Dynamic Search of Train Shortest Routes Within Microscopic Traffic Simulators

Abstract

Computer simulations are frequently used for rail traffic optimization. This approach, referred to as simulation-based optimization, typically employs simulation tools – simulators that are designed to examine railway systems at various levels of detail. Microscopic rail traffic simulators find use when examining rail traffic and the rail infrastructure in great detail. Such simulators typically serve to follow the positions and motions of rail vehicles (trains, locomotives, train cars) and their relocation as well as segments of the rail infrastructure (tracks, switches, track crossings). One of the typical problems to be solved by microscopic simulators within a simulation experiment is to determine the realistic (optimal) train and shunting routes (within the currently occupied infrastructure) along which the rail vehicles are moved. This paper describes novel dynamic route searching algorithms applicable to the relocation of rail vehicles within track infrastructure of railway systems. The following main topics are presented in turn: overview of solutions to the problem of finding track routes in the literature, a suitable rail infrastructure model (associated with algorithms that seek admissible routes for the transfer of the relocation objects of given lengths), graph search algorithms computing the shortest track routes (represented by the admissible shortest walks on graphs), illustrative examples of algorithms’ deployment, computational complexity of presented algorithms, comparison with other algorithms and summary of the benefits of newly developed algorithms. The use of the algorithms within the simulation tools (working at the microscopic level of detail) extends the modelling possibilities when searching for realistic track routes (especially for complicated shunting operations), which contributes to better modelling of complex railway traffic (than in the relevant existing rail traffic simulators) and thus to better application of the results of traffic simulations in practice.

Keywords

• Rail traffic
• simulation-based optimizations
• single-train shortest routes