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IntroductionExit selection is crucial in indoor emergency evacuation. Domestic and foreign scholars have found that exit choice behavior is influenced by three factors: environmental factors, social interactions, and individual internal factors. Previous studies have shown that in addition to a single environmental factor affecting exit decisions, the influence of other available exit options in the context can ultimately lead to a reversal of exit decisions -The context effect. However, the impact of context effects on exit decisions in emergency situations has not been thoroughly explored. Therefore, this article identifies three basic independent variables: context effects, crowd flows, and gender differences, to study the exit decisions of different gender groups facing different crowd flows, as well as how context effects affect existing exit decisions.MethodsIn this paper, we used virtual reality technology to construct an indoor fire scene and designed a total of 15 virtual experiments with different crowd distribution or context effects. 131 participants were divided into two groups, male and female, and their exit decisions were observed under different crowd flows and contextual effects.ResultsThe research results show that: 1) Both men and women have an innate preference to avoid crowded exits, and the proportion of following crowd evacuation significantly decreases when there are crowded crowds in the scene; 2) The exit decisions of female participants are more influenced by the crowd, while men tend to be more influenced by context effects when evacuating independently; 3) The context effects on exit decisions in emergency situations is statistically significant, and this performance is more significant in the male population. Further analysis reveals that similarity effects have a more significant impact on exit decisions than attraction effects.DiscussionsThese findings provide deeper insights into the exit choice behavior of the population and may contribute to the design of safe exits in indoor buildings. In addition, this article emphasizes the importance of context effects and provides a foundation for future research.

Evacuation rules for pedestrians in emergencies are of great significance for the design of building exits, exit management, and evacuation facilities. Based on the mixed reality evacuation LVC simulation system we developed, in this paper, three kinds of pedestrian exit selection experiments were carried out, in which the influence of distance and exit selection on pedestrian exit selection was studied. In line with common sense, during the single-factor control tests, the participants preferred the exit with fewer people and at a closer distance. The two-factor combined effect of the above two factors was also studied. It can be found that the participants preferred to choose the least crowded exit with a closer distance for evacuation. Among these two factors, the participants would give priority to the number of people at the exit. In addition, participants show different trajectories for the difference in the number of people at the two exits. Their walking trajectory was close to an arc line in the case of an equal number of people at two exits. The results of this paper provide a theoretical basis for research on designing evacuation facilities and guiding evacuees, and allows us to explore a new approach for mixed reality evacuation research by conducting virtual crowd experiments in a real environment.

Building evacuation can be challenging due to complex environments. A cognitive map is one of the most influential factors leading to different strategies of egress for individuals, yet there is little discussion about how pre-event experience influences individual exit choice. This study explores how pre-event spatial experience influences the evacuation exit choice. We conducted a semi-structured interview with a single evacuation drill involving 70 participants in a shopping center in Bandung, Indonesia. Participants were asked to choose an exit point in an evacuation scenario and were then interviewed about their reasoning. Analysis from the video footage of the evacuation and interview transcriptions showed four pre-event spatial experiences that influenced individual exit choice: habitual path preference, past traverse experience, access to the building, and associative events. Four elements from pre-event spatial experiences from this study are accessibility, familiarity, orientation ability, and social interaction influence exit choice. The findings contribute to the understanding of interaction between visitor behavior and circulation path. They provide insight about how experience forms familiarity as an important aspect in determining evacuation route. Lastly, this paper discusses the behavioral explanations underlying these findings and areas for future work.

This study investigated the interplay between exit selection models and local pedestrian movement patterns within floor field frameworks. Specifically, this investigation analysed the performance of a multinomial logit exit choice model, incorporating both expected utility theory and cumulative prospect theory frameworks when coupled with three distinct local-level pedestrian movement models (FF-Von Neumann, FF-Moore, and NSFF). The expected utility theory framework considers the deterministic component as a linear relationship, while the cumulative prospect theory framework further considers the decision-maker’s risky attitudes by transforming objective terms into subjective terms using a power value function. The core objective was to comprehend how local movement dynamics, as represented by the floor field models, influence decision-making during exit selection. Comparative analyses revealed intriguing variations between the three local models, despite their shared expected utility theory-based exit choice framework. These discrepancies stemmed from the diverse pedestrian trajectory behaviours generated by each model. Consequently, these local dynamics impacted the decision-maker’s assessment of critical factors, such as the number of evacuees close to the decision-maker (NCDM) and the number of evacuees close to an exit (NCE), which the exit choice model incorporates. These assessments, in turn, significantly affected higher-level decision-making. The integration of the three models with the multinomial logit exit choice model, using either cumulative prospect theory and expected utility theory frameworks, further strengthened the observed bilateral relationship. While the specific nature of this relationship varied depending on the chosen framework and its implementation details, these consistent findings demonstrate the robustness of the results. This reinforced the influence of local-level pedestrian dynamics on higher-level exit selection, highlighting the importance of accurate crowd dynamics modelling, especially when advanced exit choice models consider local movement factors.

Exit choice is essential for pedestrian safety and evacuation efficiency during the context of an emergency. Cumulative prospect theory is a widespread realistic decision-making theory that can transform choice outcomes and probabilities into subjective terms and integrate them as a parameter of cumulative prospect value (CPV), which determines the decision. The main contribution of this paper is the use of the CPV to predict exit choice. Furthermore, the different decision-making rules including Max, exponential(Expo), and Ratio (i.e., the three variable choice functions) were summarized and examined. This study used a confusion matrix to compare the predicted results with experimental data. Consequently, the parameters of Accuracy and F1-score showed that the predictions from Max and Expo were significantly more realistic while the results from Ratio were much more robust.

In this study, we firstly build up an exit choice model to describe the pedestrians’ exit choice behavior in a specific place, i.e., university canteens. The pedestrians are assumed to minimize their evacuation time in choosing exits by explicitly considering the estimated evacuation time and effects of pedestrians’ destinations. In addition, the behavior of food tray return is also captured in the proposed route choice model for pedestrians. Fusing the exit choice model and the route choice model into a cellular automata (CA)-based pedestrian simulation model, we simulate the pedestrian evacuation process in university canteen and the results illustrate the effectiveness of the modeling framework in terms of describing the evacuation process in university canteens. Specifically, destination is identified as a key influence factor for pedestrian evacuation, and pedestrians tend to select the exit that is closer to their destinations. If it is required to return the food tray to designated spots before leaving the canteen, the evacuation efficiency is significantly reduced. The simulation result can also assist in determining the optimal number of tray-return spots if maximum evacuation efficient is to be achieved. In presence of the specific parameter settings and canteen layout in the case study example, it is recommended to deploy four tray-return spots in the university canteen.

Predicting evacuation patterns is useful in emergency management situations such as an earthquake. To find out how pre-trained individuals interact with one another to achieve their own goal to reach the exit as fast as possible firstly, we investigated urban people’s evacuation behavior under earthquake disaster coditions, established crowd response rules in emergencies, and described the drill strategy and exit familiarity quantitatively through a cellular automata model. By setting different exit familiarity ratios, simulation experiments under different strategies were conducted to predict people’s reactions before an emergency. The corresponding simulation results indicated that the evacuees’ training level could affect a multi-exit zone’s evacuation pattern and clearance time. Their exit choice preferences may disrupt the exit options’ balance, leading to congestion in some of the exits. Secondly, due to people’s rejection of long distances, congestion, and unfamiliar exits, some people would hesitant about the evacuation direction during the evacuation process. This hesitation would also significantly reduce the overall evacuation efficiency. Finally, taking a community in Zhuhai City, China, as an example, put forward the best urban evacuation drill strategy. The quantitative relation between exit familiar level and evacuation efficiency was obtained. The final results showed that the optimized evacuation plan could improve evacuation’s overall efficiency through the self-organization effect. These studies may have some impact on predicting crowd behavior during evacuation and designing the evacuation plan.

The choice of the exit to egress from a facility plays a fundamental role in pedestrian modelling and simulation. Yet, empirical evidence for backing up simulation is scarce. In this contribution, we present three new groups of experiments that we conducted in different geometries. We varied parameters such as the width of the doors, the initial location and number of pedestrians which in turn affected their perception of the environment. We extracted and analysed relevant indicators such as distance to the exits and density levels. The results put in evidence the fact that pedestrians use time-dependent information to optimize their exit choice, and that, in congested states, a load balancing over the exits occurs. We propose a minimal modelling approach that covers those situations, especially the cases where the geometry does not show a symmetrical configuration. Most of the models try to achieve the load balancing by simulating the system and solving optimization problems. We show statistically and by simulation that a linear model based on the distance to the exits and the density levels around the exit can be an efficient dynamical alternative.