1,721,276 research outputs found
A mesoscopic model for the effect of density on pedestrian group dynamics
No full textWe introduce a mesoscopic model of pedestrian group behaviour, in which the internal
group dynamics is modelled using a microscopic potential, while the effect of the environment is
modelled using a harmonic term whose intensity depends on a macroscopic quantity, crowd density.
We show that, in order to properly describe the behaviour of 2-person groups, the harmonic term
is directed orthogonally to the walking direction, and its intensity grows linearly with density. We
also show that, once calibrated on 2-person groups, the model correctly predicts the velocity and
spatial extension of 3-person groups in the walking direction, while in order to describe properly
also the abreast extension of 3-person groups a modification in the microscopic group dynamics has
to be introduced. The model also correctly predicts the presence of a bifurcation phenomenon,
namely the emergence of a stable 3-person Λ configuration at high densities, while only the V
formation is stable at low densities
Intrinsic group behaviour II: On the dependence of triad spatial dynamics on social and personal features; and on the effect of social interaction on small group dynamics
Full text linkIn a follow-up to our work on the dependence of walking dyad dynamics on intrinsic properties of the group, we now analyse how these properties affect groups of three people (triads), taking also in consideration the effect of social interaction on the dynamical properties of the group. We show that there is a strong parallel between triads and dyads. Work-oriented groups are faster and walk at a larger distance between them than leisure-oriented ones, while the latter move in a less ordered way. Such differences are present also when colleagues are contrasted with friends and families; nevertheless the similarity between friend and colleague behaviour is greater than the one between family and colleague behaviour. Male triads walk faster than triads including females, males keep a larger distance than females, and same gender groups are more ordered than mixed ones. Groups including tall people walk faster, while those with elderly or children walk at a slower pace. Groups including children move in a less ordered fashion. Results concerning relation and gender are particularly strong, and we investigated whether they hold also when other properties are kept fixed. While this is clearly true for relation, patterns relating gender often resulted to be diminished. For instance, the velocity difference due to gender is reduced if we compare only triads in the colleague relation. The effects on group dynamics due to intrinsic properties are present regardless of social interaction, but socially interacting groups are found to walk in a more ordered way. This has an opposite effect on the space occupied by non-interacting dyads and triads, since loss of structure makes dyads larger, but causes triads to lose their characteristic V formation and walk in a line (i.e., occupying more space in the direction of movement but less space in the orthogonal one)
Gender profiling of pedestrian dyads
No full textIn traffic safety community, behavioral differences between genders
have been attracting considerable attention in recent decades. Various empirical
studies have proven that gender has a significant relation to drivers’, cyclists’ or
pedestrians’ decision making, route choice, rule compliance, as well as risk tak-
ing/perception. However, most studies examine behavior of individuals, and only
very few consider (pedestrian) groups with different gender profiles. Therefore,
this study investigates effect of gender composition of pedestrian dyads on the
tangible dynamics, which may potentially help in automatically understanding
and interpreting higher level behaviors such as decision making. We first propose
a set of variables to represent dyads’s physical/dynamical state. Observing em-
pirical distributions, we comment on the effect of gender interplay on locomotion
preferences. In order to verify our inferences quantitatively, we propose a gender
profile recognition algorithm. Removing one variable at a time, contribution of
each variable to recognition is evaluated. Our findings indicate that height related
variables have a more strict relation to gender, followed by group velocity and
inter-personal distance. Moreover, the “male” effect on dyad motion is found to
somehow diminish when the male is paired with a female
Spatial-size scaling of pedestrian groups under growing density conditions
No full textWe study the dependence on crowd density of the spatial size, configuration, and velocity of pedestrian
social groups. We find that, in the investigated density range, the extension of pedestrian groups in the direction orthogonal to that of motion decreases linearly with the pedestrian density around them, both for two- and three-person groups. Furthermore, we observe that at all densities, three-person groups walk slower than two-person groups, and the latter are slower than individual pedestrians, the differences in velocities being weakly affected by density. Finally, we observe that three-person groups walk in a V-shaped formation regardless of density, with a distance between the pedestrians in the front and back again almost independent of density, although the configuration appears to be less stable at higher densities. These findings may facilitate the development of more realistic crowd dynamics models and simulators
Social group behaviour of triads. Dependence on purpose and gender
Full text linkWe analysed a set of uninstructed pedestrian trajectories automatically tracked in a public area, and we asked a human coder to assess their group relationships. For those pedestrians who belong to the groups, we asked the coder to identify their apparent purpose of visit to the tracking area and apparent gender. We studied the quantitative dependence of the group dynamics on such properties in the case of triads (three people groups) and compared them to the two pedestrian group case (dyads), studied in a previous work. We found that the group velocity strongly depends on relation and gender for both triads and dyads, while the influence of these properties on spatial structure of groups is less clear in the triadic case. We discussed the relevance of these results to the modelling of pedestrian and crowd dynamics, and examined the possibility of the future works on this subject
Social force model with explicit collision prediction
No full textWe introduce a new specification of the social force model in which pedestrians
explicitly predict the place and time of the next collision in order to avoid it. This and other
specifications of the social force model are calibrated, using genetic algorithms, on a set of
pedestrian trajectories, obtained tracking with laser range finders the movement of pedestrians in
controlled experiments, and their performance is compared. The results show that the proposed
method has a better performance in describing the trajectory set
Potential for the dynamics of pedestrians in a socially interacting group
No full textWe introduce a simple potential to describe the dynamics of the relative motion of two pedestrians socially interacting in a walking group. We show that the proposed potential, based on basic empirical observations and theoretical considerations, can qualitatively describe the statistical properties of pedestrian behavior. In detail, we show that the two-dimensional probability distribution of the relative distance is determined by the proposed potential through a Boltzmann distribution. After calibrating the parameters of the model on the two-pedestrian group data, we apply the model to three-pedestrian groups, showing that it describes qualitatively and quantitatively well their behavior. In particular, the model predicts that three-pedestrian groups walk in a V-shaped formation and provides accurate values for the position of the three pedestrians. Furthermore, the model correctly predicts the average walking velocity of three-person groups based on the velocity of two-person ones. Possible extensions to larger groups, along with alternative explanations of the social dynamics that may be implied by our model, are discussed at the end of the paper
On the Influence of Group Social Interaction on Intrusive Behaviours
No full textHaving extensively investigated the influence of social bonding on the spatial dynamics of two-people groups (i.e. dyads), we more recently studied the impact of group social relation on the dynamics of individual pedestrians (i.e. non-groups) in their proximity, and, reciprocally, groups’ reaction to such encounters. In the present work, we extend this analysis to additionally study the effect of the groups’ intensity of social interaction (i.e. talking to each other, performing hand gestures, or maintaining eye contact) in similar situations. specifically, using trajectories of uninstructed pedestrians observed in an ecological setting, we analyse encounters between a dyad annotated with an intensity of interaction ranging from 0 (not interacting) to 3 (strongly interacting) and a non-group coming in the opposite direction. We compute the undisturbed minimum distance between them and compare it to the actual minimum distance. To account for the correlation between the intensity of interaction and the size of a group (i.e. the interpersonal distance between the group’s members), the two distances are normalized by the average size of groups with similar intensities of interaction. In line with our previous findings, we demonstrate that avoidance dynamics is more pronounced for groups with higher levels of interaction, while groups that interact less, or not at all, are more likely to be intruded into
Intrinsic group behaviour: Dependence of pedestrian dyad dynamics on principal social and personal features
Full text linkBeing determined by human social behaviour, pedestrian group dynamics may depend on “intrinsic properties” such as the purpose of the pedestrians, their personal relation, gender, age, and body size. In this work we investigate the dynamical properties of pedestrian dyads (distance, spatial formation and velocity) by analysing a large data set of automatically tracked pedestrian trajectories in an unconstrained “ecological” setting (a shopping mall), whose apparent physical and social group properties have been analysed by three different human coders. We observed that females walk slower and closer than males, that workers walk faster, at a larger distance and more abreast than leisure oriented people, and that inter-group relation has a strong effect on group structure, with couples walking very close and abreast, colleagues walking at a larger distance, and friends walking more abreast than family members. Pedestrian height (obtained automatically through our tracking system) influences velocity and abreast distance, both growing functions of the average group height. Results regarding pedestrian age show that elderly people walk slowly, while active age adults walk at the maximum velocity. Groups with children have a strong tendency to walk in a non-abreast formation, with a large distance (despite a low abreast distance). A cross-analysis of the interplay between these intrinsic features, taking in account also the effect of an “extrinsic property” such as crowd density, confirms these major results but reveals also a richer structure. An interesting and unexpected result, for example, is that the velocity of groups with children increases with density, at least in the low-medium density range found under normal conditions in shopping malls. Children also appear to behave differently according to the gender of the parent
Identification of social relation within pedestrian dyads
Full text linkThis study focuses on social pedestrian groups in public spaces and makes an effort to identify the type of social relation between the group members. As a first step for this identification problem, we focus on dyads (i.e. 2 people groups). Moreover, as a mutually exclusive categorization of social relations, we consider the domain-based approach of Bugental, which precisely corresponds to social relations of colleagues, couples, friends and families, and identify each dyad with one of those relations. For this purpose, we use anonymized trajectory data and derive a set of observables thereof, namely, inter-personal distance, group velocity, velocity difference and height difference. Subsequently, we use the probability density functions (pdf) of these observables as a tool to understand the nature of the relation between pedestrians. To that end, we propose different ways of using the pdfs. Namely, we introduce a probabilistic Bayesian approach and contrast it to a functional metric one and evaluate the performance of both methods with appropriate assessment measures. This study stands out as the first attempt to automatically recognize social relation between pedestrian groups. Additionally, in doing that it uses completely anonymous data and proves that social relation is still possible to recognize with a good accuracy without invading privacy. In particular, our findings indicate that significant recognition rates can be attained for certain categories and with certain methods. Specifically, we show that a very good recognition rate is achieved in distinguishing colleagues from leisure-oriented dyads (families, couples and friends), whereas the distinction between the leisure-oriented dyads results to be inherently harder, but still possible at reasonable rates, in particular if families are restricted to parent-child groups. In general, we establish that the Bayesian method outperforms the functional metric one due, probably, to the difficulty of the latter to learn observable pdfs from individual trajectories
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