Computational study of state-of-the-art path-based traffic assignment algorithms

Abstract

Recent research has demonstrated and established the viability of applying path-based algorithms to the traffic equilibrium problem in reasonably large networks. Much of the attention has been focused on two particular algorithms: the disaggregate simplicial decomposition (DSD) algorithm and the gradient projection (GP) algorithm. The purpose of this paper is to evaluate the performance of these two path-based algorithms using networks of realistic size. Sensitivity analysis is performed on randomly generated networks to examine the performance of the algorithms with respect to network sizes, congestion levels, number of origin-destination (OD) pairs, and accuracy levels. In order to be empirically convincing, a realistic large-scale network, known as the ADVANCE network, is also used to show that path-based algorithms are a viable alternative in practice.