Safety concerning human performance in complex multitask environments relies heavily upon the fundamental psychological principles of limited-capacity attention and top-down mechanisms of attention allocation. To develop a suitable model for distraction and safety with automobiles, Spencer Castro’s team at UC Merced implements converging measures from established physiological, behavioral and subjective proxies for effort in realistic goal-directed settings. In this talk, Castro presents interesting examples of measuring, modeling and attempting to predict effort in the lab, in simulations and in automobiles on the road. The work measures fluctuations in cognitive workload for various manipulations of multitasking, including instruction-induced task priority and intermittent secondary task cues. The results indicate that multiple parameters are necessary to capture variations in processing priority for people and machines, with strong implications for safety. The most robust finding suggests that - contrary to strictly resource-limited theories of attention - strategic allocation of resources can drive performance more than a slowing in the rate of information processing.
Speaker: Spencer Castro, UC Merced
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