How many crashes can connected vehicle and automated vehicle technologies prevent: A meta-analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, Ling | - |
dc.contributor.author | Zhong, Hao | - |
dc.contributor.author | Ma, Wanjing | - |
dc.contributor.author | Abdel-Aty, Mohamed | - |
dc.contributor.author | Park, Juneyoung | - |
dc.date.accessioned | 2021-06-22T09:07:18Z | - |
dc.date.available | 2021-06-22T09:07:18Z | - |
dc.date.created | 2021-01-21 | - |
dc.date.issued | 2020-03 | - |
dc.identifier.issn | 0001-4575 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1246 | - |
dc.description.abstract | The connected and automated vehicle (CAV) technologies have made great progresses. It has been commonly accepted that CV or AV technologies would reduce human errors in driving and benefit traffic safety. However, the answer of how many crashes can be prevented because of CV or AV technologies has not reached a consistent conclusion. In order to quantitatively answer this question, this study used meta-analysis to evaluate the safety effectiveness of nine common and important CV or AV technologies, and tested the safety effectiveness of these technologies for six countries. First, 73 studies about the safety impact of CV or AV technologies were filtered out from 826 CAV-related papers or reports. Second, the safety impacts of these technologies with regard to assistant types and triggering times have been compared. It shows AV technologies can play a more significant role than CV technologies, and the technologies with closer triggering time to collision time have greater safety effectiveness. Third, in the meta-analysis, the random effect model was used to evaluate the safety effectiveness, and the funnel plots and trim-and-fill method were used to evaluate and adjust publication bias, so as to objectively evaluate the safety effectiveness of each technology. Then, according to the crash data of six countries, the comprehensive safety effectiveness and compilation of safety effectiveness of the above technologies were calculated. The results show that if all of technologies were implemented in the six countries, the average number of crashes could be reduced by 3.40 million, among which the India would reduce the most (54.24%). Additionally, different countries should develop different development strategies, e.g., USA should prioritize the development of the lane change warning and intersection warning, the UK should prioritize applications related to intersection warning and rear-end warning. Overall, this study provides comprehensive and quantitative understating of the safety effectiveness of CA or AV technologies and would contribute to government, vehicle companies, and agencies in deciding the development priority of CA or AV technologies. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.subject | ADVANCED DRIVER ASSISTANCE | - |
dc.subject | AUTONOMOUS EMERGENCY BRAKING | - |
dc.subject | STABILITY CONTROL | - |
dc.subject | SAFETY BENEFITS | - |
dc.subject | SYSTEMS | - |
dc.subject | COLLISION | - |
dc.subject | SPEED | - |
dc.subject | PERFORMANCE | - |
dc.subject | ACCEPTANCE | - |
dc.subject | IMPACT | - |
dc.title | How many crashes can connected vehicle and automated vehicle technologies prevent: A meta-analysis | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Park, Juneyoung | - |
dc.identifier.doi | 10.1016/j.aap.2019.105299 | - |
dc.identifier.scopusid | 2-s2.0-85077768919 | - |
dc.identifier.wosid | 000514253000016 | - |
dc.identifier.bibliographicCitation | ACCIDENT ANALYSIS AND PREVENTION, v.136 | - |
dc.relation.isPartOf | ACCIDENT ANALYSIS AND PREVENTION | - |
dc.citation.title | ACCIDENT ANALYSIS AND PREVENTION | - |
dc.citation.volume | 136 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Public, Environmental & Occupational Health | - |
dc.relation.journalResearchArea | Social Sciences - Other Topics | - |
dc.relation.journalResearchArea | Transportation | - |
dc.relation.journalWebOfScienceCategory | Ergonomics | - |
dc.relation.journalWebOfScienceCategory | Public, Environmental & Occupational Health | - |
dc.relation.journalWebOfScienceCategory | Social Sciences, Interdisciplinary | - |
dc.relation.journalWebOfScienceCategory | Transportation | - |
dc.subject.keywordPlus | ADVANCED DRIVER ASSISTANCE | - |
dc.subject.keywordPlus | AUTONOMOUS EMERGENCY BRAKING | - |
dc.subject.keywordPlus | STABILITY CONTROL | - |
dc.subject.keywordPlus | SAFETY BENEFITS | - |
dc.subject.keywordPlus | SYSTEMS | - |
dc.subject.keywordPlus | COLLISION | - |
dc.subject.keywordPlus | SPEED | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | ACCEPTANCE | - |
dc.subject.keywordPlus | IMPACT | - |
dc.subject.keywordAuthor | Meta-analysis | - |
dc.subject.keywordAuthor | Connected vehicle and automated vehicle technologies | - |
dc.subject.keywordAuthor | Safety effectiveness | - |
dc.subject.keywordAuthor | Crash data | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.