United States Department of Transportation
i
Advancing Crash Investigation With Connected and Automated Vehicle Data – Phase 2 [supporting dataset]
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2024-09-13
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Alternative Title:Advancing Crash Investigation With Connected and Automated Vehicle Data – Phase 2 [R42]
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Abstract:This project aims to identify training needs in the area of automated driving systems (ADS) for law enforcement officers and crash investigators to identify data available for connected and automated vehicles (CAV) that can augment modern crash investigation procedures. The objective of this project is to investigate these two topics by engaging professional collision investigators for perspectives on augmenting investigations with CAV data and reconnect with law enforcement to identify training gaps. The research findings and products will be of interest to law enforcement, state agencies such as DOT and DMV, private sector crash investigators, and advocates for safety such as AAA Foundation. This work expands on CSCRS Project R25 Advancing Crash Investigation with Connected and Automated Vehicle Data which focused exclusively on the perspectives of law enforcement officers. Two key findings of the previous work showed that law enforcement tended to focus their recommendations on current shortcomings in collision investigation data, rather than on an expansion of data collection capabilities, and this focus was likely related to a lack of exposure to ADS technology.
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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.11476980). NTL staff last accessed this dataset at its repository URL on 2024-10-03. 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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