Post Take-Over Performance Varies in Drivers of Automated and Connected Vehicle Technology in Near-Miss Scenarios.

IF 2.9 3区 心理学 Q1 BEHAVIORAL SCIENCES
Human Factors Pub Date : 2024-11-01 Epub Date: 2023-12-05 DOI:10.1177/00187208231219184
Yusuke Yamani, Jeffrey Glassman, Abdalziz Alruwaili, Sarah E Yahoodik, Emily Davis, Samantha Lugo, Kun Xie, Sherif Ishak
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引用次数: 0

Abstract

Objective: This study examined the impact of monitoring instructions when using an automated driving system (ADS) and road obstructions on post take-over performance in near-miss scenarios.

Background: Past research indicates partial ADS reduces the driver's situation awareness and degrades post take-over performance. Connected vehicle technology may alert drivers to impending hazards in time to safely avoid near-miss events.

Method: Forty-eight licensed drivers using ADS were randomly assigned to either the active driving or passive driving condition. Participants navigated eight scenarios with or without a visual obstruction in a distributed driving simulator. The experimenter drove the other simulated vehicle to manually cause near-miss events. Participants' mean longitudinal velocity, standard deviation of longitudinal velocity, and mean longitudinal acceleration were measured.

Results: Participants in passive ADS group showed greater, and more variable, deceleration rates than those in the active ADS group. Despite a reliable audiovisual warning, participants failed to slow down in the red-light running scenario when the conflict vehicle was occluded. Participant's trust in the automated driving system did not vary between the beginning and end of the experiment.

Conclusion: Drivers interacting with ADS in a passive manner may continue to show increased and more variable deceleration rates in near-miss scenarios even with reliable connected vehicle technology. Future research may focus on interactive effects of automated and connected driving technologies on drivers' ability to anticipate and safely navigate near-miss scenarios.

Application: Designers of automated and connected vehicle technologies may consider different timing and types of cues to inform the drivers of imminent hazard in high-risk scenarios for near-miss events.

自动驾驶和互联汽车技术驾驶员在近距离事故场景中的接管后表现各不相同。
目的:本研究探讨了使用自动驾驶系统(ADS)时的监控指令和道路障碍物对近乎失误情况下接管后性能的影响:本研究探讨了使用自动驾驶系统(ADS)时的监控指示和道路障碍物对近乎失误情况下接管后性能的影响:背景:过去的研究表明,部分自动驾驶系统会降低驾驶员的态势感知能力,并降低接管后的性能。车联网技术可以及时提醒驾驶员即将发生的危险,从而安全地避免险情:方法:48 名使用 ADS 的持证驾驶员被随机分配到主动驾驶或被动驾驶条件下。受试者在分布式驾驶模拟器中,在有或没有视觉障碍物的情况下驾驶八个场景。实验人员驾驶另一辆模拟车辆,手动造成险情。测量了参与者的平均纵向速度、纵向速度标准偏差和平均纵向加速度:结果:与主动 ADS 组相比,被动 ADS 组的参与者表现出更大且更多变的减速率。尽管有可靠的视听警告,但在闯红灯场景中,当冲突车辆被遮挡时,参与者未能减速。实验开始和结束时,参与者对自动驾驶系统的信任度没有变化:结论:即使采用了可靠的互联汽车技术,驾驶员以被动方式与自动驾驶系统进行交互时,在差点发生交通事故的场景中可能会继续表现出更高且更多变的减速率。未来的研究可能会重点关注自动驾驶和互联驾驶技术对驾驶员预测和安全驾驭近距离碰撞场景能力的交互影响:应用:自动驾驶和互联汽车技术的设计者可以考虑采用不同的提示时间和类型,以告知驾驶员在高风险场景中即将发生的危险。
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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