Fei Song, Rong Li, Huachun Zhou, Hongke Zhang, I. You
{"title":"A Case Study for Potential Carpooling in Beijing","authors":"Fei Song, Rong Li, Huachun Zhou, Hongke Zhang, I. You","doi":"10.1109/IMIS.2014.20","DOIUrl":null,"url":null,"abstract":"This paper focuses on providing some fundamental analysis for taxi carpooling based on real taxis' GPS traces. Since the increase of resource utilization is one essential benefit for carpooling scheme, we discussed how many get on points and mileages can be reduced. In order to analyze the situation when more taxis are employed, grey prediction algorithm is adopted and validated. The performance of using such method directly is not quite satisfied. Therefore we proposed a scheme to enhance the accuracy. The final results show: when 40k taxis are running in the system, the get on point may above 198k and 37% of them can be removed if carpooling scheme is fully deployed.","PeriodicalId":345694,"journal":{"name":"2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMIS.2014.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper focuses on providing some fundamental analysis for taxi carpooling based on real taxis' GPS traces. Since the increase of resource utilization is one essential benefit for carpooling scheme, we discussed how many get on points and mileages can be reduced. In order to analyze the situation when more taxis are employed, grey prediction algorithm is adopted and validated. The performance of using such method directly is not quite satisfied. Therefore we proposed a scheme to enhance the accuracy. The final results show: when 40k taxis are running in the system, the get on point may above 198k and 37% of them can be removed if carpooling scheme is fully deployed.
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