| In recent years,urban rail transit has played an increasingly important role in urban public transportation due to its advantages such as large capacity,high speed,and high punctuality.Large-scale gathering incidents in large cities have brought huge challenges to local governments,because congestion accidents may occur when crowd density exceeds a safety threshold.Therefore,urban rail transit management should be developed to manage passengers in gathering places.This thesis constructs a urban rail transit stop-skipping model,a urban rail transit inbound passenger management model,and a collaborative optimization model to control the passenger flow of urban rail transit stations,and reduce the crowd density in gathering places.The main research contents are as follows:(1)When formulating the urban rail transit management plan,consider the process of passengers entering the station and getting on the train.According to whether to simultaneously control urban rail transit stations and trains,three urban rail transit management models are proposed,namely,a urban rail transit stop-skipping model,a urban rail transit inbound passenger management model,and a collaborative optimization model.(2)The urban rail transit stations are classified according to the walking distance between the urban rail transit stations and the gathering place,which are crowding stations,alternative stations,and ordinary stations.And then the Space-L method is used to establish a two-layer network structure including a urban rail transit network and a pedestrian road network to simulate the process of large-scale crowd gathering.Then analyze the operating characteristics of urban rail transit trains and the travel behavior of passengers.The crowd density and the road pedestrian density are set as the constraints of the model.Finally,the objective function constructed in this thesis introduces a dollar cost unit to convert time cost into expense cost,which is minimizing the total cost of passengers.(3)Extract passenger travel information from multiple traffic data,and then take the Halloween event at Window of the World in Shenzhen as an example to verify the proposed models.The results show that the three models can reduce the crowd density below the safety threshold,which verifies the effectiveness of the urban rail transit management method proposed in this thesis.Compared with the urban rail transit stop-skipping model and the urban rail transit inbound passenger management model,the passenger travel cost calculated by the collaborative optimization model is lower. |
