What is it about?
The current study explores to what extent electroencephalogram data is a good predictor of how successful a distracted driver will be able to take over control from an autonomous vehicle. Participants were driving a simulated car while being exposed to varying levels of distraction. During the ride at several moments the participants were warned to take over control, after which the control was transferred. Sometimes after taking over the control an immediate break action of the drivers was expected. It turned out that electroencephalogram based data is able to indicate to what extent participants are distracted. However, electroencephalogram based data is not able to estimate driving performance during take over control.
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Why is it important?
Driver distraction is a concern for traffic safety. Most research has been focused on validating or quantifying the relationship between eyes-off-road metrics and driving performance without specifically addressing cognitive aspects of distracted driving.
Perspectives
I have always been fascinated in optimizing human effectiveness. Humans have limited mental resources to devote to the execution of tasks. When a driver experiences driving demands that exceed his or her mental capabilities, then he or she can become mentally overloaded and the driving performance will decrease. A decrease in driving performance will increase the likelihood of mistakes when driving. Mental overload is therefore a danger to road safety. Brain activity changes as mental workload changes, and brain activity measurements can be used to estimate mental workload.
Maykel van Miltenburg
Royal Netherlands Aerospace Centre - NLR
Read the Original
This page is a summary of: Can EEG Measurements be Used to Estimate the Performance of Taking over Control from an Autonomous Vehicle for Different Levels of Distracted Driving? An Explorative Study, September 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3544999.3552324.
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