A Hybrid and Multiscale Approach to Model and Simulate Mobility in the Context of Public Events

Abstract Organizers of large events have to ensure efficient mobility to guarantee a smooth and secure event course. Traffic and crowd simulations help to predict weak spots on the event's infrastructure. Thus, we propose a hybrid and multiscale approach to provide realistic and computationally efficient simulations. Our approach is able to predict traffic and crowd flow on different spatial resolutions. Events can be modeled on three spatial scales: macroscopic, mesoscopic, and microscopic. Each scale has individual characteristics according to spatial resolution and computational efficiency. Our approach combines these scales to model multimodal aspects of mobilityduring an event course. For the macroscopic scale, a public transport approach, which combines network based optimization with simulation techniques, is presented. This optimization approach for bus transport was integrated into a crowd simulation platform, which simulates the behavior of visitors after having arrived at the event site.

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