Implicit Interaction with an Autonomous Personal Mobility Vehicle: Relations of Pedestrians' Gaze behavior with Situation Awareness and Perceived Risks
Implicit Interaction with an Autonomous Personal Mobility Vehicle: Relations of Pedestrians' Gaze behavior with Situation Awareness and Perceived Risks
复制标题
与自动个人移动车辆的隐式交互：行人的注视行为与态势感知和感知风险的关系
DOI：
10.1080/10447318.2022.2073006
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发表时间：
2022
影响因子：
4.7
通讯作者：
Hiroshi Murase
中科院分区：
文献类型：
--
作者：
Hailong LIU;Takatsugu Hirayama;Luis Yoichi Morales Saiki;Hiroshi Murase
随着自动驾驶汽车的普及，行人和自动驾驶汽车 (AV) 之间的互动将显着增加。然而，行人通常对自动驾驶汽车没有足够的信任，特别是当他们对自动驾驶汽车在交互中的意图感到困惑时。本研究旨在评估行人在交互中是否清楚地理解自动驾驶汽车的驾驶意图，并对行人的注视行为与其对自动驾驶汽车意图的理解之间的关系进行实验研究。本研究调查的假设是，行人越不了解自动驾驶汽车的驾驶意图，他们的注视行为持续时间就越长。设计了行人-车辆交互实验来验证所提出的假设。使用机器人轮椅作为手动驾驶车辆（MV）和AV，与行人互动，同时记录行人的注视数据和对驾驶意图的主观评价。实验结果支持了我们的假设，因为行人注视自动驾驶汽车的时间与他们对自动驾驶汽车驾驶意图的理解之间存在负相关。此外，大多数行人在MV上的注视时间比在AV上的要短。因此，我们向外部人机界面（eHMI）设计者提出两点建议：（1）当行人与自动驾驶汽车交互时，应提供自动驾驶汽车的驾驶意图； （2）如果自动驾驶汽车显示驾驶意图后，行人仍然注视自动驾驶汽车，则自动驾驶汽车应提供更清晰的有关其驾驶意图的信息。
Interactions between pedestrians and automated vehicles (AVs) will increase significantly with the popularity of AV. However, pedestrians often have not enough trust on the AVs , particularly when they are confused about an AV's intention in a interaction. This study seeks to evaluate if pedestrians clearly understand the driving intentions of AVs in interactions and presents experimental research on the relationship between gaze behaviors of pedestrians and their understanding of the intentions of the AV. The hypothesis investigated in this study was that the less the pedestrian understands the driving intentions of the AV, the longer the duration of their gazing behavior will be. A pedestrian--vehicle interaction experiment was designed to verify the proposed hypothesis. A robotic wheelchair was used as the manual driving vehicle (MV) and AV for interacting with pedestrians while pedestrians' gaze data and their subjective evaluation of the driving intentions were recorded. The experimental results supported our hypothesis as there was a negative correlation between the pedestrians' gaze duration on the AV and their understanding of the driving intentions of the AV. Moreover, the gaze duration of most of the pedestrians on the MV was shorter than that on an AV. Therefore, we conclude with two recommendations to designers of external human-machine interfaces (eHMI): (1) when a pedestrian is engaged in an interaction with an AV, the driving intentions of the AV should be provided; (2) if the pedestrian still gazes at the AV after the AV displays its driving intentions, the AV should provide clearer information about its driving intentions.