Assessing the Energy Impacts of Cyberattacks on Low-Level Automated Vehicles
Author(s):
Raphael Stern, Tianyi Li, Benjamin Rosenblad, Mingfeng Shang
August 2023
Report no. CTS 23-05
Projects:
Cybersecurity for mixed-autonomy traffic: detection and localization of compromised vehicles
Topics:
In this study, we investigate the potential impact of stealthy cyberattacks on automated or partially automated vehicles, and consider how they will influence traffic flow and fuel consumption. Specifically, we define stealthy cyberattacks on automated vehicles where driving behavior deviates only slightly from normal driving behavior. We use simulation analysis to consider different cyberattacks, and investigate their impact on traffic flow and aggregate fuel consumption of all vehicles in the traffic flow. We find that such attacks, while difficult to detect, may substantially degrade traffic flow, and, to a lesser extent, vehicle emissions across the traffic flow.
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