Proposed System Based on EEG and VSL to Detect Drowsiness and Curb Accidents

TLDR: A system which would efficiently detect drowsiness by integrating the real-time EEG method of detection and the concept of individual-level Hypothesized Variable Speed Limit (HVSL) is proposed.

Abstract: Drowsiness is one of the most prevalent causes of car accidents, especially after drunk driving. There have been many studies to detect drowsiness while driving using different approaches. We propose a system which would efficiently detect drowsiness by integrating the real-time EEG method of detection and our concept of individual-level Hypothesized Variable Speed Limit (HVSL). By studying the power spectral density obtained from the driver’s EEG and the overall duration of the persistence of the alpha waves, it can be determined whether the driver is going into a state of drowsiness or not. In response to elongated time periods of persisting alpha waves, an alarm will be put off to alert the driver. The HVSL module would recommend an appropriate speed depending on environmental conditions as well as drowsy level, thus monitoring the vehicle speed. Hence, drowsiness detection can be combined with HVSL system to mitigate the chances of potential accidents.