Estimation of dynamic origin–destination trip tables for a general network

In this paper, we propose a parametric optimization approach to estimate time-dependent path flows, or origin–destination (OD) trip tables, using available data on link traffic volumes for a general road network. Our model assumes knowledge of certain time-dependent link flow contribution factors that are a dynamic generalization of the path-link incidence matrix for the static case. A least squares model is accordingly formulated to determine the time-dependent trip tables. We develop a column generation approach that uses a sequence of dynamic shortest path subproblems in order to solve this problem. Computational results are presented on several variants of two sample test networks from the literature.