In real operation, railway traffic always deviates from schedule due to exogenous disturbances and disruptions, and these deviations may cause a domino effect over the whole network. Therefore, evaluating and predicting the influence of these disturbances is of significance in train operation and dispatching. Delay is a commonly used performance indicator to describe degree of these deviations, and it may propagate to other trains. The main cause of delay is the overtime occupation on exclusive blocks. However, hindrance, which evaluates the performance of railway operation from the perspective of infrastructure occupancy, is seldom studied. In this paper, a systematical description and calculation of hindrance in railway systems is introduced from the perspective of infrastructure occupancy based on blocking time theory. The railway network was modeled as several exclusive components with running directions. Based on the precedence order and length of occupancy on conflicting infrastructure components, a sequential hindrance propagation process was identified. The proposed methods were demonstrated through the case of a reference network based on railway simulations. A relationship between the overall influence of hindrance and the length of hindrance was investigated for each infrastructure component, using statistical techniques. The results proved a clear positive relationship between the overall influence of a hindrance and its length. In addition, this relationship is affected by the location of infrastructure and amount of traffic flow in the network.

Transfer synchronization is an important issue in timetable scheduling for an urban rail transit system, especially a cross-platform transfer. In this paper, we aim to optimize the performance of transfer throughout the daily operation of an urban rail transit system. The daily operation is divided into multiple time periods and each time period has a specific headway to fulfill time varied passenger demand. At the same time, the turn-back process of trains should also be considered for a real operation. Therefore, our work enhances the base of the transfer synchronization model taking into account time-dependent passenger demand and utilization of trains. A mixed integer programming model is developed to obtain an optimal timetable, providing a smooth transfer for cross-transfer platform and minimizing the transfer waiting time for all transfer passengers from different directions with consideration of timetable symmetry. By adjusting the departure time of trains based on a predetermined timetable, this transfer optimization model is solved through a genetic algorithm. The proposed model and algorithm are utilized for a real transfer problem in Beijing and the results demonstrate a significant reduction in transfer waiting time.

No abstract