Highly Automated Driving, Secondary Task Performance, and Driver State

Abstract

Objective: A driving simulator study compared the effect of changes in workload on performance in manual and highly automated driving. Changes in driver state were also observed by examining variations in blink patterns. Background: With the addition of a greater number of advanced driver assistance systems in vehicles, the driver’s role is likely to alter in the future from an operator in manual driving to a supervisor of highly automated cars. Understanding the implications of such advancements on drivers and road safety is important. Method: A total of 50 participants were recruited for this study and drove the simulator in both manual and highly automated mode. As well as comparing the effect of adjustments in driving-related workload on performance, the effect of a secondary Twenty Questions Task was also investigated. Results: In the absence of the secondary task, drivers’ response to critical incidents was similar in manual and highly automated driving conditions. The worst performance was observed when drivers were required to regain control of driving in the automated mode while distracted by the secondary task. Blink frequency patterns were more consistent for manual than automated driving but were generally suppressed during conditions of high workload. Conclusion: Highly automated driving did not have a deleterious effect on driver performance, when attention was not diverted to the distracting secondary task. Application: As the number of systems implemented in cars increases, an understanding of the implications of such automation on drivers’ situation awareness, workload, and ability to remain engaged with the driving task is important.