Latency and eye movement measures were used to examine the effects of aging, clutter, and luminance on visual search for traffic signs embedded in digitized images of driving scenes. Initially 14 older and 14 younger observers classified daytime and nighttime traffic scenes as containing low or high amounts of clutter. Next, an independent sample of 14 younger and 14 older participants searched for traffic signs contained within these scenes. Errors were more common among the elderly. Search efficiency declined with increased clutter and with aging. However, relative to the young, older adults did not suffer disproportionately as a result of increased clutter. The methods developed might be profitably employed to assess sign conspicuity and sign acquisition during driving.
The Independent LifeStyle Assistant (I.L.S.A.) is an agent-based monitoring and support system to help elderly people live longer in their homes by reducing caregiver burden. I.L.S.A. is a multiagent system that incorporates a unified sensing model, situation assessments, response planning, real-time responses, and machine learning. This paper describes the six-month study of the system we fielded in elders' homes and the major lessons we learned during development.
The present study examined age differences in trust and reliance of an automated decision aid. In Experiment 1, older and younger participants performed a simple mathematical task concurrent with a simulated medication management task. The decision aid was designed to facilitate medication management, but with varying reliability. Trust, self-confidence and usage of the aid were measured. The results indicated that older adults had greater trust in the aid and were less confident in their performance, but they did not calibrate trust differently than younger adults. In Experiment 2, a variant of the same task was used to investigate whether older adults are subject to over-reliance on the automation. Differences in omission and commission errors were examined. The results indicated that older adults were more reliant on the decision aid and committed more automationrelated errors. A signal detection analyses indicated that older adults were less sensitive to automation failures. Results are discussed with respect to the perceptual and cognitive factors that influence age differences in the use of fallible automation. q
The effects of divided attention were examined in younger adults (M = 23 years) and older adults (M = 64 years) who searched for traffic signs in digitized images of traffic scenes. Sign search was executed under single-task and dual-task conditions in scenes containing either small or large amounts of visual clutter. For both age groups, clutter and the secondary task had additive effects on search accuracy, speed, and oculomotor involvement. Compared with the younger adults, older adults were less accurate, especially with high-clutter scenes, were slower to decide that a target sign was not present, and exhibited a marginally greater divided-attention effect on reaction times. They exhibited longer fixations in the divided-attention condition, in which they also showed a disproportionate reduction in recognition memory for the content of the secondary task. Actual or potential applications of this research include methods for evaluating the distraction of conversations and safety implications of conversation on visual search behavior.
There has been a great deal of human factors research on unmanned air and ground vehicles, but there is very little research examining the unique human factors problems associated with unmanned underwater vehicles (UUVs). The lack of research is surprising considering the increased use and the envisioned future use of UUVs in military maritime operations. In this paper, it is argued that because the underwater environment is so harsh and challenging, operating UUVs presents human factors problems that are different from the challenges of surface unmanned systems. Several common human factors problems are discussed when using unmanned systems, including the loss of sensory cues and spatial awareness, the control of the remote vehicle, problems with situation awareness and workload, and problems with trust in automation. In each case, these issues are discussed with respect to underwater operations.
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