高密度高铁路网列车开行计划安全风险精细化管控研究

Research on Refined Management of Safety Risks in Train Operation Scheduling for High-Density High-Speed Rail Networks

摘要

面向某高密度高速铁路网的高峰期强耦合场景，本文构建列车开行计划安全风险精细化管控方法。首先基于德尔菲与故障 树识别运行组织、指挥协同、设备状态等风险因子，建立运行效率、调度协同性、设备可靠性三维度十五项指标并确定 权重。其次设计以TMS、CTC、CTCS为数据底座的事件驱动闭环流程与滚动冲突评估模型，提出多指标动态阈值预警机 制。以某枢纽三个月数据开展离线回放验证，结果显示冲突风险事件下降60%，调度指令偏差率下降45%，正点率提升至 99.2%，冲突消解平均用时与指令响应中位时长分别缩短近40%，同时能力利用率与设备一致性同步改善。研究验证了在高 密度与跨线占比高场景下，基于数据驱动的闭环管控可显著提升安全与秩序。

Abstract

Addressing the highly coupled peak-hour scenarios of a high-density high-speed railway network, this paper proposes a refined risk management methodology for train operation planning. First, using Delphi and fault tree analysis to identify risk factors— including operational organization, command coordination, and equipment status—the study establishes fifteen indicators across three dimensions (operational efficiency, scheduling coordination, and equipment reliability) with assigned weights. Second, an event-driven closed-loop process and rolling conflict assessment model are developed, leveraging data from TMS, CTC, and CTCS systems, alongside a multi-indicator dynamic threshold early-warning mechanism. Offline validation using three months of data from a key railway hub demonstrated a 60% reduction in conflict risk incidents, a 45% decrease in scheduling command deviation rates, a 99.2% improvement in punctuality rate, and nearly 40% reductions in both average conflict resolution time and median command response duration, alongside enhanced capacity utilization and equipment consistency. The study confirms that data-driven closed- loop management significantly enhances safety and operational efficiency under high-density and cross-line operation conditions.

关键词

高速铁路 / 开行计划 / 安全风险管控 / 动态预警 / 跨线衔接

Key words

high-speed railway / operation schedule / safety risk management / dynamic early warning / cross-line connection

参考文献

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