Patterns of Sequential Off-Road Glances Indicate Levels of Distraction in Automated Driving

Abstract

The safety concerns linked to semi-automated driving – more automation, less driver engagement – could be resolved by real-time driver monitoring with mitigation strategies. To achieve this, this paper analyzed an on-road dataset of sequential off-road glance behaviors under different levels of distraction in an autonomous vehicle trial named CANdrive. Several metrics based on sequential off-road glances were proposed and examined in terms of their capacity of measuring the levels of distraction. These findings are useful for the development of high-resolution driver state monitoring to improve safety in the collaboration between human driver and semi-autonomous vehicle