Impact of Information on Consumer Understanding of a Partially Automated Driving System

AAA Foundation for Traffic Safety · 2020 · AAA Foundation for Traffic Safety

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Summary

This study investigates how marketing branding and training methods influence drivers’ mental models and on-road behavior when using Level 2 (L2) partially automated driving systems. The research addresses the critical safety concern that consumers may develop inaccurate expectations of vehicle automation capabilities, potentially leading to over-reliance and unsafe driving practices. Specifically, the study examines whether emphasizing a system’s capabilities versus its limitations, and whether training is delivered via text, video, or in-person demonstration, affects driver confidence, willingness to engage in distracting behaviors, and reaction times during control handoffs. The researchers employed a between-subjects experimental design with 90 participants recruited from the Washington, DC area. Participants were randomly assigned to one of six conditions, combining two branding approaches (“DriveAssist,” emphasizing limitations and driver responsibility; “AutonoDrive,” emphasizing capabilities and workload reduction) with three training modes (printed quick-start guide, training video, or in-person on-road demonstration). All participants received training on Cadillac’s Super Cruise system, which was rebranded for the study. After training, participants completed a post-training questionnaire assessing their mental model of the system. They then drove the vehicle on a freeway route for approximately 35 minutes using the L2 feature, followed by a final questionnaire. Driving behaviors, including hand and foot positions and responses to an unexpected handoff event, were recorded using vehicle instrumentation. Results indicated that branding significantly influenced driver expectations and behavior. Participants exposed to the “AutonoDrive” branding, which emphasized capabilities, reported greater confidence in the system’s abilities and a higher willingness to engage in potentially distracting secondary tasks compared to those in the “DriveAssist” group. These differences in mental models persisted after the on-road drive, and in some cases, confidence in the system’s ability to handle safety-critical scenarios increased post-drive, even for situations outside the system’s operational design domain. Regarding training modes, participants who received an in-person demonstration found the training most useful and exhibited the highest confidence during the drive, evidenced by more time with hands off the steering wheel and feet off the pedals. However, this group was also the least likely to respond promptly to an unexpected handoff of control. The study concludes that marketing materials emphasizing automation capabilities can lead to mental models that overestimate system performance, potentially compromising safety by encouraging risky behaviors and slower responses to system disengagement. While the specific training mode had fewer overt safety implications, in-person demonstrations were most effective for learning but also fostered the highest levels of driver confidence and disengagement. The findings suggest that automobile manufacturers and regulators must carefully consider how information is presented to ensure drivers maintain accurate mental models of system limitations and remain attentive while using partially automated driving technologies.

Key finding

Branding that emphasizes L2 automation capabilities rather than limitations produces inflated mental models and riskier behavioral intentions even when training materials contain accurate safety information, and these effects persist after brief on-road use.

Methodology

mixed_methods

Sample size: 90

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_aaa_foundation on 2026-05-23 (6 acquisition events logged).

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

Topics

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• automation surprise
• situational awareness
• automation
• trust calibration
• odd communication
• mode awareness

Information type

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• Empirical Findings: self report data
• Theoretical Contribution: conceptual framework, computational model