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Analysis of freight transportation network redundancy: An application to Utah’s bi-modal network for transporting coal

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  • Jansuwan, Sarawut
  • Chen, Anthony
  • Xu, Xiangdong

Abstract

Freight transportation network is an essential backbone for supporting the industrial activities and economic developments of the nation and global trade. In this paper, we extend the network-based measures recently developed by Xu et al. (2018) for assessing freight transportation network redundancy – an important component in making freight transportation networks more robust and resilient against disruptions. Redundancy of freight transportation networks is characterized by two network-based measures. The route diversity measure evaluates the existence of multiple efficient routes available for freight users or the degree of connections between a specific origin-destination (O-D) pair, while the network spare capacity measure quantifies the network-wide spare capacity with an explicit consideration of congestion effect and modal split. These two measures can complement each other by providing a two-dimensional characterization of freight transportation network redundancy that can be used to provide information to freight users as well as to assist network planners in making future infrastructure investment decisions to enhance the redundancy of freight transportation networks. A case study of the Utah freight network for transporting coal is provided to demonstrate the features of the two network-based redundancy measures as well as the applicability of assessing the redundancy of freight transportation networks. The analyses reveal that the two measures provide useful results from two perspectives that may be of benefit to freight carriers and transportation system planners.

Suggested Citation

  • Jansuwan, Sarawut & Chen, Anthony & Xu, Xiangdong, 2021. "Analysis of freight transportation network redundancy: An application to Utah’s bi-modal network for transporting coal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 154-171.
    • Handle: RePEc:eee:transa:v:151:y:2021:i:c:p:154-171
    DOI: 10.1016/j.tra.2021.06.019
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    as
    1. Loo, Becky P.Y. & Leung, Kevin Y.K., 2017. "Transport resilience: The Occupy Central Movement in Hong Kong from another perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 100-115.
    2. Chang Liu & Boliang Lin & Jiaxi Wang & Jie Xiao & Siqi Liu & Jianping Wu & Jian Li, 2017. "Flow assignment model for quantitative analysis of diverting bulk freight from road to railway," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-22, August.
    3. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    4. Xu, Xiangdong & Chen, Anthony & Cheng, Lin & Yang, Chao, 2017. "A link-based mean-excess traffic equilibrium model under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 53-75.
    5. Fumitaka Kurauchi & Nobuhiro Uno & Agachai Sumalee & Yumiko Seto, 2009. "Network Evaluation Based on Connectivity Vulnerability," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 637-649, Springer.
    6. Abril, M. & Barber, F. & Ingolotti, L. & Salido, M.A. & Tormos, P. & Lova, A., 2008. "An assessment of railway capacity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 774-806, September.
    7. Reggiani, Aura & Nijkamp, Peter & Lanzi, Diego, 2015. "Transport resilience and vulnerability: The role of connectivity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 4-15.
    8. Chen, Anthony & Pravinvongvuth, Surachet & Xu, Xiangdong & Ryu, Seungkyu & Chootinan, Piya, 2012. "Examining the scaling effect and overlapping problem in logit-based stochastic user equilibrium models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1343-1358.
    9. Jansuwan, Sarawut & Ryu, Seungkyu & Chen, Anthony, 2017. "A two-stage approach for estimating a statewide truck trip table," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 274-292.
    10. David L. Alderson & Gerald G. Brown & W. Matthew Carlyle & R. Kevin Wood, 2018. "Assessing and Improving the Operational Resilience of a Large Highway Infrastructure System to Worst-Case Losses," Transportation Science, INFORMS, vol. 52(4), pages 1012-1034, August.
    11. Wong, S. C. & Yang, Hai, 1997. "Reserve capacity of a signal-controlled road network," Transportation Research Part B: Methodological, Elsevier, vol. 31(5), pages 397-402, October.
    12. Xu, Xiangdong & Chen, Anthony & Jansuwan, Sarawut & Yang, Chao & Ryu, Seungkyu, 2018. "Transportation network redundancy: Complementary measures and computational methods," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 68-85.
    13. Xu, Xiangdong & Chen, Anthony & Kitthamkesorn, Songyot & Yang, Hai & Lo, Hong K., 2015. "Modeling absolute and relative cost differences in stochastic user equilibrium problem," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 686-703.
    14. Yang, Hai & Bell, Michael G. H. & Meng, Qiang, 2000. "Modeling the capacity and level of service of urban transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(4), pages 255-275, May.
    15. Leurent, Fabien M., 1997. "Curbing the computational difficulty of the logit equilibrium assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 31(4), pages 315-326, August.
    16. Cox, Andrew & Prager, Fynnwin & Rose, Adam, 2011. "Transportation security and the role of resilience: A foundation for operational metrics," Transport Policy, Elsevier, vol. 18(2), pages 307-317, March.
    17. D’Lima, Minette & Medda, Francesca, 2015. "A new measure of resilience: An application to the London Underground," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 35-46.
    18. Lichun Chen & Elise Miller-Hooks, 2012. "Resilience: An Indicator of Recovery Capability in Intermodal Freight Transport," Transportation Science, INFORMS, vol. 46(1), pages 109-123, February.
    19. Morlok, Edward K. & Chang, David J., 2004. "Measuring capacity flexibility of a transportation system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(6), pages 405-420, July.
    20. Chen, Anthony & Kasikitwiwat, Panatda, 2011. "Modeling capacity flexibility of transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 105-117, February.
    21. Chen, Anthony & Zhou, Zhong & Lam, William H.K., 2011. "Modeling stochastic perception error in the mean-excess traffic equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1619-1640.
    22. Boyce, David, 2013. "Beckmann's transportation network equilibrium model: Its history and relationship to the Kuhn–Tucker conditions," Economics of Transportation, Elsevier, vol. 2(1), pages 47-52.
    23. Oliveira, Eduardo Leal de & Portugal, Licínio da Silva & Porto Junior, Walter, 2016. "Indicators of reliability and vulnerability: Similarities and differences in ranking links of a complex road system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 195-208.
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