An in-vehicle virtual driving assistant using neural networks

A methodology has been developed that aids drivers by suggesting a safer following distance, through the use of sensors, and optionally, vehicle to vehicle communication. Given the restricted case where there is no option to swerve into another lane, a Matlab Simulink model varies vehicle dynamics, driver reaction delay, following distance, and initial speeds when a lead vehicle suddenly decelerates. Based upon the likelihood of collision, neural networks suggest a best following distance, and the benefits of reducing reaction delay with adaptive agents are quantified.