Abstract
In order to design the traffic network more accurately, the bi-level programming model for the continuous network design problem based on the paired combinatorial Logit stochastic user equilibrium model is proposed in this study. In the model, the paired combinatorial Logit stochastic user equilibrium model which is used to characterize the route choice behaviors of the users is adopted in the lower level model, and the minimum summation of the system total costs and investment amounts is used in the upper objective function. The route-based self-regulated averaging (SRA) algorithm is designed to solve the stochastic user equilibrium model and the genetic algorithm (GA) is designed to get the optimal solution of the upper objective function. The effectiveness of the proposed combining algorithm which contains GA and SRA is verified by using a simple numerical example. The solutions of the bi-level models which use the paired combinatorial Logit stochastic user equilibrium model in the lower level model with different demand levels are compared. Finally, the impact of the dispersion coefficient parameter which influences the decision results of the network design problem is analyzed.
Highlights
Network Design Problem (NDP) is one of the hot issues in the field of traffic studies, and the research of this problem has high theoretical and practical significances
The continuous network design problem (CNDP) model is a bi-level programming model, the minimum summation of the system total costs and investment amounts is adopted as the upper level objective function and the paired combinatorial Logit (PCL)-stochastic user equilibrium models (SUE) model is used in the lower level
As can be seen from Fig. (2): with the increase of the dispersion coefficient, the root mean squared error (RMSE) indexes of both MNLSUE and PCL-SUE models used in the lower level model have downward trend, and when = 2, the RMSE indexes of different models are almost equal, that is because the increased implies that the users master more road network situations, the users' travel choices tend to be more closer to certainty choices, the assigned flows are closer to the UE model, the network design schemes by using the stochastic user equilibrium models in the lower level model are more closer to the results of UE model
Summary
Network Design Problem (NDP) is one of the hot issues in the field of traffic studies, and the research of this problem has high theoretical and practical significances. In the existing traffic network design models, the stochastic user equilibrium models (SUE) used in the lower level function are mainly traditional Logit-based models. It is necessary to adopt the stochastic user equilibrium model which could overcome the overlapping problem in the lower level model of the CNDP model, so as to reflect the route choice behaviors of the users towards the improved link capacity more objectively. The PCL-SUE model is used as the lower level model of CNDP and a new traffic network design model is built, and the genetic algorithm is designed to solve the new bi-level programming model of the continuous traffic network design. By a numerical example, the impacts on the calculation results of CNDP model established in this study under different demand levels and dispersion coefficient parameters are analyzed
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