Title: Automatic Classification of Driving Conditions for the Detection of Driver-Induced Steering Oscillation

Year of Publication: Nov - 2016
Page Numbers: 88-95
Authors: Dipak G. Sharma, Ivan Tanev, Katsunori Shimohara
Conference Name: The Second International Conference on Electronics and Software Science (ICESS2016)
- Japan


We proposed an approach of automatically identifying two different driving conditions – driving on a straight, and cornering, respectively, by a cognitively distracted human driver in TORCS environment. The cognitive distraction of the driver results in driver-induced steering oscillations. In order to detect these steering oscillations – e.g., by analysing the magnitude of power spectra of lateral acceleration – it is crucial to automatically distinguish the driving condition so that variable threshold – corresponding to these different driving conditions – could be applied. Our experimental results indicate that a specific low pass filter implemented as a sliding window averaging on the discrete sampled values of lateral acceleration identifies the driving conditions adequately.