Abstract: The goal of this effort was to explore the use of naturalistic driving data to identify those with pre-mild cognitive impairment (MCI) and to evaluate their use of advanced driver assistance systems (ADAS). Participants were delineated into either case or control groups based on answers to memory impairment questions. Metrics were calculated to evaluate the differences in driving patterns as well as usage of ADAS. Results showed moderate lane centering (LC) usage rates, with almost half of the participants driving ADAS-equipped vehicles using those technologies at any point during the study period. Statistically significant results showed the lowest average number of trips per day for cases who drove ADAS vehicles compared to cases who drove non ADAS-equipped vehicles. These results are inconsistent with other findings that have found no significant difference in driving exposure between MCI cases and controls and that MCI cases may even engage in a greater number of trips. However, in such prior efforts, they were evaluating drivers with diagnosed MCI, and none of the vehicles in those studies were equipped with ADAS. This study found that those with pre-MCI demonstrated differences compared to cognitively normal individuals.

Jon Antin, Ph.D., is a Certified Human Factors Professional with more than 35 years of experience in the field. He currently serves as Vulnerable Road User Safety Group Lead at the Virginia Tech Transportation Institute (VTTI). Dr. Antin has led several projects related to older adult driver safety and mobility emphasizing the effects of capability, behavior, training, generational affiliation, and attitude. He currently serves as the Research Program Manager for CATM, and he is also a member of the Equity Council for the Region 4 UTC - Center for Regional and Rural Connected Communities (CR2C2), also housed at NC A&T. Overall, he has been responsible for securing and/or managing research funding in excess of $30M at VTTI. Dr. Antin earned his B.S. in Psychology at L.S.U. and his M.S. and Ph.D. degrees in Industrial Engineering and Operations Research (Human Factors Option) at Virginia Tech.