Prediction algorithms for urban traffic control

Details

• Creators:
  Mengert, Peter ; Brown, P. ; Yuan, L.
• Corporate Creators:
  John A. Volpe National Transportation Systems Center (U.S.)
• Subject/TRT Terms:
  • Highway traffic control
  • Advanced traffic management systems
  • Traffic volume
  • Algorithms
  • Mathematical prediction
  • Time series analysis
• Publication/ Report Number:
  DOT-TSC-HW913-PM-79-6
• Resource Type:
  Tech Report
• Geographical Coverage:
  Toronto (Canada)
• Edition:
  Project memorandum
• Corporate Publisher:
  John A. Volpe National Transportation Systems Center (U.S.)
• NTL Classification:
  NTL-SAFETY AND SECURITY-SAFETY AND SECURITY ; NTL-SAFETY AND SECURITY-Human Factors ; NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Flow ; NTL-OPERATIONS AND TRAFFIC CONTROLS-OPERATIONS AND TRAFFIC CONTROLS
• Abstract:
  The objectives of this study are to 1) review and assess the state-of-the-art of prediction algorithms for urban traffic control in terms of their accuracy and application, and 2) determine the prediction accuracy obtainable by examining the performance of general time series analysis methods with actual data. This report is divided into two parts. Part I discusses the review and assessment, while Part II examines general time series analysis methods. Accurate prediction algorithms are necessary for the effective operation of computerized traffic responsive control systems. These systems offer the potential for reducing traffic congestion and improving operational efficiency in the existing urban roadway system.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/8583/dot_8583_DS1.pdf
• File Type:
  [PDF - 5.03 MB]
• Collection(s):
  Volpe Center
• Main Document Checksum:
  urn:sha256:14d06b36cab564367760b2742a215d98c32121ee097c69bfb9a5f883e1735ee8