traffic signal control method and control system based on svm and computer network

Abstract

The present invention proposes a traffic signal control method and control system based on SVM and computer network. First, the total traffic flow collected by cameras and electromagnetic sensors and the traffic flow of each lane going straight, turning left, and turning right are respectively used as data sets. SVM trains 95% of each data set to obtain the SVM model of going straight, turning left, and turning right; secondly, using 5% of each data set to calculate the fitting error of the SVM model, and expanding the training set according to the fitting error, and then Update the SVM model; finally, input the total traffic flow of the intersection collected by the camera in real time into the SVM model in each direction, and output the predicted value of the traffic flow of the intersection going straight, turning left, and turning right, according to the predicted value of the traffic flow, through the computer network. The passing time of the lane can realize the regulation of the traffic signal. The invention allocates and controls the passing time according to the predicted value of the traffic flow of each lane, realizes regional planning, effectively reduces road congestion in peak hours, and improves the continuity of passing.

Description

technical field [0001] The invention relates to the technical field of traffic signal control of computer network, in particular to a traffic signal control method and control system based on SVM and computer network. Background technique [0002] Support vector machine SVM is a machine learning method based on statistical learning theory, which can analyze data, identify models, and be used for classification and regression. Support vector machine SVM requires few training samples and has strong generalization ability. Support vector regression uses the kernel function to nonlinearly transform the input space into a high-dimensional feature space, and then finds the optimal classification plane in this high-dimensional feature space to minimize the distance between each point and the regression line, and then obtains the functional relationship between input and output. Computer network refers to the connection of multiple computers with independent functions in different g...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem of traffic congestion during peak hours and single control method of traffic lights, resulting in poor continuity of vehicle traffic, the present invention proposes a traffic signal control method and control system based on SVM and computer network, which can autonomously allocate and control traffic according to the traffic flow of different lanes The passing time of each lane realizes regional planning, effectively reduces road congestion during peak hours, and improves the continuity of traffic

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