Impact of passenger train capacity and level of service on shared rail corridors with multiple types of freight trains

Shih, M-C., C.T. Dick and C.P.L. Barkan. 2015. Impact of passenger train capacity and level of service on shared rail corridors with multiple types of freight trains. Transportation Research Record: Journal of the Transportation Research Board. 2475: 63-71. doi:10.3141/2475-08.

Abstract

The North American rail network is experiencing capacity constraints because of traffic growth and increases in traffic heterogeneity. Further increases in speed and frequency of passenger service will combine with record levels of crude oil carload and intermodal traffic to demand even more network capacity. Understanding the interaction between passenger trains and this mix of freight traffic can help railroads develop effective strategies to improve network capacity and mitigate delay. Although previous research has focused on heterogeneity between two train types, actual rail lines are subject to multiple classes of trains such as passenger, priority intermodal, manifest, and bulk freight trains. To understand this environment better, this study presents a capacity evaluation process to analyze the performance of lines serving three train types. Although any combination of three train types can be considered, this study focuses on the interaction of passenger, intermodal, and bulk freight trains. The presented process can estimate the maximum train throughput for a particular corridor based on the unique characteristics and required level of service for each train type. A case study demonstrates three potential uses of the capacity evaluation process: the impact of additional passenger trains on lines with multiple types of freight trains, the sensitivity of capacity to the required level of service of each train type, and the effect of train speed heterogeneity between three types of trains. The results of this study provide better insight into the interaction of multiple train types and will aid railroads in maximizing the utility of their network.