Network‐Wide Calibration of Link Capacities for Dynamic Traffic Assignment Models

Dynamic traffic assignment (DTA) models are used in many transportation planning and traffic management scenario analyses today. The aim of the DTA model is to reproduce the pattern of vehicular movements. DTA models require inputs in terms of demand and capacity of the road network and are very challenging to calibrate for large urban networks. In this paper, a new network‐wide calibration method for link capacities in urban networks is proposed. The method takes link flow observations for a subset of the links in the network to estimate the link capacities. The proposed method relies on partial least squares (PLS) regression and is demonstrated to be feasible and efficient in an urban road network (Stockholm, Sweden) compared to the simultaneous perturbation stochastic approximation (SPSA) method. Performance analysis of the proposed method for different amounts of link flow observations shows that it performs favorably for the cases in which only a small percentage of link flow observations is given.