Parallel Dispatching: A New Paradigm for High-Speed Train Operation Management and Optimization

Abstract

In order to tackle the intricate challenges of train dispatching and command within China’s extensive high-speed railways (HSRs) network, this paper presents a novel parallel dispatching approach founded on the ACP (Artificial systems, Computational experiments, and Parallel execution) methodology. We provide a comprehensive overview of the framework and technical architecture of the parallel dispatching system (PDS), offering detailed insights into each fundamental module. It initiates by establishing the PDS for HSRs, emphasizing the deep integration of the actual and artificial systems. The methods for train operation situation deduction, rapid dispatching strategy generation, and comprehensive evaluation of parallel dispatching are then expounded, each tailored to different scales. Subsequently, the paper proposes the creation of a parallel dispatching platform for HSRs, utilizing a real line’s dispatching system as a prototype. Two typical scenarios are considered to validate the effectiveness of the PDS. The computational experiments are designed and executed in the artificial dispatching system to facilitate accurate deduction of operational scenarios and swift generation of dispatching solutions within defined computational constraints. The adjustment effects are assessed and iteratively optimized through parallel execution. The research outcomes of this paper can serve as a theoretical foundation and technical resource for the design, implementation, and validation of PDS in China’s high-speed railway network.