Incident parameter estimation

The paper proposes a sampled data based estimation methodology to reconstruct local incident parameter of the macroscopic Incident Traffic Flow (ITF) models. The key idea in ITF models is to dynamically relax the traffic mean speed to the traffic equilibrium one based of an time and space varying incident term. First, the analysis of incident corrupted traffic flow models, described as an inhomogenuous nonlinear Partial Differential Equation (PDE), is presented in continuous time. Second, space and time discretization techniques are applied to derive traffic management oriented ITF models. Online parameter estimation is suggested to capture the severity of incident throughout the proposed parameter, i.e. to estimate the incident parameter. Numerical example is carried out to show the viability of macroscopic incident parameter estimation technique using data obtained from a high-fidelity microscopic simulation.