Explaining Authoritative Control Interventions in Automated Driving to Support Driver Understanding, Trust, and Reliance

• Simulator study on the effect of text messages following authoritative interventions • “ Why ” information is most supportive of driver understanding, trust, and reliance • Evaluation of the automation is primarily affected by the driving scenario type • More driver glances to HMI when control authority is taken away vs. blocked Future automated driving systems (ADS) may be given the ability to fully block or takeaway driver control authority; for example, in cases of immediate danger. During these interventions, drivers will rely on the environment and the human–machine interface to explain the system’s behavior and to regain situational awareness. To examine how information can be structured to explain an authoritative control intervention, N = 46 participants were exposed to three text message variations following interventions in two different driving scenarios in a simulator study. Text messages affected drivers’ objective and subjective responses to interventions. Including “ Why ” information about the reason for the automation’s behavior rather than “How” information about the control authority distribution increased understanding, trust, and appropriate reliance upon the automation. However, the evaluation of the automation’s behavior depended primarily on differences in the driving scenario, while text messages had only a minor influence. Driver gaze varied based on the driving scenario, with more glances to the HMI when driver control authority was taken away compared to when it was blocked. These findings have implications for human–machine interaction design, policy, and future research, highlighting the need for clear communication strategies during authoritative control interventions.

Authors

Institutions

Publication Details

Journal
Transportation Research Part F Traffic Psychology and Behaviour
Published
2025-05-08
DOI
https://doi.org/10.1016/j.trf.2025.04.013
Citations
2
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
4.88
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Explaining Authoritative Control Interventions in Automated Driving to Support Driver Understanding, Trust, and Reliance

Norbert Schneider, Dominik Mühlbacher, Martin Baumann, Frank Flemisch et al.
2 citations
Transportation Research Part F Traffic Psychology and Behaviour
Human-Automation Interaction and Safety
4.88
article

Explaining Authoritative Control Interventions in Automated Driving to Support Driver Understanding, Trust, and Reliance

Norbert Schneider, Dominik Mühlbacher, Martin Baumann, Frank Flemisch, Liza Dixon, Dennis Befelein
article en
2 citations

Abstract

• Simulator study on the effect of text messages following authoritative interventions • “ Why ” information is most supportive of driver understanding, trust, and reliance • Evaluation of the automation is primarily affected by the driving scenario type • More driver glances to HMI when control authority is taken away vs. blocked Future automated driving systems (ADS) may be given the ability to fully block or takeaway driver control authority; for example, in cases of immediate danger. During these interventions, drivers will rely on the environment and the human–machine interface to explain the system’s behavior and to regain situational awareness. To examine how information can be structured to explain an authoritative control intervention, N = 46 participants were exposed to three text message variations following interventions in two different driving scenarios in a simulator study. Text messages affected drivers’ objective and subjective responses to interventions. Including “ Why ” information about the reason for the automation’s behavior rather than “How” information about the control authority distribution increased understanding, trust, and appropriate reliance upon the automation. However, the evaluation of the automation’s behavior depended primarily on differences in the driving scenario, while text messages had only a minor influence. Driver gaze varied based on the driving scenario, with more glances to the HMI when driver control authority was taken away compared to when it was blocked. These findings have implications for human–machine interaction design, policy, and future research, highlighting the need for clear communication strategies during authoritative control interventions.

Transportation Research Part F Traffic Psychology and BehaviourVol. 113
Universität Ulm (DE), Würzburg Institute for Traffic Sciences (Germany) (DE), Institute of Industrial Engineering (AU), Technische Hochschule Ulm (DE), Fraunhofer Institute for Communication, Information Processing and Ergonomics (DE), RWTH Aachen University (DE), Robert Bosch (Germany) (DE)
Gender equality
Openalex Percentile: Top 6%
Human-Automation Interaction and Safety
4.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.