This study examined the sensitivity of heart rate, skin conductance, and respiration rate as measures of mental workload in a simulated driving environment. Workload was systematically manipulated by using increasingly difficult levels of a secondary cognitive task. In a sample of 121 young adults, heart rate increased incrementally with increasing task demand. Significant elevations in skin conductance and respiration rate were also observed. At the lower levels of added workload, secondary task performance was nearly perfect and changes in indices of driving performance were negligible. At the highest level of workload, all three physiological measures appeared to plateau, and a subtle drop in simulated driving performance became detectable. Taken together, the pattern of results indicates that physiological measures can be sensitive to changes in workload before the appearance of clear decrements in driving performance. These findings further highlight a role for physiological monitoring as a means to measure mental workload in product design and functionality research. They also support work exploring the potential for incorporating physiological measures of driver workload and attentional state in future safety systems.

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: A total of 108 relatively healthy drivers balanced by gender and across three age groups (20–29, 40–49, 60–69) engaged in three 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. Although 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 human machine interface (HMI) designs and in exploring their potential role in advanced workload detection and augmented cognition systems.

Cognitive distractions have been shown to affect drivers adversely and are a leading cause of accidents. Research indicates that drivers alter how they allocate their visual attention while engaging in secondary cognitive tasks. To evaluate the potential impact of secondary cognitive tasks on the allocation of drivers’ visual attention and on vehicle control, drivers were presented with increasingly complex forms of an auditory cognitive task while driving an instrumented vehicle. Measures of vehicle performance and eye gaze were assessed. Consistent with theories of visual tunneling, gaze distributions were significantly smaller while drivers performed certain levels of the secondary task; peripheral vision was thereby reduced. During the most difficult level of the secondary task, gaze dispersion was smaller than during any other level of the task. Changes in visual attention may provide earlier indications of cognitive distraction than changes in vehicle control, the latter of which were observed only during the most difficult level of the secondary task. Observed changes in vertical eye position suggest that drivers compensate for moderate cognitive demands by increasing their sight distance before further incremental increases in workload exceeded their abilities. In summary, the workload of a secondary cognitive task affected drivers’ visual attention. A low to moderate increase in workload was detectable as a change in gaze before vehicle control suffered. Gaze restriction appears related to the degree of cognitive workload. This work shows that visual attention is a potential method of detecting changes in driver state associated with cognitive workload.

Physiological measures provide a continuous and relatively non-invasive method of characterising workload. The extent to which such measures provide sensitivity beyond that provided by driving performance metrics is more open to question. Heart rate and skin conductance were monitored during actual highway driving in response to systematically increased levels of cognitive demand using an auditory delayed digit recall task. The protocol was consistent with an earlier simulator study, providing an opportunity to assess the validity of physiological measures recorded during driving simulation. The pattern of change in heart rate with increased cognitive demand was highly consistent between field and simulator. The findings meet statistical criteria for both relative and absolute validity, although there was a trend for absolute levels to be higher under actual driving conditions. For skin conductance level, the pattern in both environments was also quite similar and a reasonable case for overall relative validity can be made. Statement of Relevance: Growing complexity and multiple demands on modern drivers’ attention highlight the significance of determining whether physiological measures provide increased sensitivity in workload detection. Better understanding, including whether simulator assessments provide valid measures of real-world response patterns, has implications in evaluating and refining interface designs and for developing advanced workload managers.

Data from on-road and simulation studies were compared to assess the validity of measures generated in the simulator. In the on-road study, driver interaction with three manual address entry methods (keypad, touch screen and rotational controller) was assessed in an instrumented vehicle to evaluate relative usability and safety implications. A separate group of participants drove a similar protocol in a medium fidelity, fixed-base driving simulator to assess the extent to which simulator measures mirrored those obtained in the field. Visual attention and task measures mapped very closely between the two environments. In general, however, driving performance measures did not differentiate among devices at the level of demand employed in this study. The findings obtained for visual attention and task engagement suggest that medium fidelity simulation provides a safe and effective means to evaluate the effects of in-vehicle information systems (IVIS) designs on these categories of driver behaviour. Statement of Relevance: Realistic evaluation of the user interface of IVIS has significant implications for both user acceptance and safety. This study addresses the validity of driving simulation for accurately modelling differences between interface methodologies by comparing results from the field with those from a medium fidelity, fixed-base simulator.

Applied research on driving and basic vision research have held similar views on central, fovea-based vision as the core of visual perception. In applied work, the concept of the Useful Field, as determined by the Useful Field of View (UFOV) test, divides vision between a "useful" region towards the center of the visual field, and the rest of the visual field. While compelling, this dichotomization is at odds with findings in vision science which demonstrate the capabilities of peripheral vision. In this paper, we examine driving research from this new perspective, and argue for the need for an updated understanding of how drivers acquire information about their operating environment using peripheral vision. The concept of the Useful Field and the UFOV test are not discarded; instead we discuss their strengths, limitations, and future directions. We discuss key findings from vision science on peripheral vision, and a theory that provides insights into its capabilities and limitations. This more complete basic science understanding of peripheral vision informs appropriate use of the UFOV and the Useful Field in driving research going forward.