Cortical dynamics of automated driving across the spectrum of cognitive aging: A proof-of-concept study

Background: Automated vehicle (AV) technology may potentially improve road safety, independence, and mobility in older drivers with cognitive impairment (CI). Physiological sensors will be useful to provide feedback of the driver state to the AV controller system. The aim of this study was to compare changes in cortical activity recorded using electro-encephalography (EEG) during conditional automation between older adults with normal cognition (NC) and CI. Methods: Fourteen older adults (age 72.43 (6.00); 10 (71%) women; nine with NC and five with CI) completed two driving simulator scenarios. Scenario 1 included conditional automated driving with an emergency take-over request (TOR) at the end of the drive. Scenario 2 was identical but with an additional non-driving related task (NDRT). EEG was recorded in three driver tasks: resting; automation; and TOR. The interaction effect of driver task (resting state - automated driving - TOR) and cognitive status (CI - NC) on frontal theta power was calculated using linear mixed models. Results: A significant interaction effect of driver task*cognitive status on frontal theta power was found in the scenario without NDRT (F = 5.85; p = 0.001). Post-hoc effects showed that older adults with CI showed greater changes in frontal theta power from resting state to the TOR event (& beta; = 16.44 & PLUSMN; 6.35; p = 0.01) and from automated driving to the TOR event (& beta; = 17.91 & PLUSMN; 6.11; p = 0.006) compared to controls. No interaction effects were found on frontal theta power in the scenario with NDRT. Conclusions: Our study provides proof-of-concept that older adults with CI show increased cortical activity while engaging with AV technology compared to neurotypical older adults.