Intelligent algorithm based on support vector data description for automotive collision avoidance system
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yang, I. B. | - |
dc.contributor.author | Na, S. G. | - |
dc.contributor.author | Heo, H. | - |
dc.date.accessioned | 2021-09-03T10:29:59Z | - |
dc.date.available | 2021-09-03T10:29:59Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-02 | - |
dc.identifier.issn | 1229-9138 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/84799 | - |
dc.description.abstract | This paper presents a theoretical expansion of a new intelligent algorithm called extended support vector data description (E-SVDD) for the analysis and control of dynamic groups to realize macroscopic and microscopic behavior prediction in an automotive collision avoidance system. The time to collision concept was extracted as a key parameter via system modeling and used with the E-SVDD algorithm to set up the relevant generalized theoretical system. A new method, along with its practical application, to predict the behavior of micro- and macro-systems in real time and improve the control logic for collision avoidance was realized. A numerical simulation based on actual driving data was performed to compare the proposed collision avoidance logic and the conventional one. The results confirmed the improved performance and effectiveness of the proposed control logic. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | KOREAN SOC AUTOMOTIVE ENGINEERS-KSAE | - |
dc.subject | MODEL | - |
dc.title | Intelligent algorithm based on support vector data description for automotive collision avoidance system | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Heo, H. | - |
dc.identifier.doi | 10.1007/s12239-017-0007-7 | - |
dc.identifier.scopusid | 2-s2.0-84990976908 | - |
dc.identifier.wosid | 000385201800007 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY, v.18, no.1, pp.69 - 77 | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY | - |
dc.citation.title | INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY | - |
dc.citation.volume | 18 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 69 | - |
dc.citation.endPage | 77 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002193959 | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Transportation | - |
dc.relation.journalWebOfScienceCategory | Engineering, Mechanical | - |
dc.relation.journalWebOfScienceCategory | Transportation Science & Technology | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordAuthor | E-SVDD (Extended-Support Vector Data Description) | - |
dc.subject.keywordAuthor | Automotive collision avoidance system | - |
dc.subject.keywordAuthor | TTC (Time to Collision) | - |
dc.subject.keywordAuthor | Automotive control logic | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea 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.