Static origin-destination matrix estimation can be formulated as a bilevel programming problem. The upper level problem tries to make the estimated matrix satisfy certain constraints, such as traffic counts, row and column totals, and similarity to an a priori matrix. The lower level problem typically stipulates an equilibrium assignment of the matrix to a network. This framework can be extended to the dynamic case. However, as is shown in the literature, computational issues such as convergence and efficiency of the solution algorithms become a serious issue. One of the central issues is the calculation of a convergent series of descent steps in the upper level of the problem. Recently a solution was presented based on the concept of subgradients which achieved improvements in convergence and in the speed of convergence. In this paper a method is proposed to alleviate the problem of finding convergent descent steps for the upper level problem. For the covering abstract see ITRD E124693.
Samenvatting