Using Real-Time Traffic Data to Improve Traffic Flow

This research, conducted in collaboration between University of Massachusetts Amherst and University of Rhode Island, aims to improve traffic flow by providing travelers better information such as travel times. This research consists of three parts. Part one deals with short-term traffic prediction, Part two deals with travel time estimation, and Part three concerns the detection of incidents from automated traffic data.

• Record URL:
  http://utc.mit.edu/uploads/files/UMAR17-9%20FP.pdf
• 
• Supplemental Notes:
  • This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of Massachusetts, Amherst

  Department of Civil and Environmental Engineering
  130 Natural Resources Road
  Amherst, MA  United States  01003

  University of Rhode Island, Kingston

  Kingston, RI  United States  02881

  New England University Transportation Center

  Massachusetts Institute of Technology
  77 Massachusetts Avenue, Room 40-279
  Cambridge, MA  United States  01239
• Authors:
  • Ni, Daiheng
  • Shuldiner, Paul
  • Peckham, Joan
  • Swaszek, Peter
  • Thomas, Natacha
  • Hunter, Chris
• Publication Date: 2007-2

Language

• English

Media Info

• Media Type: Print
• Edition: Final Report
• Features: Figures; Maps; References; Tables;
• Pagination: 40p

Subject/Index Terms

• TRT Terms: Incident detection; Intelligent transportation systems; Intelligent transportation systems programs; Traffic data; Traffic flow; Traffic forecasting; Travel time; Travelers
• Geographic Terms: Massachusetts; Rhode Island
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Society; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01046412
• Record Type: Publication
• Contract Numbers: UMAR17-9
• Files: UTC, TRIS
• Created Date: Apr 25 2007 1:08PM