Paired Alternative Segments Based Traffic Assignment

Static traffic assignment problem(TAP)as one of the basic core of transportation planning,in all kinds of traffic problems has been widely used.With the academic research of the traffic problem is increasingly thorough,the efficient to solve the traditional static traffic assignment problems have already can't satisfy the need of research.Hence,how to solve the complex scenario which is more close to reality static traffic assignment problem efficiently and accurately,it's being more and more important.In this paper,improving the efficiency and precision of traffic assignment algorithm to solve the complex situations is the research objective.And the link capacity constraint traffic assignment problem(CTAP)and mixed equilibrium(ME)traffic assignment problem is studied.The research work of this paper mainly includes the following two aspects:On the one hand,we compared a variety of static traffic assignment algorithms,and because of the efficiency and precision paired alternative segments traffic assignment(TAPAS)algorithm is chosen to solve the sub-problem of the link capacity constraint traffic assignment problem in the frame of the Augmented Lagrangian multiplier method(ALM).Considering the disadvantage of ALM,we designed the dynamic accuracy method to solve the sub-problems.The efficiency and precision of the designed algorithm,and the effectiveness of the dynamic accuracy method is verified by numerical examples.The sensitivity analysis of the dynamic accuracy method's optimal step size is also studied.On the other hand,the variational inequality model of mixed equilibrium traffic assignment problem,is solved by diagonalization method.Based on the diagonalization method,the User-based diagonalization algorithm and the Origin-based diagonalization algorithm are designed.Considering TAPAS algorithm implied the frame of the diagonalization method,we present mixed equilibrium improved paired alternative segments traffic assignment algorithm.And we designed the numerical examples to compare the performance of the proposed algorithms,to analyze the effect of traffic demand on CPU time for each algorithm,to summarize the effect of the proportion of SO user on total system travel cost.