Highlights We challenge the static goal assumption by proposing a novel parametric distance map. We estimate a dynamic goal-based distance map using likelihood-based optimisation methods. The results indicate that pedestrians’ target change as they approach an exit.

    Abstract Identifying effective strategies describing crowd dynamics is crucial to enhance simulations of pedestrians for crowded event planning and management. Various modelling solutions have been proposed to describe how people try to exit from a built environment in normal and emergency. Several of these solutions rely on the use of distance maps or floor fields to account for the positions of existing goals and the location of obstacles to avoid. To date, distance maps are assumed to be static (they do not vary over time) and that pedestrians aim at the actual central coordinate of a door. In this work, we challenge the static goal assumption by proposing a novel parametric distance map which is variable depending on the polar coordinates defining the position of a pedestrian having the centre of an exit as the origin (i.e., the distance of the pedestrian and an angle between its direction and the perpendicular to the exit). In this work, we investigate what pedestrians head for while trying to reach an exit. Different parametric solutions are proposed and calibrated using likelihood-based optimisation methods with over 9000 trajectories of individual pedestrians who navigated through an indoor university atrium building to reach several exits. The results highlight good performance for this modelling approach: pedestrians head for targets in front of an exit when they are away from it, and their targets shift behind the exit as they get closer to it, (i.e., distance impact) while their angle does not have impact on this process. The proposed dynamic goal-based distance map can be applied for future pedestrian simulations for crowded event planning and management.


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    Titel :

    What do we head for while exiting a room? a novel parametric distance map for pedestrian dynamic simulations


    Beteiligte:


    Erscheinungsdatum :

    2023-09-06




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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