A3C-SRU-based intelligent vehicle traffic flow converging method and system

Abstract

The invention discloses an A3C-SRU-based intelligent vehicle traffic flow converging method and system. The implementation method comprises the following steps of 1, adopting environmental parametersand vehicle parameters by devices such as a digital camera, a multi-line laser radar, a millimeter-wave radar and a gps positioning system; 2, establishing a simulation environment platform by utilizing simulation software according to the environment parameters and the vehicle parameters extracted in the step ; 3, setting parameters and constraint conditions of a reinforcement learning algorithmaccording to the simulation environment in the step 2; 4, training by using an A3C-SRU algorithm according to the simulation environment constructed in the step 2 to obtain a decision of an imported traffic flow scene; and 5, obtaining the optimal action sequence obtained in the step 2 according to the model obtained in the step 4, storing the trained model, and inputting the model into the intelligent vehicle to realize a traffic flow importing task. According to the A3C-SRU-based intelligent vehicle afflux traffic flow algorithm of the invention, real-time afflux traffic flow tasks can be effectively realized according to the settings of the steps 1-5.

Description

technical field [0001] The invention discloses an A3C-SRU-based intelligent vehicle merging algorithm and system, belonging to the field of automatic driving. [0002] technical background [0003] In the entire decision-making system of unmanned vehicles, the problem of merging traffic has always been a difficult problem, and it is also a key problem that has to be solved. For human drivers, about 20% of traffic accidents occur at ramp intersections. Incoming traffic mainly needs to be considered in the complex traffic confluence scene, the traffic flow on the main road, and the changes in the surrounding environment at the intersection. Usually, an merging behavior involves a series of complex decision-making behaviors. The decision-making behavior in the process of inflow often has a great impact on the efficiency of traffic flow and the safety of inflow. However, when faced with the scene of merging traffic, the unmanned vehicle decision-making system cannot intelligentl...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the object of the present invention is to provide an A3C-SRU-based intelligent vehicle merging traffic algorithm and system, the purpose of which is to solve the problem of intelligent vehicles merging into traffic flow in complex environments. At the same time, in the existing Based on the algorithm to achieve better import performance and effectively shorten the training time

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