Impact of Cognitive Workload on Physiological Arousal and Performance in Younger and Older Drivers

Abstract

Summary:Two groups, aged 25-35 and 60-69, engaged in 3 levels of a delayed auditory recall task while driving a simulated highway. Heart rate and skin conductance increased with each level of demand, demonstrating that these indices can correctly rank order cognitive workload. Effects were also observed on speed and SD of lane position, but they were subtle, nonlinear, and did not effectively differentiate. Patterns were quite consistent across age groups. These findings on the sensitivity of physiological measures replicate those from an onroad study using a similar protocol. Together, the results support the validity of using these physiological measures of workload in a simulated environment to model differences likely to be present under actual driving conditions.

Sensitivity of Physiological Measures for Detecting Systematic Variations in Cognitive Demand From a Working Memory Task

“…This demonstrates that in addition to detecting marked changes in driving conditions such as entering a traffic circle (Brookhuis & de Waard, 2001) or in secondary task difficulty (i.e., between a 0-back and a 3-back task; Lenneman & Backs, 2009), these measures can discriminate subtle differences across a range of demand levels. A recently completed simulation study by colleagues in Korea (Son et al, 2011), based on this protocol, produced comparable findings on the question of sensitivity, providing further evidence for the generalizability of these results.…”

2C4-2 Validation of a driving simulator for driver distraction research on a two-lane highway

“…Heart rate was examined as a driver behavior measure, and found that absolute validity and relative validity were established. The result indicated that heart rate is one of the most useful measures for investigating a driver's cognitive workload for both simulated and real world driving as suggested in previous studies [14,15,16].…”

Defining workload in the context of driver state detection and HMI evaluation

“…Persons differ in the amount of these capabilities which they possess, and their strategies for employing them. (p. 22) In our research on the use of physiological measures in state detection and workload assessment, we generally focus on workload from the perspective of the level of effort or mobilization of resources that appears to be associated with a task or set of conditions [2,13,14,15,19,20,23]. This approach explicitly recognizes that the same level of objectively defined external demand is likely to produce a wide range of effective workload on different individuals depending upon their own capacities, experience, and current emotional state and reactivity.…”