Why crowds panic

In contrast to portrayals of crowds as panicking and acting selfishly to evacuate, research has shown that the opposite occurred. Hence, the decision to label instances of collective flight as panic is arbitrary. For example, a number of widely-held beliefs among the public and the media have been shown to be incorrect, such as that looting, mass panic , and selfish behaviour are common in disasters, and should be abandoned in favour of realistic, proactive emergency knowledge.

It supposedly explains the high numbers of avoidable fatalities in emergency evacuations. Under these circumstances they lose all sense of judgment and discretion. They become impervious to communication or direction, trample over one another, and fail to seek other exits of escape even if available. For these reasons mass panic rarely occurs in outside disaster circumstances. Such an image is frequently documented by isolated anecdotes used to prove the universality of such behavior.

This image suggests that individuals panic and that individuals lose their concern for others. The word is often very loosely and incorrectly used to describe virtually any type of fear, flight, or uncoordinated activity.

Because of this, officials may hesitate to issue warnings because they are convinced that the resulting panic will cause more damage than the disaster itself. Assumptions of panic may therefore be counterproductive. Such delays have contributed to subsequent flight behaviour and the crush of people who had only a few seconds left to react once the situation unexpectedly got out of hand.

When these definitions are placed side by side. While panic has recently been studied in animal experiments with mice and ants [o.

In most of these news we are able to read that people were fallen in panic or a mass- panic occurred. This is a simple, but often used explanation why people died in such situations. But is that the truth? The results show, that panic behavior in case of mass-emergencies does not as often occur as suggested.

Note that individual studies can belong to multiple categories e. Panic can affect evacuation efficiency, in both beneficial or detrimental ways. In situations of escape panics , individuals are getting nervous, i. It is shown that the variation of the model parameters allows describing different types of behaviour, from regular to panic. In panic situations many counter-intuitive phenomena e. Crisis circumstances often involve considerable uncertainty, confusion, and panic.

The bulk of the literature is restricted to the study of normal non- panic pedestrian dynamics or normal evacuation processes. The use of term panic and emergencies in this study refer to situations in which individuals have limited information and vision due to high crowd density and short time for egress , and which result in physical competition and pushing behavior.

In , Quarantelli was the first social scientist to find that there is no proof of the presence of panic in cases of major disasters. An increased stress level is not the same as panic , which can be defined as irrational, illogical and uncontrolled behaviour. Under the panic state the agents cohere closely and almost do not change the target exit. People under panic are usually willing to move along known routes, even if this means they run towards the fire, which may lead to more fatalities.

Empirical data have shown that usually the escape panic can cause more casualties than the actual disaster. Some may lose their own decision-making capacity and the herding behavior may appear for following specific individual. Panic : Breakdown of ordered, cooperative behavior of individuals due to anxious reactions to a certain event… characterized by attempted escape of many individuals from a real or perceived threat…, which may end up in trampling or crushing of people in a crowd.

We have proposed a consistent theoretical approach allowing a continuous switching between seemingly incompatible kinds of human behavior individualistic rational behavior vs. One of the most disastrous forms of collective human behaviour is the kind of crowd stampede induced by panic , often leading to fatalities as people are crushed or trampled.

The characteristic features of escape panics can be summarized as follows: 1 People move or try to move considerably faster…. Recent studies that have experimented this problem, however, have shown that, in crowded evacuation scenarios where queues form at exits , observing other people changing their exit decisions is a trigger for the observer to change the initial decision and imitate that action [ 65 , 66 ].

It has been shown in these experiments that once one evacuee decides to leave a queue formed at an exit and join another queue at another exit, it increases the likelihood of decision changing by others followed by a burst of decision changes. In such scenarios, at any point in time, there are more people not changing their decisions compared to the number of individuals who decide to change their initial choice. Numerical testing in a recent study [ 86 ] has also been shown that certain degrees of imitation in exit choice making enhances the efficiency of crowd evacuations from a system perspective.

The findings of the experiment reported by Haghani and Sarvi [ 41 ], as outlined earlier, may be regarded as evidence opposite the symmetry breaking.

The experiment showed that as urgency increases, people show even less tendency to follow the direction chosen by more people. The stark contrast between this experiment and those of the symmetry breaking experiments with ants could be worthy of note. The symmetry breaking phenomenon has been proven with ants through several independent experiments. However, recent evidence is overwhelmingly suggesting that the phenomenon does not seem to be replicable when tested with humans.

This might be only one of the areas where the escape behaviour of insects and humans differ fundamentally and thereby, generalisation across the two should be avoided [ 87 ]. In some research the notion can arise that findings from research using social insects can be extrapolated directly to emergency evacuations involving humans.

However, there are fundamental differences between species that go beyond obvious physical distinguishing factors. For example, the genetic make-up of ant colonies is largely homogeneous which is likely to affect the trade-off between individual survival and survival of other colony members.

This could explain why entire ant colonies reenter previously evacuated nests in an attempt to save their brood D. Parisi, personal communication , behaviour that is unlikely to occur at this scale in humans.

An argument in response to our proposition is that such experiments are often conducted to help us replicate the sense of real danger which cannot be possibly considered in experiments with human subjects.

It should, however, be noted that in many cases, proxies for life-threating dangers, such as creating the sense of urgency using monetary incentives, could be used within the frameworks of ethical experimentation and without imposing any real danger on participants.

Previous discussions in Section 5 revealed that the term herding is being used in the literature with lesser degrees of inconsistency in terms of the definition, compared to the terms panic and irrationality. However, in light of the empirical findings that we reviewed in this section, here we argue that, despite this relative consistency in definition, the term herding per se lacks accuracy in conveying the meaning that it is meant to embody.

Firstly, herding is a term that has been originally used in relation to animal groups. As we discussed earlier in Section 6. Secondly, our review of empirical findings showed that people exhibit various kinds of tendency towards copying or not copying the actions of others in evacuation contexts.

Their behaviour appears to be rather complex. For certain aspects of their behaviour or under certain contextual circumstances , they show tendency to avoid the action of the majority rather than follow. Also, in some cases, they might show imitative tendency but towards the action of the minority rather the majority. The literature is clearly showing that social influence on evacuation behaviour differs depending on the type of action e.

Therefore, there is a great amount of nuance involved in this phenomenon that the term herding fails to capture. It embodies both tendencies to follow or to avoid others, as well as tendencies to follow the majority or the minority.

For these reasons, we suggest that while the idea behind exploring the role of social influence in evacuation is legitimately valid and even essential, the problem does not need to be formulated as a question about herding.

We argue that this term comes with an unnecessary amount of predisposed connotation partly inherited from the panic theory as opposed to the nuance, neutrality and flexibility that is required for describing a rather complex phenomenon like this.

We have adopted a literature survey approach to investigate, in an open-minded way, if preferred or dominant definitions for the three terms we investigate have emerged over time in the literature.

While we cannot claim that our literature search is completely exhaustive, we argue that the number of publications included is sufficiently large to adequately support our findings. We acknowledge that the way we have prioritised comments on the terms we investigate within papers and the way we have grouped or reduced comments and categorised supportive or unsupportive comments, as well as the disciplines that publications belong to, is to some extent subjective.

We hope that this qualitative analysis is nevertheless a useful synthesis of the complete body of comments we found which we report in full in the Appendix, Tables 5 — 7. As the empirical base for research into human crowd dynamics continues to grow [ 6 ], such meta-analyses will become an attractive option to test the support for specific hypotheses by incorporating evidence across several studies in a similar way to what has been done in other fields of research [ 88 ].

However, we anticipate that such an analysis will not be possible for the three terms we discuss here. The unification of behavioural terminologies and hypotheses could be a major useful step towards shaping the literature in that direction. Our survey of the crowd dynamics literature illustrated that the three terms that we reviewed do not have an unequivocally accepted definition in the literature.

This is particularly the case for the terms panic and irrationality. While these terms are still used in increasing numbers of publications, they are also discussed controversially.

An additional and complicating aspect suggested by our literature search is that the terms are used and treated differently in studies from different broad disciplines of research. This is in line with what we have found by searching the literature extensively for uses of these three terms, as well as the suggestions of several authors in the field of social psychology. One is why despite the research evidence, the idea of "panic" captures the popular imagination and continues to be evoked by scholars of human behavior.

Our review suggested that the use of these terminologies has not constructively contributed value to the evacuation dynamics literature and if anything, in some cases, the clear lack of definitions for at least two of these terms has ambiguated the research field and hampered the efforts of the researchers. Having reviewed the use of these terms, for example, we were not able to identify a definition for the term panic that can be framed as a testable hypothesis.

As a result of this issue in this research domain, assumptions have been made that can neither be verified not rejected and computational prediction models have been formulated that cannot be objectively validated. These issues do not imply that anything loosely related to the three terms cannot be investigated systematically. While herding is arguably a vague concept, researchers have specified concrete behavioural phenomena instead, such as imitative behaviour, that lend themselves to scientific investigation via observations, experiments or models.

In particular, the imprecise assumptions that can accompany these terms may dissuade or divert research from studying these phenomena at the level of nuance that they require. Therefore, we argue that it would be beneficial for the progress of research in this field that the questions related to the three terms discussed here are clearly stated in terms of verifiable hypotheses and be operationalized for empirical testing.

As an illustration for why the language that is used to describe behavioural phenomena in this context matters and can potentially have a significant influence on shaping and directing the research in this field and even management practices, consider the following examples. The assumption that phenomena related to the term panic are not testable in experimental settings with humans has made many authors favour pure numerical methods over experimentation or favour experimentation with animals or insects over experiments with human crowds [ 59 — 62 , 90 — 97 ].

In terms of management practices, the theory could be cited in crises situations as a reason for withholding information from the crowd by managing authorities in order to save more lives. According to the studies that we reviewed, this is based on the rationale that if people know about a critical situation, it might agitate them, ultimately causing them to panic which will lead to irrational behaviour.

Similar important implications are also conveyed by the term herding. The term, as we showed in our detailed analysis of quotes, has largely been used in the literature to convey imitative type of behaviour [ 49 ]. However, the use of this largely animalistic term does not make it clear whether there will be contexts or aspects of behaviour in which people do not tend to imitate. It also depicts a mechanism of decision-making in which peer influence is the only factor or the dominant factor while trivialising the role of other potential contributing factors to human responses.

The research on evacuation dynamics has been actively in progress for several decades. Many scholars from a range of disciplines have been researching this topic and significant progress has been made.

However, we argued that, if thus far, this ample effort has not converged to any well-defined and empirically supported characterisation or a well-accepted numerical model for panic, then it may be unlikely that such goal be achieved in the future.

This may be an indication that some parts of the literature in this field may be in need a fundamental reformulation. It warrants that some of the concepts or terminologies, including those studied in this review, be revisited and replaced with more proper substitutes. In doing so, a more integrative approach between the numerical, empirical, and social science studies could prove useful.

Table 4 lists a summary of the conclusions that we drew based on this review regarding the use of each of the three terms, along with our recommendations. The authors declare that there are no conflicts of interest regarding the publication of this paper. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article of the Year Award: Outstanding research contributions of , as selected by our Chief Editors. Read the winning articles. Journal overview. Special Issues. Academic Editor: David F. Received 04 Apr Revised 07 Jun Accepted 01 Jul Published 08 Aug Abstract Background. Introduction As researchers working in the field of pedestrian dynamics, we have experienced that a presentation of a piece of research on the topic of crowd evacuation, whether to an academic audience or lay audience, barely goes by without researchers being confronted with these questions: How about the effect of panic?

Methods The main purpose of the review is to perform a structured literature search on the use of the terms panic, irrationality, and herding in the context of emergency evacuation of crowds. Comment Frq. Discipline Study type Soc. Table 1. Reduced comments on the term panic and their frequency among the original quotes.

Figure 1. Visualising the frequency of quotes on the term panic that convey support for the theory versus those that challenge it. The pie charts on the left show the frequency of the supporting comments across the disciplines on the top and across the study types in the bottom. Similarly, the pie charts on the right show the frequency of the contradicting comments again across the disciplines on the top and across the study types in the bottom.

The column chart in the middle compares the frequency of these comments in total regardless of the discipline or type of the study from which the comments were extracted. Figure 2. Visualising temporal analyses on quotes that include the term panic.

The column chart on the top represents the total number of quotes and the one in the bottom splits the frequency based on whether the quotes support or contradict the theory chart on the left and based on the study discipline chart on the right. The very few studies covered by this review and published prior to or in we accommodated in the first and last intervals, respectively. Table 2. Reduced comments on the term irrationality and their frequency among the original quotes.

Figure 3. Visualising the frequency of quotes on the term irrationality that convey support for the theory versus those that challenge it. Figure 4. Visualising temporal analyses on quotes that include the term irrationality. The column chart on the top represents the total number of quotes and the ones in the bottom splits the frequency based on whether the quotes support or contradict the theory chart on the left and based on the study discipline chart on the right.

The very few studies covered by this review and published prior to or in we accommodated in the first and last intervals respectively. Figure 5. Visualising the frequency of quotes on the term herding that convey support for the theory versus those that challenge it. Figure 6. Visualising temporal analyses on quotes that include the term herding. Table 3.

Reduced comments on the term herding and their frequency among the original quotes. The two can be dissociated. The question of social influence can be legitimately investigated in its own terms iii The question about the role of social influence should be studied in association with different specific aspects of the behaviour. The effect varies across various behavioural aspects. Table 4. A summary of the conclusions and the recommendations associated with each of the three terms.

Quotes Qu. Links to Ir. Furthermore, people try to move considerably faster than normal, etc. Nevertheless, it is desirable to have a model which is able to describe the whole spectrum of possible pedestrian behaviour in a unified way.

So other alternative exits are ignored. Some may accelerate the speed of movement due to the panic. Some may panic that cannot choose the right exit or even lose destination.

People in a fire scene are very likely to be affected by people around as a result of uneasiness and panic. They would like to be close to the crowd and follow the route of the mass rather than the route made by their own judgment. At exits, clogging and collisions occur, as well as rainbow-like arching structures. Negative emotions, such as panic , may induce disastrous forms of collective human behaviors, e.

Sime [o. However, reviews and case studies of emergencies show that cooperation is relatively common within and across crowds. Accordingly, things can go terribly wrong in spite of no bad intentions from anyone. Indeed, this is one of the probable goals of the terrorists.

But, contrary to these popular portrayals, group panic is relatively rare. In disasters people are often models of civility and cooperation. Smelser distinguishes it from the classic panics of escape, e.

Researchers conducting such studies generally conclude that panic is a rare form of crowd behaviour. Quarantelli and Dynes report that they have found few instances of panic after years of disaster research.

However, some influential practitioners, including crowd modellers in the fields of engineering and design, still draw upon the notion.

The term is often used when what in fact is being described is simply flight from the source of danger. This is even the case when they in fact stayed calm and behaved in a rational and prudent fashion. In contrast to portrayals of crowds as panicking and acting selfishly to evacuate, research has shown that the opposite occurred. Hence, the decision to label instances of collective flight as panic is arbitrary. For example, a number of widely-held beliefs among the public and the media have been shown to be incorrect, such as that looting, mass panic , and selfish behaviour are common in disasters, and should be abandoned in favour of realistic, proactive emergency knowledge.

It supposedly explains the high numbers of avoidable fatalities in emergency evacuations. Under these circumstances they lose all sense of judgment and discretion. They become impervious to communication or direction, trample over one another, and fail to seek other exits of escape even if available.

For these reasons mass panic rarely occurs in outside disaster circumstances. Such an image is frequently documented by isolated anecdotes used to prove the universality of such behavior. This image suggests that individuals panic and that individuals lose their concern for others. The word is often very loosely and incorrectly used to describe virtually any type of fear, flight, or uncoordinated activity.

Because of this, officials may hesitate to issue warnings because they are convinced that the resulting panic will cause more damage than the disaster itself. Assumptions of panic may therefore be counterproductive. Such delays have contributed to subsequent flight behaviour and the crush of people who had only a few seconds left to react once the situation unexpectedly got out of hand.

When these definitions are placed side by side. While panic has recently been studied in animal experiments with mice and ants [o. In most of these news we are able to read that people were fallen in panic or a mass- panic occurred. This is a simple, but often used explanation why people died in such situations.

But is that the truth? The results show, that panic behavior in case of mass-emergencies does not as often occur as suggested. Note that individual studies can belong to multiple categories e. Table 5. Links to P. Here we want to apply this model to a simple evacuation process with people trying to escape from a large room. Such a situation can lead to a panic where individuals apparently act irrationally.

Although it might not be the most optimal route, this does not imply irrationality or randomness. However, the effectiveness of behaviour is compared to an ideal way of acting. He is always in pursuit of his own interests and acts on the basis of his current estimates of where these lie.

First, definitions of panic often include exaggerated beliefs about threat and overreactions and so on. Second is the idea that the act of escape may be self-defeating. But what may be considered inappropriate, excessive, irrational or highly intense by others may not be so judged by participants themselves. Table 6. These times depend on the strength of the herding behaviour, with minimal evacuation times for some intermediate values of the couplings, i.

At the same time, they may have the herd mentality. Herding , therefore, resulted from the crowdedness and not from a change in the individual tendency to imitate neighbours. The main obstacle to answering these questions is the scarcity of detailed empirical data. For example, consider the case of an environment in which the exit routes are less clear than in our experiment or even entirely unknown.

Such behavior is the herding behavior. Rather, these passengers usually adopt a herd mentality and evacuate immediately for their security. The main ingredients of the model are an alignment term, accounting for the herding effect typical of uncertain behavior, and a random walk, accounting for the need to explore the environment under limited visibility.

Based on mice, scale-free behavior [o. This symmetry breaking is observed in both human crowds and ant colonies.

In such cases, when escaping from a closed space with two symmetrically located exits, one exit is used more often than the other. The situation encourages pedestrians to base their decisions on what they know, thus copying the actions of their immediate neighbors, which may result to herding.

In particular, the model shows that the personal aptitude to HB can have a key role in selecting an exit.

As regards to the exit choice, this can be explained by the decision of the evacuee to choose an exit just because other evacuees had selected it, instead of striving to identify the exit that would provide them with the best evacuation conditions.

In panic situations where decisions have to be made quickly under duress it is likely for individuals to lose their ability to decide on their own. Instead, these impaired individuals tend to imitate the action of their neighbors.

The tendency to rely on others is a product of experience. However, quantitative comparisons between model prediction and experimental result have remained scarce. It has been predicted theoretically that panic induced herding in individuals confined to a room can produce a non-symmetrical use of two identical exit doors. Here we demonstrate the existence of that phenomenon in experiments, using ants as a model of pedestrians… Our experimental results, combined with theoretical models, suggest that some features of the collective behavior of humans and ants can be quite similar when escaping under panic.

To the contrary, they tend to avoid the direction chosen by the majority, and the bigger the majority is, the less likely they are to follow it. The high-urgency treatment assumed to be associated with higher degrees of stress did not reverse, nor did it decrease this avoid-the-majority tendency. If anything, it even amplified it in certain choice situations. Higher levels of crowding also amplified the avoid-the-crowd tendency [opposite the herding ] in certain direction choice scenarios.

Table 7. Herding prevented the full utilization of the two exits. Table 8. References X. Yang, Z. Wu, and Y. Dias, M. Sarvi, O. Ejtemai, and M. Seyfried, O. Passon, B. Steffen, M. Boltes, T. Rupprecht, and W. Li, T. Chen, L. Pan, S. Shen, and H. View at: Google Scholar M. Haghani and M. Kobes, I.

Helsloot, B. De Vries, and J. Wang, K. Huang, Y. Cheng, and X. Shen, X. Wang, and L. Rassia and C. Guo, X.

Li, H. Kuang, Y. Bai, and H. Tong and D. Wagner and V. Song, J. Gong, Y. Cui, L. Fang, and W. Marinelli, and M. Kirchner and A. Helbing, I. Farkas, and T. Haghani, M. Sarvi, and Z. Shahhoseini, M. Sarvi, and M. Shi, Z. Ye, N. Shiwakoti, D. Tang, and J. Ehtamo, D. Helbing, and T. View at: Google Scholar J. Drury, D. Novelli, and C. Heide, Common misconceptions about disasters: Panic, the, disaster syndrome , and looting, The first 72 hours: A community approach to disaster preparedness , Drury, C.

Cocking, and S. Cocking and J. Fahy, G. Proulx, and L. View at: Google Scholar H. Kelley, J. Condry, A. Dahlke, and A. Sheppard, G. Rubin, J. Wardman, and S.

Zhao, G. Yang, W. Wang et al. Zheng and Y. Pan, C. Han, K. Dauber, and K. Kapadia, T. Thrash et al. Ji, C. Xin, S. Hong, J. Gao, and W. Albi, M. Bongini, E. Panic or chaos in a crowd can kill or injure hundreds, as happened at the Love Parade in Germany in when thousands of attendees to an electronic dance music festival piled up as they tried to enter a narrow tunnel; 21 people died of suffocation.

Fundamental science and public safety demand that we develop a complete science of crowds using a range of disciplines. Today, work by social psychologists shows that crowds are influenced by the personalities of individual members; thus, crowds can embody altruistic and helpful behaviour as well as the opposite. And now we can extend crowd science further by incorporating quantitative analysis using classical and statistical physics, computational science and the theory of complex systems — the study of groups of interacting entities.

For instance, randomly moving H 2 O molecules in liquid water suddenly link up at zero degrees Celsius to make solid ice; starlings in flight quickly form themselves into an ordered flock. Emergent behaviour can be predicted if the interaction among the entities is known, as shown in by researchers at the University of Minnesota who determined how two people in motion interact and, from that, how a crowd moves.

The researchers first considered an idea from physics, theorising that, like electrons, pedestrians avoid collision by repelling each other as they get closer. But video databases showed instead that when people see that they are about to collide, they change their paths. From this, the researchers derived an equation for what amounts to a universal force of repulsion between two people, based on time until collision, not distance.

The formula successfully reproduced the emergent real-world features of a crowd, such as forming a semicircular configuration while waiting to trickle through a narrow passage, or extemporaneously developing independent lanes as its members walk toward different exits. This makes it possible to simulate crowd behaviour to design evacuation routes, for instance. T o be useful in emergencies, crowd analysis must also account for emotional contagion. Spreading fear can change emergent behaviour, as shown by researchers at the K N Toosi University of Technology in Iran.

In , they created a computer version of a public space populated with hundreds of simulated adults and children, and security guards who directed people to the exits. Assuming that the participants were responding to a dangerous event, the simulation escalated them to greater levels of fear and panicked, random movement when they failed to find an exit. Running the simulation, the researchers found that between 18 and 99 per cent could escape, depending on the combination of participants.

The greatest number of escapes did not occur with the smallest or largest numbers of people or security agents but at intermediate values. This shows that the emotional state of a crowd can carry its dynamics into a complicated nonlinear stage.

We can determine the emotion of individuals in a real crowd by observing their physical behaviour. Crowd members running from a dangerous event such as an explosion have increased kinetic energy, which can be detected in real-time crowd video images.