CN112256062A - A unmanned aerial vehicle for highway patrols and examines - Google Patents
A unmanned aerial vehicle for highway patrols and examines Download PDFInfo
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- CN112256062A CN112256062A CN202011226264.0A CN202011226264A CN112256062A CN 112256062 A CN112256062 A CN 112256062A CN 202011226264 A CN202011226264 A CN 202011226264A CN 112256062 A CN112256062 A CN 112256062A
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- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Abstract
The invention discloses an unmanned aerial vehicle for highway inspection, which comprises an unmanned aerial vehicle and a ground platform, wherein the unmanned aerial vehicle is provided with an unmanned aerial vehicle flight module, an airborne camera module, a video processing module, an image recognition module, a video and image storage module and a communication module. According to the method, a video shot by the unmanned aerial vehicle is divided into a plurality of sections according to time length, a small number of frame images are extracted from each section of video on the unmanned aerial vehicle, semantic recognition is carried out on the images so as to preliminarily judge whether a vehicle occupies an emergency lane, the images and the video are transmitted to a ground platform when the preliminary judgment result shows that the vehicle occupies, further confirmation is carried out by the ground platform, and otherwise the video section is deleted.
Description
Technical Field
The invention relates to an unmanned aerial vehicle for highway inspection.
Background
The emergency lane is a lane which is located at the rightmost side of the road surface in the driving direction and is mainly used for parking in case of accidents or faults and specially used for rescuing, and is also commonly called a 'hard shoulder'.
The expressway emergency lane is specially used for vehicles for processing emergency affairs, such as engineering rescue, fire rescue, medical rescue or civil police performing emergency official business, and any social vehicles are prohibited from driving in or stay in the lane for various reasons.
In recent years, as the holding amount of vehicles continues to increase, the roads are often congested, and the vehicles occupy emergency lanes on the highway. When a traffic accident occurs, the rescue vehicle cannot arrive at the scene in time, the rescue activities cannot be carried out in time, and the vehicles which occupy the emergency lane illegally maliciously cannot be subjected to evidence collection and punishment so as to restrain the reoccurrence of the phenomenon.
Along with the quick development of unmanned aerial vehicle, unmanned aerial vehicle is widely used in highway road conditions and cruises and takes a candid photograph emergent lane violating regulations, but unmanned aerial vehicle among the prior art has following problem at least: in the prior art, an unmanned aerial vehicle is adopted to shoot a video of an expressway and transmit the video to a ground platform in the cruising process, and if the real-time performance is emphasized, the video data is large, the transmission cost is high, and the energy consumption in the transmission process is high. If do not require the real-time, it also can produce a large amount of storage data, need to undertake the storage cost on the one hand, and on the other hand occupies unmanned aerial vehicle resource, influences unmanned aerial vehicle normal work and continuation of the journey.
Disclosure of Invention
The invention aims to provide an unmanned aerial vehicle system which can effectively complete highway cruising and effectively reduce video transmission cost.
In order to solve the problems, the invention provides an unmanned aerial vehicle for highway inspection, which comprises an unmanned aerial vehicle and a ground platform, wherein the unmanned aerial vehicle is provided with an unmanned aerial vehicle flight module, an airborne camera module, a video processing module, an image identification module, a video and image storage module and a communication module,
the unmanned aerial vehicle flight module is used for controlling the flight and navigation of the unmanned aerial vehicle,
the onboard camera module is used for shooting videos of a high-speed road surface when the unmanned aerial vehicle flies, and is characterized in that,
the video processing module is provided with a video segment making unit, a video segment processing unit and a video segment caching unit, wherein:
the video segment making unit is in communication connection with the onboard camera module and makes videos shot by the onboard camera module into video segments according to set time lengths and stores the video segments, the video segments are called by the video segment processing unit when the image recognition module is idle, the video segment caching unit is called when the image recognition module performs work, and the video segments are deleted from the video segment making unit after being called;
-the video segment processing unit calls the video segment stored in the video segment creation unit or the video segment caching unit and extracts the image of at least one frame from the video segment, the video segment processing unit preferentially calls the video segment stored in the video segment caching unit when the video segment is stored therein;
the video segment caching unit temporarily stores the video segment after calling the video segment and accepts the calling of the video segment processing unit, the video segment cached in the video segment caching unit is more than one time, the video segment caching unit divides the called priority, the video segment cached earlier is preferentially called, and the video segment is deleted after accepting the calling;
the image identification module is used for identifying the image extracted from the video segment processing unit, judging whether a vehicle occupies an emergency lane or not, deleting the video segment in the video segment processing unit if the vehicle does not occupy the emergency lane, and storing the video segment in the video segment processing unit and the identified image into the video and image storage module if the vehicle occupies the emergency lane;
the communication module communicates with the ground platform and transmits the images and videos stored in the video and image storage module to the ground platform.
As a further improvement of the present invention, the image recognition module includes:
the image semantic segmentation unit is in communication connection with the video segment processing unit and can perform semantic analysis on the image extracted by the video segment processing unit so as to segment a lane and a background;
the lane curve fitting unit is in communication connection with the image semantic segmentation unit and performs curve fitting on a lane area on the image subjected to semantic segmentation to obtain a lane contour line and an emergency lane contour line;
and the vehicle detection unit is used for judging whether a vehicle passes through one side of the emergency lane in the extracted image.
As a further improvement of the present invention, the lane curve fitting unit obtains pixel coordinates of a lane line in a lane area on the image, performs curve fitting on the lane line coordinates by a least square method to obtain quadratic parabolic curve equations of a driving lane and an emergency lane, and finally draws the fitted driving line and emergency lane line on the lane area of the frame image according to the obtained quadratic parabolic curve equations.
As a further improvement of the present invention, the vehicle detection unit is further capable of obtaining information on the number of vehicles in the traffic lane, thereby counting the traffic flow.
The method has the advantages that the video shot by the unmanned aerial vehicle is divided into a plurality of sections according to time length, a small number of frame images are extracted from each section of video on the unmanned aerial vehicle, semantic recognition is carried out on the images so as to preliminarily judge whether a vehicle occupies an emergency lane, when the preliminary judgment result shows that the vehicle occupies the emergency lane, the images and the video are transmitted to the ground platform, further confirmation is carried out by the ground platform, and otherwise the video section is deleted.
Drawings
Fig. 1 is a schematic structural view of the present invention.
In the figure: the unmanned aerial vehicle comprises an unmanned aerial vehicle 1000, an unmanned aerial vehicle flight module 1100, an onboard camera module 1200, a video processing module 1300, a video segment making unit 1302, a video segment processing unit 1304, a video segment caching unit 1306, an image recognition module 1400, an image semantic segmentation unit 1402, a lane curve fitting unit 1404, a vehicle detection unit 1406, a video and image storage module 1600, a communication module 1800 and a ground platform 2000.
Detailed Description
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings.
As shown in fig. 1, the present invention includes a drone 1000 and a ground station 2000, the drone having a drone flight module 1100, an onboard camera module 1200, a video processing module 1300, an image recognition module 1400, a video and image storage module 1600, and a communication module 1800, wherein,
the drone flight module 1100 is used to control the flight and navigation of the drone,
the onboard camera module 1200 is used for video shooting of the high-speed road surface when the unmanned aerial vehicle flies, and is characterized in that,
the video processing module 1300 is provided with a video segment creation unit 1302, a video segment processing unit 1304, and a video segment buffer unit 1306, wherein:
the video segment creation unit 1302 is in communication connection with the onboard camera module 1200, and creates and stores the video captured by the onboard camera module 1200 into video segments according to a set time length, the video segments are called by the video segment processing unit 1304 when the image recognition module 1400 is idle, and are called by the video segment caching unit 1306 when the image recognition module 1400 performs work, and the video segments are deleted from the video segment creation unit 1302 after being called;
the video segment processing unit 1304 calls the video segments stored in the video segment creation unit 1302 or the video segment caching unit 1306, and extracts at least one frame of image from the video segments, and the video segment processing unit 1304 preferentially calls the video segments stored in the video segment caching unit 1306 when the video segments are stored in the video segment caching unit 1306;
the video segment caching unit 1306 temporarily stores the video segment after the video segment is called, and accepts the call of the video segment processing unit 1304, the video segment cached in the video segment caching unit 1306 is more than one time, the video segment caching unit 1306 divides the called priority, the calling priority is preferentially called when the calling priority is stored earlier in the video segment caching unit 1306, and the video segment is deleted after the calling is accepted;
the image recognition module 1400 is configured to recognize the image extracted from the video segment processing unit 1304, determine whether a vehicle occupies an emergency lane in the image, delete the video segment in the video segment processing unit 1304 if the vehicle does not occupy the emergency lane in the image, and store the video segment in the video segment processing unit 1304 and the recognized image in the video and image storage module 1600 if the vehicle occupies the emergency lane in the image;
the communication module 1800 communicates with the ground station 2000 and transmits the images and videos stored in the video and image storage module 1600 to the ground station 2000.
As a further improvement of the present invention, the image recognition module 1400 includes:
an image semantic segmentation unit 1402, communicatively connected to the video segment processing unit 1304, wherein the image semantic segmentation unit 1402 can perform semantic analysis on the image extracted by the video segment processing unit 1304, so as to segment a lane and a background;
the lane curve fitting unit 1404 is in communication connection with the image semantic segmentation unit 1402, and the lane curve fitting unit 1404 performs curve fitting on a lane area on the image subjected to semantic segmentation to obtain a lane contour line and an emergency lane contour line;
the vehicle detection unit 1406 determines whether or not a vehicle passes through the emergency lane side in the extracted image.
As a further improvement of the present invention, the lane curve fitting unit 1404 obtains pixel coordinates of a lane line in a lane area on the image, performs curve fitting on the lane line coordinates by a least square method to obtain quadratic parabolic curve equations of a driving lane and an emergency lane, and finally draws a fitted driving line and an emergency lane line on the lane area of the frame image according to the obtained quadratic parabolic curve equations.
As a further improvement of the present invention, the vehicle detecting unit 1406 can also obtain information on the number of vehicles in the traffic lane, thereby counting the traffic flow.
The specific principle of the invention is as follows:
(1) the unmanned aerial vehicle takes off and cruises the target highway according to airborne navigation;
(2) the onboard camera is opened, and video shooting is carried out on the expressway;
(3) the captured video is processed by the video segment creation unit 1302 to form a video segment, and temporarily stored, for example, after 5 minutes of capturing, the 5 minutes of video is temporarily stored as a video segment;
(4) it is detected whether the image recognition module 1400 is idle,
(5) if the image recognition module 1400 is not idle, the video segment caching unit 1306 invokes a video segment in the video segment creation unit 1302, and after the invocation, the video segment is deleted from the video segment creation unit 1302, and when a plurality of video segments are stored in the video segment caching unit 1306, the video segment is prioritized, wherein a video segment stored first in the video caching unit has a higher priority than a video segment stored later;
(6) if the image recognition module 1400 is idle, the video segment processing unit 1304 calls a video segment, where the video segment is from the video segment making unit 1302 or the video cache segment cache unit, and when a video segment is cached in the video segment cache unit 1306, the cache video segment in the video segment cache unit 1306 is called preferentially, and a video segment with a high priority in the video segment cache unit 1306 is called preferentially, and after being called, the video segment is deleted from the video segment making unit 1302 or the video cache segment cache unit;
(7) the video segment processing unit 1304 operates the called video segment, extracts at least one frame image from the American video segment, and determines the number of frames according to the working requirement and the length of the video segment, if the video segment is short or aims at taking violation snapshot in emergency, extracts less frame images, and if the video segment is long or aims at counting the real-time traffic flow, extracts more frame images;
(8) semantic segmentation is performed on the extracted image through the image semantic segmentation unit 1402, so that a lane area and a background area are obtained on the image, and different pixel values can be given to the lane area and the background area for distinguishing;
(9) the lane curve fitting unit 1404 obtains pixel coordinates of a lane line of a lane area on the semantically segmented image;
(10) performing curve fitting on the lane linear coordinates by a least square method to obtain quadratic parabolic curve equations of a traffic lane and an emergency lane;
(11) drawing a fitted driving line and an emergency lane line on a lane area of the image according to the obtained quadratic parabolic equation;
(12) judging whether a vehicle is on one side of the emergency lane line;
(13) if not, deleting the video segment stored in the video segment processing unit 1304, and the image recognition module 1400 is in an idle state;
(14) if yes, the video and image storage unit calls the video segment stored in the video segment processing unit 1304 to refer to the image fitted with the lane line, and stores the image, at this time, the called video segment is deleted, and the image identification module 1400 is in an idle state;
(15) the video segments and images are transmitted to the ground platform 2000 through the communication module 1800.
The technical principle of the present invention is described above in connection with specific embodiments. The description is made for the purpose of illustrating the principles of the invention and should not be construed in any way as limiting the scope of the invention. Based on the explanations herein, those skilled in the art will be able to conceive of other embodiments of the present invention without inventive effort, which would fall within the scope of the present invention.
Claims (4)
1. An unmanned aerial vehicle for highway inspection comprises an unmanned aerial vehicle and a ground platform, wherein the unmanned aerial vehicle is provided with an unmanned aerial vehicle flight module, an onboard camera module, a video processing module, an image identification module, a video and image storage module and a communication module,
the unmanned aerial vehicle flight module is used for controlling the flight and navigation of the unmanned aerial vehicle,
the onboard camera module is used for shooting videos of a high-speed road surface when the unmanned aerial vehicle flies, and is characterized in that,
the video processing module is provided with a video segment making unit, a video segment processing unit and a video segment caching unit, wherein:
the video segment making unit is in communication connection with the onboard camera module and makes videos shot by the onboard camera module into video segments according to set time lengths and stores the video segments, the video segments are called by the video segment processing unit when the image recognition module is idle, the video segment caching unit is called when the image recognition module performs work, and the video segments are deleted from the video segment making unit after being called;
-the video segment processing unit calls the video segment stored in the video segment creation unit or the video segment caching unit and extracts the image of at least one frame from the video segment, the video segment processing unit preferentially calls the video segment stored in the video segment caching unit when the video segment is stored therein;
the video segment caching unit temporarily stores the video segment after calling the video segment and accepts the calling of the video segment processing unit, the video segment cached in the video segment caching unit is more than one time, the video segment caching unit divides the called priority, the video segment cached earlier is preferentially called, and the video segment is deleted after accepting the calling;
the image identification module is used for identifying the image extracted from the video segment processing unit, judging whether a vehicle occupies an emergency lane or not, deleting the video segment in the video segment processing unit if the vehicle does not occupy the emergency lane, and storing the video segment in the video segment processing unit and the identified image into the video and image storage module if the vehicle occupies the emergency lane;
the communication module communicates with the ground platform and transmits the images and videos stored in the video and image storage module to the ground platform.
2. A drone for highway inspection according to claim 1, characterized in that said image recognition module comprises:
the image semantic segmentation unit is in communication connection with the video segment processing unit and can perform semantic analysis on the image extracted by the video segment processing unit so as to segment a lane and a background;
the lane curve fitting unit is in communication connection with the image semantic segmentation unit and performs curve fitting on a lane area on the image subjected to semantic segmentation to obtain a lane contour line and an emergency lane contour line;
and the vehicle detection unit is used for judging whether a vehicle passes through one side of the emergency lane in the extracted image.
3. The unmanned aerial vehicle for highway inspection according to claim 2, wherein the lane curve fitting unit obtains pixel coordinates of a lane line of a lane area on the image, performs curve fitting on the lane line coordinates by a least square method to obtain quadratic parabolic curve equations of a lane and an emergency lane, and finally draws a fitted lane line and an emergency lane line on the lane area of the frame image according to the obtained quadratic parabolic curve equations.
4. The unmanned aerial vehicle for highway inspection according to claim 3, wherein the vehicle detection unit is further capable of obtaining information of the number of vehicles in the traffic lane so as to count the traffic flow.
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| CN202011226264.0A CN112256062A (en) | 2020-11-05 | 2020-11-05 | A unmanned aerial vehicle for highway patrols and examines |
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| CN202011226264.0A CN112256062A (en) | 2020-11-05 | 2020-11-05 | A unmanned aerial vehicle for highway patrols and examines |
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Cited By (1)
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| CN114495537A (en) * | 2021-12-15 | 2022-05-13 | 杨金玲 | Emergency rescue system for highway engineering |
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