Deep learning and intelligent street lamp-based traffic signal lamp intelligent control system

Abstract

The invention discloses a deep learning and intelligent street lamp-based traffic signal lamp intelligent control system, and belongs to the field of intelligent public traffic. The system comprises a roadside unit and an intelligent traffic signal lamp, wherein the roadside unit and the intelligent traffic signal lamp are arranged at a traffic road intersection. The roadside unit comprises an image acquisition module, a vehicle detection module, a congestion judging module and a communication module. The image acquisition module collects road traffic images in each intersection direction and sends the images to the vehicle detection module. In this way, the vehicle flow in each intersection direction is obtained. Meanwhile, the congestion judging module determines the congestion level in each intersection direction in combination with the vehicle flow, and transmits the congestion level to the intelligent traffic signal lamp through the communication module. The intelligent traffic signal lamp adjusts and displays the transit time in real time based on the congestion level. According to the technical scheme of the invention, the road traffic condition is detected in real time. For different road sections, different congestion level threshold values are set flexibly. Therefore, the congestion condition can be automatically judged and the transit time in each direction at the intersection is adjusted. As a result, traffic signal lamps are more flexible and more intelligent to use.

Description

technical field [0001] The invention relates to the field of intelligent public transportation, in particular to intelligent control of traffic signal lights based on deep learning and intelligent street lights. Background technique [0002] At present, road congestion is a common and most urgent problem in urban road traffic. How to reasonably plan the passing time of each intersection is a key point to solve road congestion. It can be seen from daily life that the waiting time of signal lights at most intersections is basically fixed, and the time-fixed signal lights are obviously contradictory to the variability of the road traffic environment. Some cities have been aware of this problem, and have adopted methods such as traffic police assisting in controlling signal lights, installing sensors such as geomagnetic sensors, or changing the waiting frequency of signal lights according to time periods, etc., which have improved the traffic congestion problem to a certain ext...

AI Technical Summary

Problems solved by technology

Some cities have been aware of this problem, and have adopted methods such as traffic police assisting in controlling signal lights, installing sensors such as geomagnetic sensors, or changing the waiting frequency of signal lights according to time periods, etc., which have improved the traffic congestion problem to a certain extent. The method cannot fundamentally change the adaptability of the signal light to the environment, and the method of assisting the traffic police or installing a geomagnetic thanks device has caused a waste of manpower and material resources

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