Real-time Traffic Data Collection Using The Two Simulators SUMO and OMNeT++

Riham Farhani (1, 2) , Yassin El Hillali (1, 2) , Atika Rivenq (1, 2) , Abdelwahed Hajjaji (3) , Yahia Boughaleb (4)

1 IEMN - Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520
2 COMNUM - IEMN - COMmunications NUMériques - IEMN
3 ENSA El-Jadida (.)
4 University Hassan II [Casablanca]

Electric vehicles (EVs) are one of the encouraging solutions to improve energy efficiency and reduce carbon emissions in the transportation sector. Today, electric vehicles have experienced massive growth that has brought multiple benefits to the energy and transportation sectors, but they can also affect the stability of the smart grid, consuming more energy, especially during peak hours. In such deployments, energy efficiency and optimal energy distribution are among the most important constraints to be considered, to meet the energy demand of the electric vehicle. Indeed, traffic conditions have an impact on the energy consumption of electric vehicles. In this regard, it is essential to have real-time information on the traffic elements that offer flexibility in the management of the load. Faced with this challenge, the ITS-G5 technology is a promising solution that allows us to collect and transmit efficiently the traffic information in real-time and for this purpose, our work is validated by the two simulators SUMO and OMNeT++.

Domaines: Sciences de l'ingénieur [physics]

Riham Farhani, Yassin El Hillali, Atika Rivenq, Abdelwahed Hajjaji, Yahia Boughaleb. Real-time Traffic Data Collection Using The Two Simulators SUMO and OMNeT++. 2022 11th International Symposium on Signal, Image, Video and Communications (ISIVC), May 2022, El Jadida, Morocco. pp.1-4, ⟨10.1109/ISIVC54825.2022.9800716⟩. ⟨hal-03707030⟩