Inflating system expectations prior to SAE level 3 automated vehicle use: effects on monitoring behavior, resumption of control, and attitudes toward driving automation

• Introductory videos shaped perceived familiarity with SAE Level 3 automation. • Basic introductory videos and graded warnings improved take-over safety and reduced crashes. • Visual scanning patterns were similar between groups but became more variable over time. Increasing levels of vehicle automation bring new risks to drivers, particularly those who are using a new automated driving system (ADS). The overreliance on partially automated advanced driver assistance systems (SAE L2 ADAS) has led to crashes, a concern that might escalate with conditional ADS (SAE L3), which require timely driver intervention. This study examines the impact of how L3 ADS’ capabilities and limitations are communicated to users on their subjective attitudes toward ADS and their driving behavior and performance, particularly concerning safety. In a driving simulator study, participants received introductory videos about the role of drivers at different automation levels, the capabilities and limitations of L3 ADS, and its human–machine interface (HMI). Videos concluded with either “Highlighted Benefits” of higher automation levels, reflecting current marketing trends of ADAS and ADS, or an “Explicit Reminder” of driver responsibilities in L3 ADS usage. Participants then completed three driving simulator runs (repeated measures) during or after which visual monitoring behavior, take-over performance, and subjective attitudes (trust and acceptance) toward the ADS were gathered. Participants resumed control when receiving uncertainty alert from the ADS across both introductory information conditions, with minor differences in take-over performance and monitoring behavior. No significant differences were observed in road monitoring behavior, take-over performance, and subjective attitudes between conditions, except for subjective familiarity ratings, which decreased over runs for the Explicit Reminder group compared to the Highlighted Benefits group. Both conditions showed take-over performance improvements, particularly after practice. Successful crash avoidance in both groups indicates that graded warnings and practice can effectively improve take-over performance. This similarity in outcomes suggests that introductory information about ADS may not significantly affect monitoring behavior and performance of ADS users. These results highlight the potential for such systems to mitigate ADS complacency and promote safer resumption of vehicle control during automation failures.

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Publication Details

Journal
Transportation Research Interdisciplinary Perspectives
Published
2025-11-01
DOI
https://doi.org/10.1016/j.trip.2025.101725
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Inflating system expectations prior to SAE level 3 automated vehicle use: effects on monitoring behavior, resumption of control, and attitudes toward driving automation

Irina Benedyk, Srinivas Peeta, Shubham Agrawal, Yuntao Guo et al.
Transportation Research Interdisciplinary Perspectives
Human-Automation Interaction and Safety
article

Inflating system expectations prior to SAE level 3 automated vehicle use: effects on monitoring behavior, resumption of control, and attitudes toward driving automation

Irina Benedyk, Srinivas Peeta, Shubham Agrawal, Yuntao Guo, Dustin J. Souders, Yujie Li
article en

Abstract

• Introductory videos shaped perceived familiarity with SAE Level 3 automation. • Basic introductory videos and graded warnings improved take-over safety and reduced crashes. • Visual scanning patterns were similar between groups but became more variable over time. Increasing levels of vehicle automation bring new risks to drivers, particularly those who are using a new automated driving system (ADS). The overreliance on partially automated advanced driver assistance systems (SAE L2 ADAS) has led to crashes, a concern that might escalate with conditional ADS (SAE L3), which require timely driver intervention. This study examines the impact of how L3 ADS’ capabilities and limitations are communicated to users on their subjective attitudes toward ADS and their driving behavior and performance, particularly concerning safety. In a driving simulator study, participants received introductory videos about the role of drivers at different automation levels, the capabilities and limitations of L3 ADS, and its human–machine interface (HMI). Videos concluded with either “Highlighted Benefits” of higher automation levels, reflecting current marketing trends of ADAS and ADS, or an “Explicit Reminder” of driver responsibilities in L3 ADS usage. Participants then completed three driving simulator runs (repeated measures) during or after which visual monitoring behavior, take-over performance, and subjective attitudes (trust and acceptance) toward the ADS were gathered. Participants resumed control when receiving uncertainty alert from the ADS across both introductory information conditions, with minor differences in take-over performance and monitoring behavior. No significant differences were observed in road monitoring behavior, take-over performance, and subjective attitudes between conditions, except for subjective familiarity ratings, which decreased over runs for the Explicit Reminder group compared to the Highlighted Benefits group. Both conditions showed take-over performance improvements, particularly after practice. Successful crash avoidance in both groups indicates that graded warnings and practice can effectively improve take-over performance. This similarity in outcomes suggests that introductory information about ADS may not significantly affect monitoring behavior and performance of ADS users. These results highlight the potential for such systems to mitigate ADS complacency and promote safer resumption of vehicle control during automation failures.

Transportation Research Interdisciplinary PerspectivesVol. 34
Tongji University (CN), Georgia Institute of Technology (US), University at Buffalo, State University of New York (US), Clemson University (US)
Openalex Percentile: Top 60%
Human-Automation Interaction and Safety
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