Vehicle Driver Monitoring, VDM.

Purpose and goal

The aim was to find methods to measure, focusing on physiological measures, sleepiness and cognitive distraction and to study the effect on driver behaviour. Several experiments were performed that produced significant new knowledge on measuring the states and the effect on driving. In particular physiological measures, effect of contextual and individual factors and automatic detection using machine learning methods were studied. In cooperation with an in-house Volvo Cars project specifications for a measurement platform were defined. This platform was used in the project.

Expected results and effects

The results showed that physiological measures correlated with sleepiness and cognitive load but were also affected by other states. The results also showed that context, both individual and contextual, had a large impact on driver behaviours, measures and experiences. The research has increased the understanding of sleepiness and cognitive distraction, e.g. how to design experiments, measure and analyse these driver states. The knowledge has been published and will be used as base for further research on driver states and product development.

Planned approach and implementation

Initially a literature review was performed, e.g. of sleepiness and cognitive distraction. During the design of the experiments the research questions were refined based on the advances in the research of sleepiness and cognitive distraction to gain as much knowledge as possible within the project. All experiments were performed in a driving simulator for high experimental control. Data was stored in a database after pre-processing. One doctoral student was planned and another was added during the project.