{"title":"多对多需求响应运输系统的近似解析模型","authors":"Carlos F. Daganzo","doi":"10.1016/0041-1647(78)90007-2","DOIUrl":null,"url":null,"abstract":"<div><p>This paper presents an analytic model to predict average waiting and ridingtimes in urban transportation systems (such as dial-a-bus and taxicabs), which provide non-transfer door-to-door transportation with a dynamically dispatched fleet of vehicles. Three different dispatching algorithms are analyzed with a simple deterministic model, which is then generalized to capture the most relevant stochastic phenomena. The formulae obtained have been successfully compared with simulated data and are simple enough for hand calculation. They are, thus, tools which enable analysts to avoid cumbersome simulation models when contemplating implementing or modifying many-to-many demand responsive transportation systems.</p></div>","PeriodicalId":101259,"journal":{"name":"Transportation Research","volume":"12 5","pages":"Pages 325-333"},"PeriodicalIF":0.0000,"publicationDate":"1978-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0041-1647(78)90007-2","citationCount":"161","resultStr":"{\"title\":\"An approximate analytic model of many-to-many demand responsive transportation systems\",\"authors\":\"Carlos F. Daganzo\",\"doi\":\"10.1016/0041-1647(78)90007-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper presents an analytic model to predict average waiting and ridingtimes in urban transportation systems (such as dial-a-bus and taxicabs), which provide non-transfer door-to-door transportation with a dynamically dispatched fleet of vehicles. Three different dispatching algorithms are analyzed with a simple deterministic model, which is then generalized to capture the most relevant stochastic phenomena. The formulae obtained have been successfully compared with simulated data and are simple enough for hand calculation. They are, thus, tools which enable analysts to avoid cumbersome simulation models when contemplating implementing or modifying many-to-many demand responsive transportation systems.</p></div>\",\"PeriodicalId\":101259,\"journal\":{\"name\":\"Transportation Research\",\"volume\":\"12 5\",\"pages\":\"Pages 325-333\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1978-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0041-1647(78)90007-2\",\"citationCount\":\"161\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0041164778900072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0041164778900072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An approximate analytic model of many-to-many demand responsive transportation systems
This paper presents an analytic model to predict average waiting and ridingtimes in urban transportation systems (such as dial-a-bus and taxicabs), which provide non-transfer door-to-door transportation with a dynamically dispatched fleet of vehicles. Three different dispatching algorithms are analyzed with a simple deterministic model, which is then generalized to capture the most relevant stochastic phenomena. The formulae obtained have been successfully compared with simulated data and are simple enough for hand calculation. They are, thus, tools which enable analysts to avoid cumbersome simulation models when contemplating implementing or modifying many-to-many demand responsive transportation systems.