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Takeover request (TOR) effects during different automated vehicle failures
Journal of Intelligent Transportation Systems ( IF 2.8 ) Pub Date : 2021-03-10 , DOI: 10.1080/15472450.2021.1891536
Chelsea A. DeGuzman 1 , Dina Kanaan 1 , Samantha A. Hopkins 1 , Birsen Donmez 1
Affiliation  

Abstract

Research on driving automation has investigated the use of takeover requests (TORs) to warn drivers about automation failures that require their intervention. Such failures can occur with information in the environment that drivers can use to anticipate them (e.g., system-limit failures) or without such information (e.g., system-malfunction failures). There is a lack of research comparing the effectiveness of TORs prior to these different failure types. We conducted a simulator study with 19 participants to investigate whether the effect of a TOR on drivers’ monitoring and takeover performance differed by failure type. Drivers were trained on automation limits so that they could identify upcoming system-limit failures. We evaluated gaze behaviors starting from 6 seconds before the failure (corresponding to TOR onset in TOR drives and the equivalent point in no-TOR drives) until drivers took over. The effect of TORs on monitoring the roadway was significant only for system-malfunction failures, with participants looking more at the roadway in TOR drives compared to no-TOR drives. For system-limit failures, the TOR did not provide any benefit in terms of visual attention to the roadway, likely because participants were already looking at the roadway because they could anticipate the failure. However, having a TOR for system-limit failures was associated with faster takeover time than not having a TOR. Although the TOR may not have had monitoring benefits when environmental information was available, our findings suggest it was still useful as a confirmation of impending failures and a prompt to take over control of the vehicle.



中文翻译:

不同自动车辆故障期间的接管请求(TOR)效果

摘要

关于驾驶自动化的研究已经调查了使用接管请求(TOR)来警告驾驶员有关需要驾驶员干预的自动化故障的信息。如果驱动程序可以使用环境中的信息来预测此类故障(例如,系统限制故障),或者没有此类信息(例如,系统故障),则可能发生此类故障。缺乏研究比较这些不同故障类型之前TOR的有效性的研究。我们与19名参与者进行了模拟器研究,以研究TOR对驾驶员监控和接管绩效的影响是否因故障类型而异。对驾驶员进行了自动化限制方面的培训,以便他们可以识别即将到来的系统限制故障。我们评估了从故障发生前的6秒开始的凝视行为(对应于TOR驱动器中的TOR发作和无TOR驱动器中的等效点),直到驾驶员接管为止。TOR对道路的监控效果仅对系统故障而言很重要,与无TOR驾驶相比,参与者更多地关注TOR驾驶中的巷道。对于系统限制的故障,TOR在视觉上关注巷道方面并没有提供任何好处,这可能是因为参与者已经在注视巷道,因为他们可以预见到故障。但是,与没有TOR相比,拥有针对系统限制故障的TOR与更快的接管时间相关联。尽管在获得环境信息后TOR可能没有监测利益,

更新日期:2021-03-11
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