Research On Traffic Assignment Model Considering Emission Effects And Solution Algorithm

Traffic congestion and environmental pollution are two important aspects of modern urban disease.Therefore,how to improve and rectify traffic congestion as well as environmental pollution becomes a difficult issue that urban development should face up to.In this dissertation,we discussed the vehicle emission effects on urban traffic system,especially on traffic assignment,travel behavior.We established a general traffic assignment model considering emission effects,and a road network bi-level model considering reducing congestion and emission simultaneously.We introduced emission pricing,which could be used to restrain emission amount on certain link or district,in order to optimize travel behavior and travel pattern.Our goal of using this concept is to guarantee the total emission inventory of certain road network not exceed a given threshold so that we can approach the so-called equity objective.We mainly do research as follows:(1) On the basis of traditional traffic assignment model,we put forward a general,multi-class traffic assignment model considering emission effects.Emission factors were explicitly considered in our model,we used TRANSYT-7F model in emission factor model,then transferred variational inequality problem into optimization problem,introduced modified projection algorithm to solve it.By turning variatioal inequality problem into a series of quadratic programming sub-problem,and considering two classes of preferable emission sensitive travelers in the numerical examples,we found that the optimal link and path flow solution is convergent and meet Wardrop equilibrium conditions as well.The results also showed that modified projection algorithm can efficiently improve the solution process of general equilibrium problem and is feasible.In addition,we adopted a self-adaptive projection and contraction method to solve the multi-class traffic assignment model considering emission effects and its equivable nonlinear complementarity problem.By using SA-PC method,we got the user equilibrium solution of generalized travel cost function of above model.Numerical results showed that compared with other algorithms,the SA-PC method had higher solution efficiency while solving optimization problem with generalized travel cost function.(2) On the basis of Venigalla's work,we adopted two path-based algorithms, namely,gradient projection algorithm and disaggregated simplicial decomposition algorithm to solve nonadditive path cost traffic assignment problem under different engine operating modes.We compared the above two algorithms in a network example which showed that compared with the traditional Frank-Wolfe algorithm, the two path-based algorithms had a more quicker convergency while getting optimal solution,and it can obtain a satisfying solution in most cases.Additionally, with the increasing of road network congestion,the computation times of DSD and GP algorithm will also increased,however,DSD is more quicker than GP.Due to these two algorithms only used fewer shortest path while searching optimal solution, it can be applied to medium and larger size network.The compution time and convergent speed are not ideal with the increasing of network scale.(3) We discussed a road network design problem considering lessening emission and congestion simultaneously.In the bi-level programming model we established,vehicle delay on road links due to queuing was considered,and the emissions on road links were also considered at the same time.We introduced road pricing to restrict road link emissions especially on some key links,to guarantee the total emission inventory of road network not exceed a given threshold.Also,we count on it can lessen the congestion of road network.Road pricing had proved to be a great meaning of decreasing financial pressure of government,improving road network structure,providing travelers better services and eventually increasing their satisfactory degree.We used a modified particle wwarm optimization algorithm and an improved quantum evolutionary algorithm to solve the upper level problem of the above bi-level programming model respectively.As for lower level problem,we adopt Frank-Wolfe algorithm to solve it.Numerical results showed that both algorithms had an efficient solution while solving the bi-level programming model considering lessening emission and congestion.(4) We firstly introduced the concept of emission pricing,and then selected a small scale road network to analysize the road network design problem considering lessening emission and congestion from both theoretical and practical point of view. We adopt a newly bionic optimization algorithm,that is,quantum evolutionary algorithm to validate the correctness and feasibility of our model.