{"title":"WiP Abstract: A Mixed Logical Dynamical System Model for Taxi Cruising Support System","authors":"T. Ushio, Masaki Hiromoto, A. Okamoto, T. Akiyama","doi":"10.1109/ICCPS.2016.7479123","DOIUrl":null,"url":null,"abstract":"We are developing a taxi cruising support system implemented as a smartphone application. The system consists of the interface manager, the database, the demand predictor, and the optimizer. The interface manager receives data about the current status of each taxi and sends the current optimal cruising direction and predicted future demands to each taxi. The database stores all information used in the support system including historic data on demands. The optimizer computes the optimal cruising directions of taxies using the future demand predicted at the demand predictor. We derive a novel model of collective behaviors of taxies used for computation of the optimal cruising at the optimizer. The model is described by a mixed logical dynamical system.","PeriodicalId":6619,"journal":{"name":"2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)","volume":"255 1","pages":"1-1"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPS.2016.7479123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We are developing a taxi cruising support system implemented as a smartphone application. The system consists of the interface manager, the database, the demand predictor, and the optimizer. The interface manager receives data about the current status of each taxi and sends the current optimal cruising direction and predicted future demands to each taxi. The database stores all information used in the support system including historic data on demands. The optimizer computes the optimal cruising directions of taxies using the future demand predicted at the demand predictor. We derive a novel model of collective behaviors of taxies used for computation of the optimal cruising at the optimizer. The model is described by a mixed logical dynamical system.
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