A Continuous Transportation Network Design Problem With Consideration Of Speed Limit

The speed limit is a simple and effective traffic management measure, which can reduce the average speed of vehicles on the road, ensure traffic safety, reduce energy consumption, and reduce vehicle emissions. Transportation network design is an important component of urban transportation planning. Considering the speed limit into urban transportation network design, can provide more favorable conditions for the implementation of the strategy of speed limit, so as to realize the overall optimization of transportation planning and management. The main contents of the thesis are summarized as follows:(1) A bi-objective continuous transportation network design problem (NDP) with consideration of speed limit was proposed. The proposed NDP aims to simultaneously improve traffic efficiency and reduce traffic pollution by reasonable road capacity improvement and speed limit strategy. A bi-objective bi-level programming model was developed to formulate the proposed NDP. The upper level problem aims to minimize both the summation of the total system travel time and the total investment, and the cost of total vehicle emissions from the viewpoint of traffic managers, and obtains the optimal road capacity enhancing scheme and the optimal speed limiting schemes for different time periods. Based on the user equilibrium (UE) theory, the lower level problem represents travelers’route choice behavior during different time periods. A genetic algorithm based on non-dominated sorting method is designed to solve the bi-level programming model. Numerical examples were developed to illustrate the effectiveness of the proposed model and algorithm.(2) A bi-objective continuous transportation network design problem with consideration of both speed limit and road congestion pricing. The proposed NDP aims to simultaneously improve traffic efficiency and reduce traffic pollution by designing reasonable road capacity enhancing, speed limit strategy and congestion pricing scheme. A bi-objective bi-level programming model was developed to formulate the proposed network design problem. The upper level problem aims to minimize both the summation of the total system travel time and the total investment, and the cost of total vehicle emissions from the viewpoint of traffic managers, and obtains the optimal road capacity enhancing scheme, and the optimal speed limiting schemes and congestion road pricing schemes for different time periods. Based on the stochastic user equilibrium (SUE) theory, the lower level problem represents travelers’ route choice behavior during different time periods. Based on the non-dominated sorting genetic algorithm are applied to solve the bi-level programming model, a numerical example is developed to illustrate the effectiveness of the proposed model and algorithm.