Utilize Crowd-Sourced Data and Machine Learning Technology to Enhance Planning for Transportation Resilience to Flooding

Transportation plays a critical role in building community resilience to disasters. The latest federal transportation legislation requires transportation agencies to incorporate resiliency into their transportation planning process. However, agencies like metropolitan planning organizations (MPOs) and emergency management authorities are short of effective tools to assess real-time disaster conditions and affected areas in order to make quick responses. This project aims at developing a decision support system (DSS) that combines non-traditional, crowdsourced big-data with traditional data (e.g. remotely sensed data, geographic information services (GIS), and statistical data) to improve flood risk assessment and enhance transportation readiness for quick response decisions on disaster management. The project focuses on urban flooding. While not all urban flooding is severe enough to threaten lives and property loss, it is the small scale flooding events that reveal the vulnerable sites, segments, and sectors where major damages likely occur when severe storms and hurricanes hit.

Language

• English

Project

• Status: Active
• Funding: $87500
• Contract Numbers:

  69A3551747135

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Project Managers:

  Stearns, Amy

• Performing Organizations:

  Cooperative Mobility for Competitive Megaregions (CM2)

  University of Texas at Austin
  Austin, TX  United States  78712
• Principal Investigators:

  Zhang, Ming

  Pan, Qisheng

• Start Date: 20180901
• Expected Completion Date: 20190831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Crowdsourcing; Decision support systems; Disaster preparedness; Disaster resilience; Floods; Machine learning; Risk assessment; Transportation planning; Urban areas
• Subject Areas: Planning and Forecasting; Security and Emergencies; Transportation (General);

Filing Info

• Accession Number: 01674188
• Record Type: Research project
• Source Agency: Cooperative Mobility for Competitive Megaregions (CM2)
• Contract Numbers: 69A3551747135
• Files: UTC, RIP
• Created Date: Jun 29 2018 11:47AM