New Headway-Based Analytical Capacity Model Considering Heterogeneous Train Traffic

Abstract

Assessing the railway capacity of a rail network wherein a few types of trains operate with various halting patterns is very difficult, because the headway greatly varies depending on the order in which trains of different types and with different halting patterns run. This paper proposes a new headway-based analytical capacity model that considers heterogeneous train traffic. This model is based on the equalized train concept, which is a virtual train type considering the weighted performances of all train types. The equalized train allows us to ignore the heterogeneity caused by different train types and easily calculate the average headway. Additionally, the equalized train coefficient was developed to serve as a measure of traffic heterogeneity. Monte Carlo simulation was used to approximate the station headway depending on the sequence of trains with different halting patterns. The results obtained by a case study on a major corridor in the Korean railway network reveal that, compared with previous models, the proposed method can obtain a more consistent capacity in accordance with the simulation.