A Traffic Assignment Approach for Multi-Modal Transportation Networks Considering Capacity Constraints and Route Correlations

A multi-modal urban transportation network provides travelers with diversified and convenient travel options. The study of multi-modal traffic assignment encounters great challenges from the common-line problem, route correlation, and the variability of travel tools. This article starts with the construction of super-networks to solve the common-line problem of multi-modal system. From the dimensions of time, fee, comfort, and transfer penalty, a multi-modal generalized travel cost function is proposed to reflect the impact of travel mode and transfer on route choice. Based on C-logit model, considering multi-modal capacity constraint and route correlation, a nonlinear programming model equivalent to the multi-modal stochastic user equilibrium is set up. The corresponding solving algorithm is designed by combining the augmented Lagrangian multiplier method and the successive weight average algorithm. Finally, the effectiveness of the proposed model and algorithms is verified through a numerical example, and the traffic assignment approach is applied in some typical scenarios. The multi-modal transportation network equilibrium approach proposed in this article takes into account the capacity constraints of different travel modes and solves the path overlapping problem in combined modes. It provides a basis and tool to formulate the traffic management strategy for public transport and combined mode trips.