Leveraging Connected Vehicles to Enhance Traffic Responsive Traffic Signal Control

Actuated traffic signal controllers rely on sensors to detect vehicles so that green time can be allocated on a second-by-second basis. Traffic signals that are part of a closed loop system running coordination plans can also utilize detector information to select different pre-programmed plans based on the current traffic state. These Traffic Responsive Plan Selection (TRPS) algorithms currently rely on point detectors that only measure volume and occupancy. With the anticipated implementation of Connected Vehicles, sensors can be installed at signalized intersections to collect the trajectory of these vehicles, which will allow queue lengths to be estimated. Additionally, many radar-based sensors that are currently on the market are capable of tracking vehicles approaching an intersection, which can also be used to estimate queue lengths. This queue length information can be fused with the volume and occupancy data from point detectors to gain an even better understanding of the state of the signal system. This enhanced information could likely allow even better selection of pre-programmed coordination plans. When trajectory-based vehicle information becomes widespread and reliable, it is entirely possible that this information will be used by the controller logic to directly make decisions. In the meantime, this research will investigate whether this information can be leveraged to further enhance TRPS control, which is widely available in most traffic signal controllers. An existing Central system-in-the-loop simulation of a traffic signal system in Morgantown, WV will be utilized to implement and test algorithms for estimating queue lengths from vehicle trajectory data in real-time, estimating the state of the system in real-time, and communicating information back to the controllers to change the timing plans, when appropriate. The advanced TRPS will be compared to basic coordination timing plans and basic TRPS control across various volume scenarios to estimate improvements in delay, emissions, and fuel consumption.

• Record URL:
  http://www.matsutc.org/leveraging-connected-vehicles-to-enhance-traffic-responsive-traffic-signal-control/

Language

• English

Project

• Status: Completed
• Funding: $360000
• Sponsor Organizations:

  United States Department of Transportation - FHWA - LTAP

  1200 New Jersey Avenue, SE
  Washington, DC    20590

  ECONorthwest

  888 S.W. Fifth, Suite 1460
  Portland, OR  United States  97204-

  Marshall University, Huntington

  College of Information Technology and Engineering
  One John Marshall Drive
  Huntington, WV  United States  25755

  Old Dominion University

  Norfolk, VA  United States  23529

  Virginia Tech Transportation Institute

  3500 Transportation Research Plaza
  Blacksburg, Virginia  United States  24061

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590

  Mid-Atlantic Transportation Sustainability Center

  University of Virginia
  Charlottesville, VA  United States 
• Managing Organizations:

  Mid-Atlantic Transportation Sustainability Center

  University of Virginia
  Charlottesville, VA  United States 
• Performing Organizations:

  Marshall University, Huntington

  College of Information Technology and Engineering
  One John Marshall Drive
  Huntington, WV  United States  25755

  Old Dominion University

  Norfolk, VA  United States  23529

  Virginia Tech Transportation Institute

  3500 Transportation Research Plaza
  Blacksburg, Virginia  United States  24061
• Principal Investigators:

  Nichols, Andrew

  Chou, Chih-Sheng

  Cetin, Mecit

  Abbas, Montasir

• Start Date: 20160501
• Expected Completion Date: 20190330
• Actual Completion Date: 20190510

Subject/Index Terms

• TRT Terms: Feedback control; Fuel consumption; Hardware in the loop simulation; Mobile communication systems; Pollutants; Sensors; Traffic data; Traffic delays; Traffic queuing; Traffic signal control systems; Trajectory; Vehicle detectors
• Geographic Terms: Morgantown (West Virginia)
• Subject Areas: Data and Information Technology; Energy; Environment; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01593657
• Record Type: Research project
• Source Agency: Mid-Atlantic Transportation Sustainability Center
• Files: UTC, RIP
• Created Date: Mar 15 2016 6:37PM