Jie Li, Y. Chen, Hao Li, I. Andreasson, H. J. Zuylen
{"title":"Optimizing the fleet size of a Personal Rapid Transit system: A case study in port of Rotterdam","authors":"Jie Li, Y. Chen, Hao Li, I. Andreasson, H. J. Zuylen","doi":"10.1109/ITSC.2010.5625002","DOIUrl":null,"url":null,"abstract":"Cost issues have been an important concern in the development of Personal Rapid Transit (PRT) since the concept was developed several decades ago. The lightweight, computerguided electric vehicles operating the PRT system are generally a major part of the capital cost of the system, especially in larger network with high demand. A sufficient number of empty vehicles are needed to be moved to the stations where passengers are waiting or demand is expected. Generally a larger fleet size leads to a reduction in waiting time of passengers and thus a higher level of service given a specific demand, but an increased investment cost including capital cost per vehicle and additional operation and maintenance. So it requires a compromise between user cost (in terms of passenger waiting times) and operator cost (in terms of fleet sizedependent capital cost and operating/maintenance costs). There should be an optimal fleet size so that the sum of these two costs can be minimized while an expected level of service is achieved. This paper presents first the way to obtain the PRT demand, and then a prescription to determine the optimal fleet size using a cost-effectiveness analysis with traffic simulation. This prescription identifies the set of activities that are necessary to perform the optimization task. Each activity is regarded as a component in our general framework and this framework is illustrated by a case study in the Waal/ Eemshaven harbor area in the Port of Rotterdam, The Netherlands.","PeriodicalId":176645,"journal":{"name":"13th International IEEE Conference on Intelligent Transportation Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"13th International IEEE Conference on Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2010.5625002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
Cost issues have been an important concern in the development of Personal Rapid Transit (PRT) since the concept was developed several decades ago. The lightweight, computerguided electric vehicles operating the PRT system are generally a major part of the capital cost of the system, especially in larger network with high demand. A sufficient number of empty vehicles are needed to be moved to the stations where passengers are waiting or demand is expected. Generally a larger fleet size leads to a reduction in waiting time of passengers and thus a higher level of service given a specific demand, but an increased investment cost including capital cost per vehicle and additional operation and maintenance. So it requires a compromise between user cost (in terms of passenger waiting times) and operator cost (in terms of fleet sizedependent capital cost and operating/maintenance costs). There should be an optimal fleet size so that the sum of these two costs can be minimized while an expected level of service is achieved. This paper presents first the way to obtain the PRT demand, and then a prescription to determine the optimal fleet size using a cost-effectiveness analysis with traffic simulation. This prescription identifies the set of activities that are necessary to perform the optimization task. Each activity is regarded as a component in our general framework and this framework is illustrated by a case study in the Waal/ Eemshaven harbor area in the Port of Rotterdam, The Netherlands.