Smart traffic manager for speed harmonisation and stop-and-go waves mitigation dedicated to connected autonomous vehicles
Résumé
The present paper introduces a smart traffic manager, conceived as an algorithm tasked with supervising vehicles. It gathers and disseminates macroscopic traffic flow data among Connected Autonomous Vehicles (CAVs) to facilitate their attainment of string stability. This method combines machine learning techniques and physics-based traffic flow models, establishing a crucial connection between microscopic and macroscopic modeling levels. It enables CAVs to utilize mesoscopic controllers that effectively mitigate stop-and-go waves while ensuring speed harmonization, thereby proving their disturbance string stability. Simulation results demonstrate the efficacy of this proposed solution.
Mots clés
Stop-and-go mitigation
string stability
microscopic traffic control
macroscopic traffic control
mesoscopic controllers
mixed ODE-PDE control systems
freeway traffic congestion
Stop-and-go mitigation string stability microscopic traffic control macroscopic traffic control mesoscopic controllers mixed ODE-PDE control systems freeway traffic congestion
Domaines
AutomatiqueOrigine | Fichiers produits par l'(les) auteur(s) |
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