Proper understanding of automation limitations is vital in order for drivers to deal with unexpected critical situations. The present study focuses on explanation-based knowledge of the limitations given to novice drivers who have no knowledge and experience of using driving automation systems. The knowledge is discussed considering (1) the possibility of the automation failing to issue an alert when the driving automation cannot handle the situation and (2) the manner of describing the limitations from either a functional or scenic point of view. An experiment conducted under 2 × 2 conditions of explanation-based knowledge ( n = 24 participants per condition, average age of the participant = 55.9 ± 16.2 years) is implemented in a driving simulator. Data on transition time from automated control to manual control are collected. The results reveal that drivers could intervene more safely if the knowledge is described from a scenic point of view (average ratio of safe intervention = 95%, average reaction time = 2.0 s), as compared to a functional description (88%, 2.3 s). Explicit/scenic knowledge was found to be more beneficial in responding to alerts in such situations involving system limitations as well as in dealing with critical system failures. Further investigation of glance behavior and interviews revealed that novice drivers with explicit/functional knowledge are prone to be over-reliant on the automation’s capability. Therefore, the present study clarified that providing a driver with knowledge about system limitations/failures explicitly while giving is instructive for perceiving and responding to system limitations as well as unexpected hazards due to system failures.

中文翻译：

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部分驾驶自动化中指令系统限制对驾驶员干预行为的影响

正确理解自动化限制对于驾驶员处理意外的危急情况至关重要。本研究的重点是基于解释的知识，这些知识是对没有使用驾驶自动化系统的知识和经验的新手司机的限制。讨论知识时考虑到（1）当驾驶自动化无法处理情况时自动化未能发出警报的可能性，以及（2）从功能或风景的角度描述限制的方式。在基于解释的知识的 2 × 2 条件下进行的实验（每个条件 n = 24 名参与者，参与者的平均年龄 = 55.9 ± 16.2 岁）在驾驶模拟器中实施。收集有关从自动控制到手动控制的过渡时间的数据。结果表明，与功能描述（88%，2.3 s）相比，如果从风景的角度描述知识（安全干预的平均比例= 95%，平均反应时间= 2.0 s），驾驶员可以更安全地进行干预）。在涉及系统限制的情况下以及处理关键系统故障时，明确的/风景知识更有助于响应警报。对扫视行为和访谈的进一步调查显示，具有显式/功能知识的新手司机容易过度依赖自动化的能力。所以，