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The National Academies

NCHRP 03-122 [Active]

Performance-Based Management of Traffic Signals

  Project Data
Funds: $600,000
(includes $150,000 from the FHWA)
Staff Responsibility: B. Ray Derr
Research Agency: Kittelson & Associates
Principal Investigator: Brandon Nevers
Effective Date: 4/14/2016
Completion Date: 7/13/2018

OBJECTIVE

 

The objective of the research is to develop guidance for agencies across the spectrum of resource levels to implement a performance measurement approach to traffic signal management.

 

STATUS

Phase I is complete and the interim meeting was held in November 2016. The contractor's unedited interim report is available, any conclusions or recommendations are those of the authors, not the National Academies of Sciences, Engineering, and Medicine or the Transportation Research Board.

Work proceeds on Phase II tasks.

DESCRIPTION

The guidance should describe how traffic signal performance metrics could be beneficially incorporated into agency processes and, to the extent practical, the benefits and cost savings that result, such as:

  • Organizational. Reporting on system performance and agency accountability to executives, governing bodies, and the public.
  • Planning. Identifying and prioritizing locations for geometric and signal improvements (including those for pedestrians, bicycles, transit, and freight); providing complete intersection approach volumes and turning movement counts throughout the year; using safety surrogates (e.g., reducing red light running, reducing arrivals on red) to estimate safety benefits; and using performance data to estimate benefits to traveler delay, travel time, and travel time reliability.
  • Design and Construction. Determining the impacts on travelers of various maintenance-of-traffic alternatives.
  • Operations. Reducing complaint calls due to the public perceiving improved operations, providing readily accessible information to address the remaining complaint calls, reducing the need to model signal operations, validating microscopic simulation models for analyzing alternatives, and managing agency tort liability due to better data on signal operation.
  • Maintenance. Identifying failed hardware and estimating resources needed for repair and reducing call outs.

 The guidance’s primary purpose is to assist agency staff or consultants in developing the elements needed to incorporate performance measures into their traffic signal management, including:

  • Presentations, papers, and other materials to gain support from state, county, and local agency decision makers for the needed resources.
  • Use cases, needs, and requirements to support a systems engineering process for implementation of traffic signal performance measures.
  • Traffic signal performance metrics that correlate with an agency’s goals and objectives and criteria for determining the acceptable level of performance for the system. These should include performance and safety metrics for all intersection users and different contexts and operational modes. The guidance should clearly define possible metrics and discuss the types and reliability of data needed to generate each metric. It is expected that different agencies will choose to use different metrics based on their agency’s priorities and the resources available to implement a performance-metric-based approach.
  • Catalog of available data sources. The guidance should list viable data sources and include estimates of the resources and legal arrangements required to access each data source. The limitations of each data source should be discussed. Of particular interest are data sources for pedestrians and bicyclists and those that can be used in situations with limited detection (e.g., grid networks, semi-actuated or time-of-day corridors, work zones).
  • Algorithms for turning raw data into performance metrics.
  • Procedures and processes for using the performance metrics to improve the performance and safety of traffic signals and to estimate the magnitude of these improvements (to allow the determination of the return on investment). This should include setting boundaries and schedules for coordinated operation.
  • Intersection and signal design standards that allow performance data to be collected, including those for traffic signal hardware and software, detection technologies, communication system requirements, and documentation for traffic signal installations.
  • Plan for presenting the performance metrics to the various audiences, including dashboards and summaries for executives and the public, data formats for other agency consumers (e.g., planners, safety analysts), outreach to consultants preparing traffic impact analyses, and outreach to traveler information application developers.
  • Transition plan for implementation, including costs, phasing, adaptation to future technologies, and ongoing maintenance and operations. This plan may include corridors with multiple agencies controlling signals and signals operated by small agencies that lack the resources and expertise needed for this approach.
  • Workforce staffing and development plan. This plan should address the mix of in-house and contract staff, particularly for maintenance.
  • Data retention policies.

TASKS

 

Phase I

 

Task 0. Develop Amplified Work Plan and hold kick-off web conference with the project oversight panel.

 

Task 1. Conduct agency interviews to identify best practices and critical factors that foster or hinder the development of effective traffic signal operations management. The interviews will also cover implementation activities that may be beneficial for this effort.

 

Task 2. Develop use case for traffic signal performance measures.

 

Task 3. Review potential data sources for traffic signal performance measures, including both those that are currently available and those likely to become available in the future.

 

Task 4. Assess existing guidance documents covering this topic and identify gaps related to performance-based traffic signal management approaches. Develop an annotated outline for the guide.

 

Task 5. Prepare an interim report documenting the results of the preceding tasks and presenting a fully scoped work plan for Phase II. Participate in a meeting with the project oversight panel to review the interim report and subsequently prepare a technical memorandum addressing all points raised by the panel.

 

Phase II

 

Task 6. Develop case studies by reviewing implementations of signal performance measures that demonstrate the use of these measures to improve system operation. The case studies will include at least one representative large, medium, and small agency, and at least one local agency.

 

Task 7. Formulate a consolidated methodology for implementing performance measures.

 

Task 8. Develop an architecture to connect and intake multi-agency signal data and perform the automated calculation, storage, and structured output of a variety of signal performance measures.

 

Task 9. Prepare and submit a second Interim Report documenting the results of Task 6-8 along with a detailed work plan for Phase III. Participate in a meeting with the project oversight panel to review the interim report and subsequently prepare a technical memorandum addressing all points raised by the panel.

 

Phase III

 

Task 10. Develop communication materials overview the guide’s contents for critical audiences.

 

Task 11. Compile a data dictionary for existing and anticipated data sources with sample data and applications. Develop a plan for hosting and maintaining the data dictionary.

 

Task 12. Develop the guide and final report. Following project oversight panel review of all of the deliverables, revise them based on the panel’s comments and prepare a point-by-point response to each comment.

BACKGROUND
 
With over 400,000 traffic signals deployed throughout the United States, their operation profoundly impact the performance of the transportation system. Poor signal timing is one of the primary causes of recurring congestion. Ideally, traffic signals should be retimed as needed, but because signal retiming projects are quite labor intensive, there is a tendency for such projects to be deferred or placed on an arbitrary schedule on the scale of years. Consequently, many agencies rely primarily on user complaints to identify problems. However, user complaints are often difficult to substantiate and, as such, do not always lead to a resolution. The operational and maintenance issues that cause poor signal operations could be substantially improved by introducing a performance-based approach to automatically identify and report problems to the engineering staff, before they generate user complaints. There have been numerous innovations in the development of automated traffic signal performance measures that can assist in this task. However, adoption of these methodologies has, so far, been limited to a few large agencies with the ability to employ technical staff such as computer programmers to build systems for converting the data into useful information. There is currently very little guidance for agencies without such resources on how to implement a traffic signal performance measure system. In addition to the high-resolution performance data currently available from many traffic signal controllers, crowd-sourced data are being used by many agencies to assess the performance of their system. Data sources include INRIX, HERE, Google, TomTom, TrafficCast, Apple, and Waze. Traveler re-identification (using, for example, MAC addresses, toll tags, or license plates) and, in the future, connected travelers can also provide travel time information along a corridor. These data sources can complement the high-resolution data or, for financially constrained agencies, provide rudimentary performance data. Many state, county, and local agencies are interested in moving toward performance-based management of their traffic signals but the financial and organizational barriers appear formidable. Guidance is needed to help these agencies garner the needed support and resources to adopt this approach.

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