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Statistical estimation of railroad congestion delay

Author

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  • Gorman, Michael F.

Abstract

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.

Suggested Citation

  • Gorman, Michael F., 2009. "Statistical estimation of railroad congestion delay," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(3), pages 446-456, May.
    • Handle: RePEc:eee:transe:v:45:y:2009:i:3:p:446-456
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    Citations

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    Cited by:

    1. Thomas Spanninger & Beda Büchel & Francesco Corman, 2023. "Train Delay Predictions Using Markov Chains Based on Process Time Deviations and Elastic State Boundaries," Mathematics, MDPI, vol. 11(4), pages 1-23, February.
    2. Agbelie, Bismark & Libnao, Kathleen, 2018. "Unobserved heterogeneity analysis of rail transit incident delays," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 39-43.
    3. Taslimi, Bijan & Babaie Sarijaloo, Farnaz & Liu, Hongcheng & Pardalos, Panos M., 2022. "A novel mixed integer programming model for freight train travel time estimation," European Journal of Operational Research, Elsevier, vol. 300(2), pages 676-688.
    4. Chao Wen & Weiwei Mou & Ping Huang & Zhongcan Li, 2020. "A predictive model of train delays on a railway line," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 470-488, April.
    5. Huang, Ping & Wen, Chao & Fu, Liping & Lessan, Javad & Jiang, Chaozhe & Peng, Qiyuan & Xu, Xinyue, 2020. "Modeling train operation as sequences: A study of delay prediction with operation and weather data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    6. Andreas Økland & Nils O. E. Olsson, 2021. "Punctuality development and delay explanation factors on Norwegian railways in the period 2005–2014," Public Transport, Springer, vol. 13(1), pages 127-161, March.
    7. Tiong, Kah Yong & Ma, Zhenliang & Palmqvist, Carl-William, 2023. "Analyzing factors contributing to real-time train arrival delays using seemingly unrelated regression models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    8. Steven Harrod, 2011. "Modeling Network Transition Constraints with Hypergraphs," Transportation Science, INFORMS, vol. 45(1), pages 81-97, February.
    9. Yang, Cheng & Yin, Weihao & Liu, Xueting & Huang, Yanwen & Lu, Dagang & Zhang, Jie, 2024. "Tornado-induced risk analysis of railway system considering the correlation of parameters," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    10. Krier, Betty & Liu, Chia-Mei & McNamara, Brian & Sharpe, Jerrod, 2014. "Individual freight effects, capacity utilization, and Amtrak service quality," Transportation Research Part A: Policy and Practice, Elsevier, vol. 64(C), pages 163-175.

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