Updated: 16 days ago
Deadline: 23 Apr 2021
The accurate prediction of the flow dynamics and properties of a crowd of pedestrians in complex environments is critical for strategic urban planning but also for safety protocols in the presence of a pathogen, i.e. access to buildings, infrastructures etc. Pedestrian models rely on a stochastic particle-based description of human interaction, where individuals are regarded as “particles” interacting via different competing forces (i.e. short-range contact repulsion and friction, long-range social distancing) and a target desired velocity which is environment-specific. In the extraordinary health-care situation posed by COVID-19, a mathematical and numerical analysis of pedestrian flow combined with new pathogen diffusion models is a useful tool to predict the spreading of the disease in urban scenarios for control/mitigation purposes. The target of this project is to formulate a novel particle-based simulation framework to model pedestrian dynamics fully coupled with stochastic infection-transmission models and apply it to urban situations characterized by the presence of large groups of people in motion.
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