Cybersecurity for mixed-autonomy traffic: detection and localization of compromised vehicles

Principal Investigator(s):

Raphael Stern, Assistant Professor, Civil, Environmental and Geo-Engineering

Project summary:

In this project, researchers investigated the potential impact of stealthy cyberattacks on automated or partially automated vehicles and considered how they will influence traffic flow and fuel consumption. Specifically, researchers defined stealthy cyberattacks on automated vehicles where driving behavior deviates only slightly from normal driving behavior. The research team used simulation analysis to consider different cyberattacks and investigate their impact on traffic flow and aggregate fuel consumption of all vehicles in the traffic flow. Researchers found that such attacks, while difficult to detect, may substantially degrade traffic flow and, to a lesser extent, vehicle emissions across the traffic flow.

Project details: