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

Project Description:
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.

Research Directions:

1. CAV Speed Control under GNSS Attacks
   Investigate the impact of GPS jamming and spoofing on CAV speed control applications, developing strategies that ensure fuel-efficient deceleration and uninterrupted cruising while maintaining traffic flow efficiency.
2. Simulation and Network-level Evaluation
   Implement detection and mitigation strategies in MATLAB for real-time CAV control and scale evaluations to network-level traffic simulations using the INTEGRATION platform to assess overall performance and resilience.
3. Multi-sensor Mitigation using OIRS
   Explore Optical Intelligent Reflecting Surfaces to provide authenticated positioning and timing data from roadside units, allowing the Eco-CACC-I controller to gracefully degrade and reweight sensor inputs when GNSS integrity is compromised.

US DOT Priorities:
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.

Outputs:

• Develop and validate optimal speed control strategies for multiple vehicle powertrains under GPS spoofing and jamming.
• Implement detection methods using signal anomalies, estimation residuals, and cooperative V2X data.
• Demonstrate mitigation strategies via OIRS-enabled dual-channel communication systems.
• Scale real-time control strategies to network-level simulations for broader traffic efficiency evaluation.

Expected Audience:
This research will be of interest to CAV navigation system designers, CAV application developers, transportation system researchers, and members of the CARNATIONS External Advisory Board, who will be encouraged to provide feedback and collaborate throughout the project.

Outcomes/Impacts:
CAVs have the potential to reduce congestion, emissions, and improve safety. The goal of this project is to demonstrate how multi-sensor integration and resilient control strategies can maintain accurate vehicle state information at the bandwidth and sample rates required for effective vehicle control, even under GPS spoofing and jamming conditions.

Final Research Report:
Upon completion of the project, a link to the final report will be provided.

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