Etudiant : RAFI REDA

Filière : Master Systèmes Intelligents et Décisionnels (MSID)

Encadrant : Pr. AZOUGH AHMED

Annèe : 2021

Résumé : The development of self-driving vehicles has gained a lot of attention due to technology development. Autonomous vehicles depend considerably in regards to their sensors to precise the acuity of the fencing environment. Nevertheless, the data, which a vehicle uses, are confined to that from its singular sensors, and in many cases, the data sharing between vehicles and/or edge servers are defined by the available network bandwidth and the stringent real-time constraints of autonomous driving applications. In this work, we are going to address some of the challenges this area faces and propose a joint performance perception and motion prediction from 3D point clouds to achieve better object detection precision. Keywords: Autonomous driving, Connected Autonomous Vehicle, Edge Computing