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An Analytical Framework for Modeling and Synthesizing Malicious Attacks on ACC Vehicles
The primary findings indicate that strategically synthesized candidate attacks can cause significant disruptions to the traffic flow while altering the driving behavior of ACC vehicles in a subtle fashion to remain stealthy, which is supported by a series of analytical results.
Socially Compliant Control of Autonomous Vehicles with Application to Eco-Driving
Control design of autonomous vehicles (AVs) has mostly focused on achieving a prespecified goal for an individually controlled AV or for a swarm of cooperatively controlled AVs.
Detecting stealthy cyberattacks on adaptive cruise control vehicles: A machine learning approach
A novel generative adversarial network (GAN)-based anomaly detection model is proposed for real-time identification of such attacks using vehicle trajectory data.
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