Abstract
Abstract. Point clouds serve as the raw material for various models, such as Building Information Models (BIM). In this work, we investigate the reconstruction steps needed to create models that can be utilized directly for agent-based simulations. The input data for the reconstruction is captured with an indoor mobile mapping system. To show the prominence of this idea, we run social distancing and evacuation simulations on the reconstructed models. The simulations are run with multiple agents using a vision-based pedestrian model and A*-based path finding algorithm. The limitations of this approach are discussed. The video of the simulation is shared with the audience.Link to the video: https://youtu.be/r2D3IxXt7Ls
Highlights
IntroductionThe question in exceptional conditions boils down to how can living continue while the fear of illness is present
Social distancing is more important than ever
Our contribution lies in investigating the shortcut between a 3D point cloud and a functional agent-based simulation
Summary
The question in exceptional conditions boils down to how can living continue while the fear of illness is present. These questions may be answered with realistic planning using measured data. Such planning allows for optimizing between various factors, such as space, time, and the number of people. The outcome of the scanning is a three-dimensional (3D) point cloud. We refer to the simulation environment here as a simulation ’sand-box’. These sand-box simulations can be used to find answers to questions related to social distancing and evacuation
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