Intersection traffic signal lamp regulation and control method with position sensing function

Abstract

The invention discloses an intersection traffic signal lamp regulation and control method with a position sensing function. The method comprises the steps of: 1, carrying out mathematical modeling ona traffic signal control problem through employing a reinforcement learning network model, specifically, the modeling a traffic network into a graph mode , and defining a state space, an action spaceand an award according to traffic signal control problems; 2, preprocessing the original observation value oi of an intelligent agent; step 3, acquiring edge features with position perception among intelligent agents; step 4, realizing a Pos-Light message transmission model between the intelligent agents; step 5, realizing an intersection traffic signal lamp regulation and control decision of a Qnetwork; and step 6, carrying out regulation and control target training based on the Q network. Compared with the prior art, the method is more efficient in intelligent agent decision, has higher convergence speed, and can finally obtain a strategy which effectively relieves the traffic jam; and (2) the method is superior to a method for solving the traffic signal lamp control problem by using agraph neural network at present, has higher convergence speed and can obtain more stable results.

Description

technical field [0001] The invention relates to the technical field of garbage classification, in particular to an intelligent garbage classification system and method. Background technique [0002] The traditional traffic signal control is to formulate a control plan in advance based on the collected historical traffic data. For example, the SCATS traffic signal control system calculates the two indicators of the saturation and flow of the intersection based on the detection data of the traffic detector, and provides a pre-planning for the intersection. Select the appropriate signal light control scheme from the formulated scheme. According to the collected traffic data, the SMOOTH traffic signal control system adopts the "short-term prediction" strategy to obtain the current state of the intersection, and then selects the corresponding strategy plan according to the state. Both SCATS and SMOOTH traffic signal control systems must consider various traffic conditions at int...

AI Technical Summary

Problems solved by technology

However, these methods only consider the connectivity of the traffic network and equally aggregate the traffic conditions from adjacent intersections, while ignoring the spatial location of these intersections

Images