This paper presents an integrated travel demand modeling problem that accommodates the traditional travel demand modeling process in a nested logit structure for hierarchical travel choices, including travel, destination, mode, and route choices. The problem is characterized by a closed-form fixed-point model, which properly describes the asymmetric flow–cost effects of different transportation modes in an interactive traffic environment. The method of successive averages is adopted for problem solutions. The proposed model and solution method is further implemented to study travel demand distribution variations caused by model and data uncertainties. Specifically, the Monte Carlo simulation technique is adopted here to simulate and derive solution variations. Through a numerical example, the uncertainty analysis exhibits diverse demand variation patterns and degrees across different demand aggregation levels under different uncertainty sources.
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