{"title":"A stochastic approach for assessing intervention strategies in the case of metro system failures","authors":"M. Botte, L. D’Acierno, B. Montella, A. Placido","doi":"10.1109/AEIT.2015.7415258","DOIUrl":null,"url":null,"abstract":"Smart mobility is a key factor in the new conceptual urban development model, the so-called \"smart city\". We focus on rail and metro transport, proposing a multidimensional constrained optimisation model to carry out a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed operations. Indeed, after the occurrence of a disturbance or disruption, appropriate intervention strategies have to be implemented in order to address the problem and re-establish ordinary daily service conditions as rapidly as possible. The paper specifically aims to improve the traditional deterministic framework, introducing a stochastic disturbance on train performances and delays, in order to simulate operations as closely as possible to reality, with an ad-hoc objective function to be minimised. An application on a real metro line in Naples (Italy) is provided, showing the benefits of the proposed approach.","PeriodicalId":368119,"journal":{"name":"2015 AEIT International Annual Conference (AEIT)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 AEIT International Annual Conference (AEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AEIT.2015.7415258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Smart mobility is a key factor in the new conceptual urban development model, the so-called "smart city". We focus on rail and metro transport, proposing a multidimensional constrained optimisation model to carry out a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed operations. Indeed, after the occurrence of a disturbance or disruption, appropriate intervention strategies have to be implemented in order to address the problem and re-establish ordinary daily service conditions as rapidly as possible. The paper specifically aims to improve the traditional deterministic framework, introducing a stochastic disturbance on train performances and delays, in order to simulate operations as closely as possible to reality, with an ad-hoc objective function to be minimised. An application on a real metro line in Naples (Italy) is provided, showing the benefits of the proposed approach.