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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Stochastic Traffic Models for the Adaptive Train Dispatching
verfasst von : Vladimir Chebotarev, Boris Davydov, Aleksandr Godyaev
Erschienen in: Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16)
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Abstract
Adaptive dispatching allows you to adjust the movement of vehicles which improves transport service and reduces costs. Optimal dispatching decisions are taken on the basis of modeling the disturbed traffic. The paper presents the foundations of the stochastic model creation and the methodology of its use in online traffic rescheduling. The authors investigate the base principles of the train traffic stochastic models which are used for the effective dispatching. The paper propose the practical method of macro regulation the train flow which prevents local conflicts between services based on the probabilistic forecasting the headway. Computational results based on experimental data confirm effectiveness of the stochastic model when predicting and solving conflicts in the mixed traffic on the main line.