A Traffic Assignment Method Based on Genetic Tabu Algorithm for the Main Skeleton Road Network in Congested Road Sections
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The existing traffic flow allocation methods lack sufficient flexibility and adaptability by analysing the impact of parameter changes on traffic flow distribution through examples, resulting in a decrease in traffic flow allocation performance on congested road sections. A traffic flow allocation method for the main skeleton road network of congested road sections is developed on the basis of the genetic tabu algorithm. First, a traffic flow allocation model is established, and data are collected using microwave vehicle detectors and high-definition checkpoint video detectors. Subsequently, the congested sections of the main skeleton road network are analysed, and the discrete-time and continuous-time forms of the section state equation are introduced. Finally, drawing on the results of the state analysis, a flow-control equilibrium joint optimisation objective function is formulated. Finally, it is proposed to use the genetic tabu algorithm to solve the model, in order to obtain the optimal traffic flow allocation scheme and improve the network traffic rate of the main skeleton. Experimental results have shown that this method can effectively determine the impedance time function of congested road sections and complete the traffic flow allocation of the main skeleton road network of congested road sections. It effectively enhances the distribution of traffic volumes across individual sections and contributes to achieving a more balanced flow throughout the entire main skeleton road network.
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