Investigating the quality of SPSA and Spiess-like approaches for Dynamic OD Matrix Estimation


Since OD matrices are not directly observable, indirect procedures have been developed to estimate OD matrices from traffic data. Traffic management must move toward dynamic traffic assignment models because they capture congestion propagation effects. In this context, dynamic OD matrices are needed. This paper first explores the extension of a conventional bilevel analytical static method to the dynamic context, then analyses the solutions obtained regarding both convergence to measured traffic data and structural similarity to an a priori OD matrix. A simulation optimization technique, SPSA, is then proposed because its flexibility allows inclusion of traffic counts (as in Spiess method) and emerging ICT traffic measurements. The performances of these two types of algorithms are analyzed in detail, focussing on faults of classical convergence measures to obtain an estimated dynamic OD matrix structurally similarity to the a priori OD matrix and pros and cons of variants of selected methods.