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Related Concept Videos

Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Related Experiment Videos

Risk-based decision support tools: protecting rail-centered transit corridors from cascading effects.

Michael R Greenberg1, Karen Lowrie, Henry Mayer

  • 1Center for Transportation Safety, Security and Risk, EJ Bloustein School, Rutgers University. mrg@rci.rutgers.edu

Risk Analysis : an Official Publication of the Society for Risk Analysis
|May 14, 2011
PubMed
Summary

Decision support tools are crucial for passenger rail managers. Integrating models across transport modes and evaluating economic impacts are key, but complexity and cost remain challenges for practical adoption.

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Area of Science:

  • Transportation Science
  • Risk Management
  • Operations Research

Background:

  • Passenger rail systems face increasing complexity and potential disruptions.
  • Effective decision support tools (DSTs) are needed to manage these systems.
  • Current DSTs may not adequately address cascading effects or user needs.

Purpose of the Study:

  • To evaluate the value and application of DSTs for passenger rail management.
  • To identify necessary advancements in modeling and economic impact assessment for DSTs.
  • To address challenges in developing and implementing practical DSTs for rail operations.

Main Methods:

  • Conceptual framework for integrated transport modeling.
  • Discussion of probabilistic risk assessment (PRA-based) and agent-based modeling approaches.
  • Analysis of economic impact assessment methodologies for DSTs.

Main Results:

  • DSTs should model cascading events across multiple transport modes.
  • Both PRA-based and agent-based models offer complementary insights at different scales.
  • Economic impact tools require more systematic evaluation and validation.
  • Balancing theoretical elegance with practical usability is essential for DST adoption.

Conclusions:

  • DSTs need to be comprehensive, covering intermodal impacts and economic consequences.
  • Model selection (PRA vs. agent-based) depends on the scale and type of risk.
  • User trust and operational integration are critical for successful DST implementation in rail management.
  • Addressing cost and complexity is vital for widespread adoption of DSTs in budget-constrained environments.