The user interface based on Electromyography analysis to takeover Driving mode in autonomous vehicle

Abstract

In this paper, we demonstrates our Human Machine Interface through the Electromyography (EMG) analysis especially for autonomous vehicle's Driving mode takeover. Preprocessed EMG data used for classification of each proposed gesture in real-time with un-vehicle environment. This paper contains some argument about the takeover constrains while the vehicle is moving in speed for its and driver safety. Some of constrains are related with the status of the driver and the current vehicle status. Electromyography was analyzed through the recoding tools we have built. Pre-processing of Electromyography rectifies the EMG force per each cells of sensor. Statistical analysis helped to develop the gesture classifier for autonomous vehicle.