Green time usage metrics on signalized intersections and arterials using high-resolution traffic data

Renato Guadamuz, Houjun Tang, Zhengyao Yu, S. Ilgin Guler, Vikash V. Gayah

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The performance of traffic signal phasing and timing (SPaT) plans are directly related to temporal fluctuations in traffic volumes and their distribution across competing movements at the intersection. A well-timed signal plan generally allocates green times in proportion to the observed volumes. With the advance of data collection techniques and technology, it is possible to obtain and use high-resolution traffic data using detectors at intersections to measure the real-time performance of the SPaT plan to better achieve this goal. This study introduces novel green time metrics and methods to evaluate the efficiency of green time allocation along arterials and at individual intersections using automated, real-time, and high-resolution traffic data. An empirical application is presented for four intersections along a major radial arterial in Salt Lake City, Utah and a detailed analysis of the phases and movements for a single intersection located on that arterial. The proposed methods and results can help identify opportunities to improve the signal timing plan for the entire corridor or movements within secondary approaches by identifying locations and/or time periods where signal timing does not align well with observed traffic volumes. These metrics can be automated to provide traffic engineers with an alert as to when a particular intersection should be examined as a candidate for signal retiming, and they can also help identify what changes need to be made with the current SPaT plans.

Original languageEnglish (US)
Pages (from-to)509-521
Number of pages13
JournalInternational Journal of Transportation Science and Technology
Issue number3
StatePublished - Sep 2022

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Management, Monitoring, Policy and Law


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