Exit Choice Research Articles

A tunnel evacuation experiment on movement speed and exit choice in smoke

In order to increase the knowledge on human behaviour in smoke, an evacuation experiment was performed in a road tunnel in Stockholm in July 2014. Sixty-six participants, who were instructed to individually evacuate the tunnel, took part. Participants' walking speeds were measured in a smoke-filled section, as well as in a smoke-free section, of the tunnel. The walking speeds in non-irritant smoke were measured for extinction coefficients in the range of 0.5–1.1 m-1, which corresponds to approximately 2–4 m of visibility (for light reflecting signs). In addition, way-finding and exit choice in smoke were also investigated. Particularly, different emergency exit portal designs were evaluated in the smoke-filled section of the tunnel. The novel data-set on walking speed in smoke is presented, including coupled data on obstructed (movement in smoke) and unobstructed (smoke-free movement) walking speed. Results show that there is a weak relationship between an individual's ability to walk in smoke and the unobstructed walking speed, but more research is needed in this area. In addition, the results relating to way-finding and exit choice demonstrated that the emergency exit portal design in the experiments was appropriate for the intended use. However, in order to increase the performance of the design, the portal may be complemented with information signs on the wall opposite to the exit, namely way-finding signs including distances to the closest emergency exits on both tunnel walls, and a loudspeaker installation that can inform evacuees about the location of available exits.

Italian craft beer revolution: do spatial factors matter?

PurposeThe purpose of this paper is to investigate the emergence of microbreweries in Italy over the last 20 years (period 1993-2014) and assess its main determinants.Design/methodology/approachThe recent intense growth is expressed by the increasing number of entries in the sector actually accompanied, in most recent years, by an increasing number of exits. The paper proposes a quantitative assessment of this entry-exit dynamics through a sequence of econometric models known as survival models.FindingsTogether with two other orders of possible determinants (idiosyncratic characteristics and the exogenous evolution of the beer market), the paper assesses the role played by specific geographical and local factors within these dynamics. Estimation results show that, whereas market force and individual features unquestionably affect entry and exit choices, geographical and local factors are of limited relevance, especially for the recent entry dynamics.Originality/valueAlthough the literature on the so-called craft beer revolution is already vast and increasing, the novel contribution of the paper concerns the specificity (if any) of the Italian case and the role of spatial factors in this respect. This investigation is performed adopting an advanced quantitative approach and this attempt is also quite original within this literature.

Understanding human queuing behaviour at exits: an empirical study.

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.

A Computational Study of the Station Nightclub Fire Accounting for Social Relationships

Using agent-based modeling, this study presents the results of a computational study of social relationships among more than four hundreds evacuees in The Station Nightclub building in Rhode Island. The fire occurred on the night of February 20, 2003 and resulted in 100 fatalities. After summarizing and calibrating the computational method used, parametric studies are conducted to quantitatively investigate the influences of the presence of social relationships and familiarity of the building floor plan on the death and injury tolls. It is demonstrated that the proposed model has the ability to reasonably handle the complex social relationships and group behaviors present during egress. The simulations quantify how intimate social affiliations delay the overall egress process and show the extent by which lack of knowledge of a building floor plan limits exit choices and adversely affects the number of safe evacuations.

Risk-Field Based Modeling for Pedestrian Emergency Evacuation Combined with Alternative Route Strategy

For the past decades, with the frequent occurrence of emergencies, such as stampede, fire, and terrorist attack, the urgent requirements of developing realistic evacuation models to describe pedestrian and disaster dynamics are put forward. In this paper, an extended floor-field (FF) model combined with risk factors is presented for emergency evacuation. A novel dynamic rerouting mechanism is designed to elucidate the exit choice behavior of evacuees, and meanwhile, a recommended dynamic risk-field model is fully explored to deal with dynamical features of disaster. The proposed model is validated through numerical simulations with specific room structures. The effects of model parameters on evacuation efficiency and death toll are analyzed in detail. Simulation results show that the proposed model is effective and has a positive influence on evacuees’ exit choice behavior, and the death toll is closely related to the perceived information obtained by evacuee, such as the crowd density during the evacuation process.

Pedestrian crowd tactical‐level decision making during emergency evacuations

SummaryThis paper investigates pedestrian crowd tactical‐level decision making during emergency evacuations. Of particular interest is crowd exit‐choice behaviour. Two sources of stated choice data are collected and combined. One data set is derived from an experiment linked to a real‐life exit choice experience of participants (in a non‐evacuation setting). We examine aspects that have often been taken for granted in the literature in connection with egress behaviour of crowds during emergencies. We quantify evacuees' trade‐off between “distance”, “density”, “exit visibility” and “directional density” as well as the interactive effect between exit visibility and tendency to follow others. A comprehensive random‐utility analysis is conducted ranging from traditionally practiced models to the state‐of‐the‐practice methods such as random‐coefficient nested logit. Our findings suggest that (i) unless evacuees face certain levels of uncertainty in the escape environment; flows of crowd are unlikely to be followed. Otherwise, most evacuees perceive other individuals as potential sources of congestion and extra delay (generalisation to situations where crowd is completely unfamiliar with the egress geometry, however, may require careful scrutiny). (ii) Evacuees mostly prefer visible exits over the exits whose congestion level is unknown to them (i.e. the tendency to minimise ambiguity). (iii) The presence of attribute uncertainty (e.g. exit visibility) significantly changes the impact of observing decisions of others on each individual choice maker. We also found out that (iv) spatial distribution of exits has a significant influence on evacuees' decisions (presenting itself in the form of violating the IIA assumption). (v) The marginal weights that different individuals place upon attributes of exits are significantly heterogeneous. (vi) There is meaningful correlation between certain utility weights of individual evacuees. These behavioural findings can provide significant behavioural insight essential for safe evacuation planning and accurate forecast of evacuees' behaviour. Copyright © 2016 John Wiley & Sons, Ltd.

Pedestrian dynamics with explicit sharing of exit choice during egress through a long corridor

The egress literature abounds with studies and models of emergency pedestrian evacuation behavior. Each model tries to incorporate more details and features of the crowd movement dynamics to improve its accuracy. This paper combines a relatively simple pedestrian motion model with a position dependent Voter model to study the effects of opinion sharing on crowd evacuation characteristics. Effect of the presence of leaders on the final outcome of the evacuation is studied in detail. An analytical solution for a simplified version of the egress dynamics with opinion exchange is presented, followed by a set of numerical simulations. Interesting findings about the effect of the strength of interaction between individuals, number and distribution of leaders and initial bias of the evacuees on the final distribution of evacuees over available exits, mean number of steps to evacuate, etc. are presented.

Stated and revealed exit choices of pedestrian crowd evacuees

IntroductionUnderstanding fundamental behavioural features regulating the escape wayfinding decisions of pedestrian humans in built environments has major implications for the safety planning and the risk-analysis of crowded public facilities. In contrast to the vast interest invested in modelling the momentary responses of evacuees to their immediate surroundings (i.e. the collision-avoidance models), their global navigation behaviour is poorly understood albeit believed to be a major determinant of the accuracy of the crowd simulation models. The primary challenge arises from the scarcity of reliable data suitable for modelling purposes causing the experimental knowledge in the field lagging substantially behind the corresponding model developments. Observations derived from fully natural emergency contexts (in the form of modelling material) are rare and collecting data in realistic experimental settings poses its own major challenges. Only few experimental modelling attempts have been reported thus far in relation with this problem primarily using the stated-choice (SC) methods. Modelling based on revealed choices (RC), however, has remained absent in this context leaving the findings of the SC experiments mostly unverified. It is still unclear whether we can reliably learn from the wayfinding choices made in virtually visualised environments without the decision-makers interacting with real individuals and the physical elements of the environment as they do in the real-world settings. Furthermore, the extent to which the findings of these experiments are specific to the particular characteristics of the environment visualised in the experiments is also unclear. MethodsTo bridge this gap, here we report on discrete-choice estimates derived from observations of both types. Three datasets of stated exit choices (4958 observations) were collected through face-to-face interviews with pedestrians in three public places with the experiments referring to the particular geometry of the place in which the participants were interviewed. Also, 3015 disaggregate real (or more precisely, “realistic”) exit choices were extracted through individual-level video analysis of the footage of a series of novel evacuation trials that simulate pedestrians’ emergency escape. The participants competed and interacted with real individuals in an actual crowd and made actual wayfinding decisions to make the quickest possible escape. Our particular interest was investigating the sample-to-sample variations and the context-dependence of the inferred estimates. ResultsWe observed fairly similar parameter estimate patterns emerged from all four datasets, and identified many behavioural aspects upon which all models consistently agreed regardless of their context of origin. Moreover, despite the significant differences between the parameter scales of the four models, the SC-generated models made predictions that were reasonably similar to those of the RC model as well as to those of the model derived from the combined data. ApplicationsOur findings provide promising evidence as to the potential applicability of the SC methods in particular as well as other forms of virtual-reality decision experiments in general as a practical, flexible and ethical approach for the continuation of research and advancing the state of knowledge in this field.

Entrepreneurial Spawning: Experience, Education, and Exit

AbstractWe investigate the career dynamics of high‐tech entrepreneurs by analyzing the exit choice of entrepreneurs: to act as a business angel, to found another firm, or to become dependently employed. Our detailed data from CrunchBase indicate that founders are more likely to stick with entrepreneurship as a serial entrepreneur or as an angel investor in cases where the founder had prior experience either in founding other startups or working for a startup, or had a “jack‐of‐all‐trades” education.

Effects of familiarity and neighbor behavior on visually-guided exit choice in an emergency

Effects of familiarity and neighbor behavior on visually-guided exit choice in an emergency

A mixed logit model for predicting exit choice during building evacuations

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.

Human exit choice in crowded built environments: Investigating underlying behavioural differences between normal egress and emergency evacuations

Egress behaviour of pedestrians in crowded complex confined spaces is investigated in this study. Despite recent methodological progress in the development of simulation tools for predicting crowd egress and evacuation, little is known based on empirical data about the underlying rules that govern exit wayfinding of pedestrians in multi-exit places. Particularly, fundamental differences between behavioural features of emergency and non-emergency egress have not been fully explored by previous studies. Stated-choice data was collected in face-to-face interviews with passengers as they exited a major railway station in Melbourne. Participants were asked what exit decision they would have made given certain hypothetical scenarios at that same station. Econometric models (error-component mixed logit) were developed to quantify the way passengers evaluate and prioritise various contributing factors while accommodating the potential decision heterogeneity. These factors include distance, crowding, visibility of exits, proximity of the exits to their destination, impact of other passengers’ decisions; and spatial distribution of exits. Key findings of our modelling suggest that (1) for nonemergency egress, proximity of the exit points to passenger's destination is a dominant factor although not the sole determinant. (2) In an emergency, passengers place a much higher priority on avoiding crowded exits compared to non-emergency situations. (3) Directional flows of pedestrians do not significantly impact on decisions made in a normal egress. (4) In an emergency evacuation, directional flows are considered as a negative utility factor by majority of individuals, although the perception of this factor is highly heterogeneous and also depends on the visibility of the exits targeted by the flow. The proposed static models can be incorporated with a broad range of crowd simulation methods as alternatives for heuristic modeller-defined exit choice rules. They accommodate the dissimilarities of egress behaviour between emergencies and non-emergencies, thereby enabling planners to conduct virtual simulations under either scenario.

Leaving a Social Venture: Social Entrepreneurial Exit among the Maasai in Northern Tanzania

Arguing that the exit of social ventures is likely to follow specific patterns, due the uniqueness of a social entrepreneur’s goals, the social venture’s emphasis on the provision of public goods, and its relationship to stakeholders, we conduct a qualitative analysis of the entrepreneurial exit of a Dutch social venture in Northern Tanzania. Our analysis suggests that the choice of exit and the potential exit routes are indeed specific to social ventures, as the original social goals of the venture influence the decision to exit and its implementation. Specifically, we find that the goal of leaving a sustainable venture after the exit and the preference for the transfer of ownership to local community members was paramount for the social entrepreneur. Our results also highlight the difficulties associated with the unique role of stakeholders in social ventures, due to different perceptions and interests about the meaning and implementation of entrepreneurial exit.

Identifying Latent Classes of Pedestrian Crowd Evacuees

The tactical decision making of humans when they exit crowded built environments was investigated. Recent studies have shown that the relative weights and priorities that pedestrian evacuees associate with different factors contributing to their choice of exit vary significantly from person to person, yet this heterogeneity is not explainable by the demographics of the decision makers, such as gender. Hence, it is assumed that the choice could be attributable to the presence of latent classes (latent types of behavior) unassociated with observable demographic characteristics. The standard latent class and the random coefficient latent class choice models were implemented with data on stated exit choices to explore this. The latter model accommodated coefficient heterogeneity within each class by allowing the coefficients associated with each class to vary randomly. Data analyses showed that exit choice heterogeneity did not necessarily need to be represented by continuous distributions and could have been accommodated in a finite number of discrete categories. In fact, only two classes of evacuees (congestion avoiders and distance avoiders) could be identified. The terminology derived from the fact that the chief difference in evacuation behavior of the two classes was associated with their perception of crowding-related factors (i.e., exit density and directional density). The modeling results suggested that congestion avoiders outnumbered distance avoiders. The analyses also showed that the within-class heterogeneity faded into insignificance once the binary discrete classification was imposed: evacuees’ decision-making heterogeneity was sufficiently reducible into two discrete categories with negligible inner-class variation. This finding provides a more tangible interpretation of exit choice heterogeneity than the continuous mixture approach. The finding also simplifies the way in which the modeler deals with decision heterogeneity when the exit choice model is implemented for prediction purposes.

An analysis of founder power on entrepreneurs’ exit decisions after IPO

In this study, we examine the relationship between founders power and their exit decisions after IPO. We distinguish between three exit choices after IPO (managerially, financially and totally), an...

Experimental Study on Choice Behavior of Pedestrians During Building Evacuation

Understanding human behavior in emergency evacuation is a significant issue for layout optimization, crowd management and rescue. In this study, we conducted a series of controlled experiments to study choice behavior of pedestrians considering environment factors (e.g. occupant initial distribution, auditory information, and building layout). We found it was non-symmetrical for pedestrians’ exit selection and aisle selection in the room. And there was a strong positive relation between intermediate exit choice and destination choice. Pedestrians’ final destinations had significantly effects on evacuation route and intermediate facilities usage. When the final destination was uncertain, the factor of building layout performed more effect than occupant initial distribution. Pedestrian psychology, following the crowd, had a major influence on pedestrians’ exit stairs selection, especially when pedestrians were in non-limited visual field environment. Bifurcation point, where a row of pedestrians split into two streams with diametrically opposite movement directions, was a quite biased away from the side of exit. The conclusions are expected to provide valuable advice for crowd management and optimization design such as aisle-seating layout.

Modeling and assessment of civil aircraft evacuation based on finer-grid

Studying civil aircraft emergency evacuation process by using computer model is an effective way. In this study, the evacuation of Airbus A380 is simulated using a Finer-Grid Civil Aircraft Evacuation (FGCAE) model. In this model, the effect of seat area and others on escape process and pedestrian’s “hesitation” before leaving exits are considered, and an optimized rule of exit choice is defined. Simulations reproduce typical characteristics of aircraft evacuation, such as the movement synchronization between adjacent pedestrians, route choice and so on, and indicate that evacuation efficiency will be determined by pedestrian‘s “preference” and “hesitation”. Based on the model, an assessment procedure of aircraft evacuation safety is presented. The assessment and comparison with the actual evacuation test demonstrate that the available exit setting of “one exit from each exit pair” used by practical demonstration test is not the worst scenario. The half exits of one end of the cabin are all unavailable is the worst one, that should be paid more attention to, and even be adopted in the certification test. The model and method presented in this study could be useful for assessing, validating and improving the evacuation performance of aircraft.

A study of herding behaviour in exit choice during emergencies based on random utility theory

Modelling human behaviour in emergencies has become an important issue in safety engineering. Good behavioural models can help increase the safety of transportation systems and buildings in extreme situations like fires or terrorist attacks. Although it is well known that the interaction with other decision makers affects human behaviour, the role of social influences during evacuations still needs to be investigated. This paper contributes to fill this gap by analysing the occurrence of Herding Behaviour (HB) in exit choice. Theoretical explanations of HB are presented together with some modelling approaches used in different fields where HB is relevant. A discrete choice stated preference experiment is then carried out to study the role of HB in the decision-making process concerning exit choice during evacuation. A binary logit model is proposed showing that the occurrences of HB are affected by both environmental and personal factors. In particular, the model shows that the personal aptitude to HB can have a key role in selecting an exit.

Study into the Use of Signage on Exit Choice Behaviour in a Virtual Environment

The effectiveness of egress paths from a building could be attributed to good signage or intuitive Architecture but we know it is also influenced by human behaviour in fire. The extent to which human behaviour plays a role in the effectiveness of egress routes is not yet fully understood.The aim of this paper is to investigate human behaviour in a relatively simple study of exit choice. The study is conducted in a virtual environment by examining the effectiveness of additional floor-based chevron arrows when compared with conventional exit signage on the same escape routes.Fifty nine participants were asked to interact with the software to escape from a fire in the created virtual environment. Thirty two of the participants used a model with conventional exit signs only. Twenty seven of the participants used the model with exit signs and chevrons on the floor. After completing the virtual egress exercise the participants were given a questionnaire to help understand their behaviour during the task. This allowed the authors to compare results of the post experiment questionnaire with the video output of the test.This research is novel in that involves the use of already existing technologies for new purposes; in this case, commercial computer games engines, generally used for entertainment purposes. As technology reaches new levels it is inevitable that there will be overlap in functionality.This paper describes the experiments, analyses the information gleaned from the research and provides some conclusions for consideration by others in this field. By assessing exit choice behaviour and evacuation time it is possible to compare the effectiveness of the additional floor based signage as a fire protection measure provided above and beyond normal code requirements.

Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model

Mixed logit has been recognised and widely practised by researchers as a highly flexible modelling tool that can address the main shortcomings of the standard logit. Despite the potential to be generalised, the random-coefficient modelling has rarely been integrated with more advanced GEV-type models, possibly due to the unavailability of such estimation options in most econometric software. This particular generalisation has been recommended by a number of econometricians for analysing choice problems in which capturing taste variation and specific non-IIA patterns of substitution are both of modeller's concern. This way, the analyst will be able to limit the number of explanatory variables to the ones whose distributions of coefficients offer behavioural interpretations about taste variation, and leave the imposition of the desired substitution pattern to the GEV core.In this paper, we report on a mixed nested logit application aimed at understanding evacuation behaviour of human crowd, particularly the choice of exit. Evacuees' trade-off between contributing factors are elicited through a data set of stated exit choices. We attempt to improve the realism of the choice experiments by conducting face-to-face interviews with pedestrians (respondents) as they exit a building; and designing scenarios that refer to their recent actual choice of exit. The primary analysis strongly suggests the presence of taste heterogeneity as well as the violation of the IIA assumption (i.e. the presence of a particular pattern of correlation between exit utilities). We propose and estimate a mixed nested logit model through which we accommodate these two econometric aspects of the problem in a unified model. Compared to the counterpart mixed multinomial logit model in which the desired substitution pattern is embodied through specification of the explanatory variables, the proposed model reduces the dimension of simulation in the likelihood maximisation procedure, and also yields a slightly better statistical fit.