Take over! A video-clip study measuring attention, situation awareness, and decision-making in the face of an impending hazard

In highly automated driving, drivers occasionally need to take over control of the car due to limitations of the automated driving system. Research has shown that visually distracted drivers need about 7 s to regain situation awareness (SA). However, it is unknown whether the presence of a hazard affects SA. In the present experiment, 32...

Beyond mere take-over requests: The effects of monitoring requests on driver attention, take-over performance, and acceptance

In conditionally automated driving, drivers do not have to monitor the road, whereas in partially automated driving, drivers have to monitor the road permanently. We evaluated a dynamic allocation of monitoring tasks to human and automation by providing a monitoring request (MR) before a possible take-over request (TOR), with the aim to...

Validity and reliability of naturalistic driving scene categorization Judgments from crowdsourcing

A common challenge with processing naturalistic driving data is that humans may need to categorize great volumes of recorded visual information. By means of the online platform CrowdFlower, we investigated the potential of crowdsourcing to categorize driving scene features (i.e., presence of other road users, straight road segments, etc.) at...

How much time do drivers need to obtain situation awareness? A laboratory-based study of automated driving

Drivers of automated cars may occasionally need to take back manual control after a period of inattentiveness. At present, it is unknown how long it takes to build up situation awareness of a traffic situation. In this study, 34 participants were presented with animated video clips of traffic situations on a three-lane road, from an...

Human factors of transitions in automated driving: A general framework and literature survey

The topic of transitions in automated driving is becoming important now that cars are automated to ever greater extents. This paper proposes a theoretical framework to support and align human factors research on transitions in automated driving. Driving states are defined based on the allocation of primary driving tasks (i.e., lateral control,...