Identifying driving profiles after take over request in automated vehicles at SAE levels 2 and 3

IF 3.5 2区 工程技术 Q1 PSYCHOLOGY, APPLIED
Marios Sekadakis , Sandra Trösterer , Peter Moertl , George Yannis
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引用次数: 0

Abstract

Automated Driving (AD) has the potential to significantly reshape the transportation industry by improving safety, efficiency, and user comfort and acceptance. This research investigates driver behaviors during Take Over Requests (TORs) in automated vehicles at SAE Levels 2 and 3 using the HADRIAN Human-Machine Interface (HMI), designed to enhance driver support through real-time feedback and countdown displays. Analysis included clustering to develop distinct driving profiles based on key measurements collected through a driving simulator experiment, such as acceleration, deceleration, and speed, offering a deep understanding of driver behavior in responses to TORs. Three primary driving profiles were identified: “Passive driving and slow TOR response”, “Nervous driving and moderate TOR response”, and “Normal driving and quick TOR response”. This study also provides specific insights for each automation level, identifying profiles of driver behaviors at both SAE Levels 2 and 3. Results reveal that the nervous driving profile, although less frequent, poses significant safety implications due to higher deceleration rates and variability in speed and deceleration. Additionally, the study highlights that Non-Driving Related Tasks (NDRTs) increase the need for longer Take Over Time (TOT), with greater variability observed at higher automation levels, making accurate estimation of required TOT more challenging. The HADRIAN HMI is shown to positively impact driver performance by increasing TOT, allowing drivers more time to transition from automated to manual control comfortably. These insights can inform the design of more adaptive HMI systems, enhance real-time feedback mechanisms, and improve driver training programs to ensure safer transitions during TORs.
自动驾驶(AD)通过提高安全性、效率、用户舒适度和接受度,有可能极大地重塑交通运输业。本研究使用 HADRIAN 人机界面(HMI)调查了 SAE 2 级和 3 级自动驾驶汽车在接管请求(TOR)期间的驾驶员行为,HADRIAN 人机界面旨在通过实时反馈和倒计时显示增强对驾驶员的支持。分析包括基于驾驶模拟器实验收集的关键测量数据(如加速、减速和速度)进行聚类,以建立不同的驾驶特征,从而深入了解驾驶员响应 TORs 的行为。确定了三种主要的驾驶特征:"被动驾驶和缓慢的 TOR 反应"、"紧张驾驶和适度的 TOR 反应 "以及 "正常驾驶和快速的 TOR 反应"。这项研究还为每个自动化级别提供了具体的见解,确定了 SAE 2 级和 3 级驾驶员的行为特征。研究结果表明,紧张驾驶虽然频率较低,但由于减速率较高以及速度和减速的可变性,会对安全产生重大影响。此外,该研究还强调,非驾驶相关任务(NDRT)增加了对更长接管时间(TOT)的需求,在自动化水平较高时观察到的变异性更大,这使得准确估计所需的接管时间更具挑战性。事实表明,HADRIAN 人机界面通过延长接管时间对驾驶员的表现产生了积极影响,使驾驶员有更多时间从自动控制舒适地过渡到手动控制。这些见解可为设计更具适应性的人机界面系统、增强实时反馈机制和改进驾驶员培训计划提供参考,从而确保在 TOR 期间实现更安全的过渡。
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
CiteScore
7.60
自引率
14.60%
发文量
239
审稿时长
71 days
期刊介绍: Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.
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