During automated driving at SAE level 2 or level 3, the driver’s role changes from an active driver to a fallback-ready driver, whose mental state must still be prepared for a takeover request (TOR) when prompted. This preliminary study investigates the sensitivity of eye-movement measures in assessing the mental state of fallback-ready drivers in automated driving. The mental state of a fallback-ready driver is considered to be defined by two major factors: the state of workload imposed by non-driving related task, and the state of drowsiness. A visual workload (using a tablet computer), a non-visual workload (performing a cognitive task), as well as a state of drowsiness (after a prolonged interval of automated driving) were induced, and their effects on driving performance were studied in a high-fidelity driving simulator. The number and size of saccadic eye-movements, as well as the durations of eyeblinks, were measured by using electrooculography. The results indicate that the percentage of small saccades was sensitive to both visually and non-visually loaded states and can therefore be used to distinguish the two types of workload, and eyeblink duration was sensitive to the state of drowsiness. These results should be helpful in understanding the fallback-ready driver’s mental state in automated driving, and can provide a new perspective on the selection of input features in developing camera-based driver state monitoring systems.
Assessing the Mental States of Fallback-Ready Drivers in Automated Driving by Electrooculography
2019-10-01
302231 byte
Conference paper
Electronic Resource
English
Fallback Strategy for Level 4+ Automated Driving System*
IEEE | 2019
|Partially automated driving as a fallback level of high automation
Automotive engineering | 2013
|Assessing Truck Drivers’ and Fleet Managers’ Opinions Towards Highly Automated Driving
Springer Verlag | 2016
|