【摘要】 为有效评估高速铁路网络(HSRN)的运输服务性能，保障HSRN面对突发事件的可靠性，基于复杂网络理论，考虑高速铁路服务网络(HSRSN)的动态变化，将时间信息纳入HSRSN的建模，提出一种考虑时空动态特征的HSRN鲁棒性评估方法。基于中国高速铁路实证运行数据，验证考虑时空动态特征评估网络性能的必要性，并从时空维度上探究我国HSRN鲁棒性的分布特点。研究结果表明：不同站点所通过的列车流不同，网络鲁棒性表现出明显的空间分布差异性，且扰动场景不同，站点的列车频次和空间位置对站点重要性的贡献程度亦不同。扰动的发生时间和持续时间是影响网络鲁棒性的2个关键时间要素，其不同组合使网络鲁棒性具有显著的时间分布差异性，此外，扰动对不同时段的网络性能的影响程度不同，导致站点重要度排序在不同时段也存在较大波动性。更多还原

【Abstract】 In order to effectively evaluate the transportation service performance of HSRN and ensure the reliability of HSRN in the face of emergencies, based on complex network theory, a robustness evaluation method considering temporal and spatial dynamic characteristics was proposed. The dynamic changes of HSRSN was considered, and time information was incorporated into the modeling of HSRSN. Based on empirical operation data of high-speed railways in China, the necessity of considering spatiotemporal dynamic characteristics to evaluate network performance was verified, and the distribution characteristics of HSRN robustness in China were explored from the spatiotemporal dimension. The experimental results show that the train flow passing through different stations is different, and the network robustness exhibits a significant spatial distribution difference. Moreover, the disturbance scenarios are different, and the contribution of train frequency and spatial position of stations to the importance of stations is also different. In addition, the occurrence time and duration of disturbances are two key time factors that affect network robustness. Their different combinations result in significant time distribution differences in network robustness. The impact of disturbances on network performance varies at different time periods, resulting in obvious fluctuations in station importance ranking at different time periods.更多还原