Development of Model to Identify the Factors for Risky Driving Behaviour by Analyzing EEG Waveform

Traffic accidents are caused due to the main three parameters as traffic environment, driver and vehicle. As driving is a complex behavior that can be affected by an individual psychological state, emotions and environment. For safe driving and eliminating risky driving of an individual it has become necessary for estimation of psychological state of the driver. In this method, the mental status of driver is measured by EEG Waves by recording electrical activity of the brain. By using EEG headset that senses the electrical signal and transmits to the computer wirelessly through Bluetooth which reduces the number of sensor and eliminated the use of liquid on scalp while measuring EEG waves. The extracted brainwaves are then used to estimate different brain features like attention, distraction and eye blinking. The brainwaves are trained by backpropagation neural network. And whenever the risky situation occurs or when driver seems to be distracted from driving, the alarm blows. It helps a lot to eliminate the risky situation ensures safe driving.