Evaluating the cognitive and psychological effects of real-time auditory travel information on drivers using EEG

ABSTRACT

Real-time travel information design with inadequate consideration of human factors can lead to driver distraction and diminish road safety. This study measures drivers’ brain electrical activity patterns to evaluate multiple aspects of driver cognition and psychology under real-time information provision using insights from the neuroscience domain on the localisation of brain functions. The brain electrical activity patterns of 84 participants are collected using an electroencephalogram (EEG) in an interactive driving simulator environment. The impacts of real-time auditory travel information characteristics (amount, sufficiency, and content) and different time stages of interaction with information provision (before, during, and after) on the frequency band powers of EEG signals in different brain regions are analyzed using linear mixed models. Study results illustrate that drivers exert more cognitive effort to perceive/process information on routes with complex driving environments. Insufficient information may evoke increased attention to internal processing and memory processing on routes characterised by higher travel time uncertainty, while route recommendation to switch to such routes may increase drivers’ stress and anxiety. The study findings can aid information providers, both private and public, as well as auto manufacturers to incorporate driver cognition in designing safer real-time information and their delivery systems.

KEYWORDS:

• Real-time information
• driver cognition
• driver psychology
• driving simulator
• electroencephalography (EEG)
• linear mixed model

Acknowledgements

This research was funded by the United States Department of Transportation (USDOT) through the Region 5 University Transportation Center: Center for Connected and Automated Transportation (grant number 69A3551747105). Any opinions or findings expressed in this material are those of the authors and do not necessarily reflect the views of the USDOT. The authors would also like to thank the students from the NEXTRANS Center at Purdue University for their assistance in running the driving simulator experiments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

CRediT authorship contribution statement

Shubham Agrawal: Conceptualisation, Data curation, Formal analysis, Investigation, Methodology, Software, Project administration, Visualisation, Writing – Original draft. Srinivas Peeta: Conceptualisation, Methodology, Project administration, Writing – Review & Editing, Resources, Supervision, Funding acquisition. Irina Benedyk: Investigation, Methodology, Writing – Review & Editing.

Funding

This work was supported by U.S. Department of Transportation: [Grant Number 69A3551747105].