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首页> 外文期刊>Intelligent Transportation Systems Magazine, IEEE >Ready for Take-Over? A New Driver Assistance System for an Automated Classification of Driver Take-Over Readiness
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Ready for Take-Over? A New Driver Assistance System for an Automated Classification of Driver Take-Over Readiness

机译：准备好接管了吗？自动分类驾驶员接管准备情况的新驾驶员辅助系统

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摘要

Recent studies analyzing driver behavior report that various factors may influence a driver's take-over readiness when resuming control after an automated driving section. However, there has been little effort made to transfer and integrate these findings into an automated system which classifies the driver's take-over readiness and derives the expected take-over quality. This study now introduces a new advanced driver assistance system to classify the driver's takeover readiness in conditionally automated driving scenarios. The proposed system works preemptively, i.e., the driver is warned in advance if a low take-over readiness is to be expected. The classification of the take-over readiness is based on three information sources: (i) the complexity of the traffic situation, (ii) the current secondary task of the driver, and (iii) the gazes at the road. An evaluation based on a driving simulator study with 81 subjects showed that the proposed system can detect the take-over readiness with an accuracy of 79%. Moreover, the impact of the character of the take-over intervention on the classification result is investigated. Finally, a proof of concept of the novel driver assistance system is provided showing that more than half of the drivers with a low take-over readiness would be warned preemptively with only a 13% false alarm rate.
机译：分析驾驶员行为的最新研究表明，在自动驾驶部分恢复控制后，各种因素都可能影响驾驶员的接管准备。但是，几乎没有做出任何努力来将这些发现转移并集成到自动系统中，该系统对驾驶员的接管准备情况进行分类并得出预期的接管质量。现在，这项研究引入了一种新的高级驾驶员辅助系统，以在有条件的自动驾驶情况下对驾驶员的接管准备情况进行分类。所提出的系统是抢先工作的，即，如果期望低接管准备性，则提前警告驾驶员。接管准备情况的分类基于以下三个信息源：（i）交通情况的复杂性，（ii）驾驶员当前的次要任务以及（iii）凝视道路。根据对81位受试者进行的驾驶模拟器研究进行的评估表明，所提出的系统可以以79％的精度检测接管准备情况。此外，研究了接管干预的特征对分类结果的影响。最后，提供了一种新颖的驾驶员辅助系统的概念证明，显示出超过一半的接管准备程度低的驾驶员将被预警，只有13％的误报率。

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