Intelligent signal light control method and system based on HydraCNN

Abstract

The invention discloses an intelligent signal light control method and system based on HydraCNN. The method comprises the steps of collecting a traffic flow image of a road intersection in real time, and analyzing the quantity of vehicles in the traffic flow image based on a HydraCNN model; and acquiring the quantity of the vehicles at the current intersection and the entering flow entering the current intersection from an adjacent intersection on a collected traffic flow image data set, and inputting the parameters into a trained linear regression model, thus allowing the model to be able to return the overall green light time needed by the passage of the vehicles at the current intersection. According to the method and system provided by the invention, the artificial intelligence technology is applied to intelligent control of the traffic signal light at the intersection, the traffic flow images are collected in real time at the road intersection, intelligent coordination of the signal light groups at the multiple intersections is achieved through analyzing the vehicle congestion condition by the system, and setting the best red light time and green light time, and thus the traffic capacities of the intersections are improved while the traffic safety is ensured, and the extremely positive effect is achieved for solving the traffic congestion phenomenon of the modern cities.

Description

technical field

[0001] The invention relates to the field of road signal lamps, in particular to a HydraCNN-based intelligent control system and method for signal lamps. Background technique

[0002] Traffic is the lifeblood of urban economic activities and plays a very important role in the development of urban economy and the improvement of people's living standards. Since the beginning of the 21st century, urban traffic has been an important factor that plagues urban development and restricts urban economic construction. It can be said with certainty that the contradiction between the limited growth of urban roads and the unlimited increase of vehicles is the root cause of urban traffic congestion. The pressure on road capacity brought by the continuous increase of vehicles remains high and is unlikely to change in the short term. The currently used signal light system mostly uses fixed red and green light durations, and cannot provide intelligent control strategies bas...

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