Modeling Mental Workload and Task Performance for Indirect Vision Driving

Abstract

Cognitive workload and task performance are modeled for indirect vision driving with fixed flat panel displays. The model is derived from the results of a field study in which eight participants negotiated a driving course in a military vehicle with natural and indirect vision. For the latter, the vehicle was driven with fixed flat panel, liquid crystal displays in the cab and a forward viewing monocular camera array mounted on the front roof of the vehicle and tilted slightly downward. In addition to recording driving performance, the study collected test battery ratings of the mental workload measures of attention allocation, perceived workload, situational awareness, motion sickness, perceived stress, and cognitive performance. As a result of the study, a mathematical model of road speed was derived for indirect vision driving as a function of the camera's field of view. The model considers the effects of scene compression on the informational needs of the driver in a self-paced task. Concurrently, a task analysis mental workload model was derived for indirect vision driving by mapping the cognitive and mental workload measures to a “skills-rules-knowledge” model of information processing. The model successfully explains apparently conflicting results for indirect vision driving from different experiments that examined on-board and teleoperations from the different camera lens used in the studies.