Abstract
The take-over process from automatic to manual control plays a critical role in the level 3 automated driving defined by the Society of Automotive Engineering, and the driver’s state before this process has a great influence on the take-over quality. Therefore estimation and tracking of the driver’s attention level in non-driving activities could facilitate the intelligence of the take-over process to improve vehicle safety and operational efficiency. Considering playing a tablet as a specific non-driving activity, this chapter introduces a novel approach to characterise the driver’s attention level using a sliding window correlation analysis on the 3D movements of the driver’s head and tablet. The correspondence between the attention level and the estimated correlation strength with time delay is established by applying the support vector machine method. The experiment results on both stationary and non-stationary data demonstrate that the correlation of movements has the potential to act as a proxy measurement of the driver attention level if this relative movement exists.
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