A traffic state prediction method, device and electronic equipment

Abstract

The invention provides a traffic state prediction method, device and electronic equipment, which relate to the technical field of intelligent transportation. The method includes: generating a plurality of chromosome units, and each chromosome unit is used to represent a class of spatio-temporal convolutional network model; based on a sample set Calculate the loss value of the time-space convolutional network model corresponding to each chromosome unit in multiple chromosome units; update multiple chromosome units according to the loss value of the time-space convolutional network model corresponding to multiple chromosome units, and return to execute based on the sample set respectively The step of calculating the loss value of the spatio-temporal convolutional network model corresponding to each of the plurality of chromosomal units until the target chromosomal unit that meets the preset conditions is determined; based on the spatio-temporal convolutional network model corresponding to the target chromosomal unit, the pre-trained spatio-temporal Convolutional network model; Predict traffic status based on pre-trained spatio-temporal convolutional network model. The invention can improve the accuracy of predicting the traffic state.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, in particular to a traffic state prediction method, device and electronic equipment. Background technique [0002] With the continuous advancement of the urbanization process, the importance of intelligent transportation is getting higher and higher. Traffic status prediction is an important part of intelligent transportation. The predicted traffic status information can help people make travel route decisions, thereby alleviating traffic congestion and improving the happiness of urban living. In the prior art, the traffic state is usually predicted by statistical methods, and the traffic state at the next moment is predicted by counting the number of vehicles and the speed of vehicles within a period of time. However, the statistical method relies on experience to predict the traffic state, and the accuracy of predicting the traffic state is relatively low. Difference. Cont...

AI Technical Summary

Problems solved by technology

[0003] The embodiment of the present invention provides a traffic state prediction method, device and electronic equipment to solve the problem in the prior art that predicting the traffic state through statistical methods has poor accuracy in predicting the traffic state

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