Principles for Monte Carlo agent-based evacuation simulations including occupants who need assistance. From RSET to RiSET

Tinaburri, A.

doi:10.1016/j.firesaf.2021.103510

Cited by 14 publications

(3 citation statements)

References 38 publications

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“…Previous studies have measured the required safe egress time against available safe egress time (Equation (1)) when investigating the success probability of escape and evacuation, and they have found that the correct selection of a node direction along a path is critical to success [34,35]. Therefore, the present study recommends that whether the selected node direction along a path is correct or not should be considered in this calculation, as shown in Equation (2).…”

Section: Resultsmentioning

confidence: 90%

Using Smartphones for Indoor Fire Evacuation

Lin

Chuang

Hsiao

2022

IJERPH

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Fire smoke reduces the visibility of emergency direction signs, rendering them ineffective for providing appropriate guidance along evacuation routes in a fire situation. This is problematic because civilians may select evacuation routes that expose them to smoke or fire in a burning building. This study proposed using a smartphone voice-guided evacuation system (SVGES) to provide alternative evacuation routes for civilians trapped at a fire scene. To verify the efficacy of the SVGES, experiments were conducted with 26 participants in a simulated fire scenario. The experimental results showed that when using the SVGES, the participants chose the safest evacuation route with a 100% successful evacuation rate.

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Section: Resultsmentioning

confidence: 90%

Using Smartphones for Indoor Fire Evacuation

Lin

Chuang

Hsiao

2022

IJERPH

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“…The goal of Monte Carlo (MC) simulation, an analytical technique for complicated systems, is to acquire predicted values through repeated random sampling of numerous random input parameters that follow a normal distribution [59]. In the physical world, there are two highly common and significant forms of stochastic processes: Bernoulli and Poisson processes, and the contrary, which states that future events will depend on previous events and can, to some extent, predict the future.…”

Section: Parameter Combinations and Results Predictionmentioning

confidence: 99%

Fire Egress System Optimization of High-Rise Teaching Building Based on Simulation and Machine Learning

Zhou

Zhang

et al. 2023

Fire

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A fire egress system is one of the most critical aspects of fire emergency evacuation, which is the cornerstone technology of building fire safety. The high-rise teaching buildings on campus, where vast crowds of people gather, need to be qualified for rapid evacuation in the event of a fire especially. Conventional teaching building egress system design places more emphasis on individual elements (e.g., stairwells, evacuation doors, and evacuation walkways) rather than on their co-regulation as a whole. Furthermore, there are not enough holistic and effective optimal design strategies, which is because most of the existing studies rely on experiments or simulations and often suffer from a lack of sufficient data to fully reveal the interactions of individual variables. In this study, the co-effectiveness of stairwells, walkways, and room doors in reducing total evacuation time was investigated by simulation and machine learning. We selected a typical high-rise teaching building as an example and integrated two simulation software, Pyrosim and Pathfinder, to compare the available safe evacuation time (ASET) and required safe evacuation time (RSET). Then, a framework consisting of five factors—stair flight width (SFW), stairwell door width (SDW), corridor width (CW), room door width (RDW), and location of the downward stair flight (LDSF)—was established for the optimization through statistical analysis of big data obtained by the preferred machine learning algorithm. Results indicate that (1) By modifying just one factor (SFW), the total evacuation time (TET) can be reduced by at most 12.1%, with the mortality rate dropping from 26.5% to 9.5%; (2) although ASET could not be achieved either, among 4000 cases of multi-factor combinations, a maximum TET improvement degree, 29.5%, can be achieved for the evacuation optimization compared to baseline model, with a consequent reduction in mortality to 0.15%; (3) it shows that the emphasis of the egress system optimization is on the geometric features of the evacuation stairwell; furthermore, the multi-factor combination approaches have better compromised evacuation performances than the single-factor controlled schemes. The research results can be applied as rational design strategies to mitigate fire evacuation issues in high-rise teaching buildings and, in addition, the methodology suggested in this paper would be suitable to other building types.

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“…The simulation of events through computer systems is a valuable tool for assessing various strategies and options. The integration of mathematical tools with decision matrices can be used to characterize people's cognitive phases and create agent profiles representing a wide range of types of individuals [9]. This convergence of approaches provides a way to analyze and forecast how different segments of the population might respond to disasters, facilitating more accurate and adaptive planning.…”

Section: Research Background On the Modeling Of Human Behavior In Eva...mentioning

confidence: 99%

Analysis of Pedestrian Behavior for the Optimization of Evacuation Plans in Tall Buildings: Case Study Santiago, Chile

Ternero,

Sepúlveda,

Alfaro

et al. 2023

Buildings

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Countries located in the Pacific Ring of Fire, such as Chile, require robust evacuation plans for tall buildings to manage the ongoing threat of natural disasters. This study presents a methodology for developing evacuation plans by conducting pedestrian movement simulations with agents that have a model of their surroundings. This approach allows us to assess different scenarios and choose the best option based on the specific characteristics of the site. The method combines simulation and data analysis, using the Monte Carlo method to improve emergency evacuations. Initially, Pathfinder software was employed to simulate the evacuation of a tall building. This involved modeling pedestrian movements using a multiagent system. These agents were programmed to behave like real pedestrians and make decisions during evacuation scenarios, providing valuable information. The effectiveness of two evacuation strategies was then evaluated using the simulation data. The proposed methodology was validated using a case study. The simulations showed that the best strategy depends on factors such as the distribution of people, the capacity of the exits, and the time available for evacuation. Finally, the model includes a training process that uses virtual reality technology to improve situational awareness.

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Principles for Monte Carlo agent-based evacuation simulations including occupants who need assistance. From RSET to RiSET

Cited by 14 publications

References 38 publications

Using Smartphones for Indoor Fire Evacuation

Using Smartphones for Indoor Fire Evacuation

Fire Egress System Optimization of High-Rise Teaching Building Based on Simulation and Machine Learning

Analysis of Pedestrian Behavior for the Optimization of Evacuation Plans in Tall Buildings: Case Study Santiago, Chile

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