Modeling of older adults' driving exposure and avoidance using objective driving data in a naturalistic driving study.

Older adults in the United States rely heavily on driving their own vehicles to commute to work, shop for groceries, and access public services. To effectively help older adults maintain mobility and independence,we need to better understand how thecognitive, visual functioning, and health declines influence their tendency to self-restrict their driving. The objective of this study is to develop a causal model to examine the effects of age, gender, household status (specifically living alone), physical, cognitive, visual abilities, and health status on older adults' driving mobility in terms of driving exposure and avoidance. Driving exposure was measured by actual driving data, whereas driving avoidance was assessed by both self-report data and actual driving exposure to challenging situations. Structural equation modeling was used to analyze data collectedin the Second Strategic Highway Research Program Naturalistic Driving Study for establishing relationships between the selected factors and mobility. The structural equation model included a total of794 participants aged 65 and over (367 or 46.22%femalesand 427 or 53.78% males). Results indicate that poorer health is associated with less driving exposure; deteriorating cognitive and physical capabilities are associated with more self-reported driving avoidance and less actual driving in challenging situations; visual function is associated with self-reported avoidance; living alone is associated with higher driving exposure in general as well as in challenging situations; self-reported driving avoidance of challenging situations has a negative association with actual driving in those same situations. The final model could be applied to predict older adults' mobility changes according to their age, gender, household status, as well as their visual, physical, cognitive and health status.

Left Turns by Older Drivers With Vision Impairment: A Naturalistic Driving Study.

BACKGROUND AND OBJECTIVES: Older drivers are overrepresented in collisions at intersections while making left turns across oncoming traffic. Using naturalistic driving methods, we evaluated the association between vision impairment and their left-turn characteristics. RESEARCH DESIGN AND METHODS: In this prospective, observational study, vision impairment as defined by visual acuity, contrast sensitivity, visual processing speed, visual field sensitivity, and motion perception was assessed in drivers ≥70 years old. Data acquisition systems were installed in their personal vehicles recording video and vehicle kinematics. Driving during everyday life was recorded for 6 months. Data analysts evaluated a temporal data window surrounding randomly selected left turns at 4-way intersections. Left-turn traversals and turning behavior were evaluated in terms of age-adjusted associations with vision impairment. RESULTS: The sample consisted of 151 older drivers. The number of turns studied was 473; 265 turns were rated as unsafe traversals, and 201 as problematic turning behavior. Drivers with slowed visual processing speed and visual field impairment were less likely to exhibit unsafe traversals (p < .05); those with worse contrast sensitivity, slowed visual processing speed, and visual field impairment were less likely to exhibit problematic turning behavior (p < .05). DISCUSSION AND IMPLICATIONS: Using naturalistic driving, our study suggests older drivers with vision impairment exhibit better performance in making left turns than those without deficits, which contradicts older driver studies on left turns using driving simulators and on-road driving evaluations. Our findings suggest more cautious and self-regulatory behavior, which are consistent with older visually impaired drivers' commonly expressed concerns about their driving difficulties.

Driving specialist's ratings of on-road performance and naturalistic driving crashes and near-crashes.

BACKGROUND: This study aimed to evaluate the association between a Certified Driving Rehabilitation Specialist's (CDRS) ratings of on-road driving performance by older drivers and at-fault crash and near-crash involvement using naturalistic driving techniques where crashes and near-crashes are recorded in everyday driving through in-vehicle instrumentation. METHODS: This is a cohort study of 144 drivers aged 70 years and over who were recruited due to a recent ophthalmology clinic visit at the University of Alabama at Birmingham. Baseline measurements consisted of demographics, visual status, and other health variables. At-fault crashes and near-crashes over 6 months were identified through instrumentation placed in their personal vehicle that recorded vehicle kinematics and video. After 6 months, a CDRS completed an on-road assessment and provided a composite rating on specific driving behaviors and a global score. RESULTS: Rate ratios examining the association between older drivers with worse CDRS composite scores and rates of at-fault crashes, at-fault near-crashes, and combined at-fault crashes and near-crashes were significantly higher compared to drivers with better scores. Results were similar for the CDRS global score. CONCLUSIONS: Motor vehicle administrations use CDRS ratings to make decisions about licensure, and in clinical programs such as those based at rehabilitation clinics use them to make recommendations about fitness to drive and rehabilitation. This study suggests that these decisions and recommendations are valid from a safety standpoint.

Naturalistic Driving Techniques and Association of Visual Risk Factors With At-Fault Crashes and Near Crashes by Older Drivers With Vision Impairment.

IMPORTANCE: Government motor vehicle crash reports used in the study of driver safety can be biased and incomplete. Naturalistic driving methods using in-vehicle instrumentation have been developed in recent years to objectively measure crashes and near crashes as they occur on the road using video and vehicle kinematic data. OBJECTIVE: To examine visual risk factors associated with at-fault crashes and near crashes among older drivers, most of whom have age-related eye conditions associated with vision impairment. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study was conducted at an academic ophthalmology clinic from January 1, 2015, to November 10, 2018, among 154 adults 70 years of age or older who were legally licensed in Alabama and who reported currently driving at least 4 days per week; 137 of 151 participants (90.7%) had an age-related eye condition in at least 1 eye. Drivers participated in a baseline visual function assessment followed by installation of a data acquisition system recording multichannel synchronized video and vehicle kinematics in their personal vehicle. Drivers were instructed to drive for 6 months as they normally would during everyday life. Statistical analysis was performed from June 15 to September 15, 2020. MAIN OUTCOMES AND MEASURES: The rate of combined incident at-fault crashes and near crashes, defined by the number of events and the number of miles driven. RESULTS: The sample consisted of 154 drivers (85 men [55.2%]; mean [SD] age, 79.3 [5.1] years). Visual functions associated with crash and near-crash involvement included impaired contrast sensitivity (rate ratio [RR], 2.7; 95% CI, 1.3-5.5), moderate (RR, 2.3; 95% CI, 1.1-4.9) and severe (RR, 5.0; 95% CI, 2.2-11.7) slowing in visual processing speed, and elevated motion perception thresholds for a drifting grating (RR, 1.9; 95% CI, 1.1-3.5). Those with impaired peripheral visual field sensitivity had increased rates of crashes and near crashes (RR, 1.8; 95% CI, 1.0-3.3); however, this finding was not statistically significant (P = .07). CONCLUSIONS AND RELEVANCE: With the use of naturalistic driving methods in which crashes and near crashes involving older drivers are objectively measured as they occur on the road, associations have been identified between impaired contrast sensitivity, slowed visual processing speed, and impaired motion perception and an increased rate of a combined total of at-fault crashes and near crashes.

Investigating lane change behaviors and difficulties for senior drivers using naturalistic driving data.

INTRODUCTION: Lane changes can be a complicated maneuver occurring a dynamic environment requiring the integration of many streams of information. Older drivers may struggle with lane changes which may elevate crash risk. METHODS: Real-world lane change behaviors were examined using the Second Strategic Highway Research Program Naturalistic Driving Study database. A total of 393 lane changes were observed for two age groups: middle-aged (30-49), and older (70+) drivers. RESULTS: Older drivers were highly likely to fail to execute an over-the-shoulder glance prior to initiation of a lane change (in 98% of left lane changes and 92% for right lane changes). Older drivers also showed higher rates of OTS glance errors at any point during the lane change in 95% of left lane changes and 86% of right-lane changes. Additionally, older drivers frequently failed to activate the turn signal prior to lane change initiation (60% of lane changes for right changes and 59% for left lane changes). Of the older drivers that made side mirror glances, many occurred after the initiation of the maneuver (46% of left lane changes and 58% of right lane changes) suggesting glances were occurring while changing lanes. CONCLUSIONS: Results for older drivers showed that many key glances (particularly side mirror checks) and turn signal actuations observed in the current study occurred after the initiation of the lane change, ostensibly when this action may be too late to gather relevant information and avoid a conflict. Practical Applications: Knowledge of glance patterns during lane changes for older drivers can help older drivers maintain travel mobility as they age. Either through training to reinforce OTS and side mirror glances, or supplemental devices like convex mirrors or oversized rearview mirrors, older drivers can reduce high-risk lane change maneuvers and help older drivers to maintain their mobility and independence longer.

Examining Senior Drivers' Attitudes Toward Advanced Driver Assistance Systems After Naturalistic Exposure.

BACKGROUND AND OBJECTIVES: The increasing number of senior drivers may introduce new road risks due to age-related declines in physical and cognitive abilities. Advanced driver assistance systems (ADAS) have been proposed as solutions to minimize age-related declines, thereby increasing both senior safety and mobility. This study examined factors that influence seniors' attitudes toward adopting ADAS after significant exposure to the technology in naturalistic settings. RESEARCH DESIGN AND METHODS: This study recruited 18 senior drivers aged 70-79 to drive vehicles equipped with ADAS for 6 weeks in their own environments. Afterward, each participant was enrolled in 1 of the 3 focus group sessions to discuss their changes in attitude toward ADAS based on their driving experiences. We applied structural topic modeling (STM) on the focus group transcripts to reveal key topics deemed important to seniors. RESULTS: STM revealed 5 topics of importance for seniors. In order of prevalence, these were (i) safety, (ii) confidence concerning ADAS, (iii) ADAS functionality, (iv) user interface/usability, and (v) non-ADAS-related features. Based on topics and associated keywords, seniors perceived safety improvement with ADAS but expressed concerns about its limitations in coping with adverse driving conditions. Experience and training were suggested for improving seniors' confidence in ADAS. Blind spot alert and adaptive cruise control received the most discussion regarding perceived safety and comfort. DISCUSSION AND IMPLICATIONS: This study indicated that promoting road safety for senior drivers through ADAS is feasible. Acceptance and appropriate use of ADAS may be supported through intuitive and senior-friendly user interfaces, in-depth training programs, and owner's manuals specifically designed and tested for senior drivers.

The Alabama VIP older driver study rationale and design: examining the relationship between vision impairment and driving using naturalistic driving techniques.

BACKGROUND: Older drivers aged ≥70 years old have among the highest rates of motor vehicle collisions (MVC) compared to other age groups. Driving is a highly visual task, and older adults have a high prevalence of vision impairment compared to other ages. Most studies addressing visual risk factors for MVCs by older drivers utilize vehicle accident reports as the primary outcome, an approach with several methodological limitations. Naturalistic driving research methods overcome these challenges and involve installing a high-tech, unobtrusive data acquisition system (DAS) in an older driver's own vehicle. The DAS continuously records multi-channel video of driver and roadway, sensor-based kinematics, GPS location, and presence of nearby objects in front of the vehicle, providing an objective measure of driving exposure. In this naturalistic driving study, the purpose is to examine the relationship between vision and crashes and near-crashes, lane-keeping, turning at intersections, driving performance during secondary tasks demands, and the role of front-seat passengers. An additional aim is to compare results of the on-road driving evaluation by a certified driving rehabilitation specialist to objective indicators of driving performance derived from the naturalistic data. METHODS: Drivers ≥70 years old are recruited from ophthalmology clinics and a previous population-based study of older drivers, with the goal of recruiting persons with wide ranging visual function. Target samples size is 195 drivers. At a baseline visit, the DAS is installed in the participant's vehicle and a battery of health and functional assessments are administered to the driver including visual-sensory and visual-cognitive tests. The DAS remains installed in the vehicle for six months while the participant goes about his/her normal driving with no imposed study restrictions. After six months, the driver returns for DAS de-installation, repeat vision testing, and an on-road driving evaluation by a certified driving rehabilitation specialist (CDRS). The data streams recorded by the DAS are uploaded to the data coordinating center for analysis. DISCUSSION: The Alabama VIP Older Driver Study is the first naturalistic older driver study specifically focused on the enrollment of drivers with vision impairment in order to study the relationship between visual dysfunction and driver safety and performance.

A validation of the low mileage bias using naturalistic driving study data.

INTRODUCTION: This paper evaluated the low mileage bias (LMB) phenomenon for senior drivers using data mined from the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study. Supporters of the LMB construct postulate that it is only those seniors who drive the lowest annual mileage who are primarily responsible for the increased crash rates traditionally attributed to this population in general. METHOD: The current analysis included 802 participants, all aged 65 or older who were involved in 163 property damage and injury crashes, and deemed to be at-fault in 123 (75%) of those instances. Poisson regression models were used to evaluate the association between annualized mileage driven and crash risk. RESULTS: Results show that the crash rate for drivers with lower annualized mileage (i.e., especially for those driving fewer than approximately 3000miles per year) was significantly higher than that of drivers with higher annualized mileage, and that 25% of the overall sample were low- mileage drivers according to this criterion. Data were also evaluated by gender and meta-age group (i.e., younger-old: 65-74 and older-old: 75-99), and the results were consistent across these sub-groups. CONCLUSIONS: This study provides strong support for the existence of the LMB. PRACTICAL APPLICATIONS: These results can help to reshape how transportation safety stakeholders view senior drivers in general and help them to focus their efforts on those seniors most in need of either risk-reducing countermeasures or alternative means of transportation.

Performance of basic kinematic thresholds in the identification of crash and near-crash events within naturalistic driving data.

Understanding causal factors for traffic safety-critical events (e.g., crashes and near-crashes) is an important step in reducing their frequency and severity. Naturalistic driving data offers unparalleled insight into these factors, but requires identification of situations where crashes are present within large volumes of data. Sensitivity and specificity of these identification approaches are key to minimizing the resources required to validate candidate crash events. This investigation used data from the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS) and the Canada Naturalistic Driving Study (CNDS) to develop and validate different kinematic thresholds that can be used to detect crash events. Results indicate that the sensitivity of many of these approaches can be quite low, but can be improved by selecting particular threshold levels based on detection performance. Additional improvements in these approaches are possible, and may involve leveraging combinations of different detection approaches, including advanced statistical techniques and artificial intelligence approaches, additional parameter modifications, and automation of validation processes.

The effects of age on crash risk associated with driver distraction.

Background: Driver distraction is a major contributing factor to crashes, which are the leading cause of death for the US population under 35 years of age. The prevalence of secondary-task engagement and its impacts on distraction and crashes may vary substantially by driver age. Methods: Driving performance and behaviour data were collected continuously using multiple cameras and sensors in situ for 3542 participant drivers recruited for up to 3 years for the Second Strategic Highway Research Program Naturalistic Driving Study. Secondary-task engagement at the onset of crashes and during normal driving segments was identified from videos. A case-cohort approach was used to estimate the crash odds ratios associated with, and the prevalence of, secondary tasks for four age groups: 16-20, 21-29, 30-64 and 65-98 years of age. Only severe crashes (property damage and higher severity) were included in the analysis. Results: Secondary-task-induced distraction posed a consistently higher threat for drivers younger than 30 and above 65 when compared with middle-aged drivers, although senior drivers engaged in secondary tasks much less frequently than their younger counterparts. Secondary tasks with high visual-manual demand (e.g. visual-manual tasks performed on cell phones) affected drivers of all ages. Certain secondary tasks, such as operation of in-vehicle devices and talking/singing, increased the risk for only certain age groups. Conclusions: Teenaged, young adult drivers and senior drivers are more adversely impacted by secondary-task engagement than middle-aged drivers. Visual-manual distractions impact drivers of all ages, whereas cognitive distraction may have a larger impact on young drivers.

Driver crash risk factors and prevalence evaluation using naturalistic driving data.

The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.

Older driver fitness-to-drive evaluation using naturalistic driving data.

PROBLEM: As our driving population continues to age, it is becoming increasingly important to find a small set of easily administered fitness metrics that can meaningfully and reliably identify at-risk seniors requiring more in-depth evaluation of their driving skills and weaknesses. METHOD: Sixty driver assessment metrics related to fitness-to-drive were examined for 20 seniors who were followed for a year using the naturalistic driving paradigm. Principal component analysis and negative binomial regression modeling approaches were used to develop parsimonious models relating the most highly predictive of the driver assessment metrics to the safety-related outcomes observed in the naturalistic driving data. RESULTS: This study provides important confirmation using naturalistic driving methods of the relationship between contrast sensitivity and crash-related events. PRACTICAL APPLICATIONS: The results of this study provide crucial information on the continuing journey to identify metrics and protocols that could be applied to determine seniors' fitness to drive.

COMPARING THE IMPAIRMENT PROFILES OF OLDER DRIVERS AND NON-DRIVERS: TOWARD THE DEVELOPMENT OF A FITNESS-TO-DRIVE MODEL.

The purpose of this research effort was to compare older driver and non-driver functional impairment profiles across some 60 assessment metrics in an initial effort to contribute to the development of fitness-to-drive assessment models. Of the metrics evaluated, 21 showed statistically significant differences, almost all favoring the drivers. Also, it was shown that a logistic regression model comprised of five of the assessment scores could completely and accurately separate the two groups. The results of this study imply that older drivers are far less functionally impaired than non-drivers of similar ages, and that a parsimonious model can accurately assign individuals to either group. With such models, any driver classified or diagnosed as a non-driver would be a strong candidate for further investigation and intervention.