Determining driver phone use leveraging smartphone sensors

Abstract

Driver distraction by mobile phones has been a huge threat that leads to unnecessary accidents and human casualties, especially in hazardous road conditions. In this paper, we address a fundamental but critical issue of phone use during the driver behind the wheel. We propose, design and implement SafeDrive which achieves the goal of automatically determining driver phone use leveraging built-in smartphone sensors sensing driving conditions. We explore GPS and accelerometer sensors on smartphones to collect data, which can sufficiently capture driving conditions. With inputs of these data, we provide an accurate driving condition classification algorithm, that classifies driving conditions into five categories. Based on the classified driving conditions, SafeDrive makes a flexible control of driver phone use. We excessively evaluate the classification accuracy of our SafeDrive in local, highway, traffic jam, and complex conditions, respectively, and the results demonstrate that it can achieve up to 87 % classification accuracy in complex conditions.