An extended macroscopic model for traffic flow

Abstract

This paper presents a model of traffic on a highway based on the macroscopic description of traffic as a compressible fluid. We take the computationally efficient model of Papageorgiou and test it on field data. We extend the model to flow under the influence of traffic-obstructing incidents. In applications where the interest is in mass phenomena and real time computation, a macroscopic model is preferable over microscopic models. This model also permits systematic parameter identification, which makes it more useful for real traffic systems. The influence of incidents on the highway is included in the model and it is possible to tune its parameters for flow under incidents. This allows the model to compute the effect of incidents on flow capacity using field data.