Purpose: We review what we currently know about older driver safety and mobility, and we highlight important research needs in a number of key areas that hold promise for achieving the safety and mobility goals for the aging baby boomers and future generations of older drivers. Design and Methods:Through the use of a framework for transportation and safe mobility, we describe key areas of screening and assessment, remediation and rehabilitation, vehicle design and modification, technological advancements, roadway design, transitioning to nondriving, and alternative transportation to meet the goals of crash prevention and mobility maintenance for older adults. Results: Four cross-cutting themes emerged from this review: safe transportation for older adults is important; older adults have a variety of needs, abilities, and resources; research to help meet the transportation needs of older adults may be of benefit to persons with disabilities; and transportation issues concerning older adults are multifaceted. Implications: Safe mobility is essential to continued engagement in civic, social, and community life, and to the human interactions necessary for health, well-being, and quality of life. When safe driving is no longer possible for older adults, safe and practicable alternative transportation must be available. Furthermore, older adults are individuals; they have specific needs, abilities, and resources. Not all older adults will have difficulty meeting their transportation needs and no single transportation solution will work for all people. Research and countermeasures intended to help meet the transportation needs of older adults will likely also benefit younger users of the transportation system, particularly those with disabilities. The issues surrounding the maintenance of safe transportation for older adults will require an interdisciplinary research approach if we are to make significant progress in the next decade as the baby boomers begin to reach age 70.

Objectives. The objectives of this paper are to review the published research findings about the role of self-regulation in older driver safety and to report on an exploratory study to better understand the self-regulatory practices of older drivers as demonstrated through the avoidance of a number of specific driving situations including making left turns and driving alone, at night, in bad weather, in high traffic, and on the expressway and through restricting driving to familiar or local areas only. Methods. As part of a larger study on the development and testing of a self-screening instrument by older drivers, data on self-regulation were compared with data on driving-related abilities collected through clinical and on-road assessments for 68 drivers age 65 and older. Results. Findings indicate that 25% of subjects reported self-regulating their driving in some way. Of those who self-regulated, five individuals reported avoiding just one type of driving situation, six reported avoiding two, one reported avoiding three, and five reported avoiding four types of situations. The most frequently reported situations were avoiding driving at night (19.1%) in bad weather (8.8%), and driving only in local areas (13.2%). Women were considerably more likely than men to report self-regulatory practices. Consistent with the findings of low avoidance of driving situations, subjects generally reported high levels of confidence, with the exception of driving at night, for which over one third of women reported being “not at all confident.” Overall, subjects were least confident driving at night, in bad weather, and on expressways. Results from a logistic regression model indicate that subjects did appear to self-regulate their driving at night based on their performance on the on-road driving assessment (p < .01). That is, for every 10-unit decrease in driving score (with lower scores indicating poorer driving performance), subjects were 1.6 times more likely to self-regulate. Conclusions. Continuing research on the extent to which older drivers appropriately self-regulate their driving is warranted. Future studies should focus on objectively measuring self-regulation, possibly through instrumented vehicle studies, and comparing these measures with clinically determined functional abilities and driving performance. It is also important to take into account differences in self-regulation by sex, as well as the effects of confidence in driving ability and insight into functional impairments on self-regulation.

Emerging evidence suggests that atypical changes in driving behaviors may be early signals of mild cognitive impairment (MCI) and dementia. This study aims to assess the utility of naturalistic driving data and machine learning techniques in predicting incident MCI and dementia in older adults. Monthly driving data captured by in-vehicle recording devices for up to 45 months from 2977 participants of the Longitudinal Research on Aging Drivers study were processed to generate 29 variables measuring driving behaviors, space and performance. Incident MCI and dementia cases (n = 64) were ascertained from medical record reviews and annual interviews. Random forests were used to classify the participant MCI/dementia status during the follow-up. The F₁ score of random forests in discriminating MCI/dementia status was 29% based on demographic characteristics (age, sex, race/ethnicity and education) only, 66% based on driving variables only, and 88% based on demographic characteristics and driving variables. Feature importance analysis revealed that age was most predictive of MCI and dementia, followed by the percentage of trips traveled within 15 miles of home, race/ethnicity, minutes per trip chain (i.e., length of trips starting and ending at home), minutes per trip, and number of hard braking events with deceleration rates ≥ 0.35 g. If validated, the algorithms developed in this study could provide a novel tool for early detection and management of MCI and dementia in older drivers.