Research on adaptive parking planning of heavy-haul trains on Shenmu-Shuozhou railway

Planning operation curves in parking scenarios for heavy-haul trains equipped with intelligent driving features on the Shenmu-Shuozhou railway faces two primary challenges: maneuvering difficulties stemming from the inherent characteristics of heavy-haul trains and the complexity of the track environments. These factors combine to significantly complicate the planning of operation curves. This paper presents an algorithm designed to address the safety and precision-oriented parking planning requirements for heavy-haul trains on the Shenmu-Shuozhou railway. First, a longitudinal dynamic model was established based on the track characteristics and maneuvering requirements, incorporating relevant constraints. Second, the planning process was divided into air braking and non-air braking stages, with planning strategies formulated according to their respective characteristics. Subsequently, evaluation indicators were proposed, taking into account actual engineering conditions, and an adaptive weight adjustment strategy was employed to enhance the algorithm's adaptability to various parking scenarios. Additionally, a refined adjustment strategy was developed to further reduce planning errors. Finally, a hardware-in-the-loop simulation platform was utilized to test and verify the proposed algorithm in three typical sections. The verification results show that the proposed algorithm achieves an average parking planning error of 1.31 meters while meeting the safety constraints , demonstrating the algorithm’s effectiveness and highlighting its value in practical engineering applications.