A Hierarchical Approach for Dynamic Origin-Destination Matrix Estimation on Large-Scale Congested Networks

Despite the ever increasing computing power, dynamic Origin Destination (OD) estimation in congested networks remains troublesome. In previous research, the authors have shown that an unbiased estimation would require the calculation of the sensitivity of the link flows to all OD flows. This is however computationally infeasible for large-scale networks. To overcome this issue, in this paper the authors propose a hierarchical approach for decomposing the dynamic OD estimation procedure in a number of smaller networks. The main idea is to perform a more accurate dynamic OD estimation only on subareas where there is congestion spillback. The output of this estimation is then used as input for the OD estimation on the whole network. This hierarchical approach solves many practical and theoretical limitations of traditional OD estimation methods. The main advantage is that different levels of complexity of the estimation method can be used for different parts of the network as necessary. The hierarchical approach is tested on a study network and on a real network. In both cases the proposed methodology performs better than traditional OD estimation approaches, indicating its merit.