Abstract
BackgroundDriver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. To study human cognition under a specific driving task, simulated real driving using virtual reality (VR)-based simulation and designed dual-task events are built, which include unexpected car deviations and mathematics questions.MethodsWe designed five cases with different stimulus onset asynchrony (SOA) to investigate the distraction effects between the deviations and equations. The EEG channel signals are first converted into separated brain sources by independent component analysis (ICA). Then, event-related spectral perturbation (ERSP) changes of the EEG power spectrum are used to evaluate brain dynamics in time-frequency domains.ResultsPower increases in the theta and beta bands are observed in relation with distraction effects in the frontal cortex. In the motor area, alpha and beta power suppressions are also observed. All of the above results are consistently observed across 15 subjects. Additionally, further analysis demonstrates that response time and multiple cortical EEG power both changed significantly with different SOA.ConclusionsThis study suggests that theta power increases in the frontal area is related to driver distraction and represents the strength of distraction in real-life situations.
Highlights
Driver distraction is a significant cause of traffic accidents
Each subject participated in four simulated sessions inside a car with hands on the steering wheel to keep the car in the center of the third lane, which was numbered from the left lane, in a virtual reality (VR) surround scene on a four-lane freeway [23]
The response time for mathematical problem solving in dual-task condition is significantly higher than that in single-task condition
Summary
Driver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. Driver distraction has been identified as the leading cause of car accidents. The U.S National Highway Traffic Safety Administration had reported driver distraction as a high priority area about 20-30% of car accidents [1]. Distraction during driving by any cause is a significant contributor to road traffic accidents [2,3]. Commercial vehicle operators with complex incar technologies cause an increased risk as they may become increasingly distracting in the years to come [4,5]. Tijerina showed driver distraction from measurements of the static completion time of an in-vehicle task [6].
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