Multi-factor short-time traffic flow prediction method

Abstract

The invention discloses a multi-factor short-time traffic flow prediction method. The method comprises the steps that 1, distances between a specific detector and meteorological stations are calculated, the nearest meteorological station is screened out, and weather data of the meteorological station serves as weather data of the detector; 2, historical traffic flow data and historical weather data of the detector are preprocessed respectively and merged according to the time; 3, a plurality of features are constructed, and feature screening is carried out on the basis of LightGBM; 4, modelingis carried out on time sequence features and periodic features of the traffic flow data through LSTM; 5, the time sequence features and the periodic features of the traffic flow are fused with the features screened out in step 3 through a fully-connected network in a neural network; 6, the model is trained, and the short-time traffic flow is predicted. The method overcomes the defect that existing methods cannot fully use known data, can be used for deeper mining and analysis of the traffic flow data, and is high in prediction accuracy and good in robustness.

Description

technical field [0001] The invention relates to the technical field of intelligent traffic systems, in particular to a multi-factor short-term traffic flow prediction method. Background technique [0002] With the continuous development of the economy, the traffic pressure is increasing day by day, traffic accidents occur frequently, and the traffic environment is deteriorating day by day. How to improve road traffic capacity and alleviate traffic congestion is the focus of attention in both academia and industry. Intelligent Transport System (ITS, Intelligent Transport System) closely combines "people-road-vehicle" to establish an accurate, real-time and efficient traffic management system. In ITS, traffic control and real-time traffic flow guidance are particularly important. The key to realizing traffic control and guidance is real-time and accurate short-term traffic flow forecasting. [0003] The initial stage of short-term traffic flow forecasting is to use classica...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art, and propose a multi-factor short-term traffic flow forecasting method, which innovatively uses two LSTM modules to extract the time-series features and periodic features of the traffic flow, simultaneously with The fusion of weather features and time features can overcome the shortcomings of existing methods that cannot make full use of existing data, thereby improving the accuracy of traffic flow forecasting

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