Macro-Level Classification Yard Capacity Modeling

Classification yards play a very significant role in railroad freight transportation and are often regarded as bottlenecks for railroad networks. In order to understand the capacity of a railroad network, it is important to model the volume-dwell time relationship at classification yards. The dwell time at a yard is related to the yard volume and yard capacity. When the volume is over the yard capacity, the dwell time will increase sharply. Based on a generic yard simulation model, this study fits the widely used Bureau of Public Roads function used in highway capacity to represent the dwell time and volume relationship. This study develops a yard capacity model that incorporates major yard features, such as the humping speed, the number of humps, the number of classification tracks and the number of pullback engines. The model is validated by historical data from 15 classification yards.

With the developed model in this thesis, it would help decision maker understand and make use of the capacity of existing yard infrastructure, also it could be used to justify capital investment in the yard operation. For example, it can help yard workers estimate the present yard capacity based on these yard features. With this estimated yard capacity and cars volume, then yard workers can predict the future dwell time. If the estimated yard capacity is lower than the cars volume, and the dwell time is very large, then it may be necessary to expand the present yard infrastructure. Once the yard capacity can satisfy the demand of railroad freight transport, it could reduce the dwell time very much, which is sure to benefit the whole railway network.