Optimization Of Urban Rail Transit Operation Plan Under Large Activity Passenger Flow

With the continuous advancement of urbanization and the continuous improvement of the material level,the people’s spiritual and cultural life is also becoming more and more abundant.Large-scale events such as concerts and sports events are frequently held in various cities in China.Urban rail transit,as an important mode of urban transportation,undertakes a large number of passenger flow transportation tasks.Due to the high-intensity,short-term and sudden nature of passenger flow induced by large-scale events,the demand for urban rail transit passenger flow has fluctuated significantly.If the capacity provided by the existing development plan is not evacuated in time,it will cause congestion problems in urban rail transit and even cause safety hazards.The research object of this paper is the rail transit system under a single and short-term large-scale event.From the perspective of supply and demand,it is studied from the perspective of passenger flow forecast and travel plan.Provide a valuable reference for the acquisition of passenger flow demand under large-scale events,the mechanism of transportation capacity matching and the adjustment of the development plan.First,excavate and analyze the characteristics and evolution laws of sudden passenger flow under such a single short-term large-scale event,and build a feature project to predict the OD passenger flow during the large-scale event period,and clarify the sudden in and out of the station due to large-scale events.The travel demand of the passenger flow online network,from the perspective of time and space,analyzes the propagation mechanism of the passenger flow of large-scale events in the network,so as to provide a theoretical basis for the design of the adjustment method of the train operation plan.Secondly,clean the AFC historical data,consider the characteristics of the passenger flow data to construct the characteristics of the normal and active background respectively,innovatively use the corresponding reverse passenger flow of the OD pair as the input feature,use the feature extraction to expand the new feature,and apply Lasso CV for the feature select.Relying on the feature construction based on the integrated learning Seq-Att-GBDT-Apri algorithm,it predicts the OD passenger flow reflecting the demand of the online network under large-scale events.Then,based on the prediction results of urban rail transit OD passenger flow,analyze and calculate the matching degree and adjustment ideas of the following vehicle driving plan for large-scale event passenger flow.According to the passenger flow characteristics and transmission mechanism of large-scale events,the goal is to minimize the cost of passenger travel and the highest matching degree of passenger flow,and to restrict the constraints of system influencing factors,construct a mathematical model and design a genetic algorithm to solve it.Finally,taking Chengdu Metro as an example,the OD passenger flow of Chengdu Metro under a certain large-scale event is predicted,the capacity matching assessment is carried out,and the operation plan of the model rail transit train is adjusted according to the optimization model proposed in this paper.The prediction accuracy of the integrated prediction model proposed in this paper reached 94.61%.After the adjustment of the optimization model of the opening plan,the matching degree of passenger flow and transportation capacity on Chengdu Metro Line 1 increased from 40.342% to 90.057%,an increase of 49.715%,and the transportation capacity was guaranteed to cover the largest cross-section passenger flow demand.It shows that the integrated prediction model proposed in this paper can well capture the fluctuation of passenger flow under large-scale events,and the optimization model of the opening plan can effectively improve the matching degree of passenger flow and transportation capacity in the context of large-scale events,while reducing the total travel of passengers to a certain extent.Time,to provide method guidance for improving operation level,service quality,and passenger satisfaction.