Statistical Estimation of Railroad Congestion Delay
operations - traffic, planning - methods, policy - congestion, mode - rail
Traffic congestion, Statistical methods, Statistical analysis, Running time, Railways, Railroads, Mathematical techniques, Mathematical statistics, Mathematical prediction, Mathematical methods, Gridlock (Traffic), Econometric models
This research identifies factors that are the major contributors to freight rail congestion using statistical analysis. Total train running time is predicted based on free running time predictors (horsepower per ton, track topography and slow orders) and congestion-related factors (meets, passes, overtakes, prior time periods' train counts, total train hours, train spacing variability, and train departure headway). Primary congestion predictive factors (meets, passes, overtakes) are consistently found to have the largest effect on congestion delay. The predictive equations are used to forecast average monthly train running time with a 4.6% mean absolute percent error.
Gorman, Michael, (2009). Statistical Estimation of Railroad Congestion Delay. Transportation Research Part E: Logistics and Transportation Review, Volume 45, Issue 3, pp 446-456.