Efficient simulation-based method for calibrating the fundamental diagram of operational performance decaying transportation network

In this paper, a simulation-based method for calibrating the fundamental diagram of traffic network is proposed, which has the advantage of finding the optimal performance for performance-decaying road parameters in a limit number of iterations, considering the need for accurate operational performance decaying traffic network simulation based on limited traffic data to serve traffic managers. A two-layer optimization model is constructed, with the lower layer being the stochastic dynamic user equalization (SDUE) based on the LTM model, which is used to simulate the acquisition of the OD and the traffic flow of each road segment; the upper layer objective function is set to minimize the variance of the average true and simulated vehicle counts of each road, which is approximated and replaced by the resolvable metamodel, and is solved by nested into the trust-region(TR) method. A small simulation network is constructed for parameter calibration validation under operational performance decaying, and the calibration errors of each OD level are within 2% at 10% and 20% decaying levels, the calibration deviation on the complex network is also within 2% in 20 iterations, which demonstrating the applicability of the algorithm.