Y. Zhou

Pages: 13-22

Abstract
Under the background of the gradually deteriorating relationship between traffic supply and demand, in order to solve the problems of low accuracy and long time-consuming of traditional methods for evaluating the effect of urban public transportation restriction policy, an evaluation algorithm of urban public transportation restriction policy based on genetic algorithm is proposed. Firstly, the characteristics of the public transport network are analyzed from the three aspects of traffic demand, traffic flow and the capacity of public transport sections, and the evaluation indicators are selected according to the results of the analysis. The knowledge rule theory is introduced to optimize the evaluation weight of the model, thereby improving the evaluation accuracy. Analysis of the experimental results shows that this method has the characteristics of high accuracy of evaluation results and low evaluation time.
Keywords: genetic algorithm; traffic restriction; traffic network characteristics; principal component analysis; traffic index; knowledge rules