Constructal design of pedestrian evacuation from an area

The configuration of a room and the evacuee information are important factors that determine evacuation performance. While several studies have investigated the impact of these factors on evacuation behavior, little research has been done on the evacuation of a room with blocked exits and uninformed evacuees who are unaware about the position of open exit. In this paper, we propose an extended floor field model that accounts for these types of conditions and is validated by experiments. The simulation results of our model show that optimal total evacuation time is achieved when more than 40% of evacuees are informed evacuees (IEs) who know the position of the open exit if their initial positions are uniformly distributed in the crowd. Our model indicates that total evacuation time is reduced when IEs are near an open exit. In addition, our model indicates that the ratio of IEs to total evacuees, required for achieving optimal evacuation time, changes with the change in the initial position of IEs.

Human behaviour and evacuation time for large underground comprehensive buildings during fire risk process

How to accurately simulate the real collective behavior of pedestrian evacuation remains an important issue in research of complex systems. The existing crowd simulation models in general assumed that pedestrians move directly towards the exit. In real life, however, there exist “cautious” pedestrians who fear trampling and crowding during evacuation, so we use an improved social force model to investigate how their presence influences evacuation dynamics. Simulation results reveal that the total evacuation time does not increase monotonically with the increment of the number of cautious pedestrians. Specifically, the presence of a moderate number of cautious pedestrians with rational psychological tolerance might substantially facilitate evacuation efficiency, compared with a conventional evacuation scenario. In addition, lower psychological tolerance promotes emergency evacuation, while increasing the tolerance threshold is conducive to slow evacuation. We hope that our research will provide some insights into the reasonable optimal strategies for emergency evacuation.

Validation of advanced evacuation analysis on passenger ships using experimental scenario and data of full-scale evacuation

When the occupant density of buildings is large enough, evacuees are prone to congestion during emergency evacuation, which leads to the extension of the overall escape time. Especially for multi-exit buildings, it’s a challenging problem to afford an effective evacuation plan. In this paper, a novel evacuation planning algorithm applied to multi-exit buildings is proposed, which is based on an indoor route network model. Firstly, evacuees are grouped by their location proximity, then all groups are approximately equally classified into several evacuation zones, each of which has only one safe exit. After that, all evacuation groups in the same zone are sorted by their shortest path length, then the time window of each evacuation group occupying the safe exit is calculated in turn. In the case of congestion at the safe exit, the departure time of each evacuation group is delayed in its arrival order. The objectives of the proposed algorithm include minimizing the total evacuation time of all evacuees, the travel time of each evacuee, avoiding traffic congestion, balancing traffic loads among different exits, and achieving high computational efficiency. Case studies are conducted to examine the performance of our algorithm. The influences of group number, group size, evacuation speed on the total evacuation time are discussed on a single-exit network, and that of partitioning methods and evacuation density on the performance and applicability in different congestion levels are also discussed on a multi-exit network. Results demonstrate that our algorithm has a higher efficiency and performs better for evacuations with a large occupant density.

Where drills differ from evacuations: A case study on Canadian buildings

Pedestrian evacuation modeling and simulation in multi-exit scenarios

This thesis covers a variety of analytical approaches that validate the use of the EvacuatioNZ model on high-rise building analysis. Through performing a number of sensitivity analyses, several model deficiencies as well as functional limitations were improved upon and part of the model developments are continued based on the previous research done by two Master's students at the University of Canterbury. In this thesis, data from three evacuations were considered for different validating aspects. These evacuations were, a hypothetical 21-storey hotel building located in the United States of America, which was previously simulated using Simulex and EXIT89; a trial evacuation that was carried out in a 13-storey office building located in Canada; and a fire drill conducted at a 21-storey office building located in Australia. Overall, the results indicated that the EvacuatioNZ is able to produce reasonable predictions of the total evacuation time regardless of the number of floors involved. The component testing also showed satisfactory outcomes regarding the involvement of disabled occupants, complexity of node configurations, and different pre-movement time distributions. However, the current model still has a number of limitations that need to be verified and tested. These include the preferred route function and the connection problem for long stairs. Further research should also be carried out on the use of the Evacuation model on other types of building structures so as to increase the confidence level of utilizing the EvacuatioNZ model for general applications.

Characteristics of emergency evacuations in airport terminal buildings: A new event database

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.

Crowd simulation has its greatest utility in the study of safety measures for crowded events. However, total evacuation time, which is the most important feature in crowd evacuation, can vary depending on the population, the environment, the adopted strategies to decide routes, but also because people can be panicked or not. This paper presents a model to parametrize crowd simulation allowing to increase or decrease the agents stress. We use BioCrowds model and proposed an extension to consider new parameters to deal with crowd relaxing and compression, as comfort and stress. These two new parameters impact the will to go to the goal and the individual panic in trying to save itself. Indeed, our model could be integrated in other crowd simulators. This work discusses some obtained results and also presents a case study regarding a real scenario. We simulate the Hillsborough Disaster happened in 1989 in order to discuss the reliability of our method. Results indicate that our method can simulate in a coherent way the densities observed in the real life event.

Population aging phenomena are increasing the attention to safety aspects for Elderly in care homes and hospitals: individuals that can autonomously evacuate should be helped during the evacuation by providing specific devices to them. Our activities are aimed by the design of “guidance” system for these categories, and to inquiry their impact on people motion. One of the most important evacuation steps is represented by the pre-movement phase: after the fire alarm sound, individuals continue to spend time in activities not directly connected to the evacuation. This phase could be very long. This work proposes an interactive system for the pre-movement time based on an experimental analysis of pre-movement time behaviors. The system is composed of an individual wearable device: the Zig-Bee-based localization module identifies people’s positions after the alarm and understands whether they are motionless; the interactive module gives a personal stimulus to the latecomers. Technical requirements are evaluated. The effectiveness of the system is investigated through simulations: up to 30 % reduction in total evacuation time can be obtained.

Evacuation plans are traditionally based on empirical knowledge and local experience. Many studies are underway to improve and optimize the process of evacuation planning and operations. Therefore, a commonly accepted model for evacuation is necessary. During the process of an evacuation, the fact of risk of exposure(e.g. airborne toxins and radiation) may be neglected. In order to solve the Evacuation planning problem, an evacuation objective formulation is established based on total evacuation time and evacuation distance optimization, and these two parts were combined with disaster risk function which considers time-dependent disaster risk. The authors use the model to calculate the evacuation routing assignment extension, experimental results show that evacuation plan with system optimal policy can achieve no blocking and minimum network clearance time; therefore it ensures greater safety in the evacuation process.

Effect of pedestrian judgement on evacuation efficiency considering hesitation

Multi-objective evacuation routing optimization problem is defined to find out optimal evacuation routes for a group of evacuees according to multiple evacuation objectives. For improving the evacuation efficiency, we abstracted the evacuation zone as a positive-point-charge-potential-field-like model (PPCPF-like model), and we proposed PPCPF-ACO algorithm to solve this problem based on the proposed model. In PPCPF-ACO algorithm, we use non-dominated sorting based roulette wheel routing method (NSRWR) to further improve evacuation efficiency. In Wuhan Sports Center case, we compared PPCPF-ACO with HMERP-ACO (hierarchical multi-objective evacuation routing problem - ant colony optimization) and traditional ACO according to three evacuation objectives, namely, total evacuation time, total evacuation route length and cumulative congestion degree. The experimental results show that PPCPF-ACO has a better performance than HMERP-ACO algorithm and traditional ACO algorithm while solving multi-objective evacuation routing optimization problem.