Configuring One-Way Streets using Bilevel Programming Model and Genetic Algorithm-Based Solution Procedure

One-way traffic is a cost-effective strategy to alleviate traffic congestion in urban transport management; however how to reasonably configure one-way streets at the network-level is critical in practice; yet it has so far received limited attentions in the theoretical research of traffic management as well as in the practice. This paper addresses the optimization of one-way street configuration while taking into account route choice behaviors. A bilevel programming model with a binary decision vector denoting the layout of one-way streets is first formulated and a genetic algorithm-based hybrid solution procedure with a special chromosome repairing approach is proposed. A case study on Sioux Falls network is then included to demonstrate the necessity of optimizing one-way street configuration and the robustness of the proposed methodology, and the sensitivities of critical parameters in the proposed algorithm are also analyzed to depict the effects of parameter values on the optimal scheme and to obtain their empirical ranges. Furthermore, the framework of bilevel model and genetic algorithm-based solution procedure for the optimization of one-way street layout is extended to simultaneously consider signal setting with the emphasis on the constraints formulation and encoding method. Finally, the numerical experiment validates the necessity of simultaneous optimizing one-way street configuration and signal setting.