Print Email Facebook Twitter Impact of railway disruption predictions and rescheduling on passenger delays Title Impact of railway disruption predictions and rescheduling on passenger delays Author Ghaemi, N. (TU Delft Transport and Planning) Zilko, A.A. (TU Delft Applied Probability) Yan, F. (TU Delft Transport and Planning) Cats, O. (TU Delft Transport and Planning) Kurowicka, D. (TU Delft Applied Probability) Goverde, R.M.P. (TU Delft Transport and Planning) Date 2018 Abstract Disruptions such as rolling stock breakdown, signal failures, and accidents are recurrent events during daily railway operation. Such events disrupt the deployment of resources and cause delay to passengers. Obtaining a reliable disruption length estimation can potentially reduce the negative impact caused by the disruption. Different factors such as the location, cause of disruption, traffic density, etc. can determine the disruption length. The uncertainty inherent to the variability of each factor and the unavailability of sufficient data results in a wide distribution of disruption lengths from which a certain value should be selected as the length prediction. The rescheduling measure considered in this research is short-turning the trains that are heading to the disrupted area. To investigate the impact of the disruption length estimates on the rescheduling strategy and the resulting passengers delays, this research presents a framework consisting of three models: a disruption length model, short-turning model and passenger assignment model. The framework is applied to a part of the Dutch railway network. The results show the effects of short (optimistic) and long (pessimistic) estimates on the number of affected passengers, generalized travel time and number of passengers rerouting and transferring. Subject Dependence modelPassenger assignmentPredictionRailway disruptionShort-turning To reference this document use: http://resolver.tudelft.nl/uuid:ae7509ff-0ac2-4ca3-9bc9-09f6ce0a0ecd DOI https://doi.org/10.1016/j.jrtpm.2018.02.002 Embargo date 2018-11-03 ISSN 2210-9706 Source Journal of Rail Transport Planning & Management, 8 (2), 103-122 Bibliographical note Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2018 N. Ghaemi, A.A. Zilko, F. Yan, O. Cats, D. Kurowicka, R.M.P. Goverde Files PDF 1_s2.0_S2210970617300872_main.pdf 2.01 MB Close viewer /islandora/object/uuid:ae7509ff-0ac2-4ca3-9bc9-09f6ce0a0ecd/datastream/OBJ/view