Leverage Existing Adaptive Signal Control Systems Data to Create a Foundation for Building Real-Time Performance Measures to Better Manage Operations.
New Jersey DOT Evaluation of Adaptive Traffic Signal Control System Performance Measures.
Made Public Date

Real-Time Signal Performance Measurement


Traffic signal performance measurement and visualization provide insights as operational tools to help traffic management center get more benefits from infrastructure investment. The objective of this research study was to recommend and develop performance metrics, system architectures, data management, and strategies for  real-time monitoring of traffic signal performance (RT-SPM). Essentially, RT-SPM is used to measure the efficiency of adaptive signal control systems in real time. It was stated that in New Jersey multiple types of signal configurations, equipment, and vehicle detection devices were in  use for signal operations, yet antiquated equipment and inefficient detection technologies made it difficult to perform real-time traffic monitoring. Researchers  found it was important to utilize the existing field data and equipment to establish Signal Performance Measures (SPMs) for real-time monitoring. The project also determined what type of additional equipment and data were needed to generate additional SPMs for automatic real-time signal monitoring. 

In this study, researchers  aimed to assist with the existing deployment of Adaptive Traffic Signal Performance Measurement (ATSPM) and the establishment of the Arterial Management Center (AMC). In 2019, NJDOT had 76 signals fully operating in the adaptive signal control system, while there were 68 signals under construction or in final design stage and 122 signals in the concept design stage.

Lessons Learned

The lessons learned from this project can be summarized as follows:

  • Leverage existing  adaptive traffic control systems data to create a foundation for building real time performance measures and use open system approach to accommodate planned and future systems and technologies. It is important to identify strategic deployment in the short term with existing systems and in the long term with the future capital investment that encourage emerging technologies such as RT-SPM-based signal time optimization, Connected Vehicles (CVs) and Data analytics.
  • Organize targeted stakeholder meetings to collect, as much available data as possible. It was learnt during the stakeholder meeting that there was a myriad of independent data sources, and in the current architecture, their post-processing was too exhaustive to be performed in real-time. As the number of adaptive signal intersections were expected to increase substantially in the near future, novel methods had to be developed to leverage these adaptive systems to best evaluate and manage future corridors.
  • Create a detailed summary, review, and component inventory of the existing arterial management system. It was necessary to obtain a comprehensive understanding of the needs, requirements, and limitations in different arterial signal components with respect to building the RT-SPM system. The full knowledge of existing systems was essential for the development of new  deployment strategies.
  • Leverage existing systems used by other states when developing system architecture and concept of operations for an RT-SPM System. For example, bench testing can be conducted to measure the performance of existing high-resolution traffic signal controllers.
  • Develop a data management manual for adaptive traffic signal data processing. It is suggested to develop a standard data management process, such as a meta data table for testing signal controllers and validating algorithm results through a comprehensive debugging process.
  • Conduct case studies for system deployment. Test the proposed system offline with sample traffic data from different traffic signals along several corridors.
Goal Areas
System Engineering Elements