精东影业

Current Research Projects

Project 1: Improving GNSS Resiliency Using Edge AI Solutions 

Investigators: Prof. Moussa Ayyash, Dr. Sufyan Almajali, Dr. Anand Singh, and Mr. Abedl-Rahman Almodawar

Summary: This project will leverage Edge Artificial Intelligence (Edge AI) to enhance the resilience of Global Navigation Satellite Systems (GNSS) in challenging environments. By deploying AI algorithms and models on edge devices, the project aims to reduce reliance on cloud infrastructures, particularly in dense blockage scenarios where GPS signals are weak or disrupted. The goal is to explore how bringing intelligence to the edge node can improve GNSS performance and resiliency in these difficult conditions.

This project aligns with CARNATIONS's mission of reducing transportation cybersecurity risks.

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Project 2: Develop and Test Optimal Speed Control Strategies for Connected and Automated Vehicles under GPS Jamming and Spoofing

Investigators: Prof. Moussa Ayyash (精东影业) and Prof. Hesham Rakha (Virginia Tech)

Summary: While GNSS provides absolute position information in transportation systems, GPS jamming and spoofing can compromise Connected and Automated Vehicles (CAVs) at signalized intersections. This project develops and evaluates optimal speed control strategies for CAVs under such compromised positioning conditions, building on the Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I) framework. The project will generate real-time, fuel-efficient trajectories and enhance traffic flow efficiency within control zones, while leveraging detection and mitigation strategies to maintain GNSS integrity. These strategies include signal anomaly detection, estimation residual monitoring, cooperative V2X cross-checks, and novel Optical Intelligent Reflecting Surfaces (OIRS) enabling dual-channel communication via RF and visible light.

This project addresses the US DOT research priority area of Reducing Transportation System Cybersecurity Risks. Specifically, it develops robust CAV speed control strategies and detection/mitigation frameworks that maintain safety, mobility, and fuel efficiency under compromised GNSS conditions.