Analysis of Railyard Congestion and Departure Delay Relationship: a Case Study from Swedish Railways

Abstract

In this paper we propose a macroscopic model framework for departure delay prediction from railyards. The railyard is a large area comprising three sub-yards (arrival, classification, departure). In fact, timely operation at railyard is dependent on coordinated operations in these sub-yards. More importantly, punctual functioning of railyards is crucial for increasing competitiveness of rail freight services throughout the network. Despite previous models, we considered railyard congestion at the arrival yard, time availability of each wagon at the classification yard, and time availability of locomotive at the departure yard. The core part of this paper analyzes the effect of congestion at arrival yard on departure delays. Punctuality data from two Swedish railyards for a seven-year period is used. The congestion is defined as the number of arriving trains three hours before each departure. The results showed that the highest number of delayed departures occur at congestion levels of 4-10, while correlation coefficient is around zero. Analysing the whole dataset reveals that these congestion levels are common for all departures not just the delayed ones. Therefore, we conclude that as three sub-yards are interrelated, a comprehensive definition of congestion at railyard level is required. An elaborate definition of congestion can make it a proper predictor for further delay prediction models.