The current rail transit network topology model has poor dynamic scheduling ability,which leads to rail transit line congestion,a rail transit network topology model based on digital twins and multi-objective particle swarm optimization is con-structed.It integrates the basic information of the target area into the sample grid line statistics,and selects the sample grid line of urban rail transit.Digital twin technology is applied to analyze the running state of rail transit lines to realize the dynamic adjustment of rail transit.The multi-objective particle swarm optimization algorithm is used to optimize the model according to the objective function,and the final traffic network topology model is obtained.So far,the design of the topology model of rail transit network based on digital twins and multi-objective particle swarm optimization is completed.We build an experimental link to verify the application effect of this model.The experimental results show that the morphological characteristics of this model are better than the current model,and can reduce the congestion of the line to a certain extent and improve the level of transportation.
关键词
数字孪生/多目标粒子群/轨道交通网/拓扑结构/交通量预测/交通延误分析
Key words
digital twin/multi-objective particle swarm/rail transit network/topology/traffic volume prediction/traffic delay analysis
维普
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