An improved social force model (ISFM)-based crowd evacuation simulation method in virtual reality with a subway fire as a case study

Crowd evacuation simulation using virtual reality(VR)is significant for digital emergency response construction.However,existing evacuation simulation studies suffer from poor adaptation to complex environments,inefficient evacuations,and poor simulation effects and do not fully consider the impacts of specific disaster environments on crowd evacuation.To more realistically express the crowd evacuation results obtained under the influence offire environments and the subjective consciousness of pedestrians in subway stations,we designed a dynamic pedestrian evacuation path planning method under multiple constraints,analysed the influences of an‘environmental role’and a‘subjective initiative’on crowd evacuation,established an improved social force model(ISFM)-based crowd evacuation simulation method in VR,developed a prototype system and conducted experimental analyses.The experimental results show that the crowd evacuation time of the ISFM is affected by the disaster severity.In simulation experiments without disaster scenarios,the improved model’s crowd evacuation efficiency improved by averages of 12.53%and 15.37%over the commercial Pathfinder software and the original social force model,respectively.The method described herein can effectively support real-time VR crowd evacuation simulation under multiexit and multifloor conditions and can provide technical support for emergency evacuation learning and management decision analyses involving subwayfires.

An extended cellular automata model with modified floor field for evacuation

The floor field model has been widely used in evacuation simulation research based on cellular automata model. However, conventional methods of setting floor field will lead to highly insufficient utilization of the exit area when people gather on one side of the exit. In this study, an extended cellular automata model with modified floor field is proposed to solve this problem. Additionally, a congestion judgment mechanism is integrated in our model, whereby people can synthetically judge the degree of congestion and distance in front of them to determine whether they need to change another exit to evacuate or not. We contrasted the simulation results of the conventional floor field model, the extended model proposed in this paper, and Pathfinder software in a same scenario. It is demonstrated that this extended model can ameliorate the problem of insufficient utilization of the exit area and the trajectory of pedestrian movement and the crowd shape of pedestrians in front of exit in this new model are more realistic than those of the other two models. The findings have implications for modeling pedestrian evacuation.

Research on the safety evacuation near the building exit

The paper presents an improved cellular automaton model according to the feature of evacuation near the outlet. We studied friction and turning factors that affect pedestrian evacuation speed. By using mathematical methods to derive expressions of friction function and turning function. The average pedestrian outflow of the simulation that includes the effect of both the frictional function and the turning function agrees well with experiment result. On the contrary, the simulation results that only include the effect of the frictional function are not corresponding to the experiment results well. Simulation results show that friction and turning can not be ignored. By analyzing the simulation results, it verified that the model can accurately reflect the actual evacuation process and has practical value.

Research on a Multi-grid Model for Passenger Evacuation in Ships

In order to enhance the authenticity and accuracy of passenger evacuation simulation in ships, a new multi-grid model was proposed on the basis of a traditional cellular automata model. In the new model finer lattices were used, interaction of force among pedestrians or between pedestrians and constructions was considered, and static floor fields in a multi-level exit environment were simplified into cabin and exit static floor fields. Compared with the traditional cellular automata model, the multi-grid model enhanced the continuity of the passengers'track and the precision of the boundary qualifications. The functions of the dislocation distribution of passengers as well as partial overlap of tracks due to congestion were realized. Furthermore, taking the typical cabin environment as an example, the two models were used to analyze passenger evacuation under the same conditions. It was found that the laws of passenger evacuation simulated by the two models are similar, while the simulation's authenticity and accuracy are enhanced by the multi-grid model.

Assessment and simulation of evacuation in large railway stations

Evacuation systems in buildings are frequently assessed to improve emergency response processes.This paper proposes a method to evaluate the performance of different evacuation modes,and determine a rational mode for large railway stations.We developed a simulation for the evaluation of fire safety in large buildings based on an analytic hierarchy process(AHP)method.This approach includes AHP-based exploration and simulation-based refinement.We considered a typical railway station for validation,conducted a field survey to collect the data,and calculated the influencing factors based on expert opinion.The influencing factors were further processed based on the principles of a hierarchical model.The relative weights of the influencing factors were calculated through a series of pairwise comparisons using the AHP.Further,we applied factor refinement based on the evacuation simulations to determine the degree and status of influence of each factor.The influence of external factors was generally stronger than that of the internal factors.Among them,the building component characteristics and people's physiological capabilities were the core of the evacuation assessment in large railway stations.Additionally,the exit width,seat layout,visibility,speed,and reaction capabilities were crucial to the evacuation process.The proposed method is practical as it demands limited computations to provide useful information,such as a priority ranking of each influencing factor,for the evaluation process.

Simulation Research on Fire Evacuation of Large Public Buildings Based on Building Information Modeling

Reasonable evacuation strategies are important in reducing casualties in the event of a fire.In this work,we conduct a simulation of a fire evacuation of a large public building based on the building information modeling technology to find the best evacuation strategy.We identify the tolerance limit of evacuees in case of a fire as the basis of the simulation using the fire dynamics simulator software.The following four evacuation strategies are proposed and simulated:stratified evacuation only by stairs,stratified evacuation mainly by stairs and supplemented by fire elevators,holistic evacuation only by stairs,and holistic evacuation mainly by stairs and supplemented by fire elevators.The case study of a college canteen shows that if 10%of evacuees(mainly elderly people who walk slowly and children who take up less space)are instructed to evacuate via fire elevators and the other 90%of evacuees(young men and women who move fast)use the stairs,the evacuation time can be reduced to a minimum.Some improvements in the design drawing result in the enhanced efficiency of the proposed strategy.The findings of this work are of great significance for the optimization of the structural design of large public buildings and provide some references for emergency evacuation.

Deep reinforcement learning and 3D physical environments applied to crowd evacuation in congested scenarios

To avoid crowd evacuation simulations depending on 2D environments and real data,we propose a framework for crowd evacuation modeling and simulation by applying deep reinforcement learning(DRL)and 3D physical environments(3DPEs).In 3DPEs,we construct simulation scenarios from the aspects of geometry,semantics and physics,which include the environment,the agents and their interactions,and provide training samples for DRL.In DRL,we design a double branch feature extraction combined actor and critic network as the DRL policy and value function and use a clipped surrogate objective with polynomial decay to update the policy.With a unified configuration,we conduct evacuation simulations.In scenarios with one exit,we reproduce and verify the bottleneck effect of congested crowds and explore the impact of exit width and agent characteristics(number,mass and height)on evacuation.In scenarios with two exits and a uniform(nonuniform)distribution of agents,we explore the impact of exit characteristics(width and relative position)and agent characteristics(height,initial location and distribution)on agent exit selection and evacuation.Overall,interactive 3DPEs and unified DRL enable agents to adapt to different evacuation scenarios to simulate crowd evacuation and explore the laws of crowd evacuation.

A GIS-Based 3D Simulation for Occupant Evacuation in a Building

The evacuation efficiency of building plans is of obvious importance to the public safety. The complexity of building plans, however, makes it difficult for the efficiency evaluation. This paper presents a computational model AutoEscape, which can simulate the evacuation process for any given occupant distribution in buildings. Designed as an extensible multi-level structure, the model constructs the geometry level and occupant level and establishes the interactions between levels. The GIS-based environmental analysis is realized to automatically generate the geometric representation and formulate the cognition of agents. The multi-agent based technology is employed to simulate the crowd behaviors with autonomously acting individuals. A visualization component, which provides 3D free observations for the simulation process, is developed on the platform of OGRE and integrated into the system interface in form of ActiveX control. Finally, a case study has been conducted and the results have been compared with the results of an existing model to show the reliability and capacity of AutoEscape simulation.

Development of a support system for creating disaster prevention maps focusing on road networks and hazardous elements

As a disaster prevention measure based on self-assistance and mutual assistance,disaster prevention maps are being created with citizen participation throughout Japan.The process of creating disaster prevention maps is itself a disaster prevention measure that contributes to raising awareness of disaster prevention by promoting exchange and cooperation within the region.By focusing on relations between road networks and hazardous elements,we developed a system to support disaster prevention map creation that visualizes roads at high risk during a disaster and facilitates the study of evacuation simulations.This system leads to a completed disaster prevention map in three phases.In the first phase,we use a device with GPS logging functions to collect information related to hazardous elements.In the second phase,we use Google Maps(“online map,”below)to visualize roads with high evacuation risk.In the final phase,we perform a regional evaluation through simulations of disaster-time evacuations.In experimental verifications,by conducting usability tests after creating a disaster prevention map in the target area,we evaluated the system in terms of simple operability and visibility.We found that by implementing this series of processes,even users lacking specialized knowledge regarding disaster prevention can intuitively discover evacuation routes while considering the relations between visualized road networks and hazardous elements.These results show that compared with disaster prevention maps having simple site notations using existing WebGIS systems,disaster prevention maps created by residents while inspecting the target area raise awareness of risks present in the immediate vicinity even in normal times and are an effective support system for prompt disaster prevention measures and evacuation drills.

A review on passenger emergency evacuation from multimodal transportation hubs

Multimodal transportation hubs serve as transfer points with the function of collecting,transferring,and distributing passengers and play a significant role in the entire multimodal transportation network.In an emergency,the development of an effective and efficient emergency evacuation strategy to evacuate passengers from multimodal transportation hubs is very important.This paper aims to conduct a comprehensive review on passenger emergency evacuations from multimodal transportation hubs,summarize the achievements,identify gaps in existing literature,thus to lay a solid foundation for future studies.This paper first reviewed studies on evacuee behavior characteristics in emergency evacuations,including pedestrian characteristics,pedestrian behavior characteristics,and pedestrian flow characteristics.Then evacuation models,including pedestrian evacuation models and multimodal transportation evacuation models,were investigated.In addition,a retrospective analysis was carried out for evacuation simulation.It is found that while many studies have been conducted on passenger emergency evacuations from multimodal transportation hubs,most of them focus more on evacuating pedestrians from inside to outside of hub buildings;the studies on evacuation at multimodal transfer points are limited.It is also found that most existing studies tried to establish a general model to handle all types of emergency evacuations;in fact,a model would be more efficient if it is just established for a specific emergency and for a specific type of hubs.Also,existing data collection methods may collect biased data;new data collection methods need to be explored to increase the accuracy of data collection.Future study directions include the evacuation at multimodal transfer points,interactive effects between individual pedestrian behavior and pedestrian group behavior,more specific types of emergency evacuations,more accurate data collection methods,and tradeoffs between cost and benefit in emergency evacuations.

Adaptive Agent-Based Modeling Framework for Collective Decision-Making in Crowd Building Evacuation

Crowd evacuation in different situations is an important topic in the research field of safety. This paper presents a hybrid model for heterogeneous pedestrian evacuation simulation. Our adaptive agent-based model (ABM) combines the strength of human crowd behavior description from classical social force models with discrete dynamics expression from cellular automaton models by extending the conception of floor field. Several important factors which may influence the results of decision-making of pedestrians are taken into consideration, such as the location of sign, the attraction of exit, and the interaction among pedestrians. To compare the effect of information on the pedestrians, we construct three decision-making mechanisms with different assumptions. To validate these three simulation models, we compare the numerical results from different perspectives with rational range in the case study where the Tampere Theater evacuation was carried out. The ABM framework is open for rules modification and could be applied to different building plans and has implication for architectural design of gates and signs in order to increase the evacuation efficiency.