The challenge of ADAS assessment: A scale for the assessment of the HMI of advanced driver assistance technology

Biondi, FN; Getty, D; McCarty, MM; Goethe, RM; Cooper, JM; Strayer, DL; Goethe, R · 2018 · publications_jsonl

DOI: 10.1177/0361198118773569

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Summary

This paper addresses the lack of standardized tools for assessing the human–machine interfaces (HMI) of Advanced Driver Assistance Systems (ADAS). While ADAS are engineered to enhance safety, poorly designed interfaces can lead to unintended consequences, such as increased driver workload, stress, and reduced situational awareness. Although governmental bodies like the NHTSA and the European Commission have issued design guidelines, these documents lack a unified rating and benchmarking tool applicable to the broad spectrum of assistance systems currently on the market. To fill this gap, the authors developed the Utah Vehicle Technology Assessment Scale (UTA-S), a comprehensive instrument designed to evaluate the usability and demand of various ADAS HMIs. The development of the UTA-S involved an iterative process conducted by six human factors experts. The team evaluated 94 distinct assistance systems across 40 different 2017 model-year vehicles. Evaluators drove the vehicles under varying weather and lighting conditions to identify specific interface issues. The scale covers ten specific ADAS categories: rearview cameras, rear-cross traffic alert (RCTA), rear parking sensors (RPS), forward collision avoidance systems (FCAS), blind spot monitor plus lane change assist (BSM+LCA), adaptive cruise control (ACC), lane departure warning systems (LDWS), lane keeping assist systems (LKAS), automatic lane change (ALC), and automatic parallel parking (APP). The final scale consists of 59 items, each accompanied by descriptions, examples of good and bad design, and references to industry standards (ISO, SAE) and relevant literature. The assessment methodology requires at least two evaluators to rate each system against specific items using a four-point scale: No Concern (3 points), Minor Concerns (2 points), Serious Concerns (1 point), and Not Applicable (0 points). "No Concern" indicates the HMI does not compromise vehicle control or cause distraction; "Minor Concerns" suggests potential issues under specific conditions; and "Serious Concerns" indicates the HMI likely prevents safe operation or causes high stress. The scale items are tailored to each system’s function. For example, rearview camera assessments focus on image clarity, screen size, and guideline effectiveness, while ACC evaluations examine control accessibility, icon comprehension, and the naturalness of vehicle acceleration and deceleration. The rationale for each item is grounded in prior research linking specific HMI characteristics to driver behavior and safety outcomes. The significance of this work lies in providing a robust, standardized tool for benchmarking ADAS HMIs across different vehicle makes and models. By quantifying interface quality, the UTA-S aids evaluators in identifying specific design aspects that merit further attention or improvement. This facilitates more rigorous human factors evaluations and supports the development of safer, more user-friendly assistance technologies. The scale addresses the unique challenges of ADAS assessment, such as short interaction times and varying response requirements, which are not adequately covered by existing metrics for in-vehicle infotainment systems.

Key finding

A 59-item, 4-point rubric covering ten ADAS categories provides a standards-grounded HMI benchmarking tool, demonstrated on 94 production systems and able to surface specific design deficits.

Methodology

other

Provenance

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Topics

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

• automation
• ehmi external hmi
• hud ar windshield
• adas effectiveness
• situational awareness
• odd communication

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
• Methodological Resource: validation psychometrics
• Theoretical Contribution: conceptual framework