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Passenger Rail Security, Planning, and Resilience: Application of Network, Plume, and Economic Simulation Models as Decision Support Tools
Author(s) -
Greenberg Michael,
Lioy Paul,
Ozbas Birnur,
Mantell Nancy,
Isukapalli Sastry,
Lahr Michael,
Altiok Tayfur,
Bober Joseph,
Lacy Clifton,
Lowrie Karen,
Mayer Henry,
Rovito Jennifer
Publication year - 2013
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.12073
Subject(s) - hazard , trace (psycholinguistics) , work (physics) , variety (cybernetics) , transport engineering , simulation modeling , decision support system , hazard model , resilience (materials science) , engineering , computer science , operations research , business , mechanical engineering , philosophy , linguistics , chemistry , physics , organic chemistry , artificial intelligence , actuarial science , economics , thermodynamics , microeconomics
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.