Comparison of Experienced and Novice Drivers' Visual and Driving Behaviors during Warned or Unwarned Near-Forward Collisions.

Forward collision warning systems (FCWSs) monitor the road ahead and warn drivers when the time to collision reaches a certain threshold. Using a driving simulator, this study compared the effects of FCWSs between novice drivers (unlicensed drivers) and experienced drivers (holding a driving license for at least four years) on near-collision events, as well as visual and driving behaviors. The experimental drives lasted about six hours spread over six consecutive weeks.

A neuroergonomics approach to driver's cooperation with Lane Departure Warning Systems.

Lane Departure Warning Systems (LDWS) are automation that warn drivers in case of immediate lane departure. While LDWS are associated with increased road safety, little is known about the neural aspects of the cooperation between an LDWS and the driver behind the wheel. The present study addresses this issue by combining fMRI and driving simulation for experienced and novice drivers.

Visual and steering behaviours during lane departures: a longitudinal study of interactions between lane departure warning system, driving task and driving experience.

Lane Departure Warning Systems (LDWS) generate a warning in case of imminent lane departure. LDWS have proven to be effective and associated human-machine cooperation modelled. In this study, LDWS acceptance and its impact on visual and steering behaviour have been investigated over 6 weeks for novice and experienced drivers.

The cortical thickness of the area PF of the left inferior parietal cortex mediates technical-reasoning skills.

Most recent research highlights how a specific form of causal understanding, namely technical reasoning, may support the increasing complexity of tools and techniques developed by humans over generations, i.e., the cumulative technological culture (CTC).

Model-based estimation of the state of vehicle automation as derived from the driver's spontaneous visual strategies.

When manually steering a car, the driver's visual perception of the driving scene and his or her motor actions to control the vehicle are closely linked. Since motor behaviour is no longer required in an automated vehicle, the sampling of the visual scene is affected. Autonomous driving typically results in less gaze being directed towards the road centre and a broader exploration of the driving scene, compared to manual driving.

Estimating the out-of-the-loop phenomenon from visual strategies during highly automated driving.

During highly automated driving, drivers no longer physically control the vehicle but they might need to monitor the driving scene. This is true for SAE level 2, where monitoring the external environment is required; it is also true for level 3, where drivers must react quickly and safely to a take-over request. Without such monitoring, even if only partial, drivers are considered out-of-the-loop (OOTL) and safety may be compromised.

Looking at the Road When Driving Around Bends: Influence of Vehicle Automation and Speed.

When negotiating bends car drivers perform gaze polling: their gaze shifts between guiding fixations (GFs; gaze directed 1-2 s ahead) and look-ahead fixations (LAFs; longer time headway). How might this behavior change in autonomous vehicles where the need for constant active visual guidance is removed? In this driving simulator study, we analyzed this gaze behavior both when the driver was in charge of steering or when steering was delegated to automation, separately for bend approach (straight line) and the entry of the bend (turn), and at various speeds. The analysis of gaze distributions relative to bend sections and driving conditions indicate that visual anticipation (through LAFs) is most prominent before entering the bend.