Piecewise-linearized cell transmission model and parameter calibration methodology

This paper studies the development of macroscopic freeway traffic models and parameter calibration methodologies that are computationally efficient and suitable for use in real-time traffic monitoring and control applications. Toward the fulfillment of these objectives, a macroscopic traffic model, the switching-mode model (SMM), is presented; it is a piecewise-linearized version of Daganzo's cell transmission model (CTM). The observability and controllability properties of the SNIM modes are reviewed because these properties are of fundamental importance in the design of traffic estimators and on-ramp metering controllers. A semiautomated method has been developed for calibrating the CTM and SMM parameters. In this method, a least-squares data-fitting approach is applied to loop detector data to determine free-now speeds, congestion-wave speeds, and jam densities for specified subsections of a freeway. Bottleneck capacities are estimated from measured mainline and on-ramp flows. The calibration method was tested with loop detector data from Interstate 210 westbound (I-210W) in Southern California. The main traffic data source was the performance measurement system. Parameters were calibrated for a 2-mi (3-km) subsection of I-210W and were tested on both the SMM and CTM, which were shown to perform similarly and to reproduce the general behavior of traffic congestion.