Driving is an activity that facilitates physical, cognitive, and social stimulation in older adults, ultimately leading to better physical and cognitive health. However, aging is associated with declines in vision, physical health, and cognitive health, all of which can affect driving ability. One way of assessing driving ability is with the use of sensors in the older adult's own vehicle. This paper provides a framework for driving assessment and addresses how naturalistic driving studies can assist in such assessments. The framework includes driving characteristics (how much driving, speed, position, type of road), actions and reactions (lane changes, intersections, passing, merging, traffic lights, pedestrians, other vehicles), destinations (variety and distance, sequencing and route planning), and driving conditions (time of day and season). Data from a subset of Ottawa drivers from the Candrive study is used to illustrate the use of naturalistic driving data. Challenges in using naturalistic driving big data and the changing technology in vehicles are discussed.

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Keywords Big data analysis, Driving assessment, Framework, Naturalistic driving study
Persistent URL dx.doi.org/10.3390/geriatrics3020016
Journal Geriatrics (Switzerland)
Citation
Knoefel, F, Wallace, B, Goubran, R, & Marshall, S. (Shawn). (2018). Naturalistic driving: A framework and advances in using big data. Geriatrics (Switzerland), 3(2). doi:10.3390/geriatrics3020016