Calibration of the Aw-Rascle traffic flow model via flow-density diagram data

The Aw-Rascle (AR) model has attracted more and more attention, because it solves the problem of the anisotropic property of traffic flow which is proposed by Daganzo. The AR model possesses an increasing function of the density which be called as the pressure function. The calibration of the pressure function is a primary work in the research of the model application. In this paper, we calibrate the pressure function of the AR model via flow-density diagram data. Our approach is to rewrite the Lighthill-Whitham-Richards (LWR) model to the form of velocity evolution equation which based on flow-density diagram and then contrast with the velocity term of AR model. Finally, we employ the PeMS detector data as flow-density diagram data to construct the pressure function, and apply the NGSIM trajectory data to be the initial and time-dependent boundary data. Via these two data sets, we predict the traffic state at interior space in the near future using the calibrated AR model and classical AR model respectively, and compare the predicted data with real traffic data to verify the feasibility and accuracy of this calibration.