Vehicle positioning method and system based on roadside unit machine learning

Abstract

The invention discloses a vehicle positioning method and system based on roadside unit machine learning. The method comprises the steps that a vehicle sends traffic information to RSUb; a machine learning system collects the traffic information which is received by the RSUb and sent by the vehicle; steering of the vehicle at the first junction after passing the RSUb, RSUc which is going to be passed and the travelling track between RSUa and the RSUc are predicted sequentially. The system comprises a sending module and the machine learning system. Therefore, according to the vehicle positioningmethod and system based on machine learning, by means of cooperation of a roadside unit and the vehicle, the real-time traffic information is collected and uploaded to a database, the received real-time data is analyzed and processed by means of the machine learning system on the basis of the historical traffic information, dynamic prediction of the traffic state of a target vehicle is achieved,and then dynamic positioning of the target vehicle located in a communication blind district is achieved; under the condition of different traffic flows, the data delivery rate can be obviously increased, timely message delivery is guaranteed, and control overhead is reduced.

Description

technical field [0001] The technical field of the Internet of Vehicles of the present invention, in particular, relates to a vehicle positioning method and system based on roadside unit machine learning. Background technique [0002] The Internet of Vehicles system uses sensing technology, network technology, computing technology, control technology, and intelligent technology to comprehensively perceive roads and traffic, realize full-time traffic control of each vehicle, and full-time and space-time traffic control of each road. Networks and applications that focus on providing traffic efficiency and traffic safety. [0003] In the actual deployment of Internet of Vehicles facilities, due to the influence of various factors such as cost and road conditions, the coverage of RSU cannot reach 100%, so some vehicles will be in communication blind spots. Existing technologies for vehicle positioning in blind spots mainly include two categories: (1) GPS-based dynamic vehicle po...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present invention provides a vehicle positioning method and system based on machine learning, which solves the problem that vehicles in blind spots cannot be positioned in the prior art

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