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Evaluation of Eyes Off Road During L2 Activation on Uncontrolled Access Roadways [supporting dataset]
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2023-12-07
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Abstract:The current study investigated eyes-off-road (EOR) behavior of drivers when traveling on uncontrolled access roadways in vehicles equipped with SAE Level 2 (L2) automated features. Previously collected naturalistic driving data were analyzed. Events were split between L2 features being active or available but inactive and matched across a spectrum of criteria (e.g., time of day). Primary analyses focused on L2 activation status and intersection type (no intersection, straight through intersection, and turning) and any interaction between those variables. EOR glances were operationalized in two ways: EOR 1, only forward was considered on road; and EOR 2, all driving-related glances were considered on road. EOR metrics involved total EOR, mean EOR, single longest glance, and number of glances per event. Overall, results for the primary research questions indicated that EOR behavior was higher when L2 was active across all EOR metrics, that intersection type affected EOR behavior on some metrics, and that there was an interaction between these variables for select metrics. Ancillary analyses represented differences for single longest glance when excluding slower speed segments, higher EOR behavior when speeds were below 37 mph, and increased hands-off-wheel behavior when L2 systems were active.
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Content Notes:National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT’s Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. This dataset has been curated to CoreTrustSeal's curation level "C. Initial Curation." To find out more information on CoreTrustSeal's curation levels, please consult their "Curation & Preservation Levels" CoreTrustSeal Discussion Paper" (https://doi.org/10.5281/zenodo.8083359). NTL staff last accessed this dataset at its repository URL on 2024-02-14. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDataCurator@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
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