Empirical methods in pedestrian, crowd and evacuation dynamics: Part I. Experimental methods and emerging topics

Evacuation behaviour of crowds under high and low levels of urgency: Experiments of reaction time, exit choice and exit-choice adaptation

Background. The three terms “panic”, “irrationality”, and “herding” are ubiquitous in the crowd dynamics literature and have a strong influence on both modelling and management practices. The terms are also commonly shared between the scientific and nonscientific domains. The pervasiveness of the use of these terms is to the point where their underlying assumptions have often been treated as common knowledge by both experts and lay persons. Yet, at the same time, the literature on crowd dynamics presents ample debate, contradiction, and inconsistency on these topics. Method. This review is the first to systematically revisit these three terms in a unified study to highlight the scope of this debate. We extracted from peer-reviewed journal articles direct quotes that offer a definition, conceptualisation, or supporting/contradicting evidence on these terms and/or their underlying theories. To further examine the suitability of the term herding, a secondary and more detailed analysis is also conducted on studies that have specifically investigated this phenomenon in empirical settings. Results. The review shows that (i) there is no consensus on the definition for the terms panic and irrationality and that (ii) the literature is highly divided along discipline lines on how accurate these theories/terminologies are for describing human escape behaviour. The review reveals a complete division and disconnection between studies published by social scientists and those from the physical science domain and also between studies whose main focus is on numerical simulation versus those with empirical focus. (iii) Despite the ambiguity of the definitions and the missing consensus in the literature, these terms are still increasingly and persistently mentioned in crowd evacuation studies. (iv) Different to panic and irrationality, there is relative consistency in definitions of the term herding, with the term usually being associated with ‘(blind) imitation’. However, based on the findings of empirical studies, we argue why, despite the relative consistency in meaning, (v) the term herding itself lacks adequate nuance and accuracy for describing the role of ‘social influence’ in escape behaviour. Our conclusions also emphasise the importance of distinguishing between the social influence on various aspects of evacuation behaviour and avoiding generalisation across various behavioural layers. Conclusions. We argue that the use of these three terms in the scientific literature does not contribute constructively to extending the knowledge or to improving the modelling capabilities in the field of crowd dynamics. This is largely due to the ambiguity of these terms, the overly simplistic nature of their assumptions, or the fact that the theories they represent are not readily verifiable. Recommendations. We suggest that it would be beneficial for advancing this research field that the phenomena related to these three terms are clearly defined by more tangible and quantifiable terms and be formulated as verifiable hypotheses, so they can be operationalized for empirical testing.

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Panic, Irrationality, and Herding: Three Ambiguous Terms in Crowd Dynamics Research

Optimising crowd evacuations: Mathematical, architectural and behavioural approaches

The possible presence of social groups amongst occupants in indoor evacuation scenarios and the potential discrepancies between their behaviour and that of single individuals have been acknowledged in the evacuation dynamics literature. Yet, empirical studies on the behavioural characteristics of social-group evacuees, particularly those related to their decision-making mechanism, are relatively underrepresented. This study reports on a lab-in-the-field experiment of evacuations that investigates the effect of group size and stress level on multiple aspects of groups’ behaviour. These aspects include pre-movement time, decision time (i.e. time taken to reach a directional exit decision), exit-choice behaviour, exit-choice changing and intra-group decision dynamics. Our main findings showed that: (I) Group size had a significant effect on pre-movement times and decision times (and to lesser extent, on evacuation times). People took longer to initiate their movement or to make a directional exit decision when in groups compared to when acting alone. The influence of group size on pre-movement and decision times, however, was not monotonic. For smaller group sizes (sizes 2 and 3), pre-movement and decision times increased with the group size. But for the larger group size (size 4), the effect was reversed. (II) The exit-choice mechanism of groups, overall, showed a great degree of similarity to that of single individuals. This suggests that, from a modelling perspective, the directional exit choices of groups could be approximated with the models obtained from datasets of individually-made choices. (III) Groups were more likely to revisit and change their initial exit decisions under the higher level of stress. In addition, social influence was a major factor in triggering changes in the exit choices of groups. Nearly 50% of the changes in group decisions occurred shortly after another neighbour group changed its exit decision. In other words, instances of group decision-changing was often followed by another group taking a similar action. (IV) As to the within-group dynamics of decision-making, our analyses suggested that, regardless of the group size, leadership was the dominant group decision-making mechanism (compared to the consensus or the conform-to-majority mechanisms). In nearly 50% of the cases, group decisions were made by one individual taking the lead and hinting the direction of the movement to other members of the group.

Dynamics of social groups’ decision-making in evacuations

Simulating pre-evacuation times using hazard-based duration models: is waiting strategy more efficient than instant response?

We present a simple, continuous, cavity-enhanced optical absorption measurement technique based on high-bandwidth Pound-Drever-Hall (PDH) sideband locking. The technique provides a resonant amplitude quadrature readout that can be mapped onto the cavity's internal loss rate and is naturally compatible with weak probe beams. With a proof-of-concept 5-cm-long Fabry-Perot cavity, we measure an absorption sensitivity ∼10-10cm-1/Hz from 30 kHz to 1 MHz, and a minimum value of 6.6×10-11cm-1/Hz at 100 kHz, with 38 µW collected from the cavity's circulating power.

Sideband cavity absorption readout (SideCAR) with a robust frequency lock.

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Simulating pre-evacuation times using hazard-based duration models: is waiting strategy more efficient than instant response?

Sideband cavity absorption readout (SideCAR) with a robust frequency lock.