Discretized traffic state distinguishing method based on deep learning

Abstract

The invention provides a discretized traffic state distinguishing method based on deep learning, and belongs to the technical field of traffic state distinguishing. The method comprises the steps of a, utilizing monitoring equipment arranged in all directions of a crossroad to collect traffic states of the crossroad in different moments to correspondingly obtain multiple sets of traffic state information; b, conducting discretized coding description respectively on the multiple sets of traffic state information according to a discretized coding process to correspondingly obtain discretized coding data of the crossroad in the different moments; c, building a traffic state distinguishing model based on deep learning according to the discretized coding data obtained in the step b; d, distinguishing the traffic states by utilizing the traffic state distinguishing model built in the step c. According to the discretized traffic state distinguishing method based on deep learning, the traffic states can be comprehensively and truly described, experts do not need to participate in traffic state feature selection, and building of the traffic state distinguishing model can be automatically achieved in a semi-supervised mode.

Description

technical field [0001] A discretized traffic state discrimination method based on deep learning belongs to the technical field of traffic state discrimination. Background technique [0002] With the acceleration of social urbanization, large and medium-sized cities around the world are facing the pressure of traffic congestion. Similarly, the number of household cars in my country has continued to grow rapidly in recent years, and urban traffic congestion has become the focus of discussion on public travel. To solve the problem of traffic congestion, there are usually three solutions: (1) Control vehicle travel through administrative means, for example, some cities in my country implement The odd and even number restriction system, the scheme is simple and easy to implement, but it will lead to the embarrassing situation of "cars are not allowed"; (2) expanding transportation facilities and building new traffic roads, this scheme requires a lot of manpower, material resources...

AI Technical Summary

Problems solved by technology

[0005] (2) The traffic state is a complex combination of factors in the real traffic environment, and the way of manually setting the state characteristics wil

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