Efficiency-Based Mixed Network Design Considering Multi-Typed Traffic Demands

Abstract

Transportation network efficiency is a comprehensive reflection of the operation of transportation networks. An effective quantitative evaluation method for the transportation network efficiency is important as it can provide a feedback mechanism of network operation conditions in the process of network design, which gives a theoretical basis for the optimization of urban transportation network. In general, a well-designed transportation network should be adapted to multi-typed traffic demands by considering their characteristics after reconstructing. Thus, on the choice of an effective quantitative evaluation method for the transportation network efficiency, this paper proposes a bi-level programming model with the objective of maximizing transportation network efficiency in mixed network design, which has two lower users' equilibrium models corresponding to two kinds of traffic demands. A hybrid Genetic Algorithm (GA) and Frank-Wolfe Algorithm is then developed to solve the proposed problem. Results of the case study show that the network designed by the proposed model a) results in a more rational distribution of traffic flow, b) improves the adaptability of the transportation network and alleviates the traffic congestion, and c) economizes on the use of land, providing a solid foundation for the sustainable development of transportation network.