Risk-Based Formulation of the Transit Priority Network Design

Demand uncertainties are inevitable in transportation networks. The transit priority network design problem over more than a decade of development has been solved under deterministic conditions. This paper proposes a model to find the optimal transit priority scheme in a multimodal transportation network under uncertain demand. This model is formulated as a risk-based bi-level optimization problem. At the upper-level, a risk measure of expected social cost is minimized subject to a chance constraint on total travel time with a user-specified confidence level and a budget constraint. At the lower-level, a mode choice, a traffic user equilibrium assignment, and a transit assignment are applied. An ant colony algorithm is utilized to solve this complex design problem. Numerical results using a real world middle-size city network empirically demonstrate that the demand uncertainty has a significant impact on the solution and the proposed model is applicable to realistic networks.

Automated summary

This paper proposes a model to find the optimal transit priority scheme in a multimodal transportation network under uncertain demand. The model is formulated as a risk-based bi-level optimization problem and solved using an ant colony algorithm. Numerical results show that demand uncertainty has a significant impact on the solution, and the proposed model is applicable to realistic networks.