Preliminary Cognitive Modeling: Comparing Distraction-Based Cyber-Attacks and Alcohol-Related Impairments on Human Drivers

This research investigates the vulnerability and resilience of human cognitive processes in the context of rapidly advancing driving technologies susceptible to multi-modal cyber-attacks. By simulating scenarios where Advanced Driver Assistance Systems (ADAS) are attacked to distract drivers, we aim to understand the decision-making process and cognitive limits affecting safe driving and to devise a systematic approach to assess cognitive impairments. Our simulations of three generic attack models revealed that attacks requiring complex cognitive processing pose greater risks than mere distractions. To assess human driver vulnerabilities in this rapidly evolving technological landscape, we utilized Blood Alcohol Concentration (BAC) levels as a benchmark.