An integrated freight traffic assignment model for multimodal transport: a super-network approach addressing commodity and mode competition in large-scale regions

This paper presents an integrated Freight Traffic Assignment Model (FTAM) using a super-network approach to effectively address large regions, multiple commodities, and various transport modes. By connecting mode-specific networks, the model captures complex freight behaviors and introduces generalized impedance functions considering factors like commodity values and loading/unloading times. Applied to the Yangtze River Economic Belt, it demonstrates over 95% accuracy in predicting freight flows, with mode share errors under 5%. This model offers crucial insights for policymakers in freight transport dynamics.