摘要: Supposing that the travel cost on the paths and the congestion degree on the key links were considered by the urban travelers, aprice-congestion mixed dynamic evolution model was established based on analyzing the equilibrium flow model.The model was based on the economics theory of non-Walrasian equilibrium method and by simulating the traveler's route choice behavior following the economical concept of market exploration process, the equivalency of model stability and equalization was verified.The evolution model was simulated by using a simple test network and a medium size network, the evolution process of disequilibrium network traffic flow and the performance of traffic network under the disequilibrium situation were described.Analysis result indicates that the evolution model of time price regulation accords with the classical Wardrop's first principle; the result of quantity regulation of congestion allows the degree of congestion on the key links of each path between OD to be the same; the result of pricecongestion mixed regulation allows the path flow to be adjusted between the paths of lower cost and the ones of less congestion, the undulation of dynamic evolution of which is greater than that of the single regulation.In the test network, because the model only considers the choice behavior of congestion degree upon path, the congestion degree of whole traffic network is more uniform, and compared with the single price regulation model, the overall uniformity coefficient improves by 62%.However, the mean link saturation improves from 0.60 to 0.64, which indicates that the traffic network becomes congested overall.By considering the joint regulation of these two factors, the saturation of most congested link decreases from 0.936 to 0.787.The overall uniformity coefficient improves by 46%.The mean saturation of links, path travel time and congestion decrease.The test result of the medium size network also shows that such mixed equilibrium model can describe the dynamic evolution process of traffic flow on traffic network flexibly and objectively, and achieve steady state flow of traffic network system, which canexplain the traffic travel behavior better.8 tabs, 9 figs, 32 refs.更多>
