SUMMARY
Automated Traffic Signal Performance Measures: Management, Operation, and Maintenance

Automated traffic signal performance measures (ATSPMs) are developed using high-resolution controller data, which is based on signal state (i.e., red, green, yellow) and detector events that are collected up to 10 times every second. This high degree of resolution and wealth of information allows for continuous and proactive monitoring of traffic flow, traffic signal operations, and maintenance, and ATSPMs have been shown to be a promising tool at signalized intersections. Despite their well-documented benefits, the use of ATSPMs varies considerably among state departments of transportation (DOTs) in the United States. While some DOTs have already integrated ATSPMs into their day-to-day practices, others use them along key corridors, use them for pilot projects, or do not use them at all. The varying use of ATSPMs stems from challenges experienced by DOTs, including difficulties in securing funding for system deployment, upgrading physical equipment, and meeting staffing needs to operate and maintain the system. Because of the wide variety of ATSPM use by DOTs, it is critical to have a clear understanding of factors that led to successful ATSPM deployments as well as barriers that deter further adoption and utilization of ATSPMs.

It should be noted that in addition to ATSPMs, state DOTs in the United States also utilize crowdsource-based traffic signal performance measures for operation and management of traffic signals. Crowdsource-based traffic signal performance measure platforms do not rely on high-resolution signal controller data and detector data; instead, they utilize emerging datasets such as probe, connected vehicle (CV), and other data from probe vehicles. For the context of this synthesis, these solutions are defined as crowdsourced ATSPMs, while ATSPMs that utilize high-resolution signal controller and detector data are defined as traditional ATSPMs. Additionally, systems that use either crowdsourced ATSPMs or traditional ATSPMs are defined as signal performance measure (SPM) solutions. This synthesis primarily focuses on traditional ATSPMs; however, given the increasing use of crowdsourced ATSPMs by agencies, the team also examined these solutions and their use by state DOTs.

This synthesis provides the current state of the practice for traditional and crowdsourced ATSPMs in the United States using an in-depth literature review and online survey responses obtained from 42 DOTs. In addition, the synthesis includes case examples performed with five state DOTs with different levels of SPM solution deployment. The case example DOTs are North Carolina DOT, Maryland DOT, Minnesota DOT, Georgia DOT, and Utah DOT.

According to the survey results, most state DOTs (83%) indicated using either traditional or crowdsourced ATSPMs. For those that use ATSPMs, 54% indicated that they only use traditional ATSPMs, 6% use only crowdsourced ATSPMs, and the remaining 40% use both systems. For the scale of deployment of traditional ATSPMs, 18% indicated full-scale deployment, 46% reported moderate deployment, and 36% reported limited deployment.

However, among those DOTs with limited deployment, 92% reported that they have planned expansions, and similarly, for those with moderate deployment, 87% indicated planned expansions. Another interesting finding was related to the factors hindering full deployment of traditional ATSPMs. While there were several responses, the two most common obstacles were limited staff resources and outdated signal controller and detection technology. These responses were consistent for DOTs with either limited deployment and moderate deployment.

According to the survey results, when planning for the deployment of either traditional or crowdsourced ATSPMs, 37% of DOTs indicated that their initial deployment was through pilot projects, while only 14% stated that they had conducted a needs assessment prior to the deployments. When asked about funding resources for the initial deployment of traditional ATSPMs, with the option to select multiple answers, most DOTs reported using state funds (78%) and federal funds (64%). When asked about funding resources to expand traditional ATSPMs, most DOTs (79%) reported using a combination of local, state, and federal funds, while 45% reported dedicated budget allocations for technology upgrades, and approximately 24% indicated grant-based funding. (Multiple answers were allowed here as well.)

Traditional and crowdsourced ATSPMs can both support a wide range of applications to improve signal operations and maintenance practices. According to the survey results (where the DOTs had the option to select multiple answers), the most common use cases were handling public service calls (74%) and signal timing adjustments that do not include full-scale signal optimization (74%). These were followed by evaluation of intersection operations (66%) and active traffic signal performance monitoring (66%). Interestingly, only 9% of the DOTs reported multimodal analysis as a use case. When asked about the types of reports/metrics used by DOTs, Split Monitor, Purdue Phase Termination, Purdue Split Failure, and Timing and Actuation were identified as the most frequently used metrics or reports. Another important finding related to the use cases was that, for traditional ATSPMs, almost all DOTs (94%, with the option to select multiple answers) use them at the intersection level, while the use of traditional ATSPMs drops considerably at broader spatial levels: approximately 42% for corridor-level analysis and only about 15% for network-level analysis. The use of crowdsourced ATSPMs, however, showed a more even distribution across spatial levels, with approximately 88% use at the intersection level, 100% at the corridor level, and 50% at the network level.

In general, the survey responses revealed that the DOTs are at different stages of implementing traditional ATSPMs. Some have integrated traditional ATSPMs into their day-to-day practices, while others are just beginning their efforts and are using pilot corridors or early deployments. In addition, organization structure, staff resources, and infrastructure were identified as critical hurdles to deployment of traditional ATSPMs. The case examples also revealed similar findings related to the challenges and issues experienced by state DOTs during the transition to traditional ATSPMs. Additionally, the case examples highlighted the importance of strong leadership in overcoming these challenges through helping secure streamlined funding—for initial deployments, to maintain the system, and for expansions—and allocating appropriate staff resources. The case examples are included in Chapter 4.

This synthesis also identifies several gaps and suggestions for future research:

• Interviews with state DOTs for the case examples indicated that they are looking for procedures and guidance to help them integrate traditional or crowdsourced ATSPMs into their day-to-day practices. Several state DOTs emphasized the need for a clear, streamlined workflow to integrate performance measures into actionable, automated decision-making processes.

• The survey and case examples revealed that challenges in establishing a unified statewide strategic framework for signal management and operations, as well as limitations in sustained funding, are two key barriers to broader ATSPM adoption. Large-scale implementations in Utah and Georgia offer valuable guidance and insights for other state DOTs seeking to strengthen their traffic signal management practices, and there is a need to conduct further research into the policies and approaches that enabled these successes.
• This synthesis has found limited use of traditional or crowdsourced ATSPMs for multimodal operations or for safety improvements. As a result, future research should explore and develop new metrics that go beyond traditional vehicular measures.
• Most state DOTs use traditional ATSPMs for intersection-level analysis. There is a need to develop new methods that would allow corridor-level or network-level analysis.
• A gap exists in built-in tools for aggregation of ATSPM data that enable system-level analysis. Even some state DOTs that extensively use traditional ATSPMs lack this feature and consider its development as a crucial step toward facilitating broader adoption of traditional ATSPMs.