Abstract
Visualising crowds is a key pedestrian dynamics topic, with significant research efforts aiming to improve the current state-of-the-art. Sophisticated visualisation methods are a standard for modern commercial models, and can improve crowd management techniques and sociological theory development. These models often define standard metrics, including density and speed. However, modern visualisation techniques typically use desktop screens. This can limit the capability of a user to investigate and identify key features, especially in real time scenarios such as control centres. Virtual reality (VR) provides the opportunity to represent scenarios in a fully immersive environment, granting the user the ability to quickly assess situations. Furthermore, these visualisations are often limited to the simulation model that has generated the dataset, rather than being source-agnostic. In this paper we implement an immersive, interactive toolkit for crowd behaviour analysis. This toolkit was built specifically for use within VR environments and was developed in conjunction with commercial users and researchers. It allows the user to identify locations of interest, as well as individual agents, showing characteristics such as group density, individual (Voronoi) density and speed. Furthermore, it was used as a data-extraction tool, building individual fundamental diagrams for all scenario agents, and predicting group status as a function of local agent geometry. Finally, this paper presents an evaluation of the toolkit made by crowd behaviour experts.
Highlights
Crowd simulations have become increasingly important over the last decades in multiple applications
Crowd analysis software [1] exists for architects and engineers to visually and quantitatively analyse crowd movement datasets to ensure that public spaces and buildings have efficient evacuation plans and enable a smooth flow of pedestrians
Modern crowd analysis software packages have produced high quality visualisation engines, but these are typically limited to displaying the outputs from their own simulation model, rather than being source-agnostic
Summary
Crowd simulations have become increasingly important over the last decades in multiple applications (e.g., building evacuation, entertainment and surveillance systems). VR provides the opportunity to completely remove the limitation in how much data a user can observe at any time, while simultaneously allowing the user to reorient and choose which data streams to observe In evacuation planning, this tool can be used to analyse choke points such as doorways or corridors to see if at any point in the simulation these areas are subjected to dangerous levels of density or if the crowd is able to flow smoothly. This tool is used to identify all groups in the crowd, changing their tonality so they stand out, making for easier identification This toolkit was developed to provide functionality to researchers and practitioners, who could adapt and implement their own required models. Future work will develop this toolkit to include state-of-the-art theories surrounding social identification
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