Passenger Flow Short-time Prediction And Operation Organization Of Urban Rail Transit

With the speeding up of urbanization in our country, urban traffic contradiction increasingly prominent. The traditional transportation already cannot satisfy the traffic demands. Urban rail transit, with its large capacity fast on time environmental characteristics favored by the traveler. Domestic urban rail transit has developed rapidly in recent years. As of December 31, 2016, 27 cities in our country has 120 operating lines running, the total mileage of the line reached 4152 kilometers. Rapid development comes from lots of problems at the same time, such as the prediction of urban rail passenger flow inaccuracy,the station passenger flow organization unreasonable and the line train operation plan is not appropriate.How to choose proper prediction methods to forecast with the actual traffic passenger flow gap to improve the station passenger flow organization and smaller line train operation plan is of great significance.Under this background, the paper analyzes the spatial and temporal characteristics of passenger flow, which bases on the characteristics of the urban rail transit passenger volume, to forecast short-term passenger volume, the results show that prediction accuracy is higher and can be used as the basic data of urban rail transit operation. According to the result of short-term section passenger volume forecast, organize the station passenger flow and develop a program of train formation thereby draw the train routing scheme and prioritization scheme.Meanwhile, in guarantee the station passenger routes for safety and efficiency and improve the service level of urban rail and reduce operating costs at the same time. The end of this article to analyze Xi'an metro line 2 as an example,put forward the traffic organization measures, on the evening peak of Bell Tower subway station. To optimize the mainly full-day driving program, the results show that the optimized scheme has improved transport efficiency and service level, and the quantity of using train fell by almost 23.7% meanwhile effectively save the operating costs.