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研究人机界面在智能网联汽车环境下对驾驶员变道性能的影响。

Investigating the impact of HMI on drivers' merging performance in intelligent connected vehicle environment.

机构信息

Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, Hubei, China.

Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, Hubei, China.

出版信息

Accid Anal Prev. 2024 Apr;198:107448. doi: 10.1016/j.aap.2023.107448. Epub 2024 Feb 9.

DOI:10.1016/j.aap.2023.107448
PMID:38340472
Abstract

Intelligent Connected Vehicle (ICV) is considered one of the most promising active safety technologies to address current transportation challenges. Human-Machine Interface (HMI) plays a vital role in enhancing user driving experience with ICV technology. However, in an ICV environment, drivers may exhibit excessive reliance on HMI, resulting in diminished proactive observation and analysis of the road environment, and subsequently leading to a potential decrease in drivers' situational awareness. This reduced situational awareness may consequently lead to a decline in their overall engagement in driving tasks. Therefore, to comprehensively investigate the impact of HMI on driver performance in various ICV environments, this study incorporates three distinct HMI systems: Control group, Warning group, and Guidance group. The Control group provides basic information, the Warning group adds front vehicle icon and real-time headway information, while the Guidance group further includes speed and voice guidance features. Additionally, the study considers three types of mainline vehicle gaps, namely, 30 m, 20 m, and 15 m. Through our self-developed ICV testing platform, we conducted driving simulation experiments on 43 participants in a freeway interchange merging area. The findings reveal that, drivers in the Guidance group exhibited explicit acceleration while driving on the ramp. Drivers in the Guidance and Warning groups demonstrated smoother speed change trends and lower mean longitudinal acceleration upon entering the acceleration lane compared to the Control group, indicating a preference for more cautious driving strategies. During the pre-merging section, drivers in the Warning group demonstrated a more cautious and smooth longitudinal acceleration. The Guidance group's HMI system assisted drivers in better speed control during the post-merging section. Differences in mainline vehicle gaps did not significantly impact the merging positions of participants across the three HMI groups. Drivers in the Guidance group merged closest to the left side of the taper section, while the Control group merged farthest. The research findings offer valuable insights for developing dynamic human-machine interfaces tailored to specific driving scenarios in the environment of ICVs. Future research should investigate the effects of various HMIs on driver safety, workload, energy efficiency, and overall driving experience. Conducting real-world tests will further validate the findings obtained from driving simulators.

摘要

智能网联汽车(ICV)被认为是应对当前交通挑战最有前途的主动安全技术之一。人机界面(HMI)在提升 ICV 技术用户驾驶体验方面发挥着至关重要的作用。然而,在 ICV 环境中,驾驶员可能会过度依赖 HMI,从而减少对道路环境的主动观察和分析,进而导致其情境意识潜在下降。这种情境意识的降低可能会导致他们对驾驶任务的整体参与度下降。因此,为了全面研究 HMI 在各种 ICV 环境下对驾驶员性能的影响,本研究纳入了三种不同的 HMI 系统:控制组、警告组和引导组。控制组提供基本信息,警告组则增加了前车图标和实时车间距信息,而引导组则进一步包括速度和语音引导功能。此外,研究还考虑了三种主线车辆间隙类型,分别为 30m、20m 和 15m。通过我们自主研发的 ICV 测试平台,我们在高速公路进出口合并区域对 43 名参与者进行了驾驶模拟实验。研究结果表明,在匝道行驶时,引导组的驾驶员表现出明显的加速行为。与控制组相比,引导组和警告组的驾驶员在进入加速车道时,速度变化趋势更为平稳,平均纵向加速度更低,表明他们更倾向于采用更为谨慎的驾驶策略。在预合并段,警告组的驾驶员表现出更为谨慎和平稳的纵向加速度。引导组的 HMI 系统帮助驾驶员在合并段更好地控制速度。主线车辆间隙的差异并未对三个 HMI 组的驾驶员合并位置产生显著影响。引导组的驾驶员合并到最靠近变窄段左侧的位置,而控制组的驾驶员则合并到最远离左侧的位置。本研究结果为开发针对特定驾驶场景的动态人机界面提供了有价值的参考,以适应 ICV 环境。未来的研究应探讨各种 HMI 对驾驶员安全性、工作负荷、能源效率和整体驾驶体验的影响。进行真实世界的测试将进一步验证从驾驶模拟器中获得的研究结果。

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