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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.  相似文献   
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Tayfur Altiok 《Risk analysis》2011,31(12):1849-1858
We consider the value of decision support tools for passenger rail system managers. First, we call for models that follow events along main rail lines and then into the surrounding environment where they can cascade onto connected light rail, bus, auto, truck, and other transport modes. Second, we suggest that both probabilistic risk assessment (PRA‐based) and agent‐based models have a role to play at different scales of analysis and for different kinds of risks. Third, we argue that economic impact tools need more systematic evaluation. Fourth, we note that developers of decision support tools face a challenge of balancing their desire for theoretical elegance and the tendency to focus only on high consequence events against decisionmakers’ mistrust of complex tools that they and their staff cannot manage and incorporate into their routine operations, as well as the high costs of developing, updating, and applying decision support tools to transport systems undergoing budget cuts and worker and service reductions.  相似文献   
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The Strait of Istanbul, the narrow waterway separating Europe from Asia, holds a strategic importance in maritime transportation as it links the Black Sea to the Mediterranean. It is considered as one of the world's most congested and difficult-to-navigate waterways. Over 55,000 transit vessels pass through the Strait annually, roughly 20% of which carry dangerous cargo. In this study, we have analyzed safety risks pertaining to transit vessel maritime traffic in the Strait of Istanbul and proposed ways to mitigate them. Safety risk analysis was performed by incorporating a probabilistic accident risk model into the simulation model. A mathematical risk model was developed based on probabilistic arguments regarding instigators, situations, accidents, consequences, and historical data, as well as subject-matter expert opinions. Scenario analysis was carried out to study the behavior of the accident risks, with respect to changes in the surrounding geographical, meteorological, and traffic conditions. Our numerical investigations suggested some significant policy indications. Local traffic density and pilotage turned out to be two main factors affecting the risks at the Strait of Istanbul. Results further indicate that scheduling changes to allow more vessels into the Strait will increase risks to extreme levels. Conversely, scheduling policy changes that are opted to reduce risks may cause major increases in average vessel waiting times. This in turn signifies that the current operations at the Strait of Istanbul have reached a critical level beyond which both risks and vessel delays are unacceptable.  相似文献   
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