Research On Optimization Of Coordinated Passenger Flow Control And Operation Organization

With the continuous addition of urban rail transit lines and the continuous expansion of line network area with the acceleration of urbanization,the demand for passenger flow also puts forward new requirements for urban rail intelligent transportation.Based on this,urban rail transit has become the preferred travel mode for residents because of its characteristics of green energy conservation,sufficient traffic volume,safety and efficiency^[1].Due to the limited capacity of infrastructure and train carrying capacity,the problem of safe travel,which leads to passenger congestion,has become one of the main problems of rail transit operation.The design of current limiting strategy and train operation plan for urban rail transit is an important means to alleviate line congestion and match the balance between train capacity and passenger demand.In view of this,this paper analyzes the passenger flow distribution characteristics of urban rail transit,designs the platform demand constraint and platform detention constraint to control the number of people allowed to enter the station according to the actual maximum carrying capacity of the platform,and studies the theoretical methods of the optimization of off-site collaborative flow restriction and train timetable considering the platform carrying capacity and the optimization of urban rail station collaborative flow restriction and stop and jump scheme considering the platform carrying capacity.In order to minimize the number of stranded people,this paper constructs a nonlinear programming model and designs an algorithm to solve it,in order to generate the optimal flow restriction strategy and train operation plan for the system,and achieve the purpose of matching the balance between train capacity and passenger flow demand.The main research contents of this paper are as follows:（1）Firstly,this paper analyzes the passenger flow characteristics of urban rail transit,which provides a theoretical basis for the research content of this paper.Starting from the contradiction between passenger flow demand and capacity mismatch,the necessity and influencing factors of passenger flow collaborative control are discussed.Then it analyzes the influencing factors of urban rail operation organization optimization from three aspects:station collaborative flow restriction strategy,passenger flow train flow coupling process and train operation scheme.（2）This paper studies the problem of coordinated flow restriction outside the station and train timetable optimization considering the platform carrying capacity.According to the actual maximum carrying capacity of the platform,the platform demand constraint and platform retention constraint are designed to control the number of people allowed to enter the station,so as to ensure the safety of the platform.In order to minimize the number of people stranded outside the station,a mixed integer nonlinear programming model is constructed considering the constraints of passenger flow control,train platform service capacity,train timetable and platform carrying capacity.According to the structural characteristics of the model,a hybrid solution method of genetic algorithm and CPLEX is designed.（3）This paper studies the optimization of coordinated current limit and stop and jump scheme of urban rail stations considering platform carrying capacity.According to the actual maximum carrying capacity of the platform,the platform demand constraint and platform retention constraint are designed to control the number of people allowed to enter the station,so as to ensure the safety of the platform.In order to minimize the number of people stranded outside the station and on the platform,considering the passenger flow control in each period,the train platform service capacity in each period,the platform carrying capacity,the train operation plan,the train departure time defined by binary variables and the stop and jump scheme as constraints,a mixed integer nonlinear programming model is constructed and linearized,so that it can be solved by commercial optimization software.（4）Based on the AFC data of Beijing Metro Batong line,the effectiveness of the off-site collaborative current limit and train timetable optimization model considering the platform carrying capacity is verified.The results show that compared with the train timetable optimized by Shi et al.（2017）^[25],the number of people stranded outside the station is reduced by 50.86%.Without the implementation of off-site current limiting strategy,the number of people required by the platform at the downstream station exceeds the actual carrying capacity of the platform,which may cause hidden dangers to the safety of the platform.This shows that the method proposed in this paper can alleviate the pressure of line passenger flow,ensure the safety of platform and match the balance between train and transport capacity by coordinating the number of people allowed to enter the station and making train timetable.Based on the AFC data of Batong line of Beijing Metro,the effectiveness of the optimization model of coordinated current limit and stop and jump scheme of urban rail stations considering platform carrying capacity is verified.Without the implementation of the two strategies,the number of people required by the platform far exceeds the maximum carrying capacity of the actual platform,and the number of people getting on at the downstream station is less than that under the implementation of the two strategies.This shows that the method proposed in this paper can match the balance between train capacity and passenger demand and ensure platform safety by controlling the number of people allowed to enter the station and implementing the stop and jump scheme,and avoid overcrowding in downstream stations at the same time.