Decision Making Tool for Applying Adaptive Traffic Control Systems

Adaptive traffic signal control technologies have been increasingly deployed in real world situations. The objective of this project was to develop a decision-making tool to guide traffic engineers and decision-makers who must decide whether or not adaptive control is better suited for a given traffic corridor and/or intersections than the existing actuator control system. The decision-making tool contains a qualitative analysis method and a quantitative analysis method. The qualitative method is a decision tree that lists the critical factors that influence the decision. Traffic analysis on network performance and infrastructure analysis on the required resources could help make decisions step-by-step. The quantitative analysis method is based on big data analysis methods using a large amount of data from various sources such as detectors, 511 systems, weather, and special events. Regression models and support vector machines (SVM) were applied to distinguish “good” and “bad” signal performances, as well as adaptive and actuated control strategies. Results show satisfactory performances of the SVM methods, and a decision-making procedure was developed to guide the deployment of adaptive traffic control.

• Record URL:
  https://www.dot.ny.gov/divisions/engineering/technical-services/trans-r-and-d-repository/C-13-04%20Final%20Report_March%202016.pdf
• 
• Supplemental Notes:
  • Cover title: Decision-Making Tool for Applying Adaptive Traffic Control Systems.
• Corporate Authors:

  Rensselaer Polytechnic Institute

  Department of Civil and Environmental Engineering
  Troy, NY  United States 

  New York State Energy Research and Development Authority

  17 Columbia Circle
  Albany, NY  United States  12203

  New York State Department of Transportation

  Albany, NY  United States  12232

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Ban, Xuegang (Jeff)
  • Wojotowicz, Jeffrey
  • Li, Wan
• Publication Date: 2016-3

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Maps; References; Tables;
• Pagination: 76p

Subject/Index Terms

• TRT Terms: Adaptive control; Data analysis; Decision support systems; Decision trees; Performance measurement; Regression analysis; Traffic signal control systems
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01605776
• Record Type: Publication
• Report/Paper Numbers: C-13-04, No.16-12:
• Contract Numbers: 30902
• Files: TRIS, ATRI, USDOT, STATEDOT
• Created Date: Jul 11 2016 10:50AM