{"title":"数据驱动的高速铁路系统大风风险评估策略","authors":"Guanyuan Zhao, Xiaoping Ma, Xuying Qiu, Hanqing Zhang, Zhiping Zhang","doi":"10.1080/19439962.2023.2253749","DOIUrl":null,"url":null,"abstract":"AbstractRailway accidents caused by gales are indeed influenced by multiple factors, making them a complex process. However, current research and monitoring systems often focus solely on wind speed, overlooking the combined effects of other factors. This paper proposes a data-driven assessment strategy specifically designed for high-speed railways. The disaster-inducing factor, disaster-pregnant environment, disaster-bearing body, and disaster prevention/mitigation capabilities are all taken into consideration. Moreover, it explores the interrelationships between these factors. To validate the proposed mechanism, the spatial-temporal distribution of gale-induced risks along China’s high-speed railways is studied in this paper. By analyzing and interpreting the data, the researchers are able to identify areas and time periods that are particularly prone to gale-induced accidents. These findings are crucial for the development of effective strategies for disaster prevention and mitigation in the context of high-speed railways.Keywords: high-speed railgale disasterrisk assessmentrailway safety Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Natural Science Foundation of China (No. 61903023), State Key Laboratory of Rail Traffic Control and Safety (No. RCS2022ZZ002), and the Fundamental Research Funds for the Central Universities (No. 2022JBXT009).","PeriodicalId":46672,"journal":{"name":"Journal of Transportation Safety & Security","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data-driven gale-induced risk assessment strategy for the high-speed railway system\",\"authors\":\"Guanyuan Zhao, Xiaoping Ma, Xuying Qiu, Hanqing Zhang, Zhiping Zhang\",\"doi\":\"10.1080/19439962.2023.2253749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"AbstractRailway accidents caused by gales are indeed influenced by multiple factors, making them a complex process. However, current research and monitoring systems often focus solely on wind speed, overlooking the combined effects of other factors. This paper proposes a data-driven assessment strategy specifically designed for high-speed railways. The disaster-inducing factor, disaster-pregnant environment, disaster-bearing body, and disaster prevention/mitigation capabilities are all taken into consideration. Moreover, it explores the interrelationships between these factors. To validate the proposed mechanism, the spatial-temporal distribution of gale-induced risks along China’s high-speed railways is studied in this paper. By analyzing and interpreting the data, the researchers are able to identify areas and time periods that are particularly prone to gale-induced accidents. These findings are crucial for the development of effective strategies for disaster prevention and mitigation in the context of high-speed railways.Keywords: high-speed railgale disasterrisk assessmentrailway safety Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Natural Science Foundation of China (No. 61903023), State Key Laboratory of Rail Traffic Control and Safety (No. RCS2022ZZ002), and the Fundamental Research Funds for the Central Universities (No. 2022JBXT009).\",\"PeriodicalId\":46672,\"journal\":{\"name\":\"Journal of Transportation Safety & Security\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Transportation Safety & Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/19439962.2023.2253749\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Transportation Safety & Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/19439962.2023.2253749","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Data-driven gale-induced risk assessment strategy for the high-speed railway system
AbstractRailway accidents caused by gales are indeed influenced by multiple factors, making them a complex process. However, current research and monitoring systems often focus solely on wind speed, overlooking the combined effects of other factors. This paper proposes a data-driven assessment strategy specifically designed for high-speed railways. The disaster-inducing factor, disaster-pregnant environment, disaster-bearing body, and disaster prevention/mitigation capabilities are all taken into consideration. Moreover, it explores the interrelationships between these factors. To validate the proposed mechanism, the spatial-temporal distribution of gale-induced risks along China’s high-speed railways is studied in this paper. By analyzing and interpreting the data, the researchers are able to identify areas and time periods that are particularly prone to gale-induced accidents. These findings are crucial for the development of effective strategies for disaster prevention and mitigation in the context of high-speed railways.Keywords: high-speed railgale disasterrisk assessmentrailway safety Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Natural Science Foundation of China (No. 61903023), State Key Laboratory of Rail Traffic Control and Safety (No. RCS2022ZZ002), and the Fundamental Research Funds for the Central Universities (No. 2022JBXT009).