Document Type
Technical Report
Publication Date
3-2022
Keywords
Probe data, signal analytics, arterial street performance evaluation, congestion, delay
Digital Object Identifier (DOI)
https://doi.org/10.5038/CUTR-NICR-Y2-1.7
Abstract
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.
Scholar Commons Citation
Jha, Kartikeya; Albert, Luke; Albert, Debbie; and Schrank, David, "Evaluating Regional Traffic Signal Performance Measures Using Crowd-Sourced Data in 2021 Urban Mobility Report" (2022). Research Reports. 10.
https://digitalcommons.usf.edu/cutr_nicr/10
Policy Brief
