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

Adjunct Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications Pub Date : 2022-09-17 DOI:10.1145/3544999.3552324

Maykel M. P. G. Van Miltenburg, Danny J.A. Lemmers, Angelica M. Tinga, M. Christoph, R. Zon

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Abstract

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. 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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脑电图测量是否可以用于评估自动驾驶汽车在不同程度的分心驾驶下接管控制的性能?探索性研究

司机分心是交通安全的一个问题。大多数研究都集中在验证或量化眼睛越野指标与驾驶表现之间的关系，而没有具体解决分心驾驶的认知方面。目前的研究探讨了脑电图数据在多大程度上能很好地预测分心的司机能否成功地从自动驾驶汽车手中接管控制权。参与者驾驶一辆模拟汽车，同时受到不同程度的干扰。在骑行过程中，参与者被警告要接管控制权，之后控制权被转移。有时在接管控制权后，司机会立即采取刹车动作。结果表明，基于脑电图的数据能够表明参与者分心的程度。然而，基于脑电图的数据不能估计接管控制期间的驾驶性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Adjunct Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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