8 papers
MINT-V2X: A Mobility-Integrated Network Trajectory Dataset for Predictive Resource Management
Abdullah Anjum, Abdolazim Rezaei, Mehdi Sookhak
Vehicle-to-Everything (V2X) communication systems are based on datasets that not only contain vehicle trajectory data but also wireless network parameters with a realistic level of…
Parameter Efficient Hybrid Transformer (PEHT) for Network Traffic Prediction via Dynamic Urban Congestion Integration
Abdolazim Rezaei, Mehdi Sookhak, Mahboobeh Haghparast
Accurate network traffic prediction is a critical element for efficient resource allocation in dynamic urban cellular networks. However, prediction remains challenging because netw…
Privacy-Preserving in Connected and Autonomous Vehicles Through Vision to Text Transformation
Abdolazim Rezaei, Mehdi Sookhak, Ahmad Patooghy +2
Intelligent Transportation Systems (ITS) rely on a variety of devices that frequently process privacy-sensitive data. Roadside units are important because they use AI-equipped came…
Joint UAV-UGV Positioning and Trajectory Planning via Meta A3C for Reliable Emergency Communications
Ndagijimana Cyprien, Mehdi Sookhak, Hosein Zarini +2
Joint deployment of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has been shown to be an effective method to establish communications in areas affected by di…
PEFT-DML: Parameter-Efficient Fine-Tuning Deep Metric Learning for Robust Multi-Modal 3D Object Detection in Autonomous Driving
Abdolazim Rezaei, Mehdi Sookhak
This study introduces PEFT-DML, a parameter-efficient deep metric learning framework for robust multi-modal 3D object detection in autonomous driving. Unlike conventional models th…
RL-MoE: An Image-Based Privacy Preserving Approach In Intelligent Transportation System
Abdolazim Rezaei, Mehdi Sookhak, Mahboobeh Haghparast
The proliferation of AI-powered cameras in Intelligent Transportation Systems (ITS) creates a severe conflict between the need for rich visual data and the right to privacy. Existi…