Analysis of Traffic Accidents to Identify Factors Affecting Injury Severity with Fuzzy and Crisp Techniques

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dc.contributor.authorYaman T.T.
dc.contributor.authorBilgiç E.
dc.contributor.authorEsen M.F.
dc.date.accessioned2024-03-13T10:01:03Z
dc.date.available2024-03-13T10:01:03Z
dc.date.issued2021
dc.departmentİstanbul Beykent Üniversitesien_US
dc.descriptionInternational Conference on Intelligent and Fuzzy Systems, INFUS 2020 -- 21 July 2020 through 23 July 2020 -- -- 242349en_US
dc.description.abstractInjury severity in motor vehicle traffic accidents is determined by a number of factors including driver, vehicle, and environment. Airbag deployment, vehicle speed, manner of collusion, atmospheric and light conditions, degree of ejection of occupant’s body from the crash, the use of equipment or other forces to remove occupants from the vehicle, model and type of vehicle have been considered as important risk factors affecting accident severity as well as driver-related conditions such as age, gender, seatbelt use, alcohol and drug involvement. In this study, we aim to identify important variables that contribute to injury severity in the traffic crashes. A contemporary dataset is obtained from National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS). To identify accident severity groups, we performed different clustering algorithms including fuzzy clustering. We then assessed the important factors affecting injury severity by using classification and regression trees (CRT). The results indicate that the most important factor in defining injury severity is deployment of air-bag, followed by extrication, ejection occurrences, travel speed and alcohol involvement. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.identifier.doi10.1007/978-3-030-51156-2_72
dc.identifier.endpage633en_US
dc.identifier.isbn9783030511555
dc.identifier.issn2194-5357
dc.identifier.scopus2-s2.0-85088749229en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage625en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-030-51156-2_72
dc.identifier.urihttps://hdl.handle.net/20.500.12662/2943
dc.identifier.volume1197 AISCen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofAdvances in Intelligent Systems and Computingen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectData miningen_US
dc.subjectInjury severityen_US
dc.subjectTraffic accidentsen_US
dc.titleAnalysis of Traffic Accidents to Identify Factors Affecting Injury Severity with Fuzzy and Crisp Techniquesen_US
dc.typeConference Objecten_US

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