CN113573021A - Method for monitoring surrounding conditions of orchard transport vehicle - Google Patents
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- 239000002420 orchard Substances 0.000 title claims abstract description 142
- 238000012544 monitoring process Methods 0.000 title claims abstract description 30
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- 230000009466 transformation Effects 0.000 claims description 19
- 239000011159 matrix material Substances 0.000 claims description 17
- 238000013136 deep learning model Methods 0.000 claims description 3
- 238000009434 installation Methods 0.000 abstract description 7
- 230000000694 effects Effects 0.000 abstract description 6
- 238000012423 maintenance Methods 0.000 abstract description 4
- 238000004364 calculation method Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 230000002093 peripheral effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/66—Remote control of cameras or camera parts, e.g. by remote control devices
- H04N23/661—Transmitting camera control signals through networks, e.g. control via the Internet
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/695—Control of camera direction for changing a field of view, e.g. pan, tilt or based on tracking of objects
Abstract
The invention discloses a method for monitoring surrounding conditions of an orchard transport vehicle, which relates to the technical field of agricultural engineering and comprises the following steps: s1, acquiring position information of the orchard transport vehicle, and judging the camera closest to the orchard transport vehicle according to configuration information of each camera; s2, calculating rotation angle information of a camera closest to the orchard transporter, including up-down rotation angle information and left-right rotation angle information, and controlling the camera closest to the orchard transporter to rotate to a specified angle through a wireless signal; and S3, when the orchard transport vehicle rotates to a specified angle, finely adjusting the angle of the camera according to whether the orchard transport vehicle shoots the center of the image through the camera or not until the orchard transport vehicle is aligned. The method for monitoring the surrounding condition of the orchard transport vehicle simplifies system installation, upgrading and maintenance, improves the utilization effect of the fixed cameras, can monitor the plant condition of the orchard and automatically monitor the surrounding condition of the transport vehicle at the same time, and does not need to upgrade and transform the fixedly installed cameras.
Description
Technical Field
The invention relates to the technical field of agricultural engineering, in particular to a method for monitoring the surrounding conditions of an orchard transport vehicle.
Background
Southern hilly orchard slope is great, consequently for alleviateing intensity of labour, improve production efficiency, under the support of the ministry of agriculture, rail transport vechicle obtains wide application in the orchard, and the surveillance camera head of fixed mounting on rail transport vechicle is because of can long-range live image of viewing in the orchard and have the theftproof effect, can popularize in more and more orchards.
When the orchard transport vehicle runs in an orchard, the influence of shielding and video streaming delay is caused, and generally the observation is not comprehensive as much as that of a camera arranged at a high position. The vehicle-mounted camera can monitor the surrounding situation of the transport vehicle only by a plurality of cameras, the number of the lenses can be reduced by adopting the fisheye lens, but the fish-eye lens is influenced by the non-uniformity of pixels after the reduction of the fisheyes, and the recognition rate of an image cannot be guaranteed when the image is used for deep learning; the camera with a non-wide angle can obtain a better recognition effect, but due to the inherent delay of the camera, the delay of the video stream generally being more than 1s can affect the response of the transport vehicle to an object suddenly entering the visual field. Therefore, how to monitor the plant condition of the orchard and the surrounding condition of the transport vehicle simultaneously, expand the monitoring range, and simplify the system installation, upgrade and maintenance is a problem that needs to be solved urgently by technical personnel in the field.
Disclosure of Invention
In view of the above, the invention provides a method for monitoring the surrounding conditions of an orchard transport vehicle, which enlarges the monitoring range, can find the conditions of all concerned targets around the transport vehicle, and provides key information for system software to intelligently control the vehicle operation safety, route planning and the like.
In order to achieve the above purpose, the invention provides the following technical scheme:
a method for monitoring the surrounding condition of an orchard transport vehicle comprises the following steps:
s1, acquiring position information of the orchard transport vehicle, and judging the camera closest to the orchard transport vehicle according to configuration information of each camera;
s2, calculating rotation angle information of a camera closest to the orchard transporter, wherein the rotation angle information comprises vertical rotation angle information and horizontal rotation angle information, and controlling the camera closest to the orchard transporter to rotate to a specified angle through a wireless signal;
and S3, when the orchard transport vehicle rotates to a specified angle, finely adjusting the angle of the camera according to whether the orchard transport vehicle shoots the center of the image through the camera or not until the orchard transport vehicle is aligned.
The technical scheme discloses the specific steps of the method for monitoring the surrounding conditions of the orchard transport vehicle, the cameras mounted on the upright posts are fixed in the orchard, upgrading and transformation are not needed, the real-time state around the orchard transport vehicle can be better monitored by introducing the images of the monitoring cameras closest to the orchard transport vehicle, and the method is beneficial to directly mounting the cameras on the orchard transport vehicle.
Preferably, in S1, the configuration information of each camera includes: IP address, account password, video stream address, longitude and latitude, and height of camera relative reference point.
The technical scheme discloses the configuration information of the cameras, and after the position information of the orchard transport vehicle is obtained through the satellite positioning module, the cameras closest to the orchard transport vehicle can be found out more conveniently according to the recorded configuration information of the cameras.
Preferably, in S1, the determining the camera closest to the orchard transporter includes:
the position information of the orchard transport vehicle obtained by the satellite positioning module is (x)0,y0) Setting the ith camera position in the orchard as (x)i,yi) Then, the distance between the nearest camera of the distance between the orchard transport vehicle and the orchard transport vehicle is as follows:
preferably, in S2, the calculating the rotation angle information of the camera closest to the orchard transporter includes:
setting the oriental angle to be 0 degree, acquiring the vertical rotation angle theta of the camera closest to the orchard transport vehicle at the moment relative to the oriental angle, and setting the coordinates of the camera to be (0,0), wherein the current coordinates of the orchard transport vehicle are (x)0-xi,y0-yi) Left and right rotation angles: α ═ arctan ((y)0-yi)/(x0-xi) The angle (theta-alpha) degrees by which the camera closest to the orchard transporter needs to rotate.
According to the technical scheme, the method for calculating the rotation angle of the camera closest to the orchard transport vehicle is described, the image target in the camera is converted into the coordinate of the plane where the orchard transport vehicle is located, and the camera is rotated, so that the surrounding conditions of the orchard transport vehicle can be observed more comprehensively.
Preferably, in S3, the fine-tuning the camera angle until the orchard transporter is aligned includes:
s31, arranging at least 5 marks above the orchard transporter, wherein 4 vertexes of the marks are used for perspective transformation, and other marks are used for marking a positive direction;
s32, positioning the position of the mark through a target recognition algorithm according to the image shot by the orchard transporter through the camera closest to the orchard transporter, wherein 4 vertexes of the mark are { (u) respectively1,v1),(u2,v2),(u3,v3),(u4,v4) The standard coordinate system position corresponding to the plane formed by the four vertexes is { (x)1,y1),(x2,y2),(x3,y3)(x4,y4) This data is used to compute the perspective transformation matrix a:
wherein:
x'＝(x1,x2,x3,x4)T，y'＝(y1,y2,y3,y4)T，u＝(u1,u2,u3,u4)T，v＝(v1,v2,v3,v4)Tthe transformation matrix a is:
s33, substituting the coordinates of the four vertexes of the orchard transporter into a formula (2) to obtain a transformation matrix A, and obtaining transformed coordinates through the matrix A:
x and y obtained in the formulas (3) and (4) are coordinate values of images collected by the camera and transformed to a plane coordinate of the transport vehicle respectively;
s34, obtaining the rectangular frame of the orchard transport vehicle in the shot image through the deep learning model, obtaining the relative position of the orchard transport vehicle by utilizing the transformation matrix, finely adjusting the camera, and aligning the camera to the orchard transport vehicle.
The technical scheme discloses a method for finely adjusting the angle of the camera, so that the orchard transport vehicle can be positioned in the center of an image, namely the camera is rotated until the camera is aligned with the transport vehicle. The position of the orchard transport vehicle can be observed more conveniently by arranging the obvious mark above the orchard transport vehicle.
According to the technical scheme, compared with the prior art, the method for monitoring the surrounding condition of the orchard transport vehicle has the following beneficial technical effects:
(1) according to the method for monitoring the surrounding condition of the orchard transport vehicle, the camera is mounted on the high rod near the orchard transport vehicle, the monitoring of the surrounding condition of the orchard transport vehicle can be realized without a wide-angle camera, the utilization effect of the fixed camera is improved, the monitoring range is wider, all concerned target conditions around the orchard transport vehicle, particularly high-speed moving targets on the side surface, can be found, and the plant condition of the orchard and the surrounding condition of the orchard transport vehicle can be monitored simultaneously;
(2) according to the orchard allocation method, the intelligent control system arranged on the orchard transport vehicle is utilized, the fixedly installed camera is not required to be upgraded and reformed, the system installation, upgrading and maintenance are simplified, the intelligent control system plays a role in edge calculation, and real-time and efficient support is provided for all high-performance calculation of the orchard; the intelligent control system acquires agricultural data on a field and a cloud platform, can provide services such as two-dimensional codes and electronic tags for agricultural products, and can be used for orchard monitoring and control by a user with authority through any equipment which can be accessed to the cloud platform or the intelligent control system on the field.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method of monitoring the conditions around an orchard transporter according to the invention;
fig. 2 is a schematic diagram of highlighting an orchard transporter in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention discloses a method for monitoring the surrounding conditions of an orchard transporter, which comprises the following steps as shown in figure 1:
s1, acquiring position information of the orchard transport vehicle, and judging the camera closest to the orchard transport vehicle according to configuration information of each camera;
s2, calculating rotation angle information of a camera closest to the orchard transporter, wherein the rotation angle information comprises vertical rotation angle information and horizontal rotation angle information, and controlling the camera closest to the orchard transporter to rotate to a specified angle through a wireless signal;
and S3, when the orchard transport vehicle rotates to a specified angle, finely adjusting the angle of the camera according to whether the orchard transport vehicle shoots the center of the image through the camera or not until the orchard transport vehicle is aligned.
In an embodiment, according to the orchard monitoring needs, choose the position installation fixed pole setting of being convenient for to observe the orchard situation for use, install the camera in pole setting top, the camera has Wi-Fi, can have other communication modes simultaneously. The camera power supply mode is generally that solar energy supplies power for the battery, supplies power for the camera through the battery, also can select alternating current power supply. The lightning rod installed according to the standard is arranged above the camera, and the camera can control the camera to rotate by adopting a universal control protocol through wireless signals. And recording the longitude and latitude of the installation position and the height of the camera relative to the reference point through external setting during installation. The IP address, the account number and the password, the video stream address, the longitude and latitude, the height of the camera relative to the reference point and other information of each fixedly-installed camera in the orchard are output in the software through special software on an external computer, a JSON data format is generated firstly, and then a configuration file is generated through an encryption algorithm and is used by a software system on an intelligent control panel of the transport vehicle.
The intelligent control system comprises an NVIDIA edge computing terminal Jetson Xavier NX which comprises a CPU and a GPU. When the system runs, one thread of the CPU drives the camera to shoot a target, the obtained image is transferred to the GPU thread through the main thread to be processed, the processing result is returned to the other thread of the CPU, the thread operates the execution terminal through the onboard IO port through the adapter circuit according to the judging condition, and the execution terminal comprises the functions of controlling braking, giving sound and light alarm and the like. The intelligent control system opens up an independent network processing thread to upload the original image and the detection key information to the cloud server. The main thread is also responsible for processing the on-site display interface, wherein the on-site image display interface is closed by default so as to reduce the calculation of the CPU.
The frequency of the images uploaded by the network processing threads is adjustable, and after the original images are uploaded to the cloud server, the server-side processor performs the same model analysis on the images, performs image splicing and restores the field images. The GPU is used for target detection and judgment, based on which real-time can be achieved, the CPU task is decomposed into a plurality of threads, and the GPU only infers the newly acquired image.
The intelligent control part of the orchard transport vehicle adopts a deep learning development kit (NVIDIA Jetson developer kit) with a GPU (hereinafter referred to as an intelligent control board), and realizes the acquisition of external data and the control of an actuating mechanism by utilizing various onboard standard interfaces and GPIO ports through a peripheral circuit and an adapter. The peripheral circuit needs to be protected by an optocoupler or a Schottky diode and the like during design, and the intelligent control panel can be prevented from being burnt by external overloaded current. The intelligent control board is connected with the satellite positioning module, and obtains current position information and time from the module. The configuration file is copied to a software system on the intelligent control board through a network or a storage device, and the software system decrypts and loads configuration information through a decryption algorithm. And calculating position information through configuration information, connecting the closest camera, calculating the angle of the camera required to rotate, and controlling the camera to rotate to a specified angle so as to align the transport vehicle.
In one embodiment, the method for judging the camera closest to the orchard transporter comprises the following steps:
the position information of the orchard transport vehicle obtained through the satellite positioning module is (x)0,y0) Setting the ith camera position in the orchard as (x)i,yi) Then, the distance between the nearest camera of distance orchard transport vechicle and the orchard transport vechicle is:
further, the rotation angle information of the camera closest to the orchard transport vehicle is calculated, and the rotation angle information comprises the following steps:
setting the right east as an angle of 0 degree, acquiring the vertical rotation angle of a camera closest to the orchard transport vehicle at the moment relative to the right east as theta, and setting the coordinates of the camera as (0,0), wherein the current coordinates of the orchard transport vehicle are (x)0-xi,y0-yi) Left and right rotation angles: α ═ arctan ((y)0-yi)/(x0-xi) The angle (theta-alpha) degrees by which the camera closest to the orchard transporter needs to rotate.
In an embodiment, in the method of finely adjusting the angle of the camera until the camera is aligned with the orchard transport vehicle, as shown in fig. 2, 5 red circular marks may be arranged above the orchard transport vehicle, a red LED lamp is installed in the center of each mark, and when the light is insufficient, the LED lamp is turned on; wherein, the coordinates of four vertexes of the rectangular frame are fixed, one side of the rectangular frame is provided with three points which represent the reference positive direction, the position of the mark is positioned by a target identification algorithm, and the 4 vertexes of the mark are { (u) respectively1,v1),(u2,v2),(u3,v3),(u4,v4) The standard coordinate system position corresponding to the plane formed by the four vertexes is { (x)1,y1),(x2,y2),(x3,y3)(x4,y4) This data is used to compute the perspective transformation matrix a:
wherein:
x'＝(x1,x2,x3,x4)T，y'＝(y1,y2,y3,y4)T，u＝(u1,u2,u3,u4)T，v＝(v1,v2,v3,v4)Tthe transformation matrix a is:
substituting the coordinates of four vertexes of the orchard transport vehicle into a formula (2) to obtain a transformation matrix A, and obtaining transformed coordinates through the matrix A:
x and y obtained in the formulas (3) and (4) are coordinate values of images collected by the camera and transformed to a plane coordinate of the transport vehicle respectively;
the orchard transport vehicle monitoring system comprises a rectangular frame of an orchard transport vehicle in a shooting image obtained through a depth learning model, a relative position of the orchard transport vehicle is obtained through a transformation matrix, a camera is finely adjusted and is aligned to the orchard transport vehicle, accordingly, the peripheral situation of the orchard transport vehicle is monitored, a software system on an intelligent control board of the orchard transport vehicle judges whether surrounding monitoring targets affect the operation of the transport vehicle through set judgment rules, and if the monitoring targets are dangerous, the transport vehicle is controlled to brake through an interface.
If the transport vehicle is also provided with the camera, the angle information of the camera and the transformation matrix of the positive direction of the transport vehicle are configured in the software system on the intelligent control panel. And obtaining a target rectangular frame through a deep learning model, performing rotation transformation according to the angle of the camera, then performing transformation by using a transformation matrix in the positive direction, and combining the transformed result with a camera detection result fixed outside for reference of a software system.
The intelligent control board is time-synchronized with the camera by using the satellite time information, and the time delay from the acquisition of the image to the end of the image analysis can be judged by the time information embedded in the image for the reference of a software system.
In the prior art, when the orchard transport vehicle runs in an orchard, the orchard transport vehicle is influenced by shielding and video streaming delay, and is generally not installed at a high position, so that the orchard transport vehicle can be observed comprehensively. According to the method for monitoring the surrounding conditions of the orchard transport vehicle, the cameras are mounted on the high rods near the orchard transport vehicle, so that the utilization effect of the fixed cameras is improved, and the purpose of simultaneously monitoring the plant conditions of the orchard and the surrounding conditions of the orchard transport vehicle can be achieved; an intelligent control system arranged on the orchard transport vehicle is introduced, the fixedly installed camera is not required to be upgraded and modified, the system installation, upgrade and maintenance are simplified, the intelligent control system plays a role in edge calculation, and real-time and efficient support is provided for all high-performance calculation of the orchard; the intelligent control system acquires agricultural data on a field and a cloud platform, can provide services such as two-dimensional codes and electronic tags for agricultural products, and can be used for orchard monitoring and control by a user with authority through any equipment which can be accessed to the cloud platform or the intelligent control system on the field.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (5)
1. A method for monitoring the surrounding condition of an orchard transport vehicle is characterized by comprising the following steps:
s1, acquiring position information of the orchard transport vehicle, and judging the camera closest to the orchard transport vehicle according to configuration information of each camera;
s2, calculating rotation angle information of a camera closest to the orchard transporter, wherein the rotation angle information comprises vertical rotation angle information and horizontal rotation angle information, and controlling the camera closest to the orchard transporter to rotate to a specified angle through a wireless signal;
and S3, when the orchard transport vehicle rotates to a specified angle, finely adjusting the angle of the camera according to whether the orchard transport vehicle shoots the center of the image through the camera or not until the orchard transport vehicle is aligned.
2. The method for monitoring the surrounding conditions of the orchard transporter according to claim 1, wherein in the step S1, the configuration information of each camera comprises: IP address, account password, video stream address, longitude and latitude, and height of camera relative reference point.
3. The method for monitoring the surrounding conditions of the orchard transporter according to claim 1, wherein in the step S1, the step of judging the camera closest to the orchard transporter comprises the following steps:
the position information of the orchard transport vehicle obtained by the satellite positioning module is (x)0,y0) Setting the ith camera position in the orchard as (x)i,yi) Then, the distance between the nearest camera of the distance between the orchard transport vehicle and the orchard transport vehicle is as follows:
4. the orchard transporter surrounding condition monitoring method according to claim 1, wherein in the step S2, the step of calculating the rotation angle information of the camera closest to the orchard transporter comprises the steps of:
setting the oriental angle to be 0 degree, acquiring the vertical rotation angle theta of the camera closest to the orchard transport vehicle at the moment relative to the oriental angle, and setting the coordinates of the camera to be (0,0), wherein the current coordinates of the orchard transport vehicle are (x)0-xi,y0-yi) Left and right rotation angles: α ═ arctan ((y)0-yi)/(x0-xi) The angle (theta-alpha) degrees by which the camera closest to the orchard transporter needs to rotate.
5. The orchard transporter surrounding condition monitoring method according to claim 1, wherein in the step S3, fine adjustment of the angle of the camera until the orchard transporter is aligned with the camera angle comprises the following steps:
s31, arranging at least 5 marks above the orchard transporter, wherein 4 vertexes of the marks are used for perspective transformation, and other marks are used for marking a positive direction;
s32, positioning the position of the mark through a target recognition algorithm according to the image shot by the orchard transporter through the camera closest to the orchard transporter, wherein 4 vertexes of the mark are { (u) respectively1,v1),(u2,v2),(u3,v3),(u4,v4) The standard coordinate system position corresponding to the plane formed by the four vertexes is { (x)1,y1),(x2,y2),(x3,y3)(x4,y4) This data is used to compute the perspective transformation matrix a:
wherein:
x'＝(x1,x2,x3,x4)T，y'＝(y1,y2,y3,y4)T，u＝(u1,u2,u3,u4)T，v＝(v1,v2,v3,v4)Tthe transformation matrix a is:
s33, substituting the coordinates of the four vertexes of the orchard transporter into a formula (2) to obtain a transformation matrix A, and obtaining transformed coordinates through the matrix A:
x and y obtained in the formulas (3) and (4) are coordinate values of images collected by the camera and transformed to a plane coordinate of the transport vehicle respectively;
s34, obtaining the rectangular frame of the orchard transport vehicle in the shot image through the deep learning model, obtaining the relative position of the orchard transport vehicle by utilizing the transformation matrix, finely adjusting the camera, and aligning the camera to the orchard transport vehicle.
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