Modelling freeway networks by hybrid stochastic models

Traffic flow on freeways is a nonlinear, many-particle phenomenon, with complex interactions between the vehicles. This paper presents a stochastic hybrid model of freeway traffic at a time scale and at a level of detail suitable for on-line flow estimation, for routing and ramp metering control. The model describes the evolution of continuous and discrete state variables. The freeway is considered as a network of components, each component representing a different section of the network. The traffic model, designed from physical considerations, comprises sending and receiving functions describing the downstream and upstream propagation of perturbations to be controlled. Results from simulation investigations illustrate the effectiveness of our model compared to the well-known METANET model.