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Evidence suggests that older driver safety may be improved by good vehicle maintenance, in-vehicle advanced technologies, and proper vehicle adaptations. This study explored the prevalence of several measures of vehicle maintenance and damage among older drivers through inspection of their vehicles. We also investigated the prevalence of in-vehicle technologies and aftermarket adaptations. Vehicle inspections were conducted by trained research staff using an objective, standardized procedure. This procedure, developed by a multidisciplinary team of researchers, was based on a review of inspection checklists used by automobile dealerships and the project team's expertise. The study used baseline data from vehicles of 2988 participants in the multi-site Longitudinal Research on Aging Drivers (LongROAD) study. Among this cohort, vehicles were well maintained, had little damage, and contained a range of advanced technologies but few aftermarket adaptations. Implications of study findings for occupational therapy practice are discussed.

We surveyed self-reported lifetime health conditions (using National Health and Aging Trends Study questions) and related driving reduction in a large multi-site older driver cohort (n = 2,990) from the AAA Longitudinal Research on Aging Drivers (LongROAD) Study’s baseline assessment. Those reporting reduced driving (n = 337) largely attributed reduction to musculoskeletal (29%), neurologic (13%), and ophthalmologic (10%) conditions. Women reported health condition-related driving reduction more often than men (14% versus 8%, p

OBJECTIVE There are many unknowns regarding drivers' use and acceptance of advanced vehicle technologies. This research aimed to examine drivers' perceptions of advanced driver assistance systems (ADAS). METHODS This research was conducted using structured interviews and focus groups of owners of vehicles with advanced technologies. RESULTS Drivers' perceptions about ADAS were mixed, but generally safety was considered to be the greatest value of the systems. There was recognition that the systems may result in overreliance and thus encourage distraction behaviors or other bad driving habits, and participants generally expressed that they were ultimately responsible for the vehicle's operation and needed to be ready to override the system if it failed. CONCLUSIONS The findings indicate that driver characteristics and individual factors may influence perceptions, behaviors, and interactions with safety technology, and this research is a first step toward understanding any influences. Human factors issues related to automated vehicle technologies are critical for design and deployment, including those of trust, acceptance, and understanding of systems.

The primary objective of this study was to better understand how self-regulatory driving practices at multiple levels of driver decision making are influenced by various factors. Specifically, the study investigated patterns of tactical and strategic self-regulation among a sample of 246 Australian older drivers. Of special interest was the relative influence of several variables on the adoption of self-regulation, including self-perceptions of health, functioning, and abilities for safe driving and driving confidence and comfort.The research was carried out at the Monash University Accident Research Centre, as part of its Ozcandrive study, a partnership with the Canadian Driving Research Initiative for Vehicular Safety in the Elderly (Candrive), and in conjunction with the University of Michigan Transportation Research Institute (UMTRI). Candrive/Ozcandrive represents the first study to follow a large group of older drivers over several years and collect comprehensive self-reported and objectively derived data on health, functioning, and driving. This study used a subset of data from the Candrive/Ozcandrive study. Upon enrolling in the study, participants underwent a comprehensive clinical assessment during which data on visual, cognitive, and psychomotor functioning were collected. Approximately 4 months after study enrollment, participants completed the Advanced Driving Decisions and Patterns of Travel (ADDAPT) questionnaire, a computer-based self-regulation instrument developed and pilot-tested at UMTRI.Self-regulation among older adults was found to be a multidimensional concept. Rates of self-regulation were tied closely to specific driving situations, as well as level of decision making. In addition, self-regulatory practices at the strategic and tactical levels of decision making were influenced by different sets of factors.Continuing efforts to better understand the self-regulatory practices of older drivers at multiple levels of driver performance and decision making should provide important insights into how the transition from driving to nondriving can be better managed to balance the interdependent needs of public safety and personal mobility.

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.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.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 express ways. 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.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.

The primary purpose of this study was to better understand US travelers’ route guidance information preferences for Advanced Traveler Information Systems (AT1S) for tourist automobile trips in unfamiliar areas. A secondary purpose was to better understand, more generally, information needs and preferences of tourists in order to develop guidelines for designing ATIS that is specific for driving tourists. Data on information needs and preferences were collected through a mail-back questionnaire survey of US adult residents. Among other topics, the questionnaire asked respondents about their preferences for various types of route guidance information. These data are reported here. Survey respondents gave positive ratings to all nine types of route guidance information investigated in the study, including selecting best route to destination, travel routes shown on map, road conditions, traffic congestion on route, presence of construction, weather conditions, time or distance on route, options/recommendation...