Improving Real-Time Train Dispatching: Models, Algorithms and Applications

Speaker

Dr. Andrea D’Ariano
Title Improving Real-Time Train Dispatching: Models, Algorithms and Applications
When 04.12.2008
Where This PhD thesis is principally concerned with the design, implementation and evaluation of an advanced and robust laboratory tool for supporting railway traffic controllers in the everyday task of managing timetable disturbances, including the following achievements:
(i) An innovative model for railway traffic optimization is presented to predict accurately train traffic flows and to enable the computation of optimal network schedules, i.e., all trains are managed simultaneously in a railway network for a given time period.
(ii) The development of fast and effective scheduling algorithms based on the proposed model for the real-time management of a complex railway network is addressed. The objectives are to predict the evolution of train traffic within short computation times and to improve the punctuality by pro-actively detecting and solving train conflicts.
(iii) A better use of rail capacity and a further improvement of punctuality is achieved by an iterative adjustment of train orders and routes in case of disturbances. Novel problem dedicated algorithms highlight the potential use of rerouting instead of only rescheduling the trains in order to limit the delay propagation as much as possible.
(iv) Constructive algorithms for the dynamic modification of running times are provided that satisfy the timetable constraints of train orders and routes and guarantee the real-time feasibility of the running time profile, while respecting the signaling and safety systems in use.
(v) A temporal decomposition method is introduced for the short-term traffic planning and control over a time period of up to several hours. This approach is of interest for traffic controllers since delays propagate considerably in time and space during heavily perturbed operations.
(vi) A large set of computational studies on real-world instances proves that the automated decision support tool provides better solutions in terms of delay minimization compared to dispatching rules adopted by traffic controllers. Test beds are the hourly timetables of the Schiphol railway bottleneck and of the dispatching area between Utrecht and Den Bosch stations. We study practical size instances and different types of disturbances, including multiple delayed trains, dwell time perturbations and blockage of some tracks.

 
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