Semantic Traffic Data Analysis for a Local Leader Election Algorithm (LLEA)

Roua Elchaama, Rima Kilany Chamoun, Baudouin Dafflon, Yacine Ouzrout
2020 European Conference on Artificial Intelligence  
MASCAT is a research-based road traffic simulator. In this paper, we propose a plugin for MASCAT. The aim of this proposition is to provide a semantic data analysis for the simulators Multi-Agent System (MAS). The plugin introduce an interpretation phase during vehicle to vehicle communication (V2V). It will allow connected vehicles to make the most efficient behavioral decisions based on the state of surrounding environment. We designed a semantic web ontology to describe traffic data and
more » ... orate behavioral decisions. Our semantic plugin can link, structure, analyze MASCATs traffic data and can also optimize the Local Leader Election Protocol. Indeed, we demonstrate that a small percentage of connected cars can ensure traffic regulation specially in a shifting environment.
dblp:conf/ecai/ElchaamaCDO20 fatcat:26zgr4v7r5dhroenai753xp4pe