Modelling human perception processes in pedestrian dynamics: a hybrid approach

Colombi, Annachiara; Scianna, Marco

doi:10.1098/rsos.160561

Cited by 26 publications

(11 citation statements)

References 36 publications

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“…A further model improvement can be represented by the inclusion of bee gazing direction as a further degree of freedom. In this respect, as done in the case of pedestrians [15], for each insect i, it should be defined a unit vector, say g i (t) = (cos γ i (t), sin γ i (t)) (being γ i the angle between g i itself and the x-axis of the domain), defining the direction of its gaze, cf. Fig.…”

Section: Resultsmentioning

confidence: 99%

A discrete particle model reproducing collective dynamics of a bee swarm

Bernardi

Colombi

Scianna

2018

Computers in Biology and Medicine

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In this article, we present a microscopic discrete mathematical model describing collective dynamics of a bee swarm. More specifically, each bee is set to move according to individual strategies and social interactions, the former involving the desire to reach a target destination, the latter accounting for repulsive/attractive stimuli and for alignment processes. The insects tend in fact to remain sufficiently close to the rest of the population, while avoiding collisions, and they are able to track and synchronize their movement to the flight of a given set of neighbors within their visual field. The resulting collective behavior of the bee cloud therefore emerges from non-local short/long-range interactions. Differently from similar approaches present in the literature, we here test different alignment mechanisms (i.e., based either on an Euclidean or on a topological neighborhood metric), which have an impact also on the other social components characterizing insect behavior. A series of numerical realizations then shows the phenomenology of the swarm (in terms of pattern configuration, collective productive movement, and flight synchronization) in different regions of the space of free model parameters (i.e., strength of attractive/repulsive forces, extension of the interaction regions). In this respect, constraints in the possible variations of such coefficients are here given both by reasonable empirical observations and by analytical results on some stability characteristics of the defined pairwise interaction kernels, which have to assure a realistic crystalline configuration of the swarm. An analysis of the effect of unconscious random fluctuations of bee dynamics is also provided.

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Section: Resultsmentioning

confidence: 99%

A discrete particle model reproducing collective dynamics of a bee swarm

Bernardi

Colombi

Scianna

2018

Computers in Biology and Medicine

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“…Participants tended to pass behind when they looked at the interferer early in the interaction and when the duration of the fixation was long. It has even been shown that people use the gaze behavior of others to adjust their behavior (Dicks, Clashing, O'Reilly, & Mills, 2016;Colombi, Scianna, & Alaia, 2016;Colombi & Scianna, 2017), likely because it informs about the action intentions. Therefore, we focus on understanding how a person interacts with its environment based on its gaze activity.…”

Section: Introductionmentioning

confidence: 99%

Guided by gaze: Prioritization strategy when navigating through a virtual crowd can be assessed through gaze activity

Meerhoff

Bruneau

et al. 2018

Acta Psychologica

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Modelling crowd behavior is essential for the management of mass events and pedestrian traffic. Current microscopic approaches consider the individual's behavior to predict the effect of individual actions in local interactions on the collective scale of the crowd motion. Recent developments in the use of virtual reality as an experimental tool have offered an opportunity to extend the understanding of these interactions in controlled and repeatable settings. Nevertheless, based on kinematics alone, it remains difficult to tease out how these interactions unfold. Therefore, we tested the hypothesis that gaze activity provides additional information about pedestrian interactions. Using an eye tracker, we recorded the participant's gaze behavior whilst navigating through a virtual crowd. Results revealed that gaze was consistently attracted to virtual walkers with the smallest values of distance at closest approach (DCA) and time to closest approach (TtCA), indicating a higher risk of collision. Moreover, virtual walkers gazed upon before an avoidance maneuver was initiated had a high risk of collision and were typically avoided in the subsequent avoidance maneuver. We argue that humans navigate through crowds by selecting only few interactions and that gaze reveals how a walker prioritizes these interactions. Moreover, we pose that combining kinematic and gaze data provides new opportunities for studying how interactions are selected by pedestrians walking through crowded dynamic environments.

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“…This social component can also be modeled mathematically. For example, Colombi and Scianna ( 2017 ) made a first attempt to include the subjective perception of the attractor-state of multiple persons in their model. Although the model did not expand on an agent's action opportunities, it did report the that subjective perception influenced sequential (i.e., localized perception) and simultaneous (i.e., distributed perception) interactions.…”

Section: Discussionmentioning

confidence: 99%

Collision Avoidance With Multiple Walkers: Sequential or Simultaneous Interactions?

Meerhoff

Pettré

Lynch³

et al. 2018

Front. Psychol.

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Collision avoidance between multiple walkers, such as pedestrians in a crowd, is based on a reciprocal coupling between the walkers with a continuous loop between perception and action. Such interpersonal coordination has previously been studied in the case of dyadic locomotor interactions. However, when walking through a crowd of people, collision avoidance is not restricted to dyadic interactions. We examined how dyadic avoidance (1 vs. 1) compared to triadic avoidance (1 vs. 2). Additionally, we examined how the dynamics of a passable gap between two walkers affected locomotor interactions. To this end, we manipulated the starting formation of two walkers that formed a potentially pass-able gap for the other walker. We analyzed the interactions in terms of the evolution over time of the Minimal Predicted Distance and the Dynamics of the Gap, which both provide information about what action is afforded (i.e., passing in front/behind and the pass-ability of the gap). Results showed that some triadic interactions invited for sequential interactions, resulting in avoidance strategies comparable with dyadic interactions. However, some formations resulted in simultaneous interactions where the dynamics of the pass-ability of the gap revealed that the coordination strategy emerged over time through the bi-directional interactions between all walkers. Future work should address which circumstances invite for simultaneous and which for sequential interactions between multiple walkers. This study contributed toward understanding how collision is avoided between multiple walkers at the level of the local interactions.

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Modelling human perception processes in pedestrian dynamics: a hybrid approach

Cited by 26 publications

References 36 publications

A discrete particle model reproducing collective dynamics of a bee swarm

A discrete particle model reproducing collective dynamics of a bee swarm

Guided by gaze: Prioritization strategy when navigating through a virtual crowd can be assessed through gaze activity

Collision Avoidance With Multiple Walkers: Sequential or Simultaneous Interactions?

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