{"title":"交通流的贝叶斯分层建模-在马耳他道路网络中的应用","authors":"Luana Chetcuti Zammit, M. Attard, K. Scerri","doi":"10.1109/ITSC.2013.6728423","DOIUrl":null,"url":null,"abstract":"A Bayesian Hierarchical Model is presented to estimate route choice preferences between OD pairs. The methodology adopted utilizes both Origin-Destination (OD) information and traffic counts observed on some of the links in the network to estimate route choice probabilities. Route choice preferences are represented by multinomial distributions and estimated via a Markov Chain Monte Carlo (MCMC) algorithm. The proposed model takes into account measurement errors in the link counts, the uncertanties present in OD data and alternative routes choices both inside or outside the network of study. The proposed method is validated on both a synthetic example and the traffic network of Malta.","PeriodicalId":275768,"journal":{"name":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Bayesian hierarchical modelling of traffic flow - With application to Malta's road network\",\"authors\":\"Luana Chetcuti Zammit, M. Attard, K. Scerri\",\"doi\":\"10.1109/ITSC.2013.6728423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Bayesian Hierarchical Model is presented to estimate route choice preferences between OD pairs. The methodology adopted utilizes both Origin-Destination (OD) information and traffic counts observed on some of the links in the network to estimate route choice probabilities. Route choice preferences are represented by multinomial distributions and estimated via a Markov Chain Monte Carlo (MCMC) algorithm. The proposed model takes into account measurement errors in the link counts, the uncertanties present in OD data and alternative routes choices both inside or outside the network of study. The proposed method is validated on both a synthetic example and the traffic network of Malta.\",\"PeriodicalId\":275768,\"journal\":{\"name\":\"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2013.6728423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2013.6728423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bayesian hierarchical modelling of traffic flow - With application to Malta's road network
A Bayesian Hierarchical Model is presented to estimate route choice preferences between OD pairs. The methodology adopted utilizes both Origin-Destination (OD) information and traffic counts observed on some of the links in the network to estimate route choice probabilities. Route choice preferences are represented by multinomial distributions and estimated via a Markov Chain Monte Carlo (MCMC) algorithm. The proposed model takes into account measurement errors in the link counts, the uncertanties present in OD data and alternative routes choices both inside or outside the network of study. The proposed method is validated on both a synthetic example and the traffic network of Malta.