Modelling pedestrian behaviour using swarm techniques

Abstract

Modelling pedestrians and groups of people is a highly multidisciplinary technique, given the significant interest it attracts from various branches of science and engineering. This results in many different methodologies that may arise from diverse objectives. The model developed in this work is an agent-based model, in which pedestrian behaviour is defined by a set of forces. Each force models an aspect of pedestrian gait, with the objective of creating a virtual environment to train and test control systems for collaborative robots or autonomous vehicles. To meet the modelling requirements, the system employs various algorithms, such as "flocking", which simulates the coordination and formation of groups, "pathfinding", which enables agents to discover optimal routes within a given space, and algorithms specialized in avoiding walls and dynamic obstacles. These components collaborate to accurately depict how crowds move and react in different environments and situations. Thanks to the modularity of this approach, which facilitates the adjustment and expansion of the components, the developed system can be integrated into various applications, such as simulating non-playable characters (NPCs) in video games or modelling the evacuation of a building.