1,720,988 research outputs found
A collision avoiding mechanism based on a theory of mind
No full textWe develop a collision avoiding mechanism for a system of individual agents (pedestrians) that move in a crowd trying to reach their different goal points. The agents avoid
collisions on the base of a model of the other agents’ behaviour, a “Theory of Mind”,
which is realised at different levels through an iterative process (the first, or 0, level corresponds to ignore the other agents’ behaviour, level 1 to assume that the other agents
will ignore each other, and so on). We show that our model reproduces some of the more
simple organised behaviours of a system of pedestrians, and perform an evolutionary
study of the parameters of the model (as the perception of the agent’s own size, the
attraction to the goal, the radius and angle of view and the level of theory of mind
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)
Modeling the impact of interaction on pedestrian group motion
No full textMobile social robots aimed at interacting with and assisting humans in pedestrian areas need to understand the dynamics of pedestrian social interaction. In this work, we investigate the effect of interaction on pedestrian group motion by defining three motion models to represent (1) interpersonal-distance, (2) relative orientation and (3) absolute difference of velocities; and model them using a dataset of 12000+ pedestrian trajectories recorded in uncontrolled settings. Our contributions include: (i) Demonstrating that interaction has a prominent effect on the empirical distributions of the proposed joint motion attributes, where increasing levels of interaction lead to more regular behavior (ii) Developing analytic motion models of such distributions and reflect the effect of interaction on model parameters (iii) Detecting the social groups in a crowd with almost perfect accuracy utilizing the proposed models, despite the constant flow direction in the environment which causes unrelated pedestrians to move in a correlated way, and thus makes group recognition more difficult (iv) Estimating the level of intensity with considerable rates utilizing the proposed models
An Automata Based Microscopic Model Inspired by the Clonal Expansion
No full textWe present a simple model based on microscopic automata to describe
the clonal expansion process. The model is based on a repertoire of antigens and T
lymphocytes interacting via the APC cells which present the antigens peptides. Each
cell is represented by an automaton moving randomly on a two dimensional lattice.
We use this simplified model in order to introduce local and spatial considerations
in the mathematical models of clonal expansion based on differential equations, and
at the same time to attempt an analytical interpretation of the results of computer
simulations. For this reason we derive also a mean field theory, whose results are in
good agreement with the solutions of the of microscopic model, at least for situations
that are not too far from equilibrium. This model may be used as the base of a more
realistic one that could follow the clone expansion process on a simplified version of
the lymphatic network
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
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
Walk the Talk: Gestures in Mobile Interaction
No full textThis study aims at describing navigation guidelines and concerning analytic motion models for a mobile interaction robot, which moves together with a human partner. We address particularly the impact of gestures on the coupled motion of this human-robot pair. We pose that the robot needs to adjust its navigation in accordance to its gestures in a natural manner (mimicking human-human locomotion). In order to justify this suggestion, we first examine the motion patterns of real-world pedestrian dyads in accordance to 4 affective components of interaction (i.e. gestures). Three benchmark variables are derived from pedestrian trajectories and their behavior is investigated with respect to three conditions: (i) presence/absence of isolated gestures, (ii) varying number of simultaneously performed (i.e. concurring) gestures, (iii) varying size of the environment. It is observed empirically and proven quantitatively that there is a significant difference in the benchmark variables between presence and absence of the gestures, whereas no prominent variation exists in regard to the type of gesture or the number of concurring gestures. Moreover, size of the environment is shown to be a crucial factor in sustainability of the group structure. Subsequently, we propose analytic models to represent these behavioral variations and prove that our models attain significant accuracy in reflecting the distinctions. Finally, we propose an implementation scheme for integrating the analytic models to practical applications. Our results bear the potential of serving as navigation guidelines for the robot so as to provide a more natural interaction experience for the human counterpart of a robot-pedestrian group on-the-move
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
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