Details

Autor(en) / Beteiligte

• Wang, Yugang
• Lyu, Nengchao
• Wu, Chaozhong
• Du, Zijun
• Deng, Min
• Wu, Haoran

Titel

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

Ist Teil von

• Accident analysis and prevention, 2024-04, Vol.198, p.107448-107448, Article 107448

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2024

Quelle

MEDLINE

Beschreibungen/Notizen

• •Three ICV environment HMI groups: control, warning, and guidance, were designed to study their impact on driver's performance.•Warning group exhibited cautious and smooth acceleration before merging, while the Guidance group demonstrated better speed control after merging.•Mainline vehicle gaps had no significant impact on merging positions across HMI groups.•Guidance group merged closest to taper, Control group farthest.•Abundant gaps led to smaller initial merging gaps and shorter adjustment times for Guidance group. 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.