Dynamics of social groups’ decision-making in evacuations

Haghani, Milad; Sarvi, Majid; Shahhoseini, Zahra; Boltes, Maik

doi:10.1016/j.trc.2019.04.029

Cited by 52 publications

(12 citation statements)

References 63 publications

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“…In addition, the resulting density and movement speed are sensitive to the position of the measurement area and a valid time interval for the analysis. Nevertheless, the described methods are a proven approach for analysis and have been used in many prior studies, for instance in Germany, 4,53,54,57–71 Australia 72–77 Japan, 78–80 Palestine 81 and China 31–33,82,83 …”

Section: Methodsmentioning

confidence: 99%

The influence of individual impairments in crowd dynamics

et al. 2020

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Summary The importance of empirical relations to quantify the movement of pedestrians through a facility has increased during the last decades since performance‐based design methods became more common. Bottlenecks are of special interest because of their importance for egress routes and as they result in a reduced capacity. The empirical relations as the density‐dependent movement speed or flow rate were derived by studies under laboratory conditions, which were usually conducted with populations of homogeneous characteristics for better control of influencing variables. If individual characteristics of a crowd become more heterogeneous, individuals were forced to adapt their individual movement and control individual manoeuvring. These unintended interactions lead to a different shape of the fundamental empirical relations. Here, we present results from a movement study under well‐controlled boundary conditions in which participants with and without different characteristics of disabilities participated. To consider the effect of different heterogeneities on the capacity of a facility, fundamental diagrams are generated using the Voronoi method. If participants with visible disabilities (such as using assistive devices) are part of a crowd, significant differences relating to the shape of the empirical relations and the capacities are found. This indicates that the heterogeneity of a population leads to an increased interpersonal interaction which results in influenced movement characteristics.

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Section: Methodsmentioning

confidence: 99%

The influence of individual impairments in crowd dynamics

et al. 2020

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“…The open-source software PeTrack [37] is dedicated to the detection and tracking of pedestrians, both with and without markers. It is successfully used in several pedestrian dynamics calibration applications e.g., [15,[38][39][40][41]. The software uses top-view footage of cameras with low to mild radial distortion and detects pedestrians by searching for isolines of the brightness which are nearly ellipsoid.…”

Section: Related Workmentioning

confidence: 99%

“…For instance, Refs. [15,16] propose Helbing's model for evacuation scenarios and validate these based on empirical data. Karamouzas et al [17] developed a predictive collision avoidance model for the simulation of pedestrian flows.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Methodology for Characterizing the Flow of a High-Density Crowd on Footbridges: Strategy and Application

et al. 2020

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Obtaining pedestrian trajectories by a vision-based methodology is receiving increasing attention in the literature over recent decades. Within the field of study of human-induced vibrations on footbridges, practical challenges arise when collecting the trajectories of high-density crowds during measurement campaigns. A cheap and robust methodology tackling these issues is presented and applied on a case study consisting of a real-life footbridge occupied with many pedestrians. A static camera setup consisting of low-cost action cameras with limited installation height is used. In addition, a drone camera was employed to collect a limited amount of footage. Pedestrians are equipped with colored hats and detected using a straightforward color-segmenting approach. The measurements are subjected to both systematic and random measurement errors. The influence of the former is theoretically investigated and is found to be of limited importance. The effect of the latter is minimized using a Kalman filter and smoother. A thorough assessment of the accuracy results reveals that the remaining uncertainty is in the order of magnitude of 2 to 3 cm, which is largely sufficient for the envisaged purpose. Although the methodology is applied on a specific case study in the present work, the conclusions regarding the obtained accuracy and employability are generic since the measurement setup can be extended to a footbridge with virtually any length. Moreover, the empirically obtained results of the presented case study should find use in the calibration of pedestrian dynamic models that describe the flow of high-density crowds on footbridges and the further development of load models describing crowd-induced loading.

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“…They predominantly interpret herding in the context of exit choice making. However, the literature has been increasingly recognising the role of social influence in other aspects of evacuation decision-making and a few studies have looked into this problem in connection with reaction responses of evacuees [55,58,64] and exit choice adaptation (or exit choice changing) behaviour [65,66] of evacuees. Hence, in our analysis of the 24 empirical studies on this topic, we have categorised each item into one (or occasionally two) of these three categories: exit (direction) choice, exit (direction) choice changing, and reaction times.…”

Section: Definitions and Alternative Terminologies For Herdingmentioning

confidence: 99%

“…Proportionately, much less is known about the influence of peer behaviour on this aspect of evacuee's behaviour compared to the influence on exit choice. 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.…”

Section: Herding In Exit Choice Adaptationmentioning

confidence: 99%

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

Haghani

Cristiani

Bode

et al. 2019

Journal of Advanced Transportation

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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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Dynamics of social groups’ decision-making in evacuations

Cited by 52 publications

References 63 publications

The influence of individual impairments in crowd dynamics

The influence of individual impairments in crowd dynamics

Vision-Based Methodology for Characterizing the Flow of a High-Density Crowd on Footbridges: Strategy and Application

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

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