Multimodal subsidy design for network capacity flexibility optimization

Transportation networks are facing severe congestion due to the increasing burden of traffic demand and unexpected incidents. Therefore enhancing the network capacity flexibility is the urgent task of transportation managers. Apart from the expansion of road links, economic approaches such as congestion pricing are more effective ways of improving network capacity flexibility. However, congestion pricing often receives objection since it brings excessive travel cost to travelers. A more acceptable economic scheme of adjusting route choice behavior might be offering a subsidy, in a manner of reducing existing charges. In light of this incentive, we propose a solution in the form of multimodal subsidy design with the goal of optimizing network capacity flexibility. To validate the general applicability of the proposed multimodal subsidy schemes, we evaluate and quantify the network capacity flexibility by adopting three different measurement approaches, which are based on the concepts of reserve capacity, total capacity flexibility, and limited capacity flexibility respectively. Three mathematical models are established using these different capacity flexibility measurement approaches, each of which is formulated as a bi-level programming problem. The upper-level problem is to optimize the values of various subsidies, including road link subsidies, parking subsidies, and metro ticket subsidies to enhance the network capacity flexibility. The lower-level problem is a nested-logit based variation inequality program that considers multimode traffic and predicts how drivers and passengers react to the subsidy decision delivered from the upper-level problem. Numerical examples are provided to demonstrate how the proposed subsidy schemes affect network capacity flexibility as well as to compare the effects of different subsidy schemes.