Rail transit full-road-network passenger flow prediction method based on probability tree destination (D) prediction

Abstract

The invention provides a rail transit full-road-network passenger flow prediction method, which comprises the steps of: establishing a corresponding probability tree set according to the history origination and destination (OD) data, origin stations, inbound time periods and occurrence probabilities of outbound positions; continuously obtaining passenger inbound information (O data) and predicting passenger outbound information (D data) corresponding to each O data according to a prediction tree in historical statistic learning results; and overlaying influences of all OD data on full-road-network passenger flow to obtain information of the stations and the traffic zone passenger flow of the entire road network. The method solves the problem that the rail transit full-road-network passenger flow cannot be displayed and predicted in real time because the rail transit full-road-network passenger flow cannot be directly measured. Besides, the method has the advantages that the prediction result is good, the expansion is easy and the short-term passenger flow prediction and abnormal passenger flow prediction can be supported.

Description

technical field [0001] The present invention provides a new method for predicting the passenger flow of rail traffic in the entire road network based on probability tree D prediction. Binary tree), by predicting the position of the terminal station, so as to predict the passenger flow of the entire road network of rail transit, it predicts the location, time, and passenger flow of the entire road network site and driving section according to the inbound location and time prediction. Background technique [0002] With the proposal of smart city, smart transportation is an important link in smart city, and the problems it faces are particularly prominent. For nearly half a century, traffic congestion, road blockages and frequent traffic accidents have plagued major cities around the world more and more seriously. [0003] Subway has become an important means of public transportation all over the world. Compared with buses and taxis on the road, rail transit has the character...

AI Technical Summary

Problems solved by technology

At present, most subways around the world adopt a one-ticket system, so it is impossible to directly obtain real-time passenger flow information

However, the passenger flow information obtained by analyzing and counting only based on the existing OD (Origination and Destination of a trip) data has a serious lag and cannot meet the real-time requirements

Images