Enhancing Traffic Control Systems to Reduce Emissions and Fuel Consumption

The tasks completed within this project will address all aspects of traffic signal timing - design, optimization, deployment, and monitoring - with a focus on the reduction of emissions and fuel consumption. The reductions will be achieved directly through the optimization of signal timing plans to minimize emissions and fuel consumption and indirectly through the improvement of emergency vehicle preemption (EVP) control by reducing travel time for the emergency vehicle and decreasing the delay for other vehicles at the intersections impacted by the EVP. Each task will be completed by a different PI, but some information will be shared among tasks. The study corridor for this project is a heavily congested 4-lane roadway in Morgantown, WV (WV-705). The traffic signals along this corridor are collecting high resolution traffic data with a system managed by Marshall University. A VISSIM simulation model of this corridor will also be utilized in this research for various tasks. Each of the tasks will be integrated through the use of the common study corridor. Task 1. Monitoring EVP Performance with High Resolution Data (Nichols): Many traffic signal controllers are now capable of logging all events that occur at the intersection to a tenth of a second resolution. These events include common events, such as phase changes and detector calls, and rare events, such as coordination alarms and emergency vehicle preemption. Research efforts in previous years have focused on how to turn this data into useful information for traffic engineers to make decisions on signal performance and modifications. This type of information is already being produced for the WV-705 corridor and will be utilized in Task 3. To date, no one has used this data to evaluate EVP operations on a corridor. These events are difficult to observe and evaluate in the field because they do not occur on a frequent or regular basis. This task will investigate field data from the WV-705 corridor to determine EV travel time along a corridor and quantify the impact (duration) of the preempt call on each intersection. Simulation that produces high resolution data will also be utilized in this effort to conduct sensitivity analysis of the system performance. The EVP performance data will be utilized in Task 2. Task 2. Designing Signal Timing for EVP (Abbas): The current state-of-practice implementation of EVP interrupts normal operation of traffic signals on an intersection-by-intersection basis, causing degraded signal system (e.g., corridor) performance. Geographic Positioning System (GPS) based and similar emerging area-wide priority systems are currently experimented with to provide a solution to this problem, but can also introduce other issues related to false priority calls. Both systems need background timing plans that are specifically optimized to work with the priority system. An on-going Virginia Department of Transportation (VDOT) research project being conducted by Dr. Abbas is looking into the need for tools and guidelines to determine: (1) the conditions under which each system should be used and (2) the optimal timing plans and compatible configuration for the selected system. The purpose of this Mid-Atlantic Transportation Sustainability Center (MATS) project is to leverage the high-resolution data for the WV-705 corridor from Task 1 to investigate the potential use of GPS-based and similar priority systems to provide a prioritized right-of-way to EVs through signalized intersections while optimizing the overall system performance. The project will analyze the performance and robustness of timing plans that are designed with the preemption patterns in mind, under real field conditions. Task 3. Optimizing Signal Timing to Minimize Emissions and Fuel Consumption (Rakha): Currently, traffic signal timings for an isolated traffic signal or coordinated traffic signals are based on the minimization of delay (in the case of isolated traffic signals) and minimization of the combination of delay and stops (in the case of arterials). However, at this point no attempt has been made to optimize traffic signal timings with the objective of explicitly minimizing fuel consumption and vehicle emissions. The objective of this task will be to initially focus on isolated traffic signal timing and identify the optimum signal timings associated with fuel consumption and various emissions and then develop an analytical formulation for the computation of the optimum signal timings. Future work will entail working on the arterial level to identify the optimum offsets from an environmental standpoint. This effort will utilize the high resolution data from Task 1 and supplemented with simulation runs for the WV-705 corridor. Task 4. Investigating Advanced Controller Settings to Minimize Emissions and Fuel Consumption (Park); In the US, there are more than 300,000 traffic signals. Among these, more than 90% of signals are being operated under actuated control. However, none of existing off-the-shelf optimization tools optimize the impact of advanced controller settings including extension time, detector recall mode, dual entry, simultaneous gap out, etc. The objective of this task will be to investigate these advanced controller settings in terms of its emissions and fuel consumption as well as mobility measures. This effort will also utilize the high resolution data from Task 1 and supplemented with simulation runs for the WV-705 corridor existing signal timing plans. This task will also consider utilizing either software-in-the-loop or hardware-in-the-loop simulation to emulate/implement actual traffic controllers. The SILS/HILS equipment available at the Traffic Operations Lab. at the University of Virginia will be utilized in this task. The WV-705 corridor in Morgantown, WV will be used as the study corridor. Actual data being collected by the signal system will be utilized in this research. A VISSIM simulation model exists of this same corridor, which emulates the field operation through software-in-the-loop. Modifications to existing EVP parameters and signal timing plans will be evaluated in the simulation environment. Marshall University manages this signal system, so these modifications could be deployed in the field if the simulation performance is positive. Expected benefits and impacts: Task 1. Ability to leverage high resolution data being collected by many existing signal systems in order to evaluate the performance of EVP and provide information for designing signal timing plans to better account for EVP. Task 2. Optimal and robust timing plans that are designed to work in tandem with preemption will result in improved system coordination by avoiding disruption to signal operation logic and will lead to reduction in system delay, fuel consumption, and emissions. Task 3. Development of analytical formulations that explicitly consider the environment in the optimization of traffic signal timings. Task 4. Preliminary guidelines providing how to set advanced controller settings to minimize fuel consumption and emissions at intersections


  • English


  • Status: Completed
  • Funding: $132000.00
  • Contract Numbers:


  • Sponsor Organizations:

    Virginia Center for Transportation Innovation and Research

    530 Edgemont Road
    Charlottesville, VA  United States  22903

    Virginia Polytechnic Institute and State University, Blacksburg

    Blacksburg, VA  United States  24061

    Research and Innovative Technology Administration

    Office of Research, Development, and Technology
    1200 New Jersey Avenue, SE
    Washington, DC    20590
  • Performing Organizations:

    University of Virginia, Charlottesville

    Charlottesville, VA  United States 

    Multimodal Transportation and Infrastructure Consortium

    Marshall University
    1900 3rd Avenue
    Huntington, WV  United States  25703

    Virginia Polytechnic Institute and State University, Blacksburg

    Blacksburg, VA  United States  24061
  • Principal Investigators:

    Abbas, Montasir

    Rakha, Hesham

    Park, B

    Nichols, Andrew

  • Start Date: 20141001
  • Expected Completion Date: 0
  • Actual Completion Date: 20160331
  • Source Data: RiP Project 37262

Subject/Index Terms

Filing Info

  • Accession Number: 01539893
  • Record Type: Research project
  • Source Agency: Mid-Atlantic Transportation Sustainability Center
  • Contract Numbers: DTRT13-G-UTC33
  • Files: UTC, RIP
  • Created Date: Oct 7 2014 1:00AM