Modeling Workload for Target Detection from a Moving Vehicle With a Head-Mounted Display and Sound Localization

Abstract

Abstract : The effect of indirect vision systems on target detection and recognition is of interest to designers of future combat vehicles. in this report, a mode! of target detection and mental workload is described for an indirect vision system with a micro-state task time line analysis of attention workload. The model is based on the results of a field study in which participants detected and identified pop- up targets on an outdoor range from a stationary and a moving vehicle while using a head-mounted display (HMD), with and without sound localization and with direct viewing as a control. A head-slaved camera mounted on top of the vehicle provided the image to the HMD. As a result of the study, a target detection and identification model is derived for the different treatments from the data via regression analysis. The effect of indirect vision on mental workload is determined from the subjective ratings of perceived task loading that were reported in the field study. Along with the perceived workload, the study participants rated the mental measures of task-allocated attention, situational awareness, and motion sickness. Because of collinearity, the perceived workload is regressed on the factorial components of a cognitive loading space derived from a factorial analysis of the mental measures. Following rotation to a skills-rules-knowledge cognitive processing space derived from the clustering of the measures, the perceived workload is shown to be a function of the skill- and rule-based components. On this basis, a micro-state time line model is proposed for the task information processing. In addition to the attention allocated to the targeting task, the model includes attention to cognitive maps for target orienting by the audio cues and the monitoring of the internal somatic state for motion sickness.