In this study, we propose a new schedule-based itinerary-choice model, the mixed itinerary-size weibit model, to address the independently and identically distributed assumptions that are typically used in random utility models and heterogeneity of passengers’ perceptions. Specifically, the Weibull distributed random error term resolves the perception variance with respect to various itinerary lengths, an itinerary-size factor term is suggested to solve the itinerary overlapping problem, and random coefficients are used to model heterogeneity of passengers. We also apply the mixed itinerary-size weibit model to a train-scheduling model to generate a passenger-oriented schedule plan. We test the efficiency and applicability of the train-scheduling model in the south China high-speed railway network, and we find that it works well and can be applied to large real-world problems.

在这项研究中，我们提出了一个新的基于时间表的行程选择模型，即混合行程大小的weibit模型，以解决通常用于随机效用模型和乘客感知异质性的独立且分布均匀的假设。具体来说，Weibull分布随机误差项解决了针对各种行程长度的感知差异，建议使用行程大小因子项来解决行程重叠问题，并使用随机系数来建模乘客的异质性。我们还将混合行程大小的weibit模型应用于火车调度模型，以生成面向乘客的调度计划。我们测试了火车调度模型在华南高速铁路网中的效率和适用性，