This paper presents a generic framework for utilizing different types of intelligent transportation system (ITS) data for congestion monitoring and performance measurement. The generic framework is based upon standard performance monitoring/feedback cycles. Various types of ITS data are applicable, including data items typically available through loop detectors, surveillance and incident detection systems, probe vehicle systems, and arterial street signal control systems. A case study example is provided in Houston, Texas. The framework developed in this paper will assist urban areas that are implementing ITS components in measuring congestion and transportation system performance, and in quantifying the impacts that various ITS components have on congestion and system performance. (A)
Abstract