Framework for classifying how network slicing policies impact Intelligent Transportation Systems (ITS) applications, enabling dynamic resource allocation in vehicular networks.

DeepTrafficQ is a reinforcement learning-based traffic signal control system that uses Deep Q-Networks (DQN) to minimize vehicle waiting times at a 4-way intersection. By leveraging Q-learning with experience replay and a convolutional neural network (CNN), the agent dynamically adjusts traffic light phases to optimize traffic flow.

Tesi di Laurea Triennale in Informatica, Università degli Studi di Padova, A.A. 2019-2020.

AI-powered highway traffic shockwave detection and prediction system using MT-STNet deep learning model with real-time monitoring and intelligent decision support