Consumer Use & Adoption of Advanced Vehicle Systems

Seppelt, Bobbie; Coughlin, Joseph F. · 2019 · ROSA P / New England University Transportation Center

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Summary

This report addresses the safety challenges associated with drivers becoming “out-of-the-loop” when using advanced vehicle assistance systems (SAE Levels 1–3). The core problem is that drivers, removed from active control, often struggle to resume manual control safely and timely when requested to intervene or when system failures occur. The research aims to develop human-centered design solutions, specifically novel human-machine interfaces (HMIs), that maintain driver situational awareness and align driver expectations with system capabilities. The study was organized into four tasks: defining “out-of-the-loop” behavior, identifying information requirements for automation, analyzing naturalistic data on driver misconceptions, and developing HMI design recommendations. The methodology combined literature reviews, simulator experiments, large-scale surveys, and field operational trials (FOT). Task 1 involved a consensus-building review to define “in-loop” versus “out-of-the-loop” states based on physical control and monitoring requirements. Task 2 utilized a fixed-base simulator study with 48 drivers using Adaptive Cruise Control (ACC) to compare discrete warnings against continuous feedback displays (visual, auditory, and combined). Task 3 analyzed survey responses from 3,819 U.S. adults regarding their understanding of automation levels. Task 4 conducted semi-structured interviews with 24 drivers who participated in a four-week FOT using two lane-centering systems with similar functionality but different HMI implementations: Volvo’s Pilot Assist (hands-on) and Cadillac’s Super Cruise (hands-off). The findings reveal significant gaps in consumer understanding and the critical impact of HMI design on driver perception. The survey data indicated widespread misunderstanding of automation definitions, with 46.3% of respondents incorrectly believing that “self-driving” requires some degree of driver involvement. The simulator study demonstrated that continuous feedback, particularly via a combined visual-auditory interface, improved driver understanding of system limits and increased proactive responses to failures compared to discrete warnings. The FOT interviews showed that HMI design strongly influenced perceived roles; users of the hands-on Pilot Assist viewed the system as a backup to the driver, whereas users of the hands-off Super Cruise viewed themselves as the backup to the system. Consequently, Super Cruise users reported higher comfort benefits, while Pilot Assist users emphasized redundant safety benefits. The significance of this work lies in establishing clear definitions for driver engagement states and providing evidence-based guidelines for HMI design. The results suggest that to prevent unsafe handovers, interfaces must provide continuous, non-obtrusive feedback about system performance relative to operating limits, rather than just alerting to failures. Furthermore, designers must recognize that HMI features, such as hands-on versus hands-off requirements, fundamentally alter driver trust and role perception. Aligning these design choices with accurate driver expectations is essential for the safe deployment of imperfect vehicle control automation.

Key finding

Nearly half of surveyed adults incorrectly believe that self-driving vehicles require driver involvement, and HMI design dictates whether drivers perceive themselves as primary operators or fallback monitors.

Methodology

mixed_methods

Sample size: 3843

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.

• automation
• automation surprise
• mode awareness
• situational awareness
• acceptance adoption
• automation complacency bias

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: self report data
• Theoretical Contribution: conceptual framework