Exit Choice Research Articles

Modeling competing guidance on evacuation choices under time pressure using virtual reality and machine learning

Efficient emergency guidance in buildings is essential for the safe evacuation of occupants. However, occupants may be exposed to contradictory information from signage and other sources of information. This study presents a set of forced-choice VR experiments and a machine learning approach to investigate the effect of competing or conflicting guidance on exit choice in simulated scenarios. In the VR study, participants chose between two potential exits under time pressure in each trial. Attracting cues (“EXIT” signs, audio instructions) and repelling cues (“DO NOT ENTER” signs, traffic cones) were placed in front of the two exits, either individually or in combination. In total, 2,125 datapoints were recorded from 20 participants. To model exit choice, machine learning (random forest, RF) models were applied to predict and interpret the guidance on evacuation choices. The tuned-hyperparameters RF model proposed in this study showed above 75% accuracy to predict evacuation choices facing conflict cues and was superior to default RF and logistic regression models. Interestingly, repelling cues such as “DO NOT ENTER” signs had a stronger impact on exit choice than attracting cues like “EXIT” signs when people have to make choices. Overall, the study offers valuable data and insights into exit choices, revealing that negative cues are more influential than positive ones in emergencies. These findings can significantly inform the design and optimization of egress guidance systems. This bias towards negative information under pressure suggests that evacuation systems should prioritize clear and prominent negative cues to guide occupants effectively.

An investigation into the influence of context effects on crowd exit selection under gender difference in indoor evacuation.

Exit 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. In 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. The 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. These 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.

Multifactor dynamic coupled model for building fire evacuation: Case study of the Karamay Friendship Palace fire

Occupant evacuation during a building fire is a complex system that includes several highly coupled subsystems, such as building characteristics, occupant characteristics, fire behavior, and evacuation behavior. To study the interaction mechanism between these subsystems to maximize occupant safety during fire evacuation in a building, a multifactor dynamic coupled model based on the Fire Dynamic Simulator and floor field cellular automata model for occupant evacuation in a fire was established. In the model, the dynamic impact of smoke diffusion on occupant movement direction and speed, decrease in occupant health points caused by smoke and trampling, and changes in occupant exit choices in the presence of closed exits were considered in detail. The catastrophic fire accident in the Friendship Palace of Karamay, Xinjiang, China, in 1994 was used as the analysis case, in which the spatial model of the Friendship Palace was reconstructed according to real data and architectural design methods. The safety exits open or closed, radius Rtra, possibility of information transmission Psuc, and wait time twait were discussed to study the influence of these parameters on the evacuation process and results. The study shows that the model could reproduce a fire accident well with Rtra = 4, Psuc = 0.5, and twait = 30. The closed exits increased evacuation time by over 120.3 % and resulted in 439 deaths. These conclusions are important for providing better estimates, guiding architectural designs, and enhancing building safety management.

An investigation into the influence of gender on crowd exit selection in indoor evacuation

Identifying how pedestrians make exit choices in an emergency is a critical topic related to safe indoor evacuation. Personal characteristics can influence the exit choice behavior of pedestrians. In particular, the gender factor is often used as an essential variable in indoor safety evacuation studies. However, the role of gender has not been explored in depth. The paper assumes that the following behavior of pedestrians depends on gender. Therefore, three essential factors are identified: the gender factor, crowd flow patterns, and exit width size. For the paper, a virtual experiment was conducted with 196 participants, and they had to decide whether to follow the crowd or not in the presence of capturing these different factors. The findings show that pedestrians prefer the same gender following, i.e., men are more likely to follow men to make exit choices, and women are more likely to follow women to make exit choices. We refer to this change in exit choice behavior depending on the influence of gender as the ‘gender effect.’ Furthermore, it was found that pedestrians have an innate preference to avoid the majority exit. However, when the width of the exit increases, pedestrians tend to choose the more comprehensive exit. But when the flow of people at larger exits increases, pedestrians choose to avoid the broader exits and choose smaller exits with fewer people, and the effect of the gender effect between pedestrians is diminished. These findings provide greater insight into pedestrian exit choice behavior and may be helpful for pedestrian evacuation management. In addition, they highlight the importance of gender effects and provide a basis for future research.

Modelling Context Effects in Exit Choice for Building Evacuations

Understanding exit choice behaviour is essential for optimising safety management strategies in building evacuations. Previous research focused on contextual attributes, such as spatial information, influencing exit choice, often using utility models based on monotonic functions of attributes. However, during emergencies, evacuees typically make rapid, less calculated decisions. The choice of context can significantly impact the evaluation of attributes, leading to preference reversals within the same choice set but under varying context conditions. This cognitive psychological phenomenon, known as context effects, encompasses the compromise effect, the similarity effect, and the attraction effect. While researchers have long recognised the pivotal role of context effects in human decision making, their incorporation into computer-aided evacuation management remains limited. To address this gap, we introduce context effects (CE) in a social force (SF) model, CE-SF. Evaluating CE-SF’s performance against the UF-SF model, which considers only the utility function (UF), we find that CE-SF better replicates exit choice behaviour across urgency levels, highlighting its potential to enhance evacuation strategies. Notably, our study identifies three distinct context effects during evacuations, emphasising their importance in advancing safety measures.

Impact of the Local Dynamics on Exit Choice Behaviour in Evacuation Model

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.

Why individuals do not use emergency exit doors during evacuations: A virtual reality and eye-tracking experimental study

Despite being purposefully designed and strategically placed in buildings to facilitate efficient evacuation, emergency exit doors are frequently underutilized during evacuations. To address this issue, this study explores why individuals often fail to use emergency exit doors during evacuations via a virtual reality and eye-tracking experimental study and investigates human emergency wayfinding behaviors through the lens of perceptions and attention. The results show that individuals’ attention to wayfinding clues is positively related to their exit choices. Failure to notice an emergency exit door is a key contributor to explaining how familiarity affects the usage of the emergency exit door. Participants in the familiarity group were less likely to pay attention to the exit door and thus rarely use it. However, when participants had fixations on the door, their exit choices were not significantly different between the familiarity and unfamiliarity groups. In the present experiment, door color and type did not have a significant impact on participants’ visual attention and exit choices. Specifically, the effect of door type on participants’ exit choices was impaired by the presence of the stairwell sign. The experimental results reveal the conspicuity and visibility of exit doors and explicit and clear wayfinding information are crucial to increasing their usage during indoor evacuations.

Evacuation preparedness and intellectual disability: Insights from a university fire drill

People with intellectual disability are vulnerable to building fires. Yet, they continue to be one of the most underrepresented groups in evacuation research. To bridge this gap, this study presents one of the very few analyses of building evacuation for people with intellectual disability. The purpose of this study is to collect data and determine unique evacuation parameters of people with intellectual disability (as opposed to those without intellectual disability). Here, we present findings from 1) a full-scale unannounced fire drill and 2) a post-drill survey in which 18 college students with mild to moderate intellectual disability participated. First, a fire drill was conducted in a 6-story residential university building where 148 other non-disabled students were present. The drill was recorded using cameras throughout the building. Analysis of the videos provided data on five key evacuation characteristics regarding evacuation times, speeds, exit choice, and behavior (along with some of the 148 students without disabilities). Then, a post-drill survey was conducted for the 18 students with intellectual disability. Information was analyzed for evacuee decisions, pre-drill behaviors, and a general understanding of the fire drill. Our findings uniquely represent students with intellectual disability in evacuation and show that exit choice and pre-movement times for the sample of students with intellectual disability diverge from the non-disabled group. Such information is necessary to improve performance-based design of safe and accessible residential buildings and mental health care facilities.

Modelling and interpreting evacuation time and exit choice for large-scale ancient architectural complex using machine learning

The intricate spatial structures of large-scale ancient architectural complexes, combined with their complex crowd compositions, hinder evacuation efficiency. However, research on the evacuation of such complexes is limited. Moreover, among the existing evacuation studies, most solely rely on either simulation models or machine learning techniques. Few integrate the strengths of simulation modeling in capturing otherwise inaccessible evacuation data with the advantages of machine learning in addressing complex problems. This study aims to utilize random forest algorithm, based on Pathfinder simulation evacuation data, to model the evacuation time and exit choice of occupants within such complexes. Additionally, we employ tools to interpret the random forest models, analyzing the influence of various factors on evacuation time and exit choice. Specifically, this methodology was applied to examine evacuation time and exit choice of 4800 occupants, comprising both tourists and residents, within the Xidi ancient architecture complex that spans nearly 130,000 square meters. The reliability of the random forest evacuation models is validated using real experimental data. The results indicate that the impact of environmental factors on evacuation time is often nonlinear. Compared to environmental factors, individual factors tend to have a lesser influence on evacuation time. For exit choice, the influence of environmental factors varies in significance at different scales. Individual factors have a notably higher influence on exit choice than on evacuation time. We also discern that evacuation distance affects the degree to which other factors influence exit choice. Overall, this research contributes to a deeper understanding of evacuation time and exit choice in such complexes, offering decision-makers more comprehensive evacuation strategies.

Experimental Study on Pedestrian Behaviors during Fire Emergency Conditions with Minecraft: Case Studies in a Classroom

The comprehension of the fire evacuation process is crucial for developing effective evacuation management strategies to enhance pedestrian safety. In this study, we construct a classroom with internal obstacles forming intersecting pathways in Minecraft, and conduct a series of virtual evacuation experiments involving multiple pedestrians to investigate the pedestrian behaviors. Case studies in a single-exit classroom demonstrated that normal obstacles and fire in the main evacuation path prompt pedestrians to detour, and pedestrians exhibit fire-avoidance behavior in advance during fire emergency. In the two-exit classroom experiments, normal obstacles have a limited effect on the exit choices of pedestrians, as they primarily choose the nearest exit. Pedestrians positioned in the center of classroom are influenced by their initial orientations, and some pedestrians opt for exits in their initial facing directions. The presence of fire has a greater influence on pedestrians’ exit choices, with most opting for exits away from the fire. Furthermore, during fire emergencies, some pedestrians engage in risk-taking behavior by choosing higher-risk paths in pursuit of a faster evacuation. These adventurous pedestrians proactively plan routes that maximize their distance from the fire and exhibit orderly queuing behavior. These findings are helpful to reveal pedestrian behaviors during fire emergencies.

Understanding passenger exit choices during airplane emergencies: Insights from hybrid choice modeling

In transport accident rescue operations, the primary focus is on saving lives. However, people's behavior and choices in such dangerous situations are unforeseeable. This paper employs a hybrid choice model to investigate how unobservable human heterogeneity impacts passengers’ decisions in airplane emergency evacuations. Three primary latent factors – fear of flying, knowledge of air safety, and no perception of risk – were identified based on indicators from fifteen statements. Subsequently, the hybrid choice model was expanded to include a time perception variable and interaction effects. The findings revealed that compared to Chinese respondents, individuals from the USA exhibit lower fear of flying, more air safety knowledge, and a higher risk perception in flying. All else being equal, aviation professionals can accept longer distances to exits than other passengers, and individuals with higher fear of flying choose middle exits more frequently. In contrast, those with lower risk perception prefer exits at either end of the cabin. Interaction terms indicated that increased air safety knowledge and lower risk perception contribute to a greater acceptance of more distant exits. A lack of risk perception makes traveling alone a significant factor in choosing an exit other than the frontmost, and people tended to avoid following others in densely populated evacuation flows. Regarding time perception, participants perceived the frontmost exit as the quickest, followed by the backmost exit, while the middle exits were viewed as the slowest. This study provides valuable insights for exit choice behavior modeling and airplane evacuation enhancement.

Crowd model calibration at strategic, tactical, and operational levels: Full-spectrum sensitivity analyses show bottleneck parameters are most critical, followed by exit-choice-changing parameters

ABSTRACT Crowd motion simulation requires specification of a range of parameters, each reflecting certain aspects of agent behavior. But what parameters matter the most? Are they all equally important? The question is important given that available data and resources for parameter calibration are limited, and priorities often need to be made. Here, for the first time, a full-spectrum sensitivity analysis of crowd model parameters is reported. It is shown that estimates of simulated evacuation time are, by far, most dependent on the value of locomotion/operational parameters, especially those that determine discharge rate at bottlenecks. The next most critical set of parameters are those that influence change of direction choices. If a crowd simulation model fails to reproduce bottleneck flows accurately, efforts to refine other modeling layers will be in vain. Similarly, if the model fails to represent exit choice adaptation/changing accurately, efforts to refine the exit choice model will be fruitless.

No Simple Way to Say Goodbye! Untangling the Heterogeneity of Social Venture Founder Exit Intention

Using three theory-based performance criteria as decision attributes, we conducted a conjoint analysis experiment with 105 social venture founder-CEOs to examine their decisions to exit their firms voluntarily. Multilevel regression analysis of founders’ choices revealed that various exit preferences were chosen that did not support theoretical prescriptions. While achieving desired social impact was the main influence on founder exit choices, the heterogeneity of exit preferences led us to parcel them into four distinct groups: idealists, traditionalists, realists, and pragmatists. We discuss our contributions to the entrepreneurial exit and social entrepreneurship research literature and list the implications of our results for practice.

The impact of people with mobility limitations on exit choice

Demographic trends and advances in accessibility have led to more heterogeneous populations in public buildings. While providing accessible evacuation, it may be necessary to direct evacuees to different evacuation paths depending on functional capacity. The presence of people with mobility limitations (e.g., wheelchair users) may affect the evacuation of others, possibly influencing the decision making of neighbouring evacuees. This study investigates how exit choice of people is influenced by the functional capacity of other evacuees and the design of the exit. Virtual Reality was used to design a discrete choice experiment in which participants were exposed to multiple choice situations and a mixed logit model was fitted to the data. Results from 40 participants indicate that exit choice was positively influenced by other people choosing the exit, and a larger effect was found when the other person was a wheelchair user. The design of the exit also influenced the exit choice of the participants. Large inter-person differences existed. Strategies reported by the participants in the subsequent questionnaire included altruistic behaviour. These results can inform fire safety engineers when outlining evacuation strategies and evacuation model users in their assumptions concerning exit choice in building evacuation.

The influence of context effects on exit choice behavior during building evacuation combining virtual reality and discrete choice modeling

Exit choice is critical to saving lives during a building evacuation. Numerous studies have examined how environmental factors, social interactions, and individuals’ internal factors affect exit choice behavior. However, due to their limited ability to perceive and combine these multi-attributes, people do not always make strategic and rational decisions but instead rely on preferences. The choice context can facilitate or hinder the evaluation of attributes, and thus preference reversals may occur in the same choice set but in different contexts. Researchers have long known that the context effect – i.e. preference reversals depending on the availability of other options – plays an important role in decision-making behavior. However, no research on decision-making behavior has been conducted that considers the context effect on exit choice during building evacuation. To fill this gap, we conducted a series of virtual reality (VR) experiments to examine the influence of context effect on exit choice. Before conducting the experiments, the validity of exit choice behavior in the VR-based method was analysed by comparing controlled experiments in both the real world and virtual environment. The results from our VR experiments provide novel and clear empirical evidence that contextual preference reversals involving three major effects, the compromise effect, the similarity effect, and the attraction effect, play an important role in exit choice during evacuation. Additionally, we compared three models for estimating discrete choice – expected utility theory (EUT), cumulative prospect theory (CPT), and accentuation of differences (AOD) – which primarily focus on the option attributes, the risk attitude of decision-makers, and the context of options, respectively. The outstanding performance of AOD, which is based on a psychophysical law and takes into account the impact of the context of options, highlights the psychological perspective of evacuees towards various option attributes and the importance of context effects in exit choice.

Modeling exit choice behavior in airplane emergency evacuations

Understanding how people choose exits during the emergency evacuation of an airplane is fundamental to saving more lives after air accidents. Since exit choice is difficult to observe in an emergency directly, this paper utilizes a stated preference experiment to evaluate people's exit decisions in an airplane emergency evacuation. Responses were collected through online questionnaires conducted in China and the USA. Then, conditional and nested logistic models were applied, indicating significant effects from physical factors, social influences, and individual characteristics on exit choice in virtual airplane evacuations. First, a low-level emergency and traveling alone allow people to make broader exit choices. Then, people with professional aviation experience appear less likely to choose the backmost option than common air passengers, and a high BMI index positively impacts the selection of the backmost exit. Next, herding behavior was not dominant in the airplane emergency evacuation experiment, but people were found to avoid following others in rational decisions which were made in an unreal emergency. In addition, the strong impact of a family member's location on people's direction of movement was indicated in the results. Finally, the frontmost exit and movement towards the front of the aircraft were preferred in a crisis and when people travel with family. This study provides evidence of passenger exit choice behavior in airplane emergency evacuation and suggests that the seating position of family members should be taken into account to support more efficient and safer airplane evacuations.

居室避難における火源位置を考慮した出口選択推定モデルに基づく出口配置評価

To evaluate the influence of exit arrangement on room evacuation safety, evacuation risk was estimated based on exit choice according to the relative location of fire source and exits to evacuees.

Modeling Pedestrian Tactical and Operational Decisions Under Risk and Uncertainty: A Two-Layer Model Framework

Pedestrian tactical choices and operational movement in evacuations essentially pertain to decision-making under risk and uncertainty. However, in microscopic evacuation models, this attribute has been greatly overlooked, even lacking a methodology to delineate the related decision characteristics (bounded rationality and risk attitudes), let alone their effects on evacuation processes. This work presents an innovative two-layer floor field cellular automaton model framework, where three intertwined sub-modules respectively dedicated to modelling the exit choice, the locomotion movement and the exit-choice changing behaviours are proposed and integrated as an entity. By introducing various decision-making elements computed by the proposed algorithm, Cumulative Prospect Theory (CPT) is proposed for the first time to model the exit choice and locomotion decision-making under risk and uncertainty. In the exit-choice changing module, attractive and repulsive forces are invented to jointly describe the tendency to revisit the routing decision. Each sub-module and the whole framework are validated in manifold indoor environments. The simulation results of the modules with CPT accord with the empirics from the evacuation experiments and are superior over those from the state-of-the-art models. The degree of rationality and risk attitudes are proven to have significant impacts on tactical and operational decisions. Furthermore, irrational behaviour in decision-making is not variably detrimental to locomotion efficiency of pedestrians. The proposed framework can serve as an elegant tool to predict pedestrian dynamics. The behavioural findings shed new light on understanding and modelling the tactical and operational decisions in evacuations.

Exit, voice, loyalty, and neglect framework of residents' responses to urban neighborhood regeneration: The case of Shanghai, China

Neighborhood regeneration (NR) improves the living quality and environment of urban areas through the rehabilitation or renovation of dilapidated neighborhoods. In the current Chinese context, the NR is mostly dependent on governmental planning and funding. But due to the limitation of time and resources, it is impossible for the government to propose and dominate NR in every single dilapidated neighborhood. Therefore, promoting resident-initiated NR projects is an essential strategy for improving citizens' wellbeing and meeting the requirements of sustainability. However, in the dilapidated neighborhoods, the residents' cooperation in NR is not simply relied on their discourse power. Their choices of responses may be strongly influenced by various factors. Nevertheless, there have been few studies that examined the residents' choices of responses in NR. By adopting the “exit, voice, loyalty, and neglect (EVLN)” framework, this research aims to investigate how the relevant elements, including the perceived impact of NR, social capital, neighborhood environment, and residents' dependency, can influence residents' choice of responses. Two old neighborhoods in Shanghai were selected as the case study area. The data is collected through a questionnaire survey. The principal component analysis and multiple regression techniques are utilized to unveil the mask of their intrinsic relationship. The empirical results suggest how the above elements have impacted the residents' responses to NR to a certain extent. Notably, several key findings were revealed from the results. The residents with high-level dependency, perceived high-level social capital, and strong impact of NR are more likely to choose voice response. The low-level dependency, perceived poor neighborhood quality, and low social capital lead to the residents' exit choice. And the response of loyalty/neglect is due to the perceived good living environment, low-level social capital, and the ignorance of NR impact on their lives. Finally, some policy implications were drawn to promote the residents' active and positive action in initiating NR projects in their dilapidated neighborhoods.

The exit choices of European private firms: A dynamic empirical analysis

Using a European private firm sample, we conduct a dynamic empirical analysis of private firm exit choice, previously modeled as a one-time IPO versus acquisition decision. Going public may yield firms a valuation premium (over a direct acquisition) through a post-IPO acquisition, but may also involve possible delisting at a valuation discount. We explicitly account for these dynamic considerations and show that such considerations alter firms’ initial exit trade-off: firms that anticipate a higher post-IPO acquisition probability are more likely to go public initially; those that anticipate a higher post-IPO delisting probability are more likely to choose a direct acquisition.