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Passenger Rail Security, Planning, and Resilience: Application of Network, Plume, and Economic Simulation Models as Decision Support Tools

Author

Listed:
  • Michael Greenberg
  • Paul Lioy
  • Birnur Ozbas
  • Nancy Mantell
  • Sastry Isukapalli
  • Michael Lahr
  • Tayfur Altiok
  • Joseph Bober
  • Clifton Lacy
  • Karen Lowrie
  • Henry Mayer
  • Jennifer Rovito

Abstract

We built three simulation models that can assist rail transit planners and operators to evaluate high and low probability rail‐centered hazard events that could lead to serious consequences for rail‐centered networks and their surrounding regions. Our key objective is to provide these models to users who, through planning with these models, can prevent events or more effectively react to them. The first of the three models is an industrial systems simulation tool that closely replicates rail passenger traffic flows between New York Penn Station and Trenton, New Jersey. Second, we built and used a line source plume model to trace chemical plumes released by a slow‐moving freight train that could impact rail passengers, as well as people in surrounding areas. Third, we crafted an economic simulation model that estimates the regional economic consequences of a variety of rail‐related hazard events through the year 2020. Each model can work independently of the others. However, used together they help provide a coherent story about what could happen and set the stage for planning that should make rail‐centered transport systems more resistant and resilient to hazard events. We highlight the limitations and opportunities presented by using these models individually or in sequence.

Suggested Citation

  • Michael Greenberg & Paul Lioy & Birnur Ozbas & Nancy Mantell & Sastry Isukapalli & Michael Lahr & Tayfur Altiok & Joseph Bober & Clifton Lacy & Karen Lowrie & Henry Mayer & Jennifer Rovito, 2013. "Passenger Rail Security, Planning, and Resilience: Application of Network, Plume, and Economic Simulation Models as Decision Support Tools," Risk Analysis, John Wiley & Sons, vol. 33(11), pages 1969-1986, November.
    • Handle: RePEc:wly:riskan:v:33:y:2013:i:11:p:1969-1986
    DOI: 10.1111/risa.12073
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    References listed on IDEAS

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    Cited by:

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    3. Ali Jamshidi & Shahrzad Faghih‐Roohi & Siamak Hajizadeh & Alfredo Núñez & Robert Babuska & Rolf Dollevoet & Zili Li & Bart De Schutter, 2017. "A Big Data Analysis Approach for Rail Failure Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1495-1507, August.

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