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IEEE Transactions on Human-Machine Systems
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
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ZENODO
Preprint . 2023
License: CC BY
Data sources: ZENODO
DBLP
Article . 2024
Data sources: DBLP
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Driver Response to Take-Over Requests in Real Traffic

Authors: Linda Pipkorn; Emma Tivesten; Carol Flannagan; Marco Dozza;

Driver Response to Take-Over Requests in Real Traffic

Abstract

Existing research on control-transitions from automated driving (AD) to manual driving mainly stems from studies in virtual settings. There is a need for studies conducted in real settings to better understand the impacts of increasing vehicle automation on traffic safety. This study aims specifically to understand how drivers respond to take-over requests (TORs) in real traffic by investigating the associations between 1) where drivers look when receiving the TOR, 2) repeated exposure to TORs, and 3) the drivers’ response process. In total, thirty participants were exposed to four TORs after about 5–6 min of driving with AD on public roads. While in AD, participants could choose to engage in nondriving-related tasks (NDRTs). When they received the TOR, for 38% of TORs, participants were already looking on path. For those TORs where drivers looked off path at the time of the TOR, the off-path glance was most commonly towards an NDRT item. Then, for 72% of TORs (independent on gaze direction), drivers started their response process to the TOR by looking towards the instrument cluster before placing their hands on the steering wheel and their foot on the accelerator pedal, and deactivating automation. Both timing and order of these actions varied among participants, but all participants deactivated AD within 10 s from the TOR. The drivers’ gaze direction at the TOR had a stronger association with the response process than the repeated exposure to TORs did. Drivers can respond to TORs in real traffic. However, the response should be considered as a sequence of actions that requires a certain amount of time.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
hybrid
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