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Crash and disengagement data of autonomous vehicles on public roads in California
Autonomous Vehicles (AVs) are being widely tested on public roads in several countries such as the USA, Canada, France, Germany, and Australia. For the transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8610982/ https://www.ncbi.nlm.nih.gov/pubmed/34815404 http://dx.doi.org/10.1038/s41597-021-01083-7 |
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author | Sinha, Amolika Chand, Sai Vu, Vincent Chen, Huang Dixit, Vinayak |
author_facet | Sinha, Amolika Chand, Sai Vu, Vincent Chen, Huang Dixit, Vinayak |
author_sort | Sinha, Amolika |
collection | PubMed |
description | Autonomous Vehicles (AVs) are being widely tested on public roads in several countries such as the USA, Canada, France, Germany, and Australia. For the transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. These reports must be processed before any statistical analysis, which is cumbersome and time-consuming. Our dataset presents the processed disengagement data from 2014 to 2019, crash data till the 10(th) of March 2020 and supplementary road network and land-use data extracted from OpenStreetMap. Primary data are manually assessed and converted into an easily processed format. Our processed data will be advantageous to the research community and enable accelerated research in this domain. For example, the data can be utilised to discern trends in disengagement, observe the distribution of disengagement causes, and investigate the contributory factors of the crashes. Such investigations can subsequently improve the reporting protocols and make policies and laws for the smooth deployment of this disruptive technology. |
format | Online Article Text |
id | pubmed-8610982 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86109822021-12-01 Crash and disengagement data of autonomous vehicles on public roads in California Sinha, Amolika Chand, Sai Vu, Vincent Chen, Huang Dixit, Vinayak Sci Data Data Descriptor Autonomous Vehicles (AVs) are being widely tested on public roads in several countries such as the USA, Canada, France, Germany, and Australia. For the transparent deployment of AVs in California, the California Department of Motor Vehicles (CA DMV) commissioned AV manufacturers to draft and publish reports on disengagements and crashes. These reports must be processed before any statistical analysis, which is cumbersome and time-consuming. Our dataset presents the processed disengagement data from 2014 to 2019, crash data till the 10(th) of March 2020 and supplementary road network and land-use data extracted from OpenStreetMap. Primary data are manually assessed and converted into an easily processed format. Our processed data will be advantageous to the research community and enable accelerated research in this domain. For example, the data can be utilised to discern trends in disengagement, observe the distribution of disengagement causes, and investigate the contributory factors of the crashes. Such investigations can subsequently improve the reporting protocols and make policies and laws for the smooth deployment of this disruptive technology. Nature Publishing Group UK 2021-11-23 /pmc/articles/PMC8610982/ /pubmed/34815404 http://dx.doi.org/10.1038/s41597-021-01083-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Sinha, Amolika Chand, Sai Vu, Vincent Chen, Huang Dixit, Vinayak Crash and disengagement data of autonomous vehicles on public roads in California |
title | Crash and disengagement data of autonomous vehicles on public roads in California |
title_full | Crash and disengagement data of autonomous vehicles on public roads in California |
title_fullStr | Crash and disengagement data of autonomous vehicles on public roads in California |
title_full_unstemmed | Crash and disengagement data of autonomous vehicles on public roads in California |
title_short | Crash and disengagement data of autonomous vehicles on public roads in California |
title_sort | crash and disengagement data of autonomous vehicles on public roads in california |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8610982/ https://www.ncbi.nlm.nih.gov/pubmed/34815404 http://dx.doi.org/10.1038/s41597-021-01083-7 |
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