Automating the Traffic Signal Performance Measures for Adaptive Traffic Signal Control Systems

The traditional project-based signal optimization practices are time-consuming and costly. In contrast to reactive traffic operation and maintenance, data-driven Automated Traffic Signal Performance Measures (ATSPMs) provide a means to proactive management and identify problems on a signalized roadway. The ATSPMs are used as part of an extensive centralized adaptive signal control system that provides a method to assess intersection performance remotely. In a standard system deployment, such as the one used by the Utah Department of Transportation, Linux high-resolution controllers are required to provide the signal event data needed to generate performance metrics and diagrams. Upgrading an adaptive signal infrastructure system with new controllers requires significant investment in funding and labor hours. This paper focuses on customizing an ATSPM system platform so that it can accept signal event log and detector data directly from an adaptive signal control system. This paper provides an efficient and flexible approach to display adaptive traffic signal data without intensive labor configuration and new equipment investment. This approach requires a data processing module that ingests two mainstream data logs from adaptive signal control technology (ASCT) software, InSync and SCATS, into an established ATSPM system in New Jersey. The resulting performance diagrams generated from the ASCT software illustrate the feasibility of the proposed approach. They have led to signal improvement, especially on split failures, pedestrian, and minor street wait time.

Language

  • English

Media Info

  • Media Type: Web
  • Features: Figures; References; Tables;
  • Pagination: 23p

Subject/Index Terms

Filing Info

  • Accession Number: 01764348
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-04207
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:27AM