{"title":"基于数据融合的驾驶员选择行为建模信息更新","authors":"M. Dell'Orco, D. Teodorovic","doi":"10.1080/18128600802630232","DOIUrl":null,"url":null,"abstract":"In this article, a method for fusing fuzzy data relevant both to drivers’ experience and provided information is presented. Expected travel time is then updated according to the results of fusion. The method takes into account the ‘compatibility’ of data originating from different sources, and provides information about acceptability of results. Influence of uncertainty on drivers’ compliance with provided information is examined in detail, according to uncertainty-based information theory.","PeriodicalId":49416,"journal":{"name":"Transportmetrica","volume":"43 1","pages":"107 - 123"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/18128600802630232","citationCount":"9","resultStr":"{\"title\":\"Data fusion for updating information in modelling drivers’ choice behaviour\",\"authors\":\"M. Dell'Orco, D. Teodorovic\",\"doi\":\"10.1080/18128600802630232\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, a method for fusing fuzzy data relevant both to drivers’ experience and provided information is presented. Expected travel time is then updated according to the results of fusion. The method takes into account the ‘compatibility’ of data originating from different sources, and provides information about acceptability of results. Influence of uncertainty on drivers’ compliance with provided information is examined in detail, according to uncertainty-based information theory.\",\"PeriodicalId\":49416,\"journal\":{\"name\":\"Transportmetrica\",\"volume\":\"43 1\",\"pages\":\"107 - 123\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/18128600802630232\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportmetrica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/18128600802630232\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportmetrica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/18128600802630232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data fusion for updating information in modelling drivers’ choice behaviour
In this article, a method for fusing fuzzy data relevant both to drivers’ experience and provided information is presented. Expected travel time is then updated according to the results of fusion. The method takes into account the ‘compatibility’ of data originating from different sources, and provides information about acceptability of results. Influence of uncertainty on drivers’ compliance with provided information is examined in detail, according to uncertainty-based information theory.
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