A Comparative Study on Different Measures to Identify Driver States

Road accidents are major issue that creates problem in the society. To overcome the issue, driver behavior and the driving environment has to be monitored regularly and alert the driver before any accident may occur. This could be possible only on analyzing four measures: subjective, behavioral, physiological and vehicle-based. These combined hybrid measures can provide better accuracy on determining various states of driver like normal, drowsy, cognitive and visual inattention. In hybrid measures, physiological measure plays a major role by increasing the accuracy, specificity, sensitivity of the driver state detection. Physiological measures are the signals recorded from various parts of the human body using biosensors to check the internal condition of the driver while driving. These signals can be Electroencephalogram (EEG), Electrocardiogram (ECG), Electro-oculogram (EOG) and Electromyogram (EMG). EEG signals are the brain activity data which corresponds to EEG wave band determines the physical state of the driver. Most researchers have worked on EEG for better accuracy in driver state detection. This paper is one such review on various measures in determining driver states while driving. © 2019 IEEE.