Loss of situational awareness due to increased cognitive load is one of the areas considered at the AgeLab in our assessments of factors that impact driver safety. Recent findings have shown that though a driver may have his eyes on the road, his mind may be elsewhere. This lack of attention can be represented by a narrowing of vision (less visual scanning) accompanied by a slower response to incidents. To better quantify the amount of cognitive load that causes changes in driver performance, the AgeLab has developed a Delayed Digit Recall task (n-back).
The Delayed Digit Recall n-back task is a calibration method that systematically increases the cognitive demand placed on an individual. The lab has used this task in a series of studies. The most recent publication on this work is now available on-line. Titled, A Field Study on the Impact of Variations in Short-Term Memory Demand on Drivers’ Visual Attention and Driving Performance across Three Age Groups, this paper provides evidence of horizontal gaze concentration (a decrease in dispersion of gaze) with increased cognitive demand. Gaze restriction was evident during the least demanding level of the task and showed further restriction at the two higher levels of demand.
A companion paper, Sensitivity of Physiological Measures for Detecting Systematic Variations in Cognitive Demand from a Working Memory Task: An On-Road Study across Three Age Groups, has also been accepted for publication. In this work, both heart rate and skin conductance level (sweat gland activity) were found to increase in a relatively linear manner with demand. This is significant in that it demonstrates that physiological measures can be used to objectively monitor cognitive workload in the driving environment. Both papers are to appear in Human Factors: The Journal of the Human Factors and Ergonomics Society.
Paying attention to the road is not a binary operation; drivers can give varying degrees of attention to the task at hand. To simulate this, 0, 1 and 2-back tasks model increasing levels of cognitive load, which in turn result in decreased attention to scanning the roadway. This is intended to model in an objective manner what an individual may experience while, for example, having a phone conversation – even if the phone call is hands-free. An AgeLab White Paper, available here, introduces and explains the Delayed Digit Recall n-back task in detail. It is important to note that among the relatively healthy people studied, age was not found to change the basic pattern of effects observed with increased cognitive demand.
The Delayed Digit Recall n-back task is currently being used in the International Standard Organization’s (ISO) TC22/SC13/WG 8 project, Coordinated studies on the Detection Response Task (DRT), as a surrogate for cognitive demand. Studies are taking place in Germany, France, Sweden, Canada, China and the United States. Earlier work with Delayed Digit Recall task following the protocol developed at the AgeLab was performed in Korea. In a U.S. Department of Transportation - National Highway Safety Administration document, Developing a Test to Measure Distraction Potential of In-Vehicle information System Tasks in Production Vehicles, the 2-back condition of the task was suggested as a “starting point for setting a limit for acceptable ‘dose’ of cognitive distraction.”
Reimer, B., Mehler, B., Wang, Y. & Coughlin, J.F. (in press). A Field Study on The Impact of Variations in Short Term Memory Demands on Drivers’ Visual Attention and Driving Performance Across Three Age Groups. Human Factors.
Objective: To assess sensitivity of visual attention and driving performance for detecting changes in driver cognitive workload across different age groups.
Background: The literature shows mixed results concerning the sensitivity of gaze concentration metrics to variations in cognitive demand. No studies appear showing how age impacts gaze allocation during cognitive demand.
Method: Recordings of drivers’ gaze and driving performance under three levels of cognitive demand were captured under actual driving conditions in individuals in their 20s, 40s and 60s.
Results: Gaze concentration increased with task difficulty through the low and moderate levels of demand and then appeared to level out at the high demand level. At the moderate difficulty level, gaze concentration increased by 2.4cm (≈ 2 degrees) from the reference period. The degree of gaze concentration with added cognitive demand is not related to age in the relatively healthy drivers studied. Driving performance measures did not show a consistent relationship to the objective demand level.
Conclusion: Gaze concentration appears at low levels of cognitive demand prior to the appearance of marked decrements in driving control. There is no compelling evidence from this study that driving performance measures can be used to index differences in workload prior to capacity saturation.
Application: Drivers’ awareness of vehicle surroundings is incrementally impacted by increases in cognitive demand. The development of more advanced driver support systems should consider gaze concentration as a measure of driver cognitive workload. This is particularly relevant in light of the added benefits of gaze measurements for detecting visual demand.
Mehler, B., Reimer, B. & Coughlin, J.F. (in press). Sensitivity of Physiological Measures for Detecting Systematic Variations in Cognitive Demand from a Working Memory Task: An On-road Study Across Three Age Groups. Human Factors.
Objective: To assess the sensitivity of two physiological measures for discriminating between levels of cognitive demand under driving conditions across different age groups.
Background: Previous driving research presents a mixed picture concerning the sensitivity of physiological measures for differentiating tasks with presumed differences in mental workload.
Method: 108 relatively healthy drivers balanced by gender and across three age groups (20-29, 40-49, 60-69) engaged in 3 difficulty levels of an auditory presentation – verbal response working memory task.
Results: Heart rate and skin conductance level (SCL) both increased in a statistically significant fashion with each incremental increase in cognitive demand whereas driving performance measures did not provide incremental discrimination. SCL was lower in the 40s and 60s age groups; however, the pattern of incremental increase with higher demand was consistent for heart rate and SCL across all age groups. While each measure was quite sensitive at the group level, considering both SCL and heart rate improved detection of periods of heightened cognitive demand at the individual level.
Conclusion: The data provide clear evidence that two basic physiological measures can be utilized under field conditions to differentiate multiple-levels of objectively defined changes in cognitive demand. Methodological considerations, including task engagement, may account for some of the inconsistencies in previous research.
Application: These findings increase the confidence with which these measures may be applied to assess relative differences in mental workload when developing and optimizing HMI designs and in exploring their potential role in advanced workload detection and augmented cognition systems.