Idle traffic light intelligent control method based on reinforcement learning

Abstract

The invention relates to an idle traffic light control method based on reinforcement learning, and the method comprises the following steps of employing a SlimYOLOv3 model to sense an environment, analyzing a scene, recognizing all vehicle types of targets in the scene, and positioning the positions of the targets through defining a bounding box around each target; adopting a DQN-based reinforcement learning method to train a traffic light control intelligent agent, a) defining an action space, enabling the traffic lights to randomly select actions according to probabilities, and adopting a greedy algorithm to randomly select the actions according to the probabilities; b) defining a state space, wherein the road surface state observed at any moment is the number of vehicles in different intervals in each direction, and an observation state value is a six-dimensional vector; c) defining a reward function, wherein the penalty weights of the three interval road sections are respectively defined as the specification, and the reward value is the sum of the penalty weights of the road sections; and d) learning a strategy enabling the reward value to be the highest by adopting the DQN-based reinforcement learning method to obtain the traffic light control intelligent agent with high performance.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic lights, and in particular relates to a method for controlling idle traffic lights based on reinforcement learning. Background technique [0002] With the acceleration of urbanization in China, the scale of cities has gradually expanded. In the field of traffic management, the government and relevant departments are committed to strengthening the construction of urban public transport, improving road layout, and opening up the urban microcirculation. At present, most of the traffic lights at street crossroads in our country adopt a timing switching control method, that is, the switching interval is fixed. However, in idle roads with frequent signal lights, this control method cannot well satisfy the driver's driving experience. For example, when driving at night, there is less traffic on the auxiliary road, and there is often an embarrassing situation where there is no traffic on the ...

AI Technical Summary

Problems solved by technology

However, in actual driving, accidents caused by "yellow flash" occur frequently

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