Analysis Of Passenger Flow In Urban Rail Transit And Optimization Of Train Timetable

To solve the problem of urban traffic congestion,China’s major cities are building urban Rail Transit.According to the total investment of urban rail transit and the total mileage of construction during the "13th five-year plan",we can see the peak of urban rail transit construction in China.How to efficiently implement the operation and management of city rail transit system have become the hottest optimization problem,and the operation schedule as an important part of the management of urban rail transit operation,scientific and reasonable operation schedule not only can effectively improve the utilization rate of trains and equipment also can reduce the delay of the passengers in waiting or in the trains.Passenger flow of urban rail transit changes with the change of the time and space,which is basis of the timetable decision which belongs to dynamic flow and changes with the change of the time and space,is the basis of the timetable decision.Making and optimizing the timetable based on dynamic passenger flow can effectively keep the balance between the supply and the demand of urban rail transit system but also has realistic significance and applied value to meet the practical requirements and improve the service level of urban rail transit.This paper taking the actual passenger trip data which was collected in Nanchang urban rail transit automatic fare collection system as sample data clusters the distributive characteristics of passenger flow in time and space.Then referring to timetable’s design theory,an optimization model of urban rail transit operation timetable which is based on dynamic passenger flow is carried out,and a genetic algorithm is designed to solve the model.Finally,applying the results of passenger flow analysis into Nanchang Metro Line 1,it can be seen that using the optimized working day timetable,the total cost is reduced by 27.8% than before;using the optimized holiday or weekends timetable,the total cost is reduced by13.2% than before.The main work is as follows.(1)According to the formation mechanism,influencing factors,spatial and temporal distribution characteristics of the passenger flow of the urban rail transit and the layout of Nanchang rail transit,this paper analyzed the time and space characteristics of passenger flow in Nanchang Metro Line 1 by clustering analysis of time period and urban rail transit station,which used for the follow-up establishment of the optimization model of train operation schedule.(2)This paper analyzes the influence of train’s interval and dwell time on passengers’ waiting time and in-train time.In view of the passenger’s travel costs and the company’s operating costs,the optimization model of train operation schedule in urban rail transit,which based on the dynamic passenger flow,was established and to be solved with genetic algorithm.(3)Applying the cluster results into Nanchang Metro Line 1,and combining with the optimization model of train operation schedule and the result of genetic algorithm,we can see that this model can effectively reduce the travel cost of passengers and the operating cost of the urban rail transit company.