Traffic light passing strategy based on 5G hierarchical decision

Abstract

The invention discloses a traffic light passing strategy based on 5G hierarchical decision. The traffic light passing strategy comprises the following steps that 1, a vehicle transmits vehicle data toan edge cloud; the cloud server transmits information of all traffic lights to the edge cloud server; 2, the edge cloud server calculates whether the vehicle can pass through the traffic light; 3, the edge cloud server sends the instruction to the vehicle end; 4, the vehicle end controls the vehicle through a vehicle control algorithm built in the automatic driving controller according to the instruction issued by the edge cloud server. According to the traffic light passing strategy disclosed in the invention, the development of the 5G industry is promoted, the road accident rate is reduced,and the cost of automatically driving an automobile bicycle is reduced.

Description

technical field [0001] The present invention relates to a hierarchical decision-making method for autonomous vehicles based on a 5G communication network, and in particular to a traffic light traffic strategy based on a 5G hierarchical decision-making. Background technique [0002] Through the integration and analysis of the current research on the traffic light intersection algorithm for self-driving cars, it is found that the current main research has two directions: [0003] 1. Patent application number CN201810510657.0, patent publication number CN108694841A, optimize the speed curve and acceleration curve within a distance before the traffic light intersection. For example, in this patent, a cost function that integrates comfort, safety, timeliness, and economy is designed. Using this cost function, a series of candidate accelerations are screened to obtain the optimal acceleration curve and optimal vehicle speed curve. [0004] 2. Patent application number CN201711069...

AI Technical Summary

Problems solved by technology

[0006] In fact, purely relying on sensors to identify traffic light information has problems such as limited perception range, inaccurate identification, and inaccurate time acquisition.

In addition, the computing power of the vehicle is limited. Putting the calculation process on the vehicle may lead to greater calculation pressure on the vehicle, and will also increase the cost of a single vehicle.

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