Hello, is it me you're Stopping for? The Effect of external Human Machine Interface Familiarity on Pedestrians' Crossing Behaviour in an Ambiguous Situation.

IF 2.9 3区 心理学 Q1 BEHAVIORAL SCIENCES
Yee Mun Lee, Vladislav Sidorov, Ruth Madigan, Jorge Garcia de Pedro, Gustav Markkula, Natasha Merat
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引用次数: 0

Abstract

Objective: We investigated how different deceleration intentions (i.e. an automated vehicle either decelerated for leading traffic or yielded for pedestrians) and a novel (Slow Pulsing Light Band - SPLB) or familiar (Flashing Headlights - FH) external Human Machine Interface (eHMI) informed pedestrians' crossing behaviour.

Background: The introduction of SAE Level 4 Automated Vehicles (AVs) has recently fuelled interest in new forms of explicit communication via eHMIs, to improve the interaction between AVs and surrounding road users. Before implementing these eHMIs, it is necessary to understand how pedestrians use them to inform their crossing decisions.

Method: Thirty participants took part in the study using a Head-Mounted Display. The independent variables were deceleration intentions and eHMI design. The percentage of crossings, collision frequency and crossing initiation time across trials were measured.

Results: Pedestrians were able to identify the intentions of a decelerating vehicle, using implicit cues, with more crossings made when the approaching vehicles were yielding to them. They were also more likely to cross when a familiar eHMI was presented, compared to a novel one or no eHMI, regardless of the vehicle's intention. Finally, participants learned to take a more cautious approach as trials progressed, and not to base their decisions solely on the eHMI.

Conclusion: A familiar eHMI led to early crossings regardless of the vehicle's intention but also led to a higher collision frequency than a novel eHMI.

Application: To achieve safe and acceptable interactions with AVs, it is important to provide eHMIs that are congruent with road users' expectations.

你好,你是在为我停车吗?外部人机界面熟悉程度对行人在模糊情况下过马路行为的影响。
研究目的我们研究了不同的减速意图(即自动驾驶车辆要么为前方车辆减速,要么为行人让行)和新颖(慢速脉冲光带 - SPLB)或熟悉(闪烁大灯 - FH)的外部人机界面(eHMI)如何影响行人的过街行为:最近,美国汽车工程师学会(SAE)第四级自动驾驶汽车(AV)的推出,激发了人们对通过电子人机界面(eHMI)进行新形式明确交流的兴趣,从而改善了自动驾驶汽车与周围道路使用者之间的互动。在实施这些电子人机交互界面之前,有必要了解行人如何使用这些界面为其过马路决策提供依据:方法:30 名参与者使用头戴式显示器参与了研究。自变量为减速意向和电子人机界面设计。结果:行人能够识别电子人机交互界面中的减速意向和电子人机交互界面的设计:结果:行人能够利用隐性线索识别减速车辆的意图,在驶近的车辆向行人让行时,行人更倾向于横穿马路。此外,与新颖的电子人机界面或无电子人机界面相比,当出现熟悉的电子人机界面时,无论车辆的意图如何,行人都更倾向于横穿马路。最后,随着试验的进行,参与者学会了采取更加谨慎的方法,而不是仅仅根据电子人机界面做出决定:结论:无论车辆的意图如何,熟悉的电子人机交互界面都会让参与者提前通过路口,但与新颖的电子人机交互界面相比,新颖的电子人机交互界面会导致更高的碰撞频率:应用:为了实现与自动驾驶汽车安全且可接受的互动,必须提供符合道路使用者期望的电子人机交互界面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Human Factors
Human Factors 管理科学-行为科学
CiteScore
10.60
自引率
6.10%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Human Factors: The Journal of the Human Factors and Ergonomics Society publishes peer-reviewed scientific studies in human factors/ergonomics that present theoretical and practical advances concerning the relationship between people and technologies, tools, environments, and systems. Papers published in Human Factors leverage fundamental knowledge of human capabilities and limitations – and the basic understanding of cognitive, physical, behavioral, physiological, social, developmental, affective, and motivational aspects of human performance – to yield design principles; enhance training, selection, and communication; and ultimately improve human-system interfaces and sociotechnical systems that lead to safer and more effective outcomes.
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