Extracting rules to detect cognitive distractions through driving simulation

In our study, we generate rules to determine whether or not a driver is cognitively distracted, using collected data about the driver’s eye movements and driving data by Inductive Logic Programming (ILP). We assigned a mental arithmetic task to the research participants to cause cognitive distraction and then learned the rules of the cognitive distraction using the cognitively distracted state as positive examples by ILP. Using the generated rules, we hope to reduce car-driving risks by providing advice or urging caution using voice utterance when distracted driving is detected.