| KEYWORD |
Distributed machine learning on vehicles
Parole chiave MACHINE LEARNING, VEHICULAR NETWORKS
Riferimenti CLAUDIO ETTORE CASETTI, PAOLO GIACCONE
Gruppi di ricerca Telecommunication Networks Group
Tipo tesi DEVELOPMENT, SIMULATION
Descrizione Given the plethora of sensors with which vehicles are equipped, today’s automated vehicles already generate large amounts of data that enable data-driven solutions for vehicle control, safety and comfort, as well as to effectively implement convenience applications.
The goal of this thesis work is to develop a custom framework on the CARLA simulator (https://carla.org/) leveraging SUMO traces of vehicles, and other transportation means. The framework would exploit the use of different technologies (i.e., camera, lidar, radar, IMU, etc.) and distributed machine learning techniques (e.g., federated learning) in order to develop object detection applications focused on crowdsensing tasks directly from the vehicles video cameras.
Conoscenze richieste Background on machine learning
Linux
Excellent programming in Python
Scadenza validita proposta 20/12/2023
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