Evaluating Regional Traffic Signal Performance Measures Using Crowd-Sourced Data in 2021 Urban Mobility Report

Traffic signal performance measures have historically been more difficult to quantify than other mobility measures, but new datasets obtained from crowdsourced data have improved the ability of users to quantify traffic signal performance measures at statewide, urban area, and corridor levels. Calculation of these metrics at the statewide and urban area levels is useful for tracking performance and trends, and at the corridor level the metrics can be used for both performance tracking and traffic signal operations from a planning perspective. One week of October 2020 data for approximately 210,000 traffic signals in the United States was used for this study. This dataset is useful for evaluation of signal operations using traditional metrics such as average delay and level of service, in addition to newer metrics such as arrivals on green and traffic signal efficiency index. This dataset provides actionable information for local traffic engineers at the corridor level by providing granular information on operations of individual traffic signals. Community goals vary between urban areas, as some urban areas promote non-motorized transportation more than other communities, while some utilize traffic calming techniques to achieve other goals over optimizing signal systems to maximize vehicular throughput. These are important considerations when comparing urban areas to each other.

• Record URL:
  https://doi.org/10.5038/CUTR-NICR-Y2-1.7
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/64299
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program. Cover date: March 2022.
• Corporate Authors:

  Texas A&M Transportation Institute

  College Station, TX  United States 

  National Institute for Congestion Reduction

  University of South Florida
  Tampa, FL  United States  33620

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Jha, Kartikeya
  • Albert, Luke
  • Albert, Debbie
  • Schrank, David
• Publication Date: 2022-5-31

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; References; Tables;
• Pagination: 60p

Subject/Index Terms

• TRT Terms: Crowdsourcing; Data analysis; Performance measurement; Traffic data; Traffic signals
• Geographic Terms: United States
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01859568
• Record Type: Publication
• Contract Numbers: 69A3551947136, TTI# 79075-00-B
• Files: UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Sep 28 2022 11:18AM