signalized intersection operation state prediction method and system based on an LSTM model

Abstract

The invention provides a signalized intersection operation state prediction method and system based on an LSTM model. The method comprises the steps that floating vehicle data of a certain area are acquired through the mobile internet; extracting related data matched with a certain signalized intersection within a certain period of time according to the floating vehicle data, and screening the data; performing normalization processing on the screened data, dividing the data into a training data set and a test data set, training the data in the training data set through an LSTM model, and testing the trained model through the test data set to obtain a prediction model of the signalized intersection; and predicting the operation state of the signal intersection through newly collected real-time data according to the obtained prediction model of the signal intersection. According to the method, the operation state of the signal intersection is predicted through the mobile internet floating vehicle data, and the traffic operation efficiency of the signal intersection area is improved.

Description

technical field [0001] The invention relates to the field of intelligent transportation technology management, in particular to a method and system for predicting the operating state of a signalized intersection based on an LSTM model. Background technique [0002] With the development of the mobile Internet, it becomes more convenient to collect floating car data based on the smart phone of the owner of the floating car. Based on this, a large amount of floating car data can be obtained for traffic congestion identification, traffic status determination, and formulation of traffic control strategies. [0003] At present, domestic management and control methods for signalized intersections mainly include timing control, induction control and adaptive control. However, the above-mentioned existing management control methods often lead to control optimization at signalized intersections after a relatively high travel delay. That is to say, the current control methods lack the...

AI Technical Summary

Problems solved by technology

However, the above-mentioned existing management control methods often lead to control optimization at signalized intersections after a high travel delay.

That is to say, the current control method lacks a method for predicting the operation of signalized intersections, and a corresponding prediction system is urgently needed to make up for the prediction vacancy of the operation status of signalized intersections, so as to predict the operation status of signalized intersections in advance to formulate management and control plans in time

Images