Reliable but multi-dimensional cognitive demand in operating partially automated vehicles: implications for real-world automation research.

The reliability of cognitive demand measures in controlled laboratory settings is well-documented; however, limited research has directly established their stability under real-life and high-stakes conditions, such as operating automated technology on actual highways. Partially automated vehicles have advanced to become an everyday mode of transportation, and research on driving these advanced vehicles requires reliable tools for evaluating the cognitive demand on motorists to sustain optimal engagement in the driving process. This study examined the reliability of five cognitive demand measures, while participants operated partially automated vehicles on real roads across four occasions.

This Is Your Brain on Autopilot: Neural Indices of Driver Workload and Engagement During Partial Vehicle Automation.

Objective: This research explores the effect of partial vehicle automation on neural indices of mental workload and visual engagement during on-road driving.

Background: There is concern that the introduction of automated technology in vehicles may lead to low driver stimulation and subsequent disengagement from the driving environment. Simulator-based studies have examined the effect of automation on a driver's cognitive state, but it is unknown how the conclusions translate to on-road driving.

No Difference in Arousal or Cognitive Demands Between Manual and Partially Automated Driving: A Multi-Method On-Road Study.

Introduction: Partial driving automation is not always reliable and requires that drivers maintain readiness to take over control and manually operate the vehicle. Little is known about differences in drivers' arousal and cognitive demands under partial automation and how it may make it difficult for drivers to transition from automated to manual modes. This research examined whether there are differences in drivers' arousal and cognitive demands during manual versus partial automation driving.

Age-Related Differences in the Cognitive, Visual, and Temporal Demands of In-Vehicle Information Systems.

In-vehicle information systems (IVIS) refer to a collection of features in vehicles that allow motorists to complete tasks (often unrelated to driving) while operating the vehicle. These systems may interfere, to a greater extent, with older drivers' ability to attend to the visual and cognitive demands of the driving environment. The current study sought to examine age-related differences in the visual, cognitive and temporal demands associated with IVIS interactions.