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Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies
The Intelligent and Connected Vehicle (ICV) is regarded as a high-tech solution to reducing road traffic crashes in many countries across the world. However, it is not clear how effective these technologies are in avoiding crashes. This study sets out to summarize the evidence for the crash avoidanc...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431415/ https://www.ncbi.nlm.nih.gov/pubmed/34501825 http://dx.doi.org/10.3390/ijerph18179228 |
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author | Tan, Hong Zhao, Fuquan Hao, Han Liu, Zongwei |
author_facet | Tan, Hong Zhao, Fuquan Hao, Han Liu, Zongwei |
author_sort | Tan, Hong |
collection | PubMed |
description | The Intelligent and Connected Vehicle (ICV) is regarded as a high-tech solution to reducing road traffic crashes in many countries across the world. However, it is not clear how effective these technologies are in avoiding crashes. This study sets out to summarize the evidence for the crash avoidance effectiveness of technologies equipped on ICVs. In this study, three common methods for safety benefit evaluation were identified: Field operation test (FOT), safety impact methodology (SIM), and statistical analysis methodology (SAM). The advantages and disadvantages of the three methods are compared. In addition, evidence for the crash avoidance effectiveness of Advanced Driver Assistance Systems (ADAS) and Vehicle-to-Vehicle communication Systems (V2V) are presented in the paper. More specifically, target crash scenarios and the effectiveness of technologies including FCW/AEB, ACC, LDW/LDP, BSD, IMA, and LTA are different. Overall, based on evidence from the literature, technologies on ICVs could significantly reduce the number of crashes. |
format | Online Article Text |
id | pubmed-8431415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84314152021-09-11 Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies Tan, Hong Zhao, Fuquan Hao, Han Liu, Zongwei Int J Environ Res Public Health Review The Intelligent and Connected Vehicle (ICV) is regarded as a high-tech solution to reducing road traffic crashes in many countries across the world. However, it is not clear how effective these technologies are in avoiding crashes. This study sets out to summarize the evidence for the crash avoidance effectiveness of technologies equipped on ICVs. In this study, three common methods for safety benefit evaluation were identified: Field operation test (FOT), safety impact methodology (SIM), and statistical analysis methodology (SAM). The advantages and disadvantages of the three methods are compared. In addition, evidence for the crash avoidance effectiveness of Advanced Driver Assistance Systems (ADAS) and Vehicle-to-Vehicle communication Systems (V2V) are presented in the paper. More specifically, target crash scenarios and the effectiveness of technologies including FCW/AEB, ACC, LDW/LDP, BSD, IMA, and LTA are different. Overall, based on evidence from the literature, technologies on ICVs could significantly reduce the number of crashes. MDPI 2021-09-01 /pmc/articles/PMC8431415/ /pubmed/34501825 http://dx.doi.org/10.3390/ijerph18179228 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Tan, Hong Zhao, Fuquan Hao, Han Liu, Zongwei Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies |
title | Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies |
title_full | Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies |
title_fullStr | Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies |
title_full_unstemmed | Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies |
title_short | Evidence for the Crash Avoidance Effectiveness of Intelligent and Connected Vehicle Technologies |
title_sort | evidence for the crash avoidance effectiveness of intelligent and connected vehicle technologies |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431415/ https://www.ncbi.nlm.nih.gov/pubmed/34501825 http://dx.doi.org/10.3390/ijerph18179228 |
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