Comparison of Assignment Methods for Simulation-Based Dynamic-Equilibrium Traffic Assignment

Abstract

This paper reports on the evaluation of alternative algorithms for dynamic, or time-varying, equilibrium traffic assignment. The algorithms are used for pre-trip assignment, which reflects driver familiarity with expected traffic conditions, and are appropriate for off-line applications which require a more detailed analysis – such as temporal network flows and sensitivity to traffic control measures – and thus are not well served by static assignment models. The model is formulated as a time discrete variational inequality and a solution algorithm is developed. The determination of time-dependent path input flows is modeled as a master problem inspired from a simplicial decomposition approach. The determination of path travel times for a given set of path flows is the network-loading sub-problem, which is solved using the computationally efficient space-time queuing approach of Mahut. This solution method to the traffic flow problem is combined with heuristic driver behavior models to produce a fully-featured traffic simulation model. The complexity of the traffic simulation, which is motivated by a desire for a realistic representation of the system, results in an assignment map that is discontinuous and difficult to characterize analytically. Nevertheless, algorithms inspired from static network assignment have

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