The National Academies

NCHRP 03-144 [Active]

Leveraging Existing Traffic Signal Assets to Obtain Quality Traffic Counts and Enhance Transportation Monitoring Programs

  Project Data
Funds: $450,000
Staff Responsibility: Roberto Barcena
Research Agency: Texas A&M Transportation Institure
Principal Investigator: Ioannis Tsapakis
Effective Date: 9/29/2022
Completion Date: 3/28/2025
Comments: Research in progress


State departments of transportation (DOTs), metropolitan planning organizations (MPOs), counties, and other local agencies manage extensive traffic counting programs and have a need to ensure that traffic count data covers a variety of modes of travel, e.g., cycling and walking. These counts support decision-making with the aim of enhancing safety and mobility for the traveling public. There are thousands of existing traffic detection assets throughout the nation that serve traffic management operations. Moreover, other customers of traffic count data such as traffic engineers, traffic monitoring staff, transportation and active transportation planners, and data scientists, as well as non-transportation stakeholders (e.g., those responsible for realty, billboards, economic development, etc.), need to combine traffic count data sets in new ways to support various business processes.

As sensor detection technologies mature in assisting traffic operations and intelligent traffic system (ITS) programs, the providers of traffic count programs recognize the potential benefits of using existing infrastructure and data to supplement their counts. However, the diverse efforts underway are generally not summarized, publicized, or leveraged. Key issues associated with using the data from traffic signal equipment for traditional traffic volume measurement include (a) inconsistency in data quality and format that varies across vendors and technologies; (b) inconsistency in availability of sensors at all intersections as well as approaches to individual intersections; and (c) variable configuration of sensor equipment causing possible gaps in data availability, quality, and storage even though the equipment itself may be capable of counting vehicles, bikes, and pedestrians.

Research is needed to examine whether the data provided by traffic signal assets can provide accurate traffic counts.


The objectives of this research are to (a) determine the feasibility of using existing or enhanced traffic equipment to collect, store, and disseminate data for purposes other than traffic operations, particularly for traffic monitoring programs; (b) determine the suitability of traffic count data from already installed and existing traffic assets for this purpose; and (c) develop effective practices for obtaining and integrating traffic counts from existing traffic assets.

The research will evaluate types of currently installed traffic monitoring assets and assess the suitability of traffic count data for non-operational traffic data usage. In this research, (a) the term "suitability" includes the quality, applicability, and type of the data obtained from the traffic equipment; (b) the term "traffic" includes motorized vehicles, micro-mobility devices, and non-motorized modes including bicycles, pedestrians, etc.; and (c) the term "traffic assets" includes, but is not limited to, signalized intersections, crosswalk signals, video, loops, magnetometers, radar, and traffic detection cameras.




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