Urban road supervision method and system based on unmanned aerial vehicle navigation following and readable storage medium

Abstract

The invention relates to an urban road supervision method and system based on unmanned aerial vehicle navigation following, and a readable storage medium, and the method comprises the steps: collecting traffic image information through an aerial photography unmanned aerial vehicle, extracting traffic flow data vector features, and recognizing the types of traffic events through a network model; generating induction information according to the traffic event category, performing real-time guidance on the vehicle path through the induction information to obtain result information, determining anunmanned aerial vehicle navigation task, performing formation on the unmanned aerial vehicles, and determining an unmanned aerial vehicle reference track according to the unmanned aerial vehicle navigation task; acquiring a current flight path of the unmanned aerial vehicle in real time, and comparing the current flight path of the unmanned aerial vehicle with the reference flight path to obtaina deviation ratio; judging whether the deviation ratio is greater than a preset threshold value or not; if yes, generating correction information, reforming the multiple unmanned aerial vehicle nodesaccording to the correction information, generating a new planned flight path, updating the current flight path according to the new planned flight path, and controlling the unmanned aerial vehicle formation to fly along the new planned flight path.

Description

technical field [0001] The present invention relates to an urban road supervision method, in particular to an urban road supervision method, system and readable storage medium based on navigation and follow-up of a drone. Background technique [0002] As a negative externality product of urbanization overflow, traffic congestion has always been the focus of attention from all walks of life in the world. As an important part of the intelligent transportation system, intersection signal control and path guidance are being used more and more widely in the increasingly severe traffic environment. However, with the rapid development and improvement of hardware facilities, the problem of low intelligence of the traffic management system still exists. In the data, obtain hidden internal information, and make full use of information advantages to formulate scientific grooming strategies and other issues. Therefore, on the basis of massive traffic data, it is of great significance ...

AI Technical Summary

Problems solved by technology

[0003] In order to achieve precise control of urban road supervision, it is necessary to develop a matching system for control. The system collects traffic image information through aerial photography of drones, obtains traffic flow data, and uses network models to identify traffic incident categories. Generate guidance information according to the traffic event category, and guide the vehicle path in real time. During the real-time guidance process, the UAV intelligently follows and determines the UAV reference track according to the vehicle path. When the UAV’s current flight path deviates from the reference flight During the trajectory, the flight path of the UAV is dynamically adjusted, but in the process of control, how to achieve precise control and at the same time realize the precise and dynamic supervision of the road is an urgent problem to be solved

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