Railway timetables are developed to make operations robust and resilient to small delays. However, disturbances perturb the daily plan, and dispatchers adjust the plan to keep operations feasible and to limit delay propagation. Rescheduling approaches aim at updating the offline timetable at best, in the presence of delays. We present a survey of the recent approaches on online railway traffic rescheduling problems, which exhibit dynamic and stochastic (or, at least, not completely deterministic) aspects. In fact, while online static rescheduling has reached a wide degree of dissemination, much is still to be done with regard to the probabilistic nature of the railway traffic rescheduling problems, and also how to best take uncertainty into account for future states. Open challenges for the future research are finally outlined.
A Review of Online Dynamic Models and Algorithms for Railway Traffic Management
IEEE Transactions on Intelligent Transportation Systems ; 16 , 3 ; 1274-1284
2015-06-01
818266 byte
Article (Journal)
Electronic Resource
English
A Review of Online Dynamic Models and Algorithms for Railway Traffic Management
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