Hungund Apoorva Pramod, Deshmukh Radhika Jayant, Hosadurga Niraj, Pradhan Anuj Kumar
AAA Foundation for Traffic Safety, Washington, District of Columbia.
Mechanical and Industrial Engineering Department, University of Massachusetts, Amherst, Massachusetts.
Traffic Inj Prev. 2025 Jun 27:1-8. doi: 10.1080/15389588.2025.2508383.
Automated Driving Systems (ADS), classified as Level 3 automated systems (SAE 2021), can potentially reduce risks by conditionally taking control of the driving task. However, drivers must remain alert and be ready to take back control if necessary. This may introduce risks, especially if drivers are distracted. Observing driver behaviors as they engage in different types of NDRTs could help understand how behaviors differ while driving with Level 3 automation. To that end, in this study, we observed drivers when driving with Level 3 automation. Specifically, we analyzed eye movements, non-driving-related task (NDRT) engagement, and responses to takeover requests (TOR) to understand behaviors during automation and transitions to manual driving.
We conducted a simulator study with 24 fully licensed drivers. Participants drove in a simulator equipped with Level 3 automation and performed two NDRTs: a Surrogate Reference Task and a cellphone task. Drivers were notified visually and verbally about automation status and TORs. Participants' gaze behavior and takeover times were measured during the drive, and post-drive surveys assessed trust and usability scores.
NDRT type had a significant impact on takeover time, with drivers taking longer to take over during cellphone tasks. Drivers tended to focus more on non-driving related areas right until a TOR. After TORs, drivers tended to shift focus to the Instrument Cluster, underlining the criticality of displaying information about the TOR. Trust and usability scores were comparable across groups, suggesting that drivers generally found the system easy to use and exhibited a reasonable level of trust in it.
Findings reveal that regardless of the NDRT, drivers continued engaging in NDRTs right up till the TOR. Designing intuitive, context-specific interfaces that guide drivers' attention to driving-related areas and provide information can improve drivers' awareness of the TOR and, consequently, their takeover performance. The findings provide significant insights on the potential methods to keep drivers aware of their surroundings while using automation, and while transitioning to manual control. These insights provide information on driving behaviors with Level 3 automation, specifically how fully licensed drivers engage with distraction while driving with Level 3.
自动驾驶系统（ADS）被归类为3级自动化系统（SAE，2021年），可以通过有条件地控制驾驶任务来潜在地降低风险。然而，驾驶员必须保持警觉，并在必要时准备好收回控制权。这可能会带来风险，特别是当驾驶员分心时。观察驾驶员在进行不同类型的非驾驶相关任务（NDRT）时的行为，有助于了解在使用3级自动化驾驶时行为有何不同。为此，在本研究中，我们观察了驾驶员在使用3级自动化驾驶时的情况。具体而言，我们分析了眼睛运动、非驾驶相关任务（NDRT）参与情况以及对接管请求（TOR）的反应，以了解自动化过程中以及向手动驾驶过渡期间的行为。
我们对24名拥有全驾照的驾驶员进行了模拟器研究。参与者在配备3级自动化的模拟器中驾驶，并执行两项非驾驶相关任务：一项替代参考任务和一项手机任务。通过视觉和语音向驾驶员通知自动化状态和接管请求。在驾驶过程中测量参与者的注视行为和接管时间，并在驾驶后通过问卷调查评估信任度和可用性得分。
非驾驶相关任务类型对接管时间有显著影响，驾驶员在执行手机任务时接管时间更长。驾驶员在接到接管请求之前往往更关注非驾驶相关区域。接到接管请求后，驾驶员往往将注意力转移到仪表盘上，这突出了显示接管请求信息的重要性。各组的信任度和可用性得分相当，这表明驾驶员通常认为该系统易于使用，并对其表现出合理程度的信任。
研究结果表明，无论执行何种非驾驶相关任务，驾驶员在接到接管请求之前都会继续进行该任务。设计直观、针对具体情境的界面，引导驾驶员将注意力转向与驾驶相关的区域并提供信息，可以提高驾驶员对接管请求的意识，从而改善他们的接管表现。这些研究结果为在使用自动化以及向手动控制过渡期间让驾驶员保持对周围环境的意识的潜在方法提供了重要见解。这些见解提供了有关3级自动化驾驶行为的信息，特别是拥有全驾照的驾驶员在使用3级自动化驾驶时如何应对分心情况。
