Using Connected Vehicle Technology for Advanced Signal Control Strategies

For arterial roadways, most Active Traffic and Demand Management (ATDM) strategies focus on traffic signal timing optimization at signalized intersections. A critical drawback of conventional traffic signal control strategies is that they rely on measurements from point detection, and estimate traffic states such as queue length based on very limited information. The introduction of Connected Vehicle (CV) technology can potentially address the limitations of point detection via wireless communications to assist signal phase and timing optimization. In this project report, the authors present an agent-based online adaptive signal control (ASC) strategy based on real-time traffic information available from vehicles equipped with CV technology. The authors then evaluate the proposed strategy in terms of travel delay and fuel consumption, relative to a Highway Capacity Manual (HCM) based method in which hourly traffic demand is assumed to be known accurately a priori. The Connected Vehicle Adaptive Signal Control (CV-ASC) strategy is applied to an isolated traffic intersection as well as to a corridor of traffic intersections. The baseline signalization strategy for the corridor of traffic intersections is coordinated signal control. Study results indicate that for both the isolated intersection and corridor contexts, the proposed strategy outperforms the HCM based method and is very robust to traffic demand variations.

• Record URL:
  https://merritt.cdlib.org/d/ark%253A%252F13030%252Fm53z330b/1/producer%252FNCST-201607.pdf
• Record URL:
  https://ncst.ucdavis.edu/wp-content/uploads/2017/07/NCST-CV-Tech-for-Advanced-Signal-Control-Strategies_Barth-UCR_July-2016-FINAL-.pdf
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/40011
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  National Center for Sustainable Transportation

  University of California, Davis
  Davis, CA  United States 

  University of California, Riverside

  College of Engineering, Center for Environmental Research and Technology
  1084 Columbia Avenue
  Riverside, CA  United States  92507

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Kari, David
  • Wu, Guoyuan
  • Barth, Matthew
• Publication Date: 2016-7

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 60p

Subject/Index Terms

• TRT Terms: Advanced traffic management systems; Exhaust gases; Mobile communication systems; Optimization; Signalized intersections; Traffic flow; Traffic signal control systems; Travel time; Vehicle to infrastructure communications; Vehicle to vehicle communications
• Subject Areas: Environment; Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01642386
• Record Type: Publication
• Report/Paper Numbers: NCST-201607
• Files: BTRIS, UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Jul 27 2017 2:13PM