CN114919584A - Motor vehicle fixed point target distance measuring method and device and computer readable storage medium - Google Patents
Motor vehicle fixed point target distance measuring method and device and computer readable storage medium Download PDFInfo
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- 238000003384 imaging method Methods 0.000 claims abstract description 37
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- 238000009795 derivation Methods 0.000 claims abstract description 5
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
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- G—PHYSICS
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
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- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2552/00—Input parameters relating to infrastructure
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2554/00—Input parameters relating to objects
- B60W2554/80—Spatial relation or speed relative to objects
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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Abstract
The embodiment of the invention provides a method and a device for measuring distance of a fixed-point target of a motor vehicle and a computer readable storage medium, wherein the method comprises the following steps: acquiring real-time image frames from original video images shot by a vehicle-mounted camera; detecting obstacles around the motor vehicle from each frame image frame by adopting a pre-stored target detection model, and selecting a target frame of a point to be measured in two adjacent frame image frames; respectively calculating the photosensitive surface coordinates of the same position points in the target frames of two adjacent image frames corresponding to the photosensitive surface of the vehicle-mounted camera; deducing the position points of two adjacent frames of image frames according to the coordinate of the photosensitive surface based on the camera imaging principle and a geometric relationship derivation method to correspond to the lens imaging coordinate imaged on the lens of the vehicle-mounted camera; and calculating and outputting the current actual distance of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variable quantity P in the frame difference time of the original video image and the lens imaging coordinate. The embodiment can effectively reduce the detection cost and improve the detection efficiency.
Description
Technical Field
The embodiment of the invention relates to the technical field of auxiliary driving of motor vehicles, in particular to a method and a device for measuring distance of a fixed point target of a motor vehicle and a computer readable storage medium.
Background
At present, a vehicle is usually provided with a visual ranging device connected with a vehicle-mounted camera and used for detecting the distance between an obstacle and a vehicle according to an original video image provided by the vehicle-mounted camera, in order to accurately calculate the distance between the obstacle and the vehicle, the existing visual ranging method usually firstly obtains a video image of the environment around the vehicle through the vehicle-mounted camera, then constructs a three-dimensional scene map of the current environment of the vehicle through the video image, and finally calculates and determines the relative distance between the obstacle and the vehicle through the three-dimensional map. However, the inventor finds that, in the traditional method, when a three-dimensional scene map is constructed, the image depth needs to be calculated, the required hardware computation cost is high, the process is complex, and finally the overall distance measurement efficiency is relatively low.
Disclosure of Invention
The technical problem to be solved by the embodiment of the invention is to provide a method for measuring distance of a fixed point target of a motor vehicle, which can effectively reduce the detection cost and improve the detection efficiency.
The embodiment of the invention further aims to solve the technical problem of providing a distance measuring device for a fixed-point target of a motor vehicle, which can effectively reduce the detection cost and improve the detection efficiency.
A further technical problem to be solved by embodiments of the present invention is to provide a computer-readable storage medium to store a computer program that can effectively reduce the detection cost and improve the detection efficiency.
In order to solve the above technical problem, an embodiment of the present invention first provides the following technical solutions: a method for measuring distance of a fixed point target of a motor vehicle comprises the following steps:
acquiring real-time image frames from original video images shot by a vehicle-mounted camera;
detecting obstacles around the motor vehicle from the image frames frame by adopting a pre-stored target detection model starting from a first frame, marking the obstacles which are present in the two adjacent image frames and are fixed per se as point targets to be measured, and selecting the point targets to be measured in the two adjacent image frames by adopting a target frame with a predetermined standard size;
respectively calculating the photosensitive surface coordinates of the same position points in the target frames of the two adjacent image frames corresponding to the photosensitive surface of the vehicle-mounted camera;
deducing the position points of the two adjacent frames of image frames according to the photosensitive surface coordinates based on a camera imaging principle and a geometric relationship derivation method, wherein the position points correspond to lens imaging coordinates imaged on a lens of the vehicle-mounted camera; and
and calculating and outputting the current actual distance of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variable quantity P in the frame difference time of the original video image and the lens imaging coordinate.
Further, the calculating and outputting the current actual distance of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variation P within the frame difference time of the original video image and the lens imaging coordinate specifically includes:
calculating lens imaging coordinates corresponding to a plurality of pairs of different position points in the target frames of the two adjacent image frames;
correspondingly calculating a plurality of current estimated distances of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variation P in the frame difference time of the original video image and each pair of the lens imaging coordinates; and
and outputting the weighted average value of the current estimated distance corresponding to each pair of lens imaging coordinates as the current actual distance.
Further, the current estimated distance
Wherein P is the wheel speed pulse variation of the motor vehicle in the frame difference time of the original video image, and f is the vehicle-mounted shooting quantityFocal length of image head, X 2 And X 1 And the horizontal coordinate values are respectively the horizontal coordinate values of a pair of corresponding lens imaging coordinates in the two adjacent image frames.
Further, the position point is a coordinate point on the bottom side of the target frame.
Further, the target detection model is an SSD algorithm model based on deep learning.
Further, the acquiring of the real-time image frame from the original video image captured by the vehicle-mounted camera specifically means acquiring the real-time image frame from the original video image captured by the vehicle-mounted monocular camera.
On the other hand, in order to solve the above further technical problem, the embodiment of the present invention further provides the following technical solutions: a motor vehicle fixed point target distance measuring device is respectively connected with an on-board camera for shooting a video image of the surrounding environment of a motor vehicle and providing an original video image and an information display device for displaying the current actual distance output by the motor vehicle fixed point target distance measuring device, the motor vehicle fixed point target distance measuring device comprises a processor, a memory and a computer program which is stored in the memory and configured to be executed by the processor, and the processor executes the computer program to realize the motor vehicle fixed point target distance measuring method.
On the other hand, in order to solve the above further technical problem, an embodiment of the present invention further provides the following technical solutions: a computer readable storage medium comprising a stored computer program, wherein the computer program when executed controls a device on which the computer readable storage medium is located to perform a method of ranging a vehicle fixed point target as in any one of the above.
After the technical scheme is adopted, the embodiment of the invention at least has the following beneficial effects: the embodiment of the invention acquires real-time image frames from an original video image shot by a vehicle-mounted camera, marks the obstacles which are fixed in the two adjacent image frames and exist in the two adjacent image frames as point targets to be measured after detecting the obstacles around the motor vehicle from each image frame, selects the point targets to be measured in the two adjacent image frames by adopting a target frame with a preset standard size, calculates the coordinates of the same position points in the target frames of the two adjacent image frames corresponding to the light sensing surface of the vehicle-mounted camera, further deduces the lens imaging coordinates of the imaging on the lens of the vehicle-mounted camera according to the light sensing surface coordinates, has relatively simpler calculation process, and finally can calculate and output the current actual distance of the point targets to be measured relative to the motor vehicle by combining the wheel speed pulse variation P in the frame difference time of the original video image and the lens imaging coordinates, need not complicated pixel and match, vehicle-mounted camera need not to adopt the higher binocular camera of cost to realize the range finding in addition compared in the conventional art, and the cost is lower.
Drawings
FIG. 1 is a flow chart of steps of an alternative embodiment of a method for ranging a fixed point target of a motor vehicle according to the present invention.
Fig. 2 is a detailed flowchart of step S5 of an alternative embodiment of the ranging method for a vehicle fixed-point target according to the present invention.
Fig. 3 is a schematic view of the imaging principle of a point target to be measured according to an alternative embodiment of the distance measuring method for a motor vehicle fixed point target of the present invention.
Fig. 4 is a schematic block diagram of an alternative embodiment of the vehicle fixed-point target ranging device of the present invention.
Fig. 5 is a functional block diagram of an alternative embodiment of the device for measuring the distance to a target at a fixed point of a motor vehicle according to the present invention.
Detailed Description
The present application will now be described in further detail with reference to the accompanying drawings and specific examples. It should be understood that the following illustrative embodiments and description are only intended to explain the present invention, and are not intended to limit the present invention, and features of the embodiments and examples in the present application may be combined with each other without conflict.
As shown in fig. 1, an alternative embodiment of the present invention provides a method for ranging a fixed point target of a motor vehicle, comprising the steps of:
s1: acquiring real-time image frames from original video images shot by the vehicle-mounted camera 1;
s2: detecting obstacles around the motor vehicle from each frame of image frames by adopting a pre-stored target detection model, marking the obstacles which are both present in the two adjacent frame of image frames and are fixed by the obstacles as point targets to be measured, and respectively selecting the point targets to be measured from the two adjacent frame of image frames by adopting target frames with the same size;
s3: respectively calculating the photosurface coordinates of the same position points in the target frames of the two adjacent image frames, which correspond to the photosurfaces of the vehicle-mounted camera 1;
s4: deducing a lens imaging coordinate of the position point of the two adjacent frames corresponding to the lens imaged on the lens of the vehicle-mounted camera 1 according to the photosensitive surface coordinate based on a camera imaging principle and a geometric relationship derivation method; and
s5: and calculating and outputting the current actual distance of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variable quantity P in the frame difference time of the original video image and the lens imaging coordinate.
The embodiment of the invention obtains real-time image frames from an original video image shot by a vehicle-mounted camera 1, marks obstacles which exist in two adjacent image frames and are fixed in the two adjacent image frames as point targets to be measured after detecting the obstacles around the motor vehicle from each image frame, selects the point targets to be measured in the two adjacent image frames by adopting a target frame with a preset standard size, then calculates the coordinates of the same position points in the target frames of the two adjacent image frames corresponding to the light-sensitive surface on the light-sensitive surface of the vehicle-mounted camera, further deduces the lens imaging coordinates imaged on the lens of the vehicle-mounted camera 1 according to the coordinates of the light-sensitive surface, has relatively simpler calculation process, and finally can calculate and output the current actual distance of the point targets to be measured relative to the motor vehicle by combining the wheel speed pulse variation P in the frame difference time of the original video image and the lens imaging coordinates, need not complicated pixel and matches, vehicle-mounted camera 1 need not to adopt the higher binocular camera of cost to realize the range finding in addition compared in the conventional art, and the cost is lower.
In an alternative embodiment of the present invention, as shown in fig. 2, the step S5 specifically includes:
s51: calculating lens imaging coordinates corresponding to a plurality of pairs of different position points in the target frames of the two adjacent image frames;
s52: correspondingly calculating a plurality of current estimated distances of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variation P in the frame difference time of the original video image and each pair of the lens imaging coordinates; and
s53: and outputting the weighted average value of the current estimated distance corresponding to each pair of lens imaging coordinates as the current actual distance.
In the embodiment, a current estimated distance is calculated according to each pair of lens imaging coordinates by calculating the lens imaging coordinates corresponding to a plurality of pairs of different position points, and finally, the current actual distance is determined by calculating the weighted average of each current estimated distance, so that the system error can be effectively reduced, and the distance calculation accuracy is improved. In specific implementation, the number of the lens imaging coordinates can be determined by the shooting frame rate of the specific vehicle-mounted camera 1, the running speed of the motor vehicle, and the like.
In an alternative embodiment of the present invention, as shown in FIG. 3, the current estimated distance
Wherein P is the wheel speed pulse variation of the motor vehicle in the frame difference time of the original video image, f is the focal length of the vehicle-mounted camera 1, and X is 2 And X 1 And the horizontal coordinate values are respectively the horizontal coordinate values of a pair of corresponding lens imaging coordinates in the two adjacent image frames. In this embodiment, as shown in fig. 3, since the ordinate of the object imaged on the lens of the vehicle-mounted camera 1 is always constant, point a represents the target point of the vertex to be measured, and is represented by the coordinate O of the photosensitive surface 1 (u 1 ，v 1 ) And O 2 (u 2 ，v 2 ) A pair of lens imaging coordinates B (X) corresponding to the two adjacent image frames can be calculated 1 ，Y 1 ) And C (X) 2 ，Y 1 ) Move and moveThe displacement of the vehicle in the frame difference time is represented by the wheel speed pulse variation in the frame difference time, using triangle ABC and triangle AO in FIG. 3 1 O 2 Similarly, the following equation can be derived:
Z/(Z-f)＝P/|X 2 -X 1 l (equation 1)
From the above, an expression of the current estimated distance Z can be derived.
In an optional embodiment of the present invention, the position point is a coordinate point on a bottom side of the target frame. In this embodiment, the coordinate point on the bottom side of the target frame is used as the position point to perform coordinate calculation, which facilitates the extraction and calculation of the coordinate. In specific implementation, the OPENCV function is adopted to extract the coordinates of the photosensitive surface.
In an optional embodiment of the present invention, the target detection model is an SSD algorithm model based on deep learning. In the embodiment, the SSD algorithm model based on deep learning is adopted, and a large amount of learning and training are performed in advance, so that the target frame of the point target to be detected can be quickly and accurately detected in the actual application process.
In an optional embodiment of the present invention, the acquiring the real-time image frame from the original video image captured by the vehicle-mounted camera 1 specifically refers to acquiring the real-time image frame from the original video image captured by the vehicle-mounted monocular camera. In this embodiment, the vehicle-mounted camera 1 is a monocular camera, which is relatively low in cost and can effectively detect the distance of a fixed-point target.
On the other hand, as shown in fig. 4, an embodiment of the present invention further provides a vehicle fixed point target distance measuring device 3, which is respectively connected to an on-board camera 1 for capturing a video image of the surroundings of the vehicle and providing an original video image, and an information display device 5 for displaying the current actual distance output by the vehicle fixed point target distance measuring device 3, wherein the vehicle fixed point target distance measuring device 3 comprises a processor 30, a memory 32, and a computer program stored in the memory 32 and configured to be executed by the processor, and when the processor 30 executes the computer program, the vehicle fixed point target distance measuring method as described in any one of the above items is implemented.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory 42 and executed by the processor to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program in the reticle repair control. For example, the computer program may be divided into functional modules in the vehicle fixed point target ranging apparatus 3 shown in fig. 5, wherein the image frame extraction module 41, the target frame extraction module 42, the light sensing plane coordinate calculation module 43, the lens imaging coordinate derivation module 44, and the distance calculation module 45 respectively perform the above steps S1-S5.
The motor vehicle fixed point target distance measuring device 3 can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The vehicle fixed point target ranging device 3 may include, but is not limited to, a processor 30, a memory 32. It will be understood by those skilled in the art that the schematic diagram is merely an example of the vehicle pointing target ranging device 3 and does not constitute a limitation of the vehicle pointing target ranging device 3, and may include more or less components than those shown, or some components in combination, or different components, for example: the motor vehicle fixed point target distance measuring device 3 may further include an input/output device, a network access device, a bus, and the like.
The Processor 30 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor, etc., and the processor 30 is a control center of the vehicle fixed point target distance measuring device 3, and various interfaces and lines are used to connect various parts of the whole vehicle fixed point target distance measuring device 3.
The memory 32 can be used to store the computer program and/or module, and the processor 30 implements various functions of the vehicle fixed-point target distance measuring device 3 by running or executing the computer program and/or module stored in the memory 32 and calling the data stored in the memory 32. The memory 32 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function (such as a pattern recognition function, a pattern stacking function, etc.), and the like; the storage data area may store data (such as graphic data, etc.) created according to the use of the ranging apparatus, etc. Further, the memory 32 may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The functions described in the embodiments of the present invention may be stored in a storage medium readable by a computing device if they are implemented in the form of software functional modules or units and sold or used as independent products. Based on such understanding, all or part of the flow in the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by the processor 30, the steps of the above-described method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer-readable medium may contain suitable additions or subtractions depending on the requirements of legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable media may not include electrical carrier signals or telecommunication signals in accordance with legislation and patent practice.
In another aspect, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, and when the computer program runs, a device on which the computer-readable storage medium is located is controlled to perform the method for ranging a fixed point target of a motor vehicle according to any one of the above described methods.
In the present specification, the embodiments are described in a progressive manner, and each embodiment focuses on differences from other embodiments, and the same or similar parts between the embodiments are referred to each other.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A method for ranging a fixed point target of a motor vehicle, comprising the steps of:
acquiring real-time image frames from original video images shot by a vehicle-mounted camera;
detecting obstacles around the motor vehicle from the image frames frame by adopting a pre-stored target detection model starting from a first frame, marking the obstacles which are present in the two adjacent image frames and are fixed per se as point targets to be measured, and selecting the point targets to be measured in the two adjacent image frames by adopting a target frame with a predetermined standard size;
respectively calculating the photosurface coordinates of the same position points in the target frames of the two adjacent image frames, which correspond to the photosurfaces of the vehicle-mounted cameras;
deducing the position points of the two adjacent frames of image frames according to the photosensitive surface coordinates based on a camera imaging principle and a geometric relationship derivation method, wherein the position points correspond to lens imaging coordinates imaged on a lens of the vehicle-mounted camera; and
and calculating and outputting the current actual distance of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variable quantity P in the frame difference time of the original video image and the lens imaging coordinate.
2. The method as claimed in claim 1, wherein the step of calculating and outputting the current actual distance of the target to be measured from the vehicle by combining the wheel speed pulse variation P within the frame difference time of the original video image and the lens imaging coordinates comprises:
calculating lens imaging coordinates corresponding to a plurality of pairs of different position points in the target frames of the two adjacent image frames;
correspondingly calculating a plurality of current estimated distances Z of the point target to be measured relative to the motor vehicle by combining the wheel speed pulse variable quantity P in the frame difference time of the original video image and each pair of the lens imaging coordinates; and
and outputting the weighted average value of the current estimated distance Z corresponding to each pair of lens imaging coordinates as the current actual distance.
3. The method of claim 2, wherein the current estimated distance is a distance between the target and the vehicle
Wherein P is the wheel speed pulse variation of the motor vehicle in the frame difference time of the original video image, f is the focal length of the vehicle-mounted camera, and X 2 And X 1 The horizontal seats of a pair of lens imaging coordinates corresponding to two adjacent image frames respectivelyAnd (5) carrying out value marking.
4. The method of claim 1, wherein the location point is a coordinate point on a bottom side of the target frame.
5. The method of claim 1, wherein the object detection model is a deep learning based SSD algorithm model.
6. The method as claimed in any one of claims 1 to 5, wherein the step of obtaining real-time image frames from the original video images captured by the vehicle-mounted camera is to obtain real-time image frames from the original video images captured by the vehicle-mounted monocular camera.
7. A motor vehicle fixed-point target ranging device, which is respectively connected to an on-board camera for capturing video images of the surroundings of a motor vehicle and providing original video images, and an information display device for displaying the current actual distance output by the motor vehicle fixed-point target ranging device, wherein the motor vehicle fixed-point target ranging device comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the motor vehicle fixed-point target ranging method according to any one of claims 1 to 6 when executing the computer program.
8. A computer-readable storage medium, comprising a stored computer program, wherein the computer program, when executed, controls an apparatus on which the computer-readable storage medium is located to perform the method of ranging a fixed-point object of a vehicle according to any one of claims 1 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115527199A (en) * | 2022-10-31 | 2022-12-27 | 通号万全信号设备有限公司 | Rail transit train positioning method, device, medium and electronic equipment |
| CN116863124A (en) * | 2023-09-04 | 2023-10-10 | 所托(山东)大数据服务有限责任公司 | Vehicle attitude determination method, controller and storage medium |
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2022
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115527199A (en) * | 2022-10-31 | 2022-12-27 | 通号万全信号设备有限公司 | Rail transit train positioning method, device, medium and electronic equipment |
| CN115527199B (en) * | 2022-10-31 | 2023-05-12 | 通号万全信号设备有限公司 | Rail transit train positioning method, device, medium and electronic equipment |
| CN116863124A (en) * | 2023-09-04 | 2023-10-10 | 所托(山东)大数据服务有限责任公司 | Vehicle attitude determination method, controller and storage medium |
| CN116863124B (en) * | 2023-09-04 | 2023-11-21 | 所托(山东)大数据服务有限责任公司 | Vehicle attitude determination method, controller and storage medium |
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