title: Factors affecting performance on a target monitoring task employing an automatic tracker.
abstract: The experiments in this paper examined the extent to which performance on a task employing an automatic tracker was similar to performance on tasks employing other types of automation that have been studied more extensively. Automated target tracking is being used in many sensor and navigation systems to improve performance and help the operator cope with increased data loads. With many automated systems these goals are not met. In particular, the operator often misses errors made by the automated system and may report no decrease in workload. Several hypotheses have been offered for the operator's failure to monitor an automated system adequately. These include lack of experience with the manual task, a vigilance decrement, complacency, and inappropriate level of automation. The relevance of each of these hypotheses to failure to monitor an automatic tracker adequately was examined. Performance and perceived workload on a target tracking task employing an automatic tracker, in which participants had to detect and then update the position of several targets (e.g. ships) at regular intervals, were measured as a function of number of targets, training with the manual task, experience, and time on task. The results suggested that failure to detect errors made by the automated system was due largely to the lack of visibility of the automation errors relative to other errors. However, complacency could not be ruled out entirely. Unlike some other tasks, the availability of a reliable automatic tracker did lead to a substantial reduction in perceived workload.
authors.affiliation: Defence R & D Canada--Toronto, Toronto, Ontario M3M 3B9, Canada. sharon.mcfadden@drdc-rddc.gc.ca
authors.forename: Sharon M
authors.initials: SM
authors.lastname: McFadden
authors.forename: Abhirami
authors.initials: A
authors.lastname: Vimalachandran
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Blackmore
mesh_terms: D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D001331:Automation / Q000295:instrumentation / Q000379:methods*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D008875:Middle Aged; D013647:Task Performance and Analysis; D013663:Teaching / Q000379:methods; D013995:Time; D014584:User-Computer Interface; D016526:Workload