Multivariate differences in driver workload: Test track versus on-road driving

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Abstract

In a continuing effort to examine data from the Crash Avoidance Metrics Partnership (CAMP), Driver Workload Metrics Project (DWM) (The Driver Workload Metrics project, a co-operative agreement between the NHTSA, Ford, GM, Nissan, and Toyota, was conducted under the Crash Avoidance Metrics Partnership (CAMP), established by Ford and GM to undertake joint precompetitive work in advanced collision avoidance systems.) this paper identified correlates of driver workload, a construct defined as the competition in driver resources (perceptual, cognitive, or physical) between the driving task and a concurrent secondary task occurring over that task’s duration. Data from 24 onroad and 24 test-track subjects who performed visual-manual, auditory vocal, a combination of both, or just drive tasks, were analyzed using Maximum Likelihood Factor Analysis (MLFA). Results found that there were seven hidden factors that still explained about 62% of the original variance from the original 42 variables. Factors scores for each subject were analyzed with Multivariate Analysis of Variance (MANOVA). Results found highly statistically significant workload differences in venue, age groups, task type, and gender. Results from radar plots visually define the subjective concept of driver workload.

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Auflick, J. L. (2018). Multivariate differences in driver workload: Test track versus on-road driving. In Advances in Intelligent Systems and Computing (Vol. 597, pp. 927–936). Springer Verlag. https://doi.org/10.1007/978-3-319-60441-1_89

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