Early warning processing system and method for instruction non-compliance rate of automatic driving automobile based on vehicle-road cooperation

Abstract

The invention discloses an early warning processing system and method for the instruction non-compliance rate of an automatic driving automobile based on vehicle-road cooperation. The early warning processing system comprises an Auto-DT automatic drive test system, a vehicle-road cooperation center and an automatic vehicle-mounted system. The Auto-DT automatic drive test system is used for collecting vehicle and road data information and performing denoising processing on the vehicle and road data information to obtain an effective invoking automatic vehicle data information base; the vehicle-road cooperation center is used for sending a driving instruction to an automatic automobile, calculating an automatic automobile instruction non-compliance rate and a traffic flow influence factor, and determining an automatic automobile violation grade and providing a specific processing scheme (deducting a corresponding integral and sending a corresponding level early warning prompt); and the automatic vehicle-mounted system is used for receiving the instruction and prompt information sent by the vehicle-road cooperation center and executing vehicle driving operation. According to the invention, the traffic intelligence and safety of the automatic driving special lane can be realized.

Description

technical field [0001] The present invention relates to a system and method for pre-warning and disposing of the disobedience rate of instructions of autonomous vehicles based on vehicle-road coordination. Specifically, the calculation of the influence coefficient on traffic flow based on the disobedience rate of instructions of autonomous vehicles is used to determine the level of violations of autonomous vehicles, and Take appropriate precautions. Background technique [0002] The development of self-driving cars and Internet of Vehicles technology will make the future traffic flow randomly mixed by artificially driven autonomous vehicles and autonomous vehicles with cooperative adaptive cruise control. In the case of mixed traffic flow, due to the complexity of the mixture of human-driven autonomous vehicles and cooperative adaptive cruise control autonomous vehicles, various uncontrollable unexpected factors will be generated, which can easily lead to traffic accidents a...

AI Technical Summary

Problems solved by technology

However, due to the complexity of road traffic, self-driving cars will be affected by problems such as neighbor car violations, abnormal road conditions, and self-vehicle system failures, and cannot accurately execute the instructions issued by the vehicle-road coordination center, thus affecting the normal flow of traffic. Threat, causing traffic jams, may lead to traffic accidents in severe cases

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