Effect of driver-initiated driver control during scheduled transitions with recommendations on reaction times and vehicle control performance in conditional driving automation

A control transition from automation to humans is required in conditional driving automation. Considerable research has been conducted on automation-initiated driver-control that restores drivers into the control loop. However, there is a lack of research on achieving driver-initiated driver control (DIDC) transitions, where drivers deactivate the automated driving at their initiative and pace. This study proposes a DIDC strategy with a recommendation rather than a request for action selection: “I recommend that you deactivate the automated driving mode.” The objective is to investigate the effect of the proposed DIDC strategy on the reaction times and vehicle control performance in scheduled transitions. A scheduled transition scenario was designed with a driving simulator. The current study sought to explore the type of message contents that could achieve DIDC transition: (1) no situational message, (2) situational message, (3) situational message to encourage monitoring, and (4) situational message to recommend deactivation. The behavioral data were analyzed from thirty-nine drivers in simulation for a 21 min drive on a highway. This study found that with the recommendation, the drivers stayed longer with their hands on the steering wheel, focused on the road ahead, and deactivated the automated driving. When achieving DIDC transition, the vehicle control performance was safer at avoiding obstacles. The proposed DIDC strategy is helpful for drivers to deactivate automated driving at their initiative and pace. However, this strategy did not necessarily result in DIDC transition. One challenge is designing escalation steps that accelerate the formation of intentions to deactivate the automated driving. • A strategy for deactivating automated driving at human initiative was explored. • Verbal message with recommendations was designed to help drivers return into loop. • Effects of this strategy were investigated by conducting a simulator experiment. • Automation deactivation times in scheduled transitions were assessed. • This strategy allowed drivers to return to the loop at their initiative and pace.

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Publication Details

Journal
Transportation Research Interdisciplinary Perspectives
Published
2025-09-01
DOI
https://doi.org/10.1016/j.trip.2025.101593
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
2.44

Funders

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article

Effect of driver-initiated driver control during scheduled transitions with recommendations on reaction times and vehicle control performance in conditional driving automation

T. Sato, Makoto Itoh, Yuichi Saito, Yusaku Ichinose
1 citations
Transportation Research Interdisciplinary Perspectives
Human-Automation Interaction and Safety
2.44
article

Effect of driver-initiated driver control during scheduled transitions with recommendations on reaction times and vehicle control performance in conditional driving automation

T. Sato, Makoto Itoh, Yuichi Saito, Yusaku Ichinose
article en
1 citations

Abstract

A control transition from automation to humans is required in conditional driving automation. Considerable research has been conducted on automation-initiated driver-control that restores drivers into the control loop. However, there is a lack of research on achieving driver-initiated driver control (DIDC) transitions, where drivers deactivate the automated driving at their initiative and pace. This study proposes a DIDC strategy with a recommendation rather than a request for action selection: “I recommend that you deactivate the automated driving mode.” The objective is to investigate the effect of the proposed DIDC strategy on the reaction times and vehicle control performance in scheduled transitions. A scheduled transition scenario was designed with a driving simulator. The current study sought to explore the type of message contents that could achieve DIDC transition: (1) no situational message, (2) situational message, (3) situational message to encourage monitoring, and (4) situational message to recommend deactivation. The behavioral data were analyzed from thirty-nine drivers in simulation for a 21 min drive on a highway. This study found that with the recommendation, the drivers stayed longer with their hands on the steering wheel, focused on the road ahead, and deactivated the automated driving. When achieving DIDC transition, the vehicle control performance was safer at avoiding obstacles. The proposed DIDC strategy is helpful for drivers to deactivate automated driving at their initiative and pace. However, this strategy did not necessarily result in DIDC transition. One challenge is designing escalation steps that accelerate the formation of intentions to deactivate the automated driving. • A strategy for deactivating automated driving at human initiative was explored. • Verbal message with recommendations was designed to help drivers return into loop. • Effects of this strategy were investigated by conducting a simulator experiment. • Automation deactivation times in scheduled transitions were assessed. • This strategy allowed drivers to return to the loop at their initiative and pace.

Transportation Research Interdisciplinary PerspectivesVol. 33
University of Tsukuba (JP), National Institute of Advanced Industrial Science and Technology (JP)
Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science, Japan Science and Technology Agency
Openalex Percentile: Top 10%
Human-Automation Interaction and Safety
2.44
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