Choice set robustness and internal consistency in correlation-based logit stochastic user equilibrium models

Abstract

The Stochastic User Equilibrium (SUE) traffic assignment model is a well-known approach for investigating the behaviours of travellers on congested road networks. SUE compensates for driver/modelling uncertainty of the route travel costs by supposing the costs include stochastic terms. Two key challenges for SUE modelling, however, are capturing route correlations and dealing with unrealistic routes. Numerous correlation-based SUE models have been proposed, but issues remain over both internal consistency and choice set robustness. This paper formulates (and proves solution existence for) new internally consistent SUE formulations of GEV structure and correction term logit route choice models, where the functional forms in the correlation components are based upon generalised, flow-dependent congested costs, rather than e.g. length / free-flow travel time as done typically. Numerical experiments are then conducted on the Sioux Falls and Winnipeg networks, where computational feasibility for obtaining internally consistent solutions, choice set robustness, and internal consistency are assessed/compared.