Research and Application of Ultra-short-term Passenger Flow Prediction Model for Urban Rail Transit
Ultra-short-term passenger flow prediction is a key fundamental issue in the dispatch and command of urban rail transit.The existing methods and models have their own advantages and disadvantages,and cannot fully meet the needs of practical work on site.Firstly,based on the massive passenger flow data of Shanghai urban rail transit,this paper extracts and analyzes passenger flow characteristics and influence factors,and introduces the K-nearest neighbor algorithm to study and establish an ultra-short-term passenger flow prediction model.The initial application and result analysis based on the Shanghai urban rail transit network as the actual background demonstrate that the research results have good accuracy,timeliness,and practicality,providing strong passenger flow data(during 7:00-10:00 and 17:00-20:00)support for dispatch and command,and helping to build an intelligent transportation organization and scheduling system for urban rail transit network.
万方数据
维普
