Research On Key Technology Of Urban Rail Transit Organization Under Passenger Flow Fluctuation

Population structure is growing, the rapid expansion of urban rail transit network structure, rail transit in the way of residents in the dominant position is more and more obvious. At present, China's urban rail transit capacity and passenger demand matching degree is slightly lower, the rail transit operations fiscal revenue and expenditure imbalance,most of the urban rail transit needs the government's financial subsidies to maintain. It is of great theoretical significance to construct the matching system of passenger flow fluctuation and transportation ability, which is of great theoretical significance to improve the operational efficiency under the premise of satisfying the passenger demand. In this paper,clustering analysis is used to cluster the passenger flow according to the distribution characteristics of time and space. The transportation economics theory and the optimization theory are used to optimize the urban rail transit capacity under passenger flow fluctuation.Based on the above research significance and research methods, this paper first studies several short-term passenger flow forecasting methods. Then, based on the predicted passenger flow, the matching decision function of the fluctuating passenger flow and the transport capacity is established to quickly determine the matching node of passenger flow and transport capacity. Finally, It is the main research result of this paper to adjust the transportation capacity at this stage and to construct the matching system of fluctuating passenger flow and transportation capacity. Specifically include the following:(1) The method of short-term passenger flow forecasting for urban rail transit is put forward from the perspective of frequent passenger flow and emergent incident, and the acquisition and processing of the basic data of passenger flow forecasting are introduced.The data acquisition of real-time monitoring passenger flow of urban rail transit TCC system is introduced Method and data processing method based on sample clustering analysis.(2) The spatial and temporal variability of passenger flow fluctuation is analyzed by means of passenger data of urban rail transit in Tianjin, the influencing factors of transport capacity are studied, and the calculation method of transportation capacity is introduced. On this basis, the relationship between passenger flow and transport capacity is analyzed,The matching function of passenger flow and transportation capacity is established, the matching node of passenger flow and transportation capacity is established, and the matching process is given.(3) Several adjustment methods of transportation capacity of urban rail transit under different passenger flow and transport capacity are studied. At the same time, it determines the lower bound of the bottom of the vehicle under different adjustment schemes, which provides a strong theoretical reference for the purchase and application of the vehicle at the time of adjusting the transportation capacity of the urban rail transit operation department.(4) Constructs an optimization model of urban rail transit capacity based on passenger demand, and designs a highly efficient and reasonable algorithm to solve the model, and proves the correctness of the model and algorithm with the concrete case.