PREVENT (PREdiction VEhicular Network Traffic): Accurate predictions for vehicular traffic on networks in urban society
The aim of this project is the developing of a mathematical model to accurately reproduce the traffic evolution in order to improve the drivers' safety and to estimate vehiculars' emissions and pollution produced by traffic jams or stop and go waves.
Investigations about these phenomena suggest to mix different scales and define a new multiscale model, which couples macroscopic and microscopic approaches, combining in a unique system ODEs and PDEs.
The perspective is to study the wellposedness of the problem both from a theoretical and a numerical point of view, including the calibration and the validation of the Euler-Godunov numerical scheme associated since both Eulerian (flux-based) and Lagrangian (GPS) traffic data are available as real measurements.