ArticleScientific data2025
A Dataset on Takeover during Distracted L2 Automated Driving.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Personalized Classification of Scenario-Derived Operational Driver-State Classes from Non-Intrusive Wearable Signals in Real-World SAE Level 2 Automated Driving.Sensors (Basel, Switzerland) · 2026Article
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automated driving systems enable drivers to perform various non-driving tasks, which has led to concerns regarding driver distraction during automated driving. These concerns have spurred numerous studies investigating driver performance of fallback to driving (i.e., takeover). However, publicly available datasets that present takeover performance data are insufficient. The lack of datasets limits advancements in developing safe automated driving systems. This study introduces TD2D, a dataset collected from 50 drivers with balanced gender representation and diverse age groups in an L2 automated driving simulator. The dataset comprises 500 cases including takeover performance, workload, physiological, and ocular data collected across 10 secondary task conditions: (1) no secondary tasks, (2) three visual tasks, and (3) six auditory tasks. We anticipate that this dataset will contribute significantly to the advancement of automated driving systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.