Application of the Traffic Fundamental Diagram to Assess Detector Performance

Katherine Riffle, Edward J. Smaglik, Steven Procaccio, Steven R. Gehrke, Brendan J. Russo, David Hurwitz

Research output: Contribution to journalArticlepeer-review

Abstract

This study develops new methods for evaluating detector health via event-based outputs and existing traffic flow theory. In this work, event-based detector data outputs were used to develop empirical vehicle volume-density curves per Greenshields fundamental model. Through integration, these empirical lines were compared with a conceptual volume-density curve for each detector, which was generated with average headway and posted speed limit data. The detector performance and site information were also used to model a predicted volume-density relationship for each detector on the basis of empirical observations, which was then compared with the conceptual line in the same manner as the empirical lines. The outcomes of each comparison were then used to create a database for assessing detector health within the structure of an algorithm. The algorithm is presented and discussed, followed by directions for future research, applications for practice, lessons learned, and limitations of this work.

Original languageEnglish (US)
Pages (from-to)279-291
Number of pages13
JournalJournal of Intelligent and Connected Vehicles
Volume7
Issue number4
DOIs
StatePublished - 2024

Keywords

  • detector health
  • detector malfunction
  • signalized intersection
  • traffic detector
  • traffic signal

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Automotive Engineering
  • Transportation
  • Mechanical Engineering

Fingerprint

Dive into the research topics of 'Application of the Traffic Fundamental Diagram to Assess Detector Performance'. Together they form a unique fingerprint.

Cite this