Modeling And Optimization Of Metro Operation Strategy Considering Passenger Route Choice

With the acceleration of urbanization and the expansion of the scale of metro network,the demand of passenger flow increases sharply and presents an unbalanced distribution.Especially during the peak passenger flow period,some passengers are stranded on the platform because of the limited train capacity.In order to adapt to the spatial and temporal distribution characteristics of passengers,reduce the retention of passengers,and meet the travel needs of passengers,the operation efficiency and service level of metro can be improved by formulating reasonable metro operation strategies.Based on the analysis of full-length,express and short-turn operation strategies,this paper puts forward the mixed operation strategy that a combination of full-length,express and shortturn.Based on the study of passenger travel path selection behavior under the operation strategy,an optimization model of train operation strategy is established to minimize passenger travel time and enterprise cost,and a genetic algorithm of floating-point number coding is designed to solve the problem.The main work of the thesis includes the following four aspects:(1)This paper analyzes the distribution characteristics of metro passenger flow and the unbalanced characteristics of passenger flow distribution from two dimensions of time and space.It expounds the operation and organization conditions of local and express mode and full-length and short-turn mode in the metro system,and puts forward the mixed operation strategy according to their advantages and disadvantages.(2)Passengers are classified according to the spatial travel path,passengers choose the travel path according to the "shortest travel time",and passengers’ transfer behavior between different operation strategies is considered to study the travel path choice behavior of passengers.(3)On the basis of passenger travel route choice behavior,we established a bi-objective optimization model of train operation strategies under the constraints of the train capacity,the number of express trains,the number of short-turn trains,the stopping limit of express trains,the departure interval and the minimum tracking interval.In this model,we take the train service quantity,express stop scheme,train service sequence and train departure intervals as decision variables,and design the floating-point coding genetic algorithm to optimize the model.(4)Taking Chengdu metro line 2 as the research object,based on the passenger flow distribution analysis of the line,the established model and the designed algorithm are optimized for its operation strategy to verify the feasibility and effectiveness of the model.During the morning rush hour,the optimized scheme saved 954.81 hours of travel time,which was 4.1% lower,and the operating cost of the enterprise was saved 48,550 yuan,which was8.0% lower.Finally,sensitivity analysis is carried out on the parameters affecting the operation strategy,such as the train departure ratio,the value of passenger travel time and the additional cost of stopping.