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

Details

• Creators:
  Lu, Wei ; Liu, Cheng ; Bhaduri, Budhendra L.
• Corporate Creators:
  Oak Ridge National Laboratory
• Subject/TRT Terms:
  Demographics Emergency Management Evacuation Real Time Information Traffic Assignment Traffic Simulation Urban Areas
• Resource Type:
  Tech Report
• Geographical Coverage:
  Seattle (Washington)
• Corporate Publisher:
  Oak Ridge National Laboratory
• 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.
  
  
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:08fc615eb62e4aadfec4774e24b455e65d33dfb99f20b8a9865b4a667d12595c
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/28288/dot_28288_DS1.pdf
• File Type:
  [PDF - 1.02 MB ]