Swain Ritwik, Kaye Sherrie-Anne, Rakotonirainy Andry
Centre for Accident Research and Road Safety-Queensland (CARRS-Q), Queensland University of Technology (QUT), Brisbane, Queensland, Australia.
Traffic Inj Prev. 2025;26(4):398-406. doi: 10.1080/15389588.2024.2421215. Epub 2024 Dec 12.
In conditional automation for automated vehicles (AVs), drivers are tasked with remaining vigilant and ready to assume control should the system encounter a malfunction. However, little to no information is provided to the driver either about the AV's intended maneuvers or the AV's awareness of potential threats in the surrounding environment. To address this research gap, the present study proposes 2 human-machine interaction (HMI) concepts: Firstly, the shared intended pathway (SIP), which presents a forecast of the AV's intended maneuvers and, secondly, object recognition bounding boxes (ORBBs), which place transparent blue squares around other road users likely to contribute to a crash.
An online experiment with both within- and between-group factors tested 2 HMI designs: One with both SIP and ORBB and one with SIP only. Six videos were presented sequentially, each depicting 10 to 15 s of automated driving, to 394 participants ( = 28.24 years, 64% male) in Australia. Participants monitored the AV in each of the videos, which were presented in 1 of 3 randomized conditions: no HMI display, SIP only, or SIP + ORBB. Questions after each video measured trust, situational awareness, stress, and user acceptance, as measured by the technology acceptance model (TAM) about user acceptance.
Results suggest that SIP is beneficial in conditional automation monitoring, in terms of reduced stress, increased perceived usefulness, and future intentions to use AVs. Further, ORBB presence increased participant ratings of perceived usefulness and intentions to use AVs compared to no ORBB. The findings also provided support for the TAM, because perceived ease of use and perceived usefulness were found to be significant positive predictors of future intentions to use AVs.
The current study provides some evidence to suggest that SIP may be beneficial in automated driving. However, further on-road testing of HMI displays for AVs that include SIP and ORBBs are needed to enhance the user experience and acceptability of AVs and to provide more ecological validity.
在自动驾驶车辆的条件自动化中，驾驶员的任务是保持警惕，并在系统遇到故障时随时准备接管控制权。然而，关于自动驾驶车辆的预期操作或其对周围环境中潜在威胁的感知，几乎没有或根本没有向驾驶员提供任何信息。为了填补这一研究空白，本研究提出了两种人机交互（HMI）概念：第一，共享预期路径（SIP），它呈现自动驾驶车辆的预期操作预测；第二，目标识别边界框（ORBB），它在可能导致碰撞的其他道路使用者周围放置透明蓝色方块。
一项包含组内和组间因素的在线实验测试了两种HMI设计：一种同时包含SIP和ORBB，另一种仅包含SIP。向澳大利亚的394名参与者（平均年龄=28.24岁，64%为男性）依次展示六个视频，每个视频描绘10至15秒的自动驾驶场景。参与者监测每个视频中的自动驾驶车辆，视频以三种随机条件之一呈现：无HMI显示、仅SIP或SIP + ORBB。每个视频后的问题测量了信任、态势感知、压力以及通过技术接受模型（TAM）测量的用户接受度。
结果表明，SIP在条件自动化监测中是有益的，可减轻压力、提高感知有用性以及增加未来使用自动驾驶车辆的意愿。此外，与没有ORBB相比，ORBB的存在提高了参与者对感知有用性的评分以及使用自动驾驶车辆的意愿。研究结果还为TAM提供了支持，因为感知易用性和感知有用性被发现是未来使用自动驾驶车辆意愿的显著正向预测因素。
当前研究提供了一些证据表明SIP在自动驾驶中可能是有益的。然而，需要对包含SIP和ORBB的自动驾驶车辆HMI显示器进行进一步的道路测试，以提高自动驾驶车辆的用户体验和可接受性，并提供更高的生态效度。
