Multi-scale and Collaborative Disaster Evacuation Planning Framework

Details

• Creators:
  Zhang, Kai ; Liu, Yongxin ; Yang, Yupeng ; Liu, Dahai ; Song, Houbing
• Corporate Creators:
  North Carolina A&T Sate University. Transportation Institute. Center For Advanced Transportation Mobility
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Air transportation
  • Decision support systems
  • Disaster preparedness
  • Evacuation
  • Disasters and emergency operations
  • Social factors
  • Simulation
  • Social force model
  • Automatic Dependent Surveillance-Broadcast (ADS-B)
• Publication/ Report Number:
  CATM-2021-R2.ERAU
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final
• Corporate Publisher:
  North Carolina A&T Sate University. Transportation Institute. Center For Advanced Transportation Mobility
• Abstract:
  When emergency occurs, no tools are available to assist the decision-making of airline planning and Coordination. In this project, we use big data and multi-agent modeling to integrate ADS-B data and Weather information, to optimize and visualize the airspace strategic planning during disaster, and Develop a forecast and recommendation system to aid the authorities and public for optimal airline Evacuation process, by using the deep reinforcement learning technique.
• Format:
  PDF
• Funding:
  271028P
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/62609/dot_62609_DS1.pdf
• File Type:
  [PDF - 2.26 MB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha256:a0afb5b1f4829b41c0a6d9bf46f734206874560d343021dae0e03e865d539bc5