Human Machine Interface for Connected Vehicle: Requirements, Development and Assessment

Ahmed, Mohamed; Gaweesh, Sherif; Subedi, Biraj; Raddaoui, Omar; Yang, Guangchuan · 2021 · ROSA P / Wyoming. Department of Transportation

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Summary

This study addresses the critical challenge of designing safe and effective Human Machine Interfaces (HMI) for Connected Vehicle (CV) technologies, specifically within the Wyoming Department of Transportation’s CV Pilot on Interstate 80. While CV applications like Spot Weather Impact Warnings (SWIW) and Work Zone Warnings (WZW) aim to enhance driver situational awareness and safety, there is a significant concern that in-vehicle displays may introduce cognitive and visual distraction, potentially compromising safety. The research was motivated by the high incidence of weather-related crashes on this corridor and the need to ensure that HMI designs support proactive decision-making without overwhelming drivers, particularly professional truck drivers and highway patrol troopers who operate in complex, high-workload environments. To evaluate HMI performance, the researchers conducted a two-phase experimental study using high-fidelity driving simulators at the University of Wyoming. The first phase involved twenty professional truck drivers using a semi-trailer simulator, while the second phase included ten Wyoming Highway Patrol troopers using a passenger car simulator equipped with patrol-specific devices. Participants underwent E-training modules before engaging in simulated driving scenarios that included baseline conditions (no CV warnings) and various CV notification modalities. Data collection methods included vehicle dynamics metrics (speed, lane position, braking) via SimObserver, eye-tracking data via SmartEye systems to measure visual demand and glance duration, and post-drive surveys to assess user perception of readability and distraction. The results indicated that exposure to CV notifications yielded promising safety benefits, manifested through improved driver behavior such as earlier and smoother braking, reduced speed variability, and earlier lane merging in hazardous conditions. Both weather and work zone notifications received high approval from participants regarding usefulness and ease of understanding. However, the study found that while weather notifications introduced negligible distraction, work zone notifications induced moderate visual and cognitive demand, likely due to the rapid display of multiple small-sized icons. For highway patrol troopers, the "enlarged icons with beeps" modality resulted in significantly less distraction compared to other formats, although vehicle dynamics improvements were consistent across all CV-enabled conditions. The significance of this research lies in its evidence-based recommendations for HMI design to balance safety benefits with minimal distraction. The findings suggest that warnings must be clearly visible, timely, and easily recognizable to ensure appropriate driver responses. The study concludes that while CV technology enhances safety, the specific modality of information delivery is crucial; simplified, larger visual cues combined with auditory alerts are preferable for reducing cognitive load. These insights provide actionable guidelines for the Wyoming CV Pilot and broader transportation agencies to optimize HMI implementations, ensuring that emerging technologies contribute to road safety without introducing new risks through driver distraction.

Key finding

Exposure to connected vehicle notifications improved driver behavior and hazard response with little to moderate distraction introduced by the interface.

Methodology

simulator

Sample size: 30

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• ehmi external hmi
• hud ar windshield
• visual
• in vehicle coaching
• vru facing ehmi
• external distraction

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Applied Guidance: design guidelines
• Empirical Findings: behavioral performance data
• Methodological Resource: tool software