Disentangling the Impact of Social Groups on Response Times and Movement Dynamics in Evacuations

Bode, Nikolai W. F.; Höll, Stefan; Mehner, Wolfgang; Seyfried, Armin

doi:10.1371/journal.pone.0121227

Cited by 93 publications

(65 citation statements)

References 23 publications

(44 reference statements)

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“…Former studies have looked at the problem from a wide range of perspectives such as certain macro-scale phenomena that emerge as a result of the collective motion of crowds [7], issues affecting the psychological state of individuals in large crowds [8, 9], or the impact of individuals’ social association within a crowd on their behavior [10, 11]. One particular topic to which a great deal of attention has been paid is emergency evacuations of crowds from confined environments.…”

Section: Introductionmentioning

confidence: 99%

How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies

et al. 2016

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How humans resolve non-trivial tradeoffs in their navigational choices between the social interactions (e.g., the presence and movements of others) and the physical factors (e.g., spatial distances, route visibility) when escaping from threats in crowded confined spaces? The answer to this question has major implications for the planning of evacuations and the safety of mass gatherings as well as the design of built environments. Due to the challenges of collecting behavioral data from naturally-occurring evacuation settings, laboratory-based virtual-evacuation experiments have been practiced in a number of studies. This class of experiments faces the traditional question of contextual bias and generalizability: How reliably can we infer humans’ behavior from decisions made in hypothetical settings? Here, we address these questions by making a novel link between two different forms of empirical observations. We conduct hypothetical emergency exit-choice experiments framed as simple pictures, and then mimic those hypothetical scenarios in more realistic fashions through staging mock evacuation trials with actual crowds. Econometric choice models are estimated based on the observations made in both experimental contexts. The models are contrasted with each other from a number of perspectives including their predictions as well as the sign, magnitude, statistical significance, person-to-person variations (reflecting individuals’ perception/preference differences) and the scale (reflecting context-dependent decision randomness) of their inferred parameters. Results reveal a surprising degree of resemblance between the models derived from the two contexts. Most strikingly, they produce fairly similar prediction probabilities whose differences average less than 10%. There is also unexpected consensus between the inferences derived from both experimental sources on many aspects of people’s behavior notably in terms of the perception of social interactions. Results show that we could have elicited peoples’ escape strategies with fair precision without observing them in action (i.e., simply by using only hypothetical-choice data as an inexpensive, practical and non-invasive experimental technique in this context). As a broader application, this offers promising evidence as to the potential applicability of the hypothetical-decision experiments to other decision contexts (at least for non-financial decisions) when field or real-world data is prohibitively unavailable. As a practical application, the behavioral insights inferred from our observations (reflected in the estimated parameters) can improve how accurately we predict the movement patterns of human crowds in emergency scenarios arisen in complex spaces. Fully-generic-in-parameters, our proposed models can even be directly introduced to a broad range of crowd simulation software to replicate navigation decision making of evacuees.

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Section: Introductionmentioning

confidence: 99%

How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies

et al. 2016

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“…For example, structured social interactions (e.g. with friends or family; [39]) could result in the introduction of compromise decisions in heuristics. Staying close to family members or friends may stand in contrast to moving quickly through a narrow bottleneck.…”

Section: Discussionmentioning

confidence: 99%

How cognitive heuristics can explain social interactions in spatial movement

Seitz

Bode

Köster

2016

J. R. Soc. Interface.

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The movement of pedestrian crowds is a paradigmatic example of collective motion. The precise nature of individual-level behaviours underlying crowd movements has been subject to a lively debate. Here, we propose that pedestrians follow simple heuristics rooted in cognitive psychology, such as 'stop if another step would lead to a collision' or 'follow the person in front'. In other words, our paradigm explicitly models individual-level behaviour as a series of discrete decisions. We show that our cognitive heuristics produce realistic emergent crowd phenomena, such as lane formation and queuing behaviour. Based on our results, we suggest that pedestrians follow different cognitive heuristics that are selected depending on the context. This differs from the widely used approach of capturing changes in behaviour via model parameters and leads to testable hypotheses on changes in crowd behaviour for different motivation levels. For example, we expect that rushed individuals more often evade to the side and thus display distinct emergent queue formations in front of a bottleneck. Our heuristics can be ranked according to the cognitive effort that is required to follow them. Therefore, our model establishes a direct link between behavioural responses and cognitive effort and thus facilitates a novel perspective on collective behaviour.

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“…For example, interactions within social groups, such as friends, could be considered [2]. Our framework could also be developed further to permit analysis of wider bottlenecks (an important topic, as wider bottleneck occur frequently and pedestrians appear to preferentially exit through wider bottlenecks [3]).…”

Section: Discussionmentioning

confidence: 99%

Statistical Models for Pedestrian Behaviour in Front of Bottlenecks

Bode

Codling

2016

Traffic and Granular Flow '15

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms Statistical Models for Pedestrian Behaviour in Front of Bottlenecks Nikolai Bode and Edward CodlingAbstract Understanding the movement of human crowds is important for our general understanding of collective behaviour and for applications in building design and event planning. Here, we focus on the flow of a crowd through a narrow bottleneck. We develop statistical models that describe how pedestrian behaviour immediately in front of a bottleneck affects the time lapse between consecutive pedestrians passing through the bottleneck. With this approach we isolate the most important aspects of pedestrian behaviour from a number of candidate models. We fit our models to experimental data and find that pedestrian interactions immediately in front of the bottleneck appear to be less important for the observed time lapses than interactions further away from the bottleneck. Furthermore, we demonstrate how our approach can be used to rigorously compare microscopic pedestrian behaviours across different contexts by fitting the same statistical models to three separate datasets. We suggest that our approach is a promising tool to establish similarities and differences between simulated and real pedestrian behaviour.

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Disentangling the Impact of Social Groups on Response Times and Movement Dynamics in Evacuations

Cited by 93 publications

References 23 publications

How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies

How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies

How cognitive heuristics can explain social interactions in spatial movement

Statistical Models for Pedestrian Behaviour in Front of Bottlenecks

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