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"evacuation simulation"
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Evacuation of Shelter in Place at Subway Transfer Stations Based on BIM and Proposal of a Strengthening Method
Among public facilities, facilities belonging to Multi-Group (I) include high-rise buildings, tunnels, and subway stations, and the location of Shelter in Place (SIP) is an important factor in the safety of citizens. However, subway evacuation maps usually induce evacuation to ground level or the tunnel of a subway platform without considering the location of SIP. In other words, since the location of the SIP is not determined, conditions, such as ventilation, air conditioning facilities, and structural durability required for the SIP cannot be satisfied. It is difficult to suggest the location of SIP because the domestic standards limit only the time it takes to move from the outside to the facility designated as SIP during an emergency evacuation. Therefore, in this study, when there is a situation of emergency evacuation in the subway, the total allowed time to evacuate to SIP is limited to 6 min. We designate a space that can accommodate the number of evacuees at the location and compare and analyze the results of the evacuation simulation using six scenarios. Additionally, suggestions are made for improvement methods relating to evacuation as well as the proposal of reinforcement methods through an experiment to satisfy the structural requirements of SIP in subway stations.
Journal Article
A Non-Signalized Junction Model for Agent-Based Simulations of Car–Pedestrian Mode Mass Evacuations
During major disasters, such as a subduction earthquake and the associated tsunami, combinations of uncommon conditions such as non-functioning traffic signals, a large number of pedestrians on traffic lanes, and debris scattered on roads can be widespread. It is vital to take these uncommon conditions into account since they can significantly influence the evacuation progress. Agent-Based Models (ABMs) with capabilities to reproduce evacuees’ behaviors as emergent phenomena is promising method to simulate combinations of such rare conditions. This paper presents a new model to cover the current research gap in accurately modeling car–car and car–pedestrian interactions at non-signalized junctions. Specifically, the details of accurately approximating car trajectories at junctions and automated construction, approximating free-flow speed of cars along curved trajectories, and accurately calculating the points of collision and time to collision are presented. As a demonstrative application, we simulated a hypothetical evacuation scenario with non-functioning traffic signals in which different numbers of slow evacuees are allowed to use cars. While the ABM is yet to be thoroughly validated, the presented demonstrative scenarios indicates that a considerable number of the needy can be allowed to use cars for evacuation if their routes and evacuation start time window are well planned.
Journal Article
Pedestrian Flow Model Based on Cellular Automata Under Visual Trajectory and Multi-Scenario Evacuation Simulation Research
Precise modeling and simulation of pedestrian flow are crucial for public space safety design and emergency management. This study proposes an interdisciplinary method integrating computer vision and cellular automata (CA). First, unidirectional pedestrian flow video data with different densities were collected from an overpass scene via controlled experiments. High-precision pedestrian trajectory extraction and tracking were achieved using the YOLO 11 model and DeepSORT algorithm, with image distortion corrected by perspective transformation. For the first time, the probability distribution of pedestrian turning angles derived from trajectory analysis was converted into data-driven transition probabilities for the Moore neighborhood in the CA model. An improved evacuation model was then constructed, comprehensively considering real-data-based transition probabilities, speed–density distribution, panic coefficient, individual life value, and hazard source dynamics. Multi-scenario simulations show that moderate panic may shorten evacuation time, while excessive panic causes behavioral disorders; group movement is constrained by the slowest individual, and increased hazard source speed reduces the proportion of safe pedestrians. This study provides new insights and methodological support for refined pedestrian evacuation simulation and safety management.
Journal Article
Bidirectional Evacuation in Subway Fires Considering the Number of Retrograders and Proactive Avoidance Behavior Based on Experiments and Simulations
Subway fires often cause significant casualties and property losses. There are some special bidirectional coupling scenarios during subway fires, such as firefighters moving against the evacuation flow to extinguish fires, emergency managers going to the fire scene to respond to emergencies, or other similar scenarios. How to evacuate passengers quickly and enable responders to enter the fire scene has become a big challenge for subway fire evacuation and response. The core goal is to reduce the degree of mutual interaction between these people moving in opposite directions. In this study, the impact of counterflow individuals and proactive avoidance behavior on evacuation processes was investigated through experiments and simulations. The Fire Dynamic Simulator was used to simulate the development of a fire scenario to determine the available safe egress time. Micro-evacuation experiments were conducted to obtain actual evacuation parameters, such as the speeds of different objects. With these parameters as input, a macro subway fire scenario was built to simulate the bidirectional evacuation process. Consistent conclusions were obtained from the experiments and evacuation simulations. The results indicate that the overall evacuation time increases with the number of retrograders. Proactive avoidance behavior can effectively reduce the travel time of counterflow individuals, but it causes slight delays for forward-moving evacuees. An optimization strategy was implemented through conductor guidance. All passengers can successfully evacuate under the optimization strategy, with a 25.3% improvement in overall evacuation time. This research provides some insights into the coordinated evacuation and emergency response during subway fires or similar scenarios.
Journal Article
Optimizing Key Evacuation Features for Safer Egress in Complex Buildings with Underground Connections: A Simulation-Based Approach to Resilient and Sustainable Design
This study explores the impact of key evacuation features on occupant safety in complex buildings with underground connections in Seoul, the city with the highest concentration of such buildings in the country. By analyzing factors like exit spacing, exit width, stairwell distances, and stairway configurations, the study assesses evacuation safety using fire and evacuation simulations, comparing available safe egress time (ASET) with required safe egress time (RSET). Reducing interior exit facility spacing from the legal standard of 100 m to 50 m improved evacuation time by 77.5% (from 36 min to 8 min and 7 s), with a further reduction to 40 m improving performance by an additional 23.3% (to 6 min and 13 s). In downward evacuations, reducing the walking distance to exterior exits from over 50 m to 30 m cut evacuation time by at least 59.9% (from 23 min and 55 s to 9 min and 35 s), ensuring successful evacuations. These findings demonstrate that optimizing evacuation routes, addressing bottlenecks, and improving evacuation feature standards can significantly enhance safety and minimize casualties. By adjusting building design and fire safety regulations, these optimizations promote resilient urban infrastructure, reduce disaster-related socio-economic impacts, and inform evidence-based policies, offering valuable insights for policymakers and guiding future improvements in fire safety and evacuation protocols.
Journal Article
Modelling and simulation of assisted hospital evacuation using fuzzy-reinforcement learning based modelling approach
Available hospital evacuation simulation models usually focus on the movement of the evacuees while ignoring the crucial behavioural factors of the evacuees’ which impact the simulation results. For instance, the issue of patient prioritization behaviour during evacuation simulation is often overlooked and oversimplified in these models. Furthermore, to control the movement of the evacuees, almost all these models utilize rule-based artificial intelligence to develop navigation systems, which sometimes do not guarantee realistic and optimal movement behaviour. This research aims to address these problems by modelling feasible and novel solutions. In this research, we propose to develop a hospital evacuation simulation model which utilizes a hybrid of fuzzy logic and reinforcement learning to simulate assisted hospital evacuation using the Unity3D game engine. We propose a novel and effective approach to model patient prioritization using a fuzzy logic controller; a reinforcement learning based navigation system to tackle the issues related to the rule-based navigation system by proposing novel reward formulation, observation formulation, action formulation and training procedure. The results and findings exhibited by the proposed model are found to be in line with the available literature. For instance, available literature suggests that an increased number of patients increases the evacuation time, and an increased number of staff or exits decreases the evacuation time. The proposed model also demonstrates similar findings. Moreover, the proposed navigation system is found to take a “near shortest distance” to reach the target as the mean difference between “shortest vector distance” and “distance covered” is approximately 1.73 m. The proposed simulation model simulates the repeated patient collection more realistically and can be used to estimate the Required Safe Egress Time, which enables the establishment of safety performance levels. The evacuation performance of different scenarios can be compared using the proposed model. This research can play a vital role in future developments of hospital evacuation simulation models.
Journal Article
A Weighted Network Approach for Evaluating Building Evacuation Efficiency: A Case Study of a Primary School Teaching Facility
Ensuring the safety of building occupants during emergency evacuations is a critical aspect of building design. The spatial configuration and functional layout of buildings significantly influence overall evacuation efficiency. However, accurately assessing evacuation performance based on spatial characteristics remains challenging. This study proposes a weighted network analysis approach to evaluate the evacuation efficiency of buildings. It establishes the “Space-to-Network” diagram translation principles for converting spatial configurations into graph-based representations, defines analytical indicators for evacuation-weighted networks, and introduces a systematic methodology and workflow. A case study demonstrates the effectiveness of this approach, showing that the average relative deviation from evacuation simulation results is less than 10%. The method is particularly well suited for evaluating designs during the early stages. This research offers a novel perspective for evacuation analysis and provides a concise and reliable tool for the quantitative evaluation and performance optimization of building evacuation space.
Journal Article
Effectiveness assessment and simulation of a wearable guiding device for ship evacuation
The evacuation of a modern passenger ship is a challenging task which might be hindered by a complex ship’s internal layout and/or the blocking of escape routes due to fire/flooding. In this work, the application of mobile technology to reduce travel time is investigated. A pilot system has been developed and tested on the RoPax ship GNV Bridge. It is composed of a server and a mobile application running on wearable smartbands. The guidance and localisation of devices have been carried out through Bluetooth beacons. A test area has been identified on GNV Bridge including 2 cabins corridors on deck 6 and the main lounge on deck 5. The corridors and the lounge are connected by three staircases, defining three alternative escape routes starting from cabins and arriving at the muster station in the main lounge. In the trials, the escape routes have been randomly blocked to assess the reduction of travel time achieved providing guidance through wearable devices to a sample population. It resulted in a 16.9% reduction in travel time. Besides, a strategy to simulate with a certified tool the effect of a guiding system has been defined. This is essential to make trials’ results transferable in different environments (e.g., other RoPax or cruise ships). In particular, experimental data coming from the trials have been used to assess agents’ speed reduction rate due to mobile device consultation. Although available experimental data were limited by the pandemic, the 2.5% agent’s speed reduction applicable to simulations has been assessed as most probable.
Journal Article
Congestion-Based Earthquake Emergency Evacuation Simulation Model for Underground Structure
Herein, the Dijkstra algorithm was used to develop a model that considers evacuee congestion and derives an optimal evacuation route in underground structures in the event of an earthquake. The ground conditions and seismic intensities were varied, and the evacuation route was analyzed for four cases. The damage index for each underground structure due to an earthquake was determined considering the ground conditions and structure depth, and the evacuation speed reduction was evaluated as a function of the damage index. A congestion coefficient was applied when the evacuation capacity exceeded the threshold to reflect the evacuation speed reduction due to increased congestion in the same evacuation route. The evacuation route in some sections changed when congestion was considered, and the final evacuation time increased significantly when the congestion coefficient was applied. When the evacuation capacity at each node exceeded the threshold, the 1/3 value was applied as the congestion coefficient to evacuation velocity. When the original evacuation route was used after applying the congestion coefficient, the evacuation time increased by up to 220%. However, the evacuation time can be reduced by applying an alternative route that considers congestion. When an alternative route derived from considering congestion was used, the evacuation time decreased by up to 45% compared to that when the original route was used, and the time required decreased by up to 840 s. Hence, the reduction in evacuation speed due to evacuee congestion must be considered to derive alternative, optimal evacuation routes in the event of a disaster. In addition, evacuation routes should account for the location of evacuees using technologies such as real-time indoor positioning to consider the congestion level of evacuees.
Journal Article