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arXiv 2602.11507cs.HC

一种教育型人机接口,提供介入请求触发和解释以增强驾驶员对ADS系统限制的理解

An Educational Human Machine Interface Providing Request-to-Intervene Trigger and Reason Explanation for Enhancing the Driver's Comprehension of ADS's System Limitations

Ryuji Matsuo, Hailong Liu, Toshihiro Hiraoka, Takahiro Wada

AI总结:

本文提出一种基于语音的教育型人机接口,通过提供介入请求触发和解释,帮助驾驶员理解ADS系统限制,实验表明其能提升驾驶员的理解并减少碰撞。

摘要:

三级自动驾驶系统(ADS)已引起广泛关注并进入商业化阶段。三级ADS在操作设计域(ODD)超出时会发出介入请求(RtI)以提示驾驶员接管。然而,复杂交通情况可能导致驾驶员同时感知多个RtI触发因素,造成犹豫或困惑。因此,驾驶员需要清楚了解ADS的系统限制以确保安全接管。本研究提出一种基于语音的教育型人机接口(HMI),用于提供RtI触发提示和解释,以帮助驾驶员理解ADS的系统限制。使用驾驶模拟器进行的组间实验结果显示,将有效的触发提示和解释纳入RtI与提升驾驶员对ADS系统限制的理解相关。此外,大多数参与者通过所提出的方法指导,在RtI失效时能够主动接管ADS;同时,他们的碰撞次数比其他RtI HMI条件下的参与者更低。因此,通过所提出的方法持续增强驾驶员对ADS系统限制的理解,与更安全和有效的实时与ADS交互相关。

英文摘要:

Level 3 automated driving systems (ADS) have attracted significant attention and are being commercialized. A level 3 ADS prompts the driver to take control by issuing a request to intervene (RtI) when its operational design domains (ODD) are exceeded. However, complex traffic situations can cause drivers to perceive multiple potential triggers of RtI simultaneously, causing hesitation or confusion during take-over. Therefore, drivers need to clearly understand the ADS's system limitations to ensure safe take-over. This study proposes a voice-based educational human machine interface~(HMI) for providing RtI trigger cues and reason to help drivers understand ADS's system limitations. The results of a between-group experiment using a driving simulator showed that incorporating effective trigger cues and reason into the RtI was related to improved driver comprehension of the ADS's system limitations. Moreover, most participants, instructed via the proposed method, could proactively take over control of the ADS in cases where RtI fails; meanwhile, their number of collisions was lower compared with the other RtI HMI conditions. Therefore, using the proposed method to continually enhance the driver's understanding of the system limitations of ADS through the proposed method is associated with safer and more effective real-time interactions with ADS.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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