Driving exposure, patterns and safety critical events for older drivers with and without mild cognitive impairment: Findings from a naturalistic driving study

Personality, functional performance, and travel patterns related to older drivers' risky driving behavior: A naturalistic driving study

Older drivers are among the most vulnerable demographics within the road traffic system. The rising number of elderly motorists has raised public concern regarding their driving safety. It is crucial to understand the factors influencing risky driving behaviors among older drivers to enhance their safety. This study aimed to analyze the personality, functional performance, and travel patterns related to older drivers' risky driving behavior. The analysis utilized a sample of 58 older drivers, aged 65 years and above (mean age = 72.41 years; 40 males and 18 females) from the Nagoya metropolitan area. Risky driving behaviors and travel patterns were assessed using naturalistic driving data. Bivariate correlation analysis revealed that impulsivity and diminished contrast sensitivity were significantly correlated with more frequent risky driving behaviors. Additionally, both low driving exposure and high-risk driving routes (i.e., more frequent left and right turns, driving more on minor roads) were significantly correlated with an increased risk of harsh events. Moreover, a strong association was observed between driving exposure and driving route, indicating that the driving route of lower mileage drivers tend to be riskier. When the relationship between driving exposure and risky driving behaviors was adjusted for driving route, the strength of the correlation diminished from 0.35 to 0.16, rendering it insignificant. This partial correlation analysis suggests that the increased driving risk among low-mileage drivers can be partially attributed to their high-risk driving routes. The findings of this study provide further evidence regarding the role of personality in explaining older drivers' risky driving behavior and the explanation of older drivers' low-mileage bias.

Driving among individuals with chronic conditions: A systematic review of applied research using kinematic driving sensors

BACKGROUND

Kinematic driving data studies are a novel methodology relevant to health care, but prior studies have considerable variance in their methods, populations, and findings suggesting a need for critical analysis and appraisal for feasibility and methodological guidelines.

METHODS

We assessed kinematic driving studies of adults with chronic conditions for study feasibility, characteristics, and key findings, to generate recommendations for future study designs, and to identify promising directions for applications of kinematic driving data. PRISMA was used to guide the review and searches included PubMed, CINAHL, and Compendex. Of 379 abstract/titles screened, 49 full-text articles were reviewed, and 29 articles met inclusion criteria of analyzing trip-level kinematic driving data from adult drivers with chronic conditions.

RESULTS

The predominant chronic conditions studied were Alzheimer's disease and related Dementias, obstructive sleep apnea, and diabetes mellitus. Study objectives included feasibility testing of kinematic driving data collection in the context of chronic conditions, comparisons of simulation with real-world kinematic driving behavior, assessments of driving behavior effects associated with chronic conditions, and prognostication or disease classification drawn from kinematic driving data. Across the studies, there was no consensus on devices, measures, or sampling parameters; however, studies showed evidence that driving behavior could reliably differentiate between adults with chronic conditions and healthy controls.

CONCLUSIONS

Vehicle sensors can provide driver-specific measures relevant to clinical assessment and interventions. Using kinematic driving data to assess and address driving measures of individuals with multiple chronic conditions is positioned to amplify a functional outcome measure that matters to patients.

Application of naturalistic driving data: A systematic review and bibliometric analysis

The application of naturalistic driving data (NDD) has the potential to answer critical research questions in the area of driving behavior assessment, as well as the impact of exogenous and endogenous factors on driver safety. However, the presence of a large number of research domains and analysis foci makes a systematic review of NDD applications challenging in terms of information density and complexity. While previous research has focused on the execution of naturalistic driving studies and on specific analysis techniques, a multifaceted aggregation of NDD applications in Intelligent Transportation System (ITS) research is still unavailable. In spite of the current body of work being regularly updated with new findings, evolutionary nuances in this field remain relatively unknown. To address these deficits, the evolutionary trend of NDD applications was assessed using research performance analysis and science mapping. Subsequently, a systematic review was conducted using the keywords "naturalistic driving data" and "naturalistic driving study data". As a result, a set of 393 papers, Published between January 2002-March 2022, was thematically clustered based on the most common application areas utilizing NDD. the results highlighted the relationship between the most crucial research domains in ITS, where NDD had been incorporated, and application areas, modeling objectives, and analysis techniques involving naturalistic databases.

Driving Errors Predicting Pass/Fail On-Road Assessment Outcomes Among Cognitively Impaired Older Drivers

Older drivers with cognitive impairment (CI)/dementia make significantly more driving errors than healthy controls; however, whether driving errors are predictive of pass/fail outcomes in older drivers with CI/dementia are unclear. This study determined the driving errors that predicted failing an on-road assessment in drivers with CI. We retrospectively collected comprehensive driving evaluation data of 80 participants (76.1 ± 9.3 years) from an Ontario driving assessment center. Adjustment to stimuli (area under the curve [AUC] = 0.88), lane maintenance (AUC = 0.84), and speed regulation errors (AUC = 0.85) strongly predicted pass/fail outcomes. Worse performance on the Trails B (time) and Useful Field of View® (Subtest 2, Subtest 3, and risk index) were significantly correlated with adjustment to stimuli (p < .05), lane maintenance (p < .05), and speed regulation errors (p < .05). Adjustment to stimuli, lane maintenance, and speed regulation errors may be critical indicators of failing an on-road assessment in older drivers with CI. Prioritizing these errors may help identify at-risk drivers.

An innovative therapeutic educational program to support older drivers with cognitive disorders: Description of a randomized controlled trial study protocol

Older drivers face the prospect of having to adjust their driving habits because of health problems, which can include neurocognitive disorders. Self-awareness of driving difficulties and the interaction between individual with neurocognitive disorders and natural caregiver seem to be important levers for the implementation of adaptation strategies and for the subsequent voluntary cessation of driving when the cognitive disorders become too severe. This study aims to evaluate an educational program for patient/natural caregiver dyads who wish to implement self-regulation strategies in driving activity, and to improve self-awareness of driving ability. The ACCOMPAGNE program is based on seven group workshops, which target the dyad. The workshops deal with the impact of cognitive, sensory and iatrogenic disorders on driving. They tackle questions about responsibility, and about autonomy and social life. They also provide alternative solutions aimed at maintaining outward-looking activities even if driving is reduced or stopped. A randomized controlled trial is planned to evaluate the effectiveness of the program 2 months and 6 months after inclusion, and to compare this to the effectiveness of conventional approaches. The main outcome of this trial (i.e., the implementation of self-regulated driving strategies), will be measured based on scores on the “Current Self-Regulatory Practices” subscale of the Driver Perception and Practices Questionnaire. The Driving Habits Questionnaire will be used to measure secondary outcomes (indicators of driving changes; indicators of changes in mood, quality of life and caregiver burden; and self-awareness of driving abilities). Indicators will be collected for both patients and natural caregivers. This cognitive, social and psychological program should allow older individuals with cognitive disorders to drive more safely, and help to maintain the quality of life and mood of both patient and natural caregiver despite driving limitations. The patient's care path would be optimized, as he/she would become an actor in the process of giving up driving, which will, most certainly, be needed at some point in the progress of neurocognitive disorders. This process ranges from becoming aware of driving difficulties, to implementing self-regulation strategies, through to complete cessation of driving when necessary.

Clinical trial registration number

NCT04493957.

A Longitudinal Study Examining Self-Regulation Practices in Older Drivers with and without Suspected Mild Cognitive Impairment

Purpose

Mild cognitive impairment can impact driving performance and self-regulation practices. However, there is little evidence on how cognitive impairment may impact these self-regulation practices over a period of time. Therefore, the aim of this study was to examine changes in the number and type of situations in which older drivers with and without suspected mild cognitive impairment (MCI) self-regulate their driving over a one-year period, after accounting for relevant confounders.

Participants and Methods

A longitudinal cohort study involving older drivers (65+ years) from metropolitan Western Australia was interviewed by a telephone interview at baseline and one-year follow-up. The Telephone Cognitive Screen (T-CogS) was also administered to determine changes in their cognitive status. The outcome of interest was the number and type of situations older drivers self-regulated their driving.

Results

A total of 670 drivers were interviewed at baseline (suspected MCI: n = 227; no cognitive impairment: n = 443) and one-year follow-up (suspected MCI: n = 251; no cognitive impairment: n = 419), which provided 1340 observations. Drivers with suspected MCI increased the number of driving situations in which they self-regulated by 13% over a period of one-year compared with drivers without cognitive impairment (IRR = 1.13, 95% CI = 1.02–1.27, p = 0.025). Specifically, drivers with suspected MCI had 60% increased odds of self-regulating when “making turns across oncoming traffic” compared with drivers without cognitive impairment (unadjusted OR = 1.60, 95% CI = 1.02–2.53, p = 0.041). Other significant factors included being female (IRR = 1.87, 95% = 1.52–2.32, p = 0.001), aged 75+ years (IRR = 1.33, 95% CI = 1.10–1.60, p = 0.003), higher number of comorbidities (1–3 comorbidities: IRR = 1.26, 95% CI = 1.01–1.58, p = 0.040; 4+ comorbidities: IRR = 1.39, 95% CI = 1.08–1.78, p = 0.011), “decreased driving confidence” (IRR = 1.32, 95% CI = 1.10–1.58, p-value = 0.003) and “preference of having someone else drive” (IRR = 1.38, 95% CI = 1.12–1.70, p = 0.003). Having one or more traffic infringements was also associated with a decrease in the number of self-regulated driving situations (IRR = 0.80, 95% CI = 0.67–0.95, p = 0.011).

Conclusion

Over a one-year period, drivers with suspected MCI increased the number of situations in which they self-regulated their driving compared with drivers without cognitive impairment, particularly when “making turns across oncoming traffic”. Future studies should examine whether this increase in the types and number of self-regulated driving situations is enough to compensate for declines in cognition.

Assessing safety critical driving patterns of heavy passenger vehicle drivers using instrumented vehicle data - An unsupervised approach

Assessing the individual's driving profile and identifying the at-fault behaviors contributes to road safety, riding comfort, and driver assistance systems. This study proposes a framework to identify aggressive driving patterns in longitudinal control using real-time driving profiles of heavy passenger vehicle (HPV) drivers. The main objective is to detect and quantify the instantaneous driving decisions and classify the identified maneuvers (acceleration, braking) using unsupervised machine learning techniques without any prior-ground truth. To this end, total 8295 acceleration events, and 7151 braking events, were extracted from 142 driving profiles collected using high-resolution (10 Hz) GPS instrumentation. The principal component analysis was conducted on a multi-dimensional feature set, followed by a two-stage k-means clustering on the reduced feature subspace. The results showed that 86.5% of accelerations and 65.3% of braking maneuvers were characterized as non-aggressive, indicating safe or base-line driving behavior. However, 13.5% of accelerations and 34.7% of braking maneuvers were featured to be aggressive, indicative of the actual risky behaviors. Further analysis demonstrated the heterogeneity in drivers' trip-level frequency of aggressive maneuvers and highlighted the need for a continuous driving assessment. The study also revealed that the thresholds derived from the obtained clusters featuring the aggressive accelerations (+0.3 to +0.48 g) and aggressive braking (-0.42 to -0.27 g) maneuvers were beyond the acceptable limits of passenger safety and comfort. The insights from the study aids in developing driver assistance systems for personalized feedback provision and improve driver behavior.

The Impact of Cognition and Gender on Speeding Behaviour in Older Drivers with and without Suspected Mild Cognitive Impairment

Purpose

Mild cognitive impairment and gender can impact different aspects of driving performance and behaviour in older drivers. However, there is little evidence on how these may affect naturalistic speeding behaviour. Therefore, the aim of this study was to examine the relationship between speeding events and cognitive status for older male and female drivers.

Participants and Methods

A naturalistic driving study collected objective driving information over a two-week period using an in-vehicle monitoring device from 36 older drivers with suspected mild cognitive impairment and 35 older drivers without cognitive impairment. The outcome of interest examined was the number of speeding events, defined as travelling 5+ km/h over the posted speed limit for at least a minute.

Results

The majority of participants (n=58, 81.69%) did not have a speeding event during the two-week monitoring period. Twenty-three speeding events were recorded among seven drivers with suspected mild cognitive impairment and six drivers without cognitive impairment. The majority of speeding events (82.61%) were by older male drivers and occurred in 60km/h and 70km/h speed zones. The results of the two negative binomial regression models found that in older male drivers, suspected mild cognitive impairment (IRR=7.45, 95% CI=1.53–36.15, p=0.01) was associated with a significantly higher rate of speeding events, while increasing age was associated with a lower rate of speeding events (IRR=0.80, 95% CI=0.64–1.00, p=0.04). For older female drivers, there were no factors significantly associated with the rate of speeding events.

Conclusion

While the overall number of speeding events were infrequent, suspected mild cognitive impairment was associated with a significant increase in the rate of speeding events for older male drivers, but not for older female drivers. Speeding interventions and injury prevention policy strategies may need to be targeted differently for male and female drivers with mild cognitive impairment.