zheng

Tian

Zhang

et al. 2019

Discrete Dynamics in Nature and Society

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Pedestrian merging flows are common in a stairs evacuation process, which involves complex interactions among pedestrians that substantially restrict the efficiency of the stairs evacuation process. Analyzing the pedestrian merging flows process and improving the efficiency of stairs evacuation are urgent and essential tasks. A novel simplified stairs evacuation model for simulating and analyzing the stairs evacuation process, which considers the impact of merging flows, is proposed in this process. The dynamic pedestrian output rate of a floor platform is calculated by the number of pedestrians on the floor platform. The merging ratio determined by the design size of stairs is adopted to determine the ratio between the stairs pedestrian flow and the floor pedestrian flow in the pedestrian output rate of the floor platform. To evaluate the stairs evacuation process is divided into three stages based on the pedestrian merging flows process, and the evacuation time at each stage is computed by the dynamic pedestrian output rate of the floor platform. The stairs evacuation capacity is calculated by the evacuation time and the number of pedestrians. A case study of a six-floor building evacuation is investigated, and the reliability and feasibility of the proposed model is verified. By establishing different merging ratios, the optimal merging ratio is obtained by comparing the evacuation capacities of different merging ratios, which provides a reference of stairs design for designers.

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“…This reflects on stations that face enormous pressure from passenger congestion and the high level of overcrowding in peak times. The metro systems in Beijing and Shanghai provide a daily transport service for more than nine million passengers, and statistics indicate that the annual usage has almost doubled from 2011 to 2015 [2,3]. In the UK, the number of rail passenger journeys has more than doubled over the transfer distance and transfer time.…”

Section: Introductionmentioning

confidence: 99%

Utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Overcrowding Level Risk Assessment in Railway Stations

Alawad

Kaewunruen

2020

Applied Sciences

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The railway network plays a significant role (both economically and socially) in assisting the reduction of urban traffic congestion. It also accelerates the decarbonization in cities, societies and built environments. To ensure the safe and secure operation of stations and capture the real-time risk status, it is imperative to consider a dynamic and smart method for managing risk factors in stations. In this research, a framework to develop an intelligent system for managing risk is suggested. The adaptive neuro-fuzzy inference system (ANFIS) is proposed as a powerful, intelligently selected model to improve risk management and manage uncertainties in risk variables. The objective of this study is twofold. First, we review current methods applied to predict the risk level in the flow. Second, we develop smart risk assessment and management measures (or indicators) to improve our understanding of the safety of railway stations in real-time. Two parameters are selected as input for the risk level relating to overcrowding: the transfer efficiency and retention rate of the platform. This study is the world’s first to establish the hybrid artificial intelligence (AI) model, which has the potency to manage risk uncertainties and learns through artificial neural networks (ANNs) by integrated training processes. The prediction result shows very high accuracy in predicting the risk level performance, and proves the AI model capabilities to learn, to make predictions, and to capture risk level values in real time. Such risk information is extremely critical for decision making processes in managing safety and risks, especially when uncertain disruptions incur (e.g., COVID-19, disasters, etc.). The novel insights stemmed from this study will lead to more effective and efficient risk management for single and clustered railway station facilities towards safer, smarter, and more resilient transportation systems.

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Modelling and Analysis on Emergency Evacuation from Metro Stations

Cited by 16 publications

References 25 publications

Emergency Evacuation Simulation and Optimization for a Complex Rail Transit Station: A Perspective of Promoting Transportation Safety

Emergency Evacuation Simulation and Optimization for a Complex Rail Transit Station: A Perspective of Promoting Transportation Safety

A Stairs Evacuation Model Considering the Pedestrian Merging Flows

Utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Overcrowding Level Risk Assessment in Railway Stations

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