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The body of research on cognitive distraction while driving is vast and spans many decades. To this research, the authors of the target article add three experiments that measure a number of cognitive tasks across laboratory, simulation, and on-road contexts. The pattern of decrements is similar across contexts, when expressed as an index, and when compared to previous research. Measurement, task, and generalizability issues arise from the approaches taken by the authors. For example, the use of "pure" cognitive tasks may not necessarily generalize to everyday driving behavior, wherein visual and physical distractions are inherently interleaved with cognitive tasks. A valuable contribution of the authors' future research on cognitive distractions would be to predict relative crash risk.

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.

A modified version of the flicker technique to induce change blindness was used to examine the effects of time constraints on decision-making accuracy at intersections on a total of 62 young (18-25 years), middle-aged (26-64 years), young-old (65-73 years), and old-old (74 + years) drivers. Thirty-six intersection photographs were manipulated so that one object (i.e., pedestrian, vehicle, sign, or traffic control device) in the scene would change when the images were alternated for either 5 or 8 s using the modified flicker method. Young and middle-aged drivers made significantly more correct decisions than did young-old and old-old drivers. Logistic regression analysis of the data indicated that age and/or time were significant predictors of decision performance in 14 of the 36 intersections. Actual or potential applications of this research include driving assessment and crash investigation.

Objective An up-to-date meta-analysis of experimental research on talking and driving is needed to provide a comprehensive, empirical, and credible basis for policy, legislation, countermeasures, and future research. Background The effects of cell, mobile, and smart phone use on driving safety continues to be a contentious societal issue. Method All available studies that measured the effects of cell phone use on driving were identified through a variety of search methods and databases. A total of 93 studies containing 106 experiments met the inclusion criteria. Coded independent variables included conversation target (handheld, hands-free, and passenger), setting (laboratory, simulation, or on road), and conversation type (natural, cognitive task, and dialing). Coded dependent variables included reaction time, stimulus detection, lane positioning, speed, headway, eye movements, and collisions. Results The overall sample had 4,382 participants, with driver ages ranging from 14 to 84 years ( M = 25.5, SD = 5.2). Conversation on a handheld or hands-free phone resulted in performance costs when compared with baseline driving for reaction time, stimulus detection, and collisions. Passenger conversation had a similar pattern of effect sizes. Dialing while driving had large performance costs for many variables. Conclusion This meta-analysis found that cell phone and passenger conversation produced moderate performance costs. Drivers minimally compensated while conversing on a cell phone by increasing headway or reducing speed. A number of additional meta-analytic questions are discussed. Application The results can be used to guide legislation, policy, countermeasures, and future research.

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.

Objective We examine the relationships between contemporary progress in on‐road vehicle automation and its coherence with an envisioned "autopia" (automobile utopia) whereby the vehicle operation task is removed from all direct human control. Background The progressive automation of on‐road vehicles toward a completely driverless state is determined by the integration of technological advances into the private automobile market; improvements in transportation infrastructure and systems efficiencies; and the vision of future driving as a crash‐free enterprise. While there are many challenges to address with respect to automated vehicles concerning the remaining driver role, a considerable amount of technology is already present in vehicles and is advancing rapidly. Methods A multidisciplinary team of experts met to discuss the most critical challenges in the changing role of the driver, and associated safety issues, during the transitional phase of vehicle automation where human drivers continue to have an important but truncated role in monitoring and supervising vehicle operations. Results The group endorsed that vehicle automation is an important application of information technology, not only because of its impact on transportation efficiency, but also because road transport is a life critical system in which failures result in deaths and injuries. Five critical challenges were identified: driver independence and mobility, driver acceptance and trust, failure management, third-party testing, and political support. Conclusion Vehicle automation is not technical innovation alone, but is a social as much as a technological revolution consisting of both attendant costs and concomitant benefits.