Analysis Of Passenger Flow Characteristics And Train Timetable Optimization For Metro Lines Connecting To Airport Based On Flight Information

The subway system has become one of the main modes of transportation which connects the airport playing an important role in transporting passengers.The service level of airport express line,especially the passenger waiting time depends on the train timetable to a large extent.Therefore,based on the take-off and landing time of the flight as well as the parameters of transfer tunnel,this paper formulates one model to characterize the passenger flow for both sides of the airport express line.On this basis,train timetable of bi-directional airport express line has been optimized to minimize passenger waiting time and reduce the operation cost of the enterprise.The main research contents and conclusions are as follows:1.Unlike the ordinary subway line where most passenger flows are commuter flows,the passenger flow of the airport express line mainly come from the passengers who leave or arrive at the airport.For passengers returning from the airport,the passenger flow often presents a strong imbalance in the time line,which is greatly influenced by the arrival time of the flight.This paper first analyzes the whole process form the site where passengers get off the plane to the subway station platform.Taking the information such as the estimated arrival time of the flights,flight capacity,load factor,transfer distance,transfer tunnel node facility capacity,etc.as input.Then one mathematical model is formulated to describe the time distribution of transfer passenger flow to the subway station platform.Case study shows that the total passenger demand calculated by the above model is basically consistent with the practical statistical data,and the deviation of passenger demand in each period is less than 10%.2.For the passenger flow to the airport,this paper adopted the method of reverse calculation.Firstly,based on the characteristic that the arrival time of passengers at the airport is restricted by the terminated boarding time of the flight,the distribution of cumulative arrival passenger flow can be calculated according to the departure time of each flight.Then,according to the distribution of arrival passenger flow in the terminal and the required time for passengers to walk form the airport express line station to the terminal,the distribution of passenger flow of the airport express line station can be obtained in reverse.On this basis,based on the information of the location of each station along the airport express line as well as the interval running time and train timetable of connecting lines,etc.,the distribution of passenger flow of each station on the airport express line to the airport is calculated.Case study shows that the total deviation of passenger demand calculated by the above model is about 5%,and the deviation of passenger demand in each period is less than 20%.3.To optimize Airport express line's timetable,this paper put the passenger flow calculated by the above model as input,and put forward two timetable optimization models.One with fixed number of departure trains are formulated with the goal of minimization of total waiting time of all passengers in the whole line,the other minimize total waiting time of passengers as well as the total cost of the train operation,respectively.And genetic algorithm is devised to solve the problems above.Considering the constraint of upper and lower limits of travel interval,under the principle of both sides' balanced,this paper calculated the optimal train numbers and timetable.And it put the minimization of total waiting time of passengers as well as the total cost of the train operation as optimization objective.Finally,take the sum of waiting time of passengers in each station of the airport line as the optimization objective and put the passenger flow in both directions as input,the overall optimization of the train operation diagram of the airport line is carried out.The optimized operation diagram can save the total waiting time of passengers by 12.01%and 6.31%compared with the equally interval operation diagram and the actual operation diagram.