About this Research Topic
Motor vehicle crashes are a global challenge to public health and the leading cause of injury and mortality in adolescents and young adults worldwide. Research suggests both development and experience are responsible, as the crash rate declines with age at licensure-holding and continuous driving experience. There are multiple transient influences, including distraction while driving (e.g., cell phone use), drug use, and drowsiness, all of which can interfere with attention to the road and the ability to control the vehicle. Furthermore, stable individual differences that are related to attention and motor skills (e.g., ADHD, autism) also play a role.
Older adults are also at heightened risk for motor vehicle crashes, which may be attributable to the decline in attentional and motor skills that accompany the aging process. With cognitive impairment now one of the most important healthcare issues for today’s aging population, recent research shows that poorer cognitive function in older adults may be a risk factor for crashes, even in individuals without diagnosed dementia. Furthermore, dementia can impair driving performance and increase crash risk (reported as 2-18 times higher) in older drivers with dementia compared to age-matched controls.
Despite the hope for autonomous vehicles that can remove the driver from responsibility for the control of the vehicle, these systems are at present only semi-autonomous, still requiring the vigilance of the driver, and a reality that will continue for the foreseeable future. Thus, the need to identify interventions and assessments that can reduce the risk of crashes across age groups and driving conditions, while enabling mobility for those with deficits in driving ability, remains a priority. To this end, there is increasing interest in studying brain processes that might provide insight into the ability to control a vehicle under various driving conditions. These studies typically use driver simulation technology to place drivers behind the wheel while brain processes are monitored, with a few on-road, naturalistic studies also conducted. A variety of neuroscience/neuroimaging methodologies are increasingly used (both standard MRI procedures as well as EEG, fNIRS, and MEG methodologies) in combination with driver assessment, human factors, and human-computer interaction methodologies. In addition, as these data sources challenge analyses, both in terms of structure and size, new methods in traditional and machine learning techniques are increasingly being used.
In this Research Topic, we welcome original research and reviews to (1) spark increased interdisciplinary research that incorporates neuroscientific methods in the study of safe driving as a critical health behavior; and (2) to advance greater understanding of novel neuroscience approaches to driving science.
Keywords: Driving, Brain Development, Neuroimaging, Adolescents, Assisted Driving, Aging
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