Objective The goal of this review is to investigate the relationship between indirect physiological measurements and direct measures of situation awareness (SA). Background Assessments of SA are often performed using techniques designed specifically to directly measure SA, such as SA global assessment technique (SAGAT), situation present assessment method (SPAM), and/or SA rating technique (SART). However, research suggests that physiological sensing methods may also be capable of inferring SA. Method Seven databases were searched. Eligibility criteria included human–subject experiments that used at least one direct SA assessment technique as well as at least one physiological measurement. Information extracted from each article were the physiological metric(s), direct SA measurement(s), correlation between these two metrics, and experimental task(s). Results Twenty-five articles were included in this review. Eye tracking techniques were the most commonly used physiological measures, and correlations between conscious aspects of eye movement measures and direct SA scores were observed. Evidence for cardiovascular predictors of SA was mixed. Only three electroencephalography (EEG) studies were identified, and their results suggest that EEG was sensitive to changes in SA. Overall, medium correlations were observed among the studies that reported a correlation coefficient between physiological and direct SA measures. Conclusion Reviewed studies observed relationships between a wide range of physiological measurements and direct assessments of SA. However, further investigations are needed to methodically collect more evidence. Application This review provides researchers and practitioners a summary of observed methods to indirectly assess SA with sensors and highlights research gaps to be addressed in future work.

Objective This research sought to determine whether people can perceive and process three nonredundant (and unrelated) signals in vision, hearing, and touch at the same time and how aging and concurrent task demands affect this ability. Background Multimodal displays have been shown to improve multitasking and attention management; however, their potential limitations are not well understood. The majority of studies on multimodal information presentation have focused on the processing of only two concurrent and, most often, redundant cues by younger participants. Method Two experiments were conducted in which younger and older adults detected and responded to a series of singles, pairs, and triplets of visual, auditory, and tactile cues in the absence (Experiment 1) and presence (Experiment 2) of an ongoing simulated driving task. Detection rates, response times, and driving task performance were measured. Results Compared to younger participants, older adults showed longer response times and higher error rates in response to cues/cue combinations. Older participants often missed the tactile cue when three cues were combined. They sometimes falsely reported the presence of a visual cue when presented with a pair of auditory and tactile signals. Driving performance suffered most in the presence of cue triplets. Conclusion People are more likely to miss information if more than two concurrent nonredundant signals are presented to different sensory channels. Application The findings from this work help inform the design of multimodal displays and ensure their usefulness across different age groups and in various application domains.

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The rapid growth of autonomous vehicles is expected to improve roadway safety. However, certain levels of vehicle automation will still require drivers to ‘takeover’ during abnormal situations, which may lead to breakdowns in driver-vehicle interactions. To date, there is no agreement on how to best support drivers in accomplishing a takeover task. Therefore, the goal of this study was to investigate the effectiveness of multimodal alerts as a feasible approach. In particular, we examined the effects of uni-, bi-, and trimodal combinations of visual, auditory, and tactile cues on response times to takeover alerts. Sixteen participants were asked to detect 7 multimodal signals (i.e., visual, auditory, tactile, visual-auditory, visual-tactile, auditory-tactile, and visual-auditory-tactile) while driving under two conditions: with SAE Level 3 automation only or with SAE Level 3 automation in addition to performing a road sign detection task. Performance on the signal and road sign detection tasks, pupil size, and perceived workload were measured. Findings indicate that trimodal combinations result in the shortest response time. Also, response times were longer and perceived workload was higher when participants were engaged in a secondary task. Findings may contribute to the development of theory regarding the design of takeover request alert systems within (semi) autonomous vehicles.

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