The broad goal of this research project is to identify patterns of driving performance associated with age-related cognitive decline. This project to date has disclosed several novel relationships between cognitive abilities such as attention, decision-making and memory in older drivers, and their driving performance, patterns of safety errors, and susceptibility to crashes. Guided by our findings thus far, the next phase of this project addresses several specific aims to: (1) obtain a comprehensive longitudinal picture of age-related changes in older driver abilities by following a cohort of 120 drivers over age 65, most of whom are currently enrolled in this project;(2) study a particularly high-risk group of 100 older drivers over age 65 who had their licenses suspended and reinstated (n = 50) or revoked (n = 50) in the past year;(3) determine which cognitive impairments contribute the most to driving errors and crashes and to develop predictive models of driving fitness. A comprehensive battery of neuropsychological and psychophysical measures, an instrumented vehicle, and a state-of-the-art driving simulator will be used to assess a set of cognitive and behavioral variables that may contribute to driver safety errors and crashes. Experimental driving scenarios will address mechanisms underlying side-impact collisions at traffic intersections, collisions with lead or merging vehicles due to inaccurate time-to-contact estimates, and run-off-the-road crashes on curved roads. As an outcome of these studies, we expect to: (1) obtain a more detailed picture of the natural history of driving and cognition in a stable cohort of aging individuals;(2) obtain better chronological evidence on predicting future driving success or failure based on cognitive abilities and demographic factors at any given time;(3) determine which cognitive impairments contribute the most to specific driving safety errors and crash types in different at-risk groups of older drivers. Identifying reliable and valid cognitive and driving performance measures for predicting driving safety errors and crashes will advance driver risk assessment, mitigate vehicle crashes and injuries caused by cognitively impaired drivers, and protect the mobility and social independence of elderly drivers who do not pose undue safety risks.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
Project #
Application #
Study Section
Cognition and Perception Study Section (CP)
Program Officer
King, Jonathan W
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Iowa
Schools of Medicine
Iowa City
United States
Zip Code
McLaurin, Elease J; Lee, John D; McDonald, Anthony D et al. (2018) Using Topic Modeling to Develop Multi-level Descriptions of Naturalistic Driving Data from Drivers with and without Sleep Apnea. Transp Res Part F Traffic Psychol Behav 58:25-38
Aksan, Nazan; Sager, Lauren; Hacker, Sarah et al. (2017) Individual differences in cognitive functioning predict effectiveness of a heads-up lane departure warning for younger and older drivers. Accid Anal Prev 99:171-183
Dawson, Jeffrey D; Bair, Elizabeth; Askan, Nazan et al. (2017) CONTEXTUALIZING NATURALISTIC DRIVING DATA IN A RURAL STATE AMONG DRIVERS WITH AND WITHOUT OBSTRUCTIVE SLEEP APNEA. Proc Int Driv Symp Hum Factors Driv Assess Train Veh Des 2017:23-29
Aksan, Nazan; Marini, Robert; Tippin, Jon et al. (2017) Effects of Actigraphically Acquired Sleep Quality onDriving Outcomes in Obstructive Sleep Apnea Patientsand Control drivers: A Naturalistic Study. Proc Int Driv Symp Hum Factors Driv Assess Train Veh Des 2017:242-250
Aksan, Nazan; Hacker, Sarah D; Sager, Lauren et al. (2016) Correspondence between Simulator and On-Road Drive Performance: Implications for Assessment of Driving Safety. Geriatrics (Basel) 1:
Tippin, Jon; Aksan, Nazan; Dawson, Jeffrey et al. (2016) Sleep remains disturbed in patients with obstructive sleep apnea treated with positive airway pressure: a three-month cohort study using continuous actigraphy. Sleep Med 24:24-31
Aksan, Nazan; Sager, Lauren; Hacker, Sarah et al. (2016) Forward Collision Warning: Clues to Optimal Timing of Advisory Warnings. SAE Int J Transp Saf 4:107-112
Rusch, Michelle L; Schall Jr, Mark C; Lee, John D et al. (2016) Time-to-contact estimation errors among older drivers with useful field of view impairments. Accid Anal Prev 95:284-91
Muir, Carlyn; Charlton, Judith L; Odell, Morris et al. (2016) Medical review licensing outcomes in drivers with visual field loss in Victoria, Australia. Clin Exp Optom 99:462-8
Lester, Benjamin D; Sager, Lauren N; Dawson, Jeffrey et al. (2015) PILOT RESULTS ON FORWARD COLLISION WARNING SYSTEM EFFECTIVENESS IN OLDER DRIVERS. Proc Int Driv Symp Hum Factors Driv Assess Train Veh Des 2015:345-351

Showing the most recent 10 out of 55 publications