Proactive vs. reactive car driving: EEG evidence for different driving strategies of older drivers

PLoS One. 2018 Jan 19;13(1):e0191500. doi: 10.1371/journal.pone.0191500. eCollection 2018.

Abstract

Aging is associated with a large heterogeneity in the extent of age-related changes in sensory, motor, and cognitive functions. All these functions can influence the performance in complex tasks like car driving. The present study aims to identify potential differences in underlying cognitive processes that may explain inter-individual variability in driving performance. Younger and older participants performed a one-hour monotonous driving task in a driving simulator under varying crosswind conditions, while behavioral and electrophysiological data were recorded. Overall, younger and older drivers showed comparable driving performance (lane keeping). However, there was a large difference in driving lane variability within the older group. Dividing the older group in two subgroups with low vs. high driving lane variability revealed differences between the two groups in electrophysiological correlates of mental workload, consumption of mental resources, and activation and sustaining of attention: Older drivers with high driving lane variability showed higher frontal Alpha and Theta activity than older drivers with low driving lane variability and-with increasing crosswind-a more pronounced decrease in Beta activity. These results suggest differences in driving strategies of older and younger drivers, with the older drivers using either a rather proactive and alert driving strategy (indicated by low driving lane variability and lower Alpha and Beta activity), or a rather reactive strategy (indicated by high driving lane variability and higher Alpha activity).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aging / physiology*
  • Aging / psychology*
  • Alpha Rhythm
  • Attention / physiology
  • Automobile Driving / psychology*
  • Behavior
  • Beta Rhythm
  • Cognition / physiology
  • Computer Simulation
  • Electroencephalography
  • Female
  • Humans
  • Male
  • Middle Aged
  • Task Performance and Analysis
  • Theta Rhythm
  • Wind
  • Workload / psychology
  • Young Adult

Grants and funding

This work was supported by a grant awarded to MK by the German Research Foundation (DFG http://www.dfg.de/; KA 412072-1). The publication of this article was supported by the Open Access Fund of the Leibniz Association and by the Open Access Fund of the Technical University of Dortmund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding for this study.