Formulating the express railway network design for relieving in-vehicle crowding, incorporating a bi-level modeling approach

Crowding in vehicles is worse in concentrated urban areas. It is necessary to extend the public transit network, delivering travelers with a high level of service. This study aims to develop a design model of an express railway to improve mobility and relieve congestion on the existing urban rail transit network. A bi-level structure has been employed to solve the network design problem. The upper-level model is formulated to maximize the net-benefit of the entire rail network, whereas the lower-level model is formulated to grasp the effect of crowding on vehicles. A genetic algorithm is employed to solve the combinatorial optimization problem in a reasonable time. The results show that the developed model can find the optimal express railway by reflecting the relation of the trade-off between accessibility and mobility of the system. This study contributes to the establishment of the long-term plan for public transit networks in metropolitan areas.