Agent-based large-scale emergency evacuation using real-time open government data.
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Agent-based large-scale emergency evacuation using real-time open government data.

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  • English

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    • Abstract:
      The open government initiatives have provided tremendous data resources for the

      transportation system and emergency services in urban areas. This paper proposes

      a traffic simulation framework using high temporal resolution demographic data

      and real time open government data for evacuation planning and operation. A

      comparison study using real-world data in Seattle, Washington is conducted to

      evaluate the framework accuracy and evacuation efficiency. The successful

      simulations of selected area prove the concept to take advantage open government

      data, open source data, and high resolution demographic data in emergency

      management domain. There are two aspects of parameters considered in this study:

      user equilibrium (UE) conditions of traffic assignment model (simple Non-UE vs.

      iterative UE) and data temporal resolution (Daytime vs. Nighttime). Evacuation

      arrival rate, average travel time, and computation time are adopted as Measure of

      Effectiveness (MOE) for evacuation performance analysis. The temporal

      resolution of demographic data has significant impacts on urban transportation

      dynamics during evacuation scenarios. Better evacuation performance estimation

      can be approached by integrating both Non-UE and UE scenarios. The new

      framework shows flexibility in implementing different evacuation strategies and

      accuracy in evacuation performance. The use of this framework can be explored to

      day-to-day traffic assignment to support daily traffic operations.

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