Road segment traffic index estimation system based on unmanned aerial vehicle measurement

Abstract

The invention relates to a road segment traffic index estimation system based on unmanned aerial vehicle measurement. The estimation system is arranged on an unmanned aerial vehicle and comprises an aerial camera, an image processor, a pressure altitude sensor and a main controller, the aerial camera is connected with the image processor, shot road segment images are sent to the image processor to be processed, the main controller is respectively connected with the image processor and the pressure altitude sensor, and a road segment traffic index is estimated according to the image processing result of the image processor and the altitude, detected by the pressure altitude sensor, of the unmanned aerial vehicle. By means of the road segment traffic index estimation system, traffic crowdedness information of key road segments can be provided for road traffic management departments, data are more visual and more accurate, and the road traffic management departments can conveniently develop accurate and effective traffic processing measures.

Description

technical field [0001] The invention relates to the field of unmanned aerial vehicle measurement, in particular to a road segment traffic index estimation system based on unmanned aerial vehicle measurement. Background technique [0002] Unmanned aerial vehicle, or unmanned aircraft, whose English abbreviation is "UAV", is an unmanned aircraft controlled by radio remote control equipment and its own program control device. From a technical point of view, it can be divided into several categories: unmanned helicopters, unmanned fixed-wing aircraft, unmanned multi-rotor aircraft, unmanned airships, and unmanned parawing aircraft. In terms of usage, it can be divided into military drones and civilian drones. For military use, it can be used to complete battlefield reconnaissance and surveillance, positioning and calibration, damage assessment, electronic warfare, and for civilian use, it can be used for border patrol, nuclear radiation detection, aerial photography, aerial pro...

AI Technical Summary

Problems solved by technology

The limited means of calculating road section traffic index in the prior art is only to calculate the traffic index of road section through tens of thousands of taxis in the city returning to the GPS positioning data of the traffic control monitoring platform, but there are following defects in such a calculation method: ( 1) The calculation accuracy is highly dependent on the number of taxis in the road section, but when there are no taxis on the key road section to be calculated, the traffic index of the key road section cannot be calculated; (2) The amount of data transmitted is large, and each taxi Both return GPS positioning data, causing the traffic management and traffic management monitoring platform to bear a huge calculation load

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