3 / 2019-09-30 22:57:50

Correlation Studies on the Cognitive Responses of Distracted Drivers during Conversational Tasks

Distracted Driver behavior, cognitive correlates, electroencephalography (EEG), Secondary driving tasks, support vector machines

Correlation studies between distracted driving and conversational tasks is investigated in this paper. It is a fact that as technology becomes more ubiquitous, we become more dependent on its integration into our daily routines, including driving tasks. With the integration of technology and cars, drivers can become easily distracted with the bombardment of secondary tasks such as cell phone usage, navigation systems, listening to podcasts, etc. We analyzed the cognitive correlations between distracted driving behavior based on electroencephalography (EEG) signals using conversation with co-passengers as a secondary driving task and a linear support vector machine (SVM) for classification. Results indicated that EEG features may provide a salient feature set for detecting driver distraction behavior. Furthermore, when compared with previous classification methods, the accuracy rating improved by 5% using SVM classification. Therefore, from these preliminary results, we posit that cognitive data can be used as a valid feature for classifying distracted driver behaviors. Future studies will further validate this result. The authors suggest, however, that a combination of EEG data with physiological features using SVM classification may provide a more robust system with improved performance accuracy.