Risk avoiding system based on unmanned transport train set in foggy weather

Abstract

The invention provides a risk avoiding system based on an unmanned transport train set in foggy weather, and belongs to the field of unmanned train safe transportation. A visibility recognition module comprises a calculation unit which is used for receiving data information sent by a vehicle-road cooperation system and performing calculation processing on the data information; a grading module is used for completing grading of the road fog area and determination of an operation mode according to a calculation result of the calculation unit; an unmanned train set control module comprises a vehicle-mounted OS used for receiving a signal sent by the vehicle-road cooperation system; a BCM body control module controls a corresponding controller according to the received information; a laser radar is in communication connection with the BCM vehicle body control module and is used for judging current unmanned train set spacing and controlling the spacing; and a vehicle-mounted ECU is used for controlling the current vehicle speed and completing control over the speed and the vehicle spacing. According to the system, vehicle-road cooperation and a deep learning algorithm are adopted, visibility whole-process monitoring and vehicle operation control in the heavy fog weather are achieved, and traffic accidents can be greatly reduced.

Description

Technical field [0001] The present invention belongs to the unmanned vehicle column safety transportation, which specifically involves a risk avoidance system based on unmanned vehicle columns in foggy weather. Background technique [0002] With the continuous maturity of unmanned car technology, no driving is ushered in the world's explosion period. Especially in the past two years, logistics unmanned technology has gradually developed from the laboratory, and the application, no warehouse, drone, and unmanned transport vehicles have entered the public vision. The unmanned car is the main research object of the intelligent transportation system, and the independent team system is an important subsystem of the system, where the queue is the most common formation in the independent team system. [0003] The driving focus of the queue lies in the perception and control of the environment. Although traditional drone technology can recognize the route, avoid obstacles, etc., can effi...

AI Technical Summary

Problems solved by technology

[0003] The driving focus of queues lies in the perception and control of the environment. Although traditional unmanned driving technology can identify routes, avoid obstacles, etc., and can efficiently avoid traffic accidents caused by human blind spots, there are still many problems in its development. Technical problems, such as foggy, snowy and other harsh environments, often lead to deviations in their perception of the environment, and the climate environment and road conditions may lead to accidents

Under non-clear conditions such as dense fog, the detection ability of the existing recognition system will be greatly attenuated by lidar. expensive

Furthermore, its huge information flow requires a professional processor to achieve its purpose

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