{"title":"基于车载网络理论的城市车辆交通拥堵特性建模与分析","authors":"Minglei Song, Rongrong Li, Binghua Wu, MinWoo Lee","doi":"10.1504/ijvics.2020.10030790","DOIUrl":null,"url":null,"abstract":"In order to solve the problems of pollution and traffic safety caused by vehicle traffic congestion, this paper establishes an analysis model of urban vehicle traffic congestion characteristics based on vehicle network theory. Through the application of vehicular network, the extended mobility model of vehicular network is established, and the extended motion model of vehicular network is simulated with simulation tools and middleware tools to obtain the trajectory data of urban traffic vehicles. Based on the trajectory data, the survival analysis of urban vehicle traffic congestion is carried out. Kaplan-Meyer non-parametric regression model was used to estimate the duration of urban vehicle traffic congestion, and its distribution characteristics were quantitatively analysed. The experimental results show that the traffic congestion characteristics of urban vehicles are significantly different under different influencing factors, and the error of the trajectory data of urban traffic vehicles obtained by the proposed model is less than 1%.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modelling and analysis of urban vehicle traffic congestion characteristics based on vehicle-borne network theory\",\"authors\":\"Minglei Song, Rongrong Li, Binghua Wu, MinWoo Lee\",\"doi\":\"10.1504/ijvics.2020.10030790\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problems of pollution and traffic safety caused by vehicle traffic congestion, this paper establishes an analysis model of urban vehicle traffic congestion characteristics based on vehicle network theory. Through the application of vehicular network, the extended mobility model of vehicular network is established, and the extended motion model of vehicular network is simulated with simulation tools and middleware tools to obtain the trajectory data of urban traffic vehicles. Based on the trajectory data, the survival analysis of urban vehicle traffic congestion is carried out. Kaplan-Meyer non-parametric regression model was used to estimate the duration of urban vehicle traffic congestion, and its distribution characteristics were quantitatively analysed. The experimental results show that the traffic congestion characteristics of urban vehicles are significantly different under different influencing factors, and the error of the trajectory data of urban traffic vehicles obtained by the proposed model is less than 1%.\",\"PeriodicalId\":39333,\"journal\":{\"name\":\"International Journal of Vehicle Information and Communication Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Vehicle Information and Communication Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijvics.2020.10030790\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Vehicle Information and Communication Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijvics.2020.10030790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Modelling and analysis of urban vehicle traffic congestion characteristics based on vehicle-borne network theory
In order to solve the problems of pollution and traffic safety caused by vehicle traffic congestion, this paper establishes an analysis model of urban vehicle traffic congestion characteristics based on vehicle network theory. Through the application of vehicular network, the extended mobility model of vehicular network is established, and the extended motion model of vehicular network is simulated with simulation tools and middleware tools to obtain the trajectory data of urban traffic vehicles. Based on the trajectory data, the survival analysis of urban vehicle traffic congestion is carried out. Kaplan-Meyer non-parametric regression model was used to estimate the duration of urban vehicle traffic congestion, and its distribution characteristics were quantitatively analysed. The experimental results show that the traffic congestion characteristics of urban vehicles are significantly different under different influencing factors, and the error of the trajectory data of urban traffic vehicles obtained by the proposed model is less than 1%.