11 papers
Monitoring physical distancing for crowd management: real-time trajectory and group analysis
Caspar A. S. Pouw, Federico Toschi, Frank van Schadewijk +1
Physical distancing, as a measure to contain the spreading of Covid-19, is defining a "new normal". Unless belonging to a family, pedestrians in shared spaces are asked to observe…
Controlling Rayleigh-Bénard convection via Reinforcement Learning
Gerben Beintema, Alessandro Corbetta, Luca Biferale +1
Thermal convection is ubiquitous in nature as well as in many industrial applications. The identification of effective control strategies to, e.g., suppress or enhance the convecti…
Pedestrian orientation dynamics from high-fidelity measurements
Joris Willems, Alessandro Corbetta, Vlado Menkovski +1
We investigate in real-life conditions and with very high accuracy the dynamics of body rotation, or yawing, of walking pedestrians - an highly complex task due to the wide variety…
High-statistics modeling of complex pedestrian avoidance scenarios
Alessandro Corbetta, Lars Schilders, Federico Toschi
Quantitatively modeling the trajectories and behavior of pedestrians walking in crowds is an outstanding fundamental challenge deeply connected with the physics of flowing active m…
Measurement and analysis of visitors' trajectories in crowded museums
Pietro Centorrino, Alessandro Corbetta, Emiliano Cristiani +1
We tackle the issue of measuring and analyzing the visitors' dynamics in crowded museums. We propose an IoT-based system -- supported by artificial intelligence models -- to recons…
Deep learning velocity signals allows to quantify turbulence intensity
Alessandro Corbetta, Vlado Menkovski, Roberto Benzi +1
Turbulence, the ubiquitous and chaotic state of fluid motions, is characterized by strong and statistically non-trivial fluctuations of the velocity field, over a wide range of len…