Effects of Fatigue on Real-World Driving in Diseased and Control Participants

This study evaluated real world driver errors and sleepiness in 66 drivers with Obstructive Sleep Apnea (OSA) and 34 matched controls (24 younger and 22 older). Driving errors and driver state were derived from analyses of video data from “black-box” event recorders. Sleep fragmentation data in OSA was derived from actigraphy for 15 days prior to beginning standard treatment (positive airway pressure, PAP) and 15 days after beginning PAP treatment. Prior to starting PAP, OSAs appeared sleepier than controls in general and particularly at intersections, while making safety errors following nights with high levels of fragmented sleep compared to matched controls. Adverse effects of sleep fragmentation during the pre-PAP phase were reduced post-PAP. Greater hours of PAP-use were associated with lower sleepiness and errors on the road. PAP-use was associated with a decrease in high sleep fragmented nights. Findings suggest reduction in acute sleepiness is unlikely to be the only mediating factor that explains the driving safety benefits of PAP in OSA

Differences in Simulated Car Following Behavior of Younger and Older Drivers

Older drivers are at risk for vehicle crashes due to impairments of visual processing and attention, placing these drivers at greater risk in driving tasks that require continuous attention to neighboring traffic, especially lead vehicles (LVs). We investigated car following behavior in 42 younger drivers (ages 18 to 44 years) and 58 older drivers (ages 65 to 86 years) in a driving simulator. The drivers were instructed to maintain two car lengths from a virtual LV. The LV varied its velocity according to a sum of three sine waves, making the velocity changes unpredictable to the drivers. A Fourier analysis was performed using the vehicle trajectory data to derive measures of coherence, gain, and delay as indices of car following behavior. These measures as well as headway distance were compared between the two groups. Older drivers were less able to match changes in the LV velocity indicated by lower coherence (0.76 v. 0.84, p=0.019) and larger gain (2.24 v. 1.74, p=0.031). However, these drivers followed further behind the LV than younger drivers, a potential compensatory strategy that may reduce collision risk for older drivers

Risk Factors Associated With Aortic and Carotid Intima-Media Thickness in Adolescents and Young Adults The Muscatine Offspring Study

ObjectivesThis study sought to determine whether cardiovascular risk factors are associated with aortic intima-media thickness (aIMT) and carotid intima-media thickness (cIMT) in adolescents and young adults.BackgroundAtherosclerotic lesions begin developing in youth, first in the distal abdominal aorta and later in the carotid arteries. Knowledge of how risk factors relate to aIMT and cIMT may help in the design of early interventions to prevent cardiovascular disease.MethodsParticipants were 635 members of the Muscatine Offspring cohort. The mean aIMT and cIMT were measured using an automated reading program.ResultsThe mean (SD) values of aIMT and cIMT were 0.63 (0.14) and 0.49 (0.04) mm, respectively. In adolescents (age 11 to 17 years), aIMT was associated with triglycerides, systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), and waist/hip ratio, after adjusting for age, sex, and height. In young adults (age 18 to 34 years), aIMT was associated with those same 5 risk factors, plus high-density lipoprotein cholesterol and pulse pressure. In adolescents, cIMT was associated with SBP, pulse pressure, heart rate, BMI, and waist/hip ratio. In young adults, cIMT was associated with total cholesterol, low-density lipoprotein cholesterol, triglycerides, SBP, DBP, BMI, waist/hip ratio, and glycosylated hemoglobin. In both age groups, aIMT and cIMT were significantly correlated with the Pathobiological Determinants of Atherosclerosis in Youth coronary artery risk score.ConclusionsBoth aIMT and cIMT are associated with cardiovascular risk factors. Using aIMT in adolescents gives information beyond that obtained from cIMT alone. Measurement of aIMT and cIMT may help identify those at risk for premature cardiovascular disease

Contextualizing Naturalistic Driving Data in a Rural State Among Drivers With and Without Obstructive Sleep Apnea

In naturalistic studies, Global Positioning System (GPS) data and date/time stamps can link driver exposure to specific environments (e.g., road types, speed limits, night driving, etc.), providing valuable context for analyzing critical events, such as crashes, near crashes, and breaches of accelerometer limits. In previous work, we showed how to automate this contextualization, using GPS data obtained at 1 Hz and merging this with Geographic Information Systems (GIS) databases maintained by the Iowa Department of Transportation (DOT). Here we further demonstrate our methods by analyzing data from 80 drivers with obstructive sleep apnea (OSA) and 48 controls, and comparing the two groups with respect to several factors of interest. The majority of comparisons found no difference between groups, suggesting similar patterns of exposures to driving environments in OSA and control drivers. However, OSA drivers appeared to spend slightly more time on roads with annual traffic counts of 500-10,000 and less time driving on wider highways, during twilight, and on roads with 10,000-25,000 annual traffic counts

Collision Avoidance Training Using a Driving Simulator in Drivers with Parkinson\u27s Disease: A Pilot Study

Parkinson’s disease (PD) impairs driving performance, and simulator studies have shown increased crashes compared to controls. In this pilot study, eight drivers with PD participated in three drive sessions with multiple simulator intersections of varying visibility and traffic load, where an incurring vehicle posed a crash risk. Over the course of the three sessions (once every 1-2 weeks), we observed reduction in crashes (p=0.059) and reaction times (p=0.006) to the vehicle incursion. These findings suggest that our simulator training program is feasible and potentially useful in drivers with PD. Future research questions include transfer of training to different driving tasks, duration of benefit, and the effect on long term real life outcomes in comparison to a standard intervention (e.g., driver education class) in a randomized trial

Feedback from Naturalistic Driving Improves Treatment Compliance in Drivers with Obstructive Sleep Apnea

As part of a study in drivers with obstructive sleep apnea (OSA), we conducted a randomized clinical trial to assess whether individualized feedback can increase compliance with continuous positive airway pressure (CPAP) therapy. After completing 3.5 months of naturalistic driving monitoring, OSA drivers were randomized either to receive an intervention, which was feedback regarding their own naturalistic driving record and CPAP compliance, or to receive no such intervention. In the week immediately after the intervention date, drivers receiving feedback (n=30) improved their CPAP usage by an average of 35.8 minutes per night (p=0.008; 95% CI=9.6, 62.0) to a mean level of 296 minutes. By contrast, CPAP usage in the non-feedback group (n=36) decreased an average of 27.5 minutes per night (p=0.022; 95% CI=4.0, 51.0) to a mean level of 236 minutes. The mean group-specific changes were higher (better) in the feedback group than in the non-feedback group during the first, second, and third weeks of follow-up (p0.25 in all cases). Our study suggests that CPAP compliance can be increased using individualized feedback, but that follow-up feedback sessions or reminders may be necessary for sustained improvement

Linking GPS Data to GIS Databases in Naturalistic Studies: Examples from Drivers with Obstructive Sleep Apnea

In naturalistic studies, it is vital to give appropriate context when analyzing driving behaviors. Such contextualization can help address the hypotheses that explore a) how drivers perform within specific types of environment (e.g., road types, speed limits, etc.), and b) how often drivers are exposed to such specific environments. In order to perform this contextualization in an automated fashion, we are using Global Positioning System (GPS) data obtained at 1 Hz and merging this with Geographic Information Systems (GIS) databases maintained by the Iowa Department of Transportation (DOT). In this paper, we demonstrate our methods of doing this based on data from 43 drivers with obstructive sleep apnea (OSA). We also use maps from GIS software to illustrate how information can be displayed at the individual drive or day level, and we provide examples of some of the challenges that still need to be addressed

Pilot Results on Forward Collision Warning System Effectiveness in Older Drivers

Advanced Driver Assistance Systems (ADAS) have largely been developed with a “one-size-fits-all” approach. This approach neglects the large inter-individual variability in perceptual and cognitive abilities that affect aging ADAS users. We investigated the effectiveness of a forward collision warning (FCW) with fixed response parameters in young and older drivers with differing levels of cognitive functioning. Drivers responded to a pedestrian stepping into the driver’s path on a simulated urban road. Behavioral metrics included response times (RT) for pedal controls and two indices of risk penetration (e.g., maximum deceleration and minimum time-to-collision (TTC)). Older drivers showed significantly slower responses at several time points compared to younger drivers. The FCW facilitated response times (RTs) for older and younger drivers. However, older drivers still showed smaller safety gains compared to younger drivers at accelerator pedal release and initial brake application when the FCW was active. No significant differences in risk metrics were observed within the condition studied. The results demonstrate older drivers likely differ from younger drivers using a FCW with a fixed parameter set. Finally, we briefly discuss how future research should examine predictive relationships between domains of cognitive functioning and ADAS responses to develop parameter sets to fit the individual

“Choking Under Pressure” in Older Drivers

Aging can impair executive control and emotion regulation, affecting driver decision-making and behavior, especially under stress. We used an interactive driving simulator to investigate ability to make safe left-turns across oncoming traffic under pressure in 13 older (\u3e 65 years old) and 16 middle-aged (35-56 years old) drivers. Drivers made left-turns at an uncontrolled intersection with moderately heavy oncoming traffic. Gaps between oncoming vehicles varied and increased gradually from 2 s to 10 s. Drivers made two left-turns with a vehicle honking aggressively behind (pressure condition), and two left-turns without the honking vehicle (control condition). Results showed that middle-aged drivers made more cautious turning decisions under pressure (by waiting for larger and safer gaps, p \u3c .001), but older drivers did not. Further, older driver turning paths deviated under pressure compared to the control condition (p \u3c .05), but the middle-aged group did not. Moreover, across all subjects, better executive function was significantly correlated with larger increases of accepted gap size from control to honking (p \u3c .01). The findings suggest that older drivers are more sensitive to traffic challenges from environmental pressure and that neural models of older driver performance and safety must factor in age-related changes in executive control and emotion processing

Predicting Driver Safety in Parkinson’s Disease: An Interim Report of an Ongoing Longitudinal Study

This article summarizes the baseline results of an ongoing longitudinal, NIH-funded study on prediction of driver safety in patients with Parkinson’s disease (PD). Patients with even mild to moderate PD who drive and live independently suffer from visual and cognitive dysfunction, which appear to be the main contributors to decreased driving performance and safety, rather than the motor dysfunction for which PD is known