S. Zhankaziev, A. V. Zamytskih, A. Vorobyev, M. Gavrilyuk, M. Pletnev
{"title":"Predicting Traffic Accidents Using the Conflict Coefficient","authors":"S. Zhankaziev, A. V. Zamytskih, A. Vorobyev, M. Gavrilyuk, M. Pletnev","doi":"10.1109/TIRVED56496.2022.9965547","DOIUrl":null,"url":null,"abstract":"The article presents theoretical approaches to the development of a methodology for predicting the occurrence of road accidents on public roads that occur as a result of collisions of two or more vehicles. The methodology for predicting the occurrence of road accidents is based on data received from transport detectors in real time. The advantage of using the method described above is the possibility of using it in real or forecast time. The described technique can be used for a comprehensive assessment of road safety on public roads, including in real time, when creating control algorithms for highly automated vehicles, as well as when creating intelligent transport systems.","PeriodicalId":173682,"journal":{"name":"2022 Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED)","volume":"561 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIRVED56496.2022.9965547","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The article presents theoretical approaches to the development of a methodology for predicting the occurrence of road accidents on public roads that occur as a result of collisions of two or more vehicles. The methodology for predicting the occurrence of road accidents is based on data received from transport detectors in real time. The advantage of using the method described above is the possibility of using it in real or forecast time. The described technique can be used for a comprehensive assessment of road safety on public roads, including in real time, when creating control algorithms for highly automated vehicles, as well as when creating intelligent transport systems.