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Title: Incorporating weather impact in railway traffic control
Author: Wang, Ying
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2018
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Abnormal weather events can have significant impacts on the safety and operational performance of the railways. In Great Britain, weather related train delays run into 1 to 2 million of minutes each year. With the rapid advances in weather forecasting and emerging information technology, the weather forecasting data can be utilised to improve the performance of train control models in dealing with weather events. In this thesis, the forecasted moving weather fronts are map in terms of their temporal and spatial coverage, as well as the corresponding speed restrictions and/or track blockages according to the severity of the weather fronts, onto the railway lines. This enables the control models to consider multiple disruptions in advance of them commencing, instead of dealing with them one by one after they have commenced. Then the proactive train control methods are proposed, i.e. mixed integer liner programming (MILP) and genetic algorithm (GA) for single-track rescheduling in adverse condition, and an MILP model for simultaneous train rerouting and rescheduling model, taking into account forecasted severe weather perturbations. In the models, the forecasted moving weather perturbations on different parts of the rail network are represented as individual constraints, whereby, trains travelling through the adversely impacted zones follow reduced speed limits and in the severely impacted zones where the tracks are blocked, trains need to be rerouted or wait until the blockage disappears. The case studies indicate: a) compared with existing control methods our rescheduling methods have shown to make significant reduction in total train delays (in the case studies examined, an average 21% reduction in delays); b) within the timescale considered, the further ahead the weather forecast information is considered, the less the overall delay tends to be; c) under severe weather disruptions (with track blockage), the proposed rerouting and rescheduling model is shown to be able to effectively and efficiently find a cost effective route and timetable.
Supervisor: Liu, Ronghui ; Kwan, Raymond Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available