A meshfree particle method for a vision-based macroscopic pedestrian model
N.K. Mahato, A. Klar, S. Tiwari

TL;DR
This paper introduces a meshfree particle numerical method for a macroscopic pedestrian model based on vision, focusing on collision avoidance, and compares its efficiency with existing models like the social force model.
Contribution
It presents a novel meshfree particle approach for solving a vision-based pedestrian flow model, emphasizing computational efficiency and comparison with established models.
Findings
The meshfree method effectively simulates pedestrian dynamics.
The model accurately predicts collision avoidance behavior.
The approach reduces computation time compared to traditional models.
Abstract
In this paper we present numerical simulations of a macroscopic vision-based model [1] derived from microscopic situation rules described in [2]. This model describes an approach to collision avoidance between pedestrians by taking decisions of turning or slowing down based on basic interaction rules, where the dangerousness level of an interaction with another pedestrian is measured in terms of the derivative of the bearing angle and of the time-to-interaction. A meshfree particle method is used to solve the equations of the model. Several numerical cases are considered to compare this model with models established in the field, for example, social force model coupled to an Eikonal equation [3]. Particular emphasis is put on the comparison of evacuation and computation times. References 1. Degond P., Appert-Rolland C., Pettere J., Theraulaz G., Vision-based macroscopic pedestrian…
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Taxonomy
TopicsEvacuation and Crowd Dynamics · Landslides and related hazards · Fluid Dynamics Simulations and Interactions
