Train delays are a persistent issue in railway systems, particularly in suburban networks where operational complexity is heightened by frequent services and high passenger volumes. Traditional delay models often overlook the temporal and structural dynamics of real delay propagation. This work applies continuous-time multi-state models to analyze the temporal evolution of delay on the S5 suburban line in Lombardy, Italy. Using detailed operational, meteorological, and contextual data, the study models delay transitions while accounting for observable heterogeneity. The findings reveal how delay dynamics vary by travel direction, time slot, and route segment. Covariates such as station saturation and passenger load are shown to significantly affect the risk of delay escalation or recovery. The study offers both methodological advancements and practical results for improving the reliability of rail services.

翻译：列车延误是铁路系统中持续存在的问题，尤其在郊区网络中，频繁的班次和高客流量加剧了运营复杂性。传统延误模型常忽略实际延误传播的时间与结构动态。本研究应用连续时间多状态模型，分析意大利伦巴第大区S5郊区线路延误的时间演化。通过详细的运营、气象及环境数据，该研究在建模延误转移时考虑了可观测的异质性。研究结果揭示了延误动态如何因行驶方向、时段和路段而异。车站饱和度和乘客负载等协变量被证明显著影响延误升级或恢复的风险。该研究为提升铁路服务可靠性提供了方法论进展与实践成果。