Automated Congestion Prediction With Smart Phones

Details

• Creators:
  Gokhale, Swapna S. ; Lownes, Nicholas
• Corporate Creators:
  New England University Transportation Center ; University of Connecticut. Connecticut Transportation Institute ; Massachusetts Institute of Technology
• Corporate Contributors:
  United States. Department of Transportation. Research and Innovative Technology Administration
• Subject/TRT Terms:
  • Data collection
  • Feasibility analysis
  • Mobile applications
  • Smartphones
  • Traffic congestion
  • Traffic flow
  • Traffic forecasting Data and Information Technology
  • Highways
  • Cell phones
  • Operations and Traffic Management
  More +
• Resource Type:
  Brief
• Geographical Coverage:
  United States;Connecticut
• Edition:
  Final Report
• Corporate Publisher:
  New England University Transportation Center
• Abstract:
  Accurate collection of traffic data is essential for tactical efficient highway operations and strategic planning. Currently, the collection of such traffic data relies on physical sensors, which gather limited measurements of vehicle speeds and times as observed from fixed locations. These sensors cannot systematically acquire data on the mobility dynamics of individual vehicles and collective interactions among them, preventing the formulation of detailed models of vehicle flow within a transportation network. Finally, deployment and maintenance of physical sensors is expensive and time consuming.
• Format:
  PDF
• Funding:
  DTRT12-G-UTC01;UCNR24-29
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/39683/dot_39683_DS1.pdf
• File Type:
  [PDF - 172.81 KB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:0dcd5eab4f4017b5251957429800579b8e385ea4318e3b4a58b703e9790c7a8a41cb509058ee62e9807f58b8bca378abcf18b21a442de7ae9ce19765bf0b4a0c