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.
A stochastic approach for assessing intervention strategies in the case of metro system failures / Botte, Marilisa; D'Acierno, Luca; Montella, Bruno; Placido, Antonio. - (2015), pp. 1-6. (Intervento presentato al convegno AEIT International Annual Conference 2015 “A sustainable development in the Mediterranean area” tenutosi a Naples, Italy nel October 2015) [10.1109/AEIT.2015.7415258].
A stochastic approach for assessing intervention strategies in the case of metro system failures
BOTTE, MARILISA;D'ACIERNO, LUCA;MONTELLA, BRUNO;PLACIDO, ANTONIO
2015
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.