CN113569698B - Vehicle monitoring method, vehicle and computer readable storage medium - Google Patents
Vehicle monitoring method, vehicle and computer readable storage medium Download PDFInfo
- Publication number
- CN113569698B CN113569698B CN202110833635.XA CN202110833635A CN113569698B CN 113569698 B CN113569698 B CN 113569698B CN 202110833635 A CN202110833635 A CN 202110833635A CN 113569698 B CN113569698 B CN 113569698B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- obstacle
- scratch
- information
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000012544 monitoring process Methods 0.000 title claims abstract description 47
- 238000004590 computer program Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 description 18
- 238000004891 communication Methods 0.000 description 5
- 238000011156 evaluation Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 241001465754 Metazoa Species 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000005654 stationary process Effects 0.000 description 2
- 239000004575 stone Substances 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 238000010171 animal model Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000003973 paint Substances 0.000 description 1
- 238000006748 scratching Methods 0.000 description 1
- 230000002393 scratching effect Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- General Health & Medical Sciences (AREA)
- Entrepreneurship & Innovation (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Molecular Biology (AREA)
- Evolutionary Computation (AREA)
- Economics (AREA)
- Data Mining & Analysis (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a vehicle monitoring method, a vehicle and a storage medium, wherein the method comprises the following steps: acquiring the real-time speed of the vehicle, and determining the running state of the vehicle according to the real-time speed of the vehicle; if the vehicle running state is stationary, acquiring vehicle position information and picture information in a first preset range around the vehicle, and detecting whether an obstacle exists in the first preset range around the vehicle according to the vehicle position information and the picture information; if so, acquiring the type of the obstacle and a first interval distance between the obstacle and the vehicle according to the picture information, and judging whether the vehicle is in scratch risk or not according to the type of the obstacle and the interval distance; if the vehicle is at scratch risk, acquiring video information containing the vehicle body condition and generating early warning information, and sending the video information and the early warning information to a preset user terminal. The invention improves the user experience.
Description
Technical Field
The present invention relates to the field of vehicles, and more particularly, to a vehicle monitoring method, a vehicle, and a computer-readable storage medium.
Background
With the expansion of urban range and the improvement of living standard of people, automobiles enter common families and become main vehicles in cities.
When the vehicle is stopped at the roadside and the vehicle owner is not nearby, after the vehicle is scratched, the situation at the time can be recorded only through surrounding monitoring cameras, and the passing of the accident is known. However, not every place is monitored, and the monitoring camera has a blind area. Meanwhile, surrounding monitoring cameras cannot evaluate scratch risks of vehicles stopped at roadsides, and if scratch accidents occur, an owner can only bear economic losses. Therefore, how to effectively reduce the scratch accident between the vehicle and the obstacle, and how to record the scratch process when the scratch accident occurs become the problem to be improved.
Disclosure of Invention
The invention mainly aims to provide a vehicle monitoring method, a vehicle and a computer readable storage medium, and aims to solve the problem that scratch accidents cannot be reduced by the existing monitoring technology.
In order to achieve the above object, the present invention provides a vehicle monitoring method, comprising the steps of:
acquiring the real-time speed of the vehicle, and determining the running state of the vehicle according to the real-time speed of the vehicle;
if the vehicle running state is stationary, acquiring vehicle position information and picture information in a first preset range around the vehicle, and detecting whether an obstacle exists in the first preset range around the vehicle according to the vehicle position information and the picture information;
if so, acquiring the type of the obstacle and a first interval distance between the obstacle and the vehicle according to the picture information, and judging whether the vehicle is in scratch risk or not according to the type of the obstacle and the interval distance;
if the vehicle is at scratch risk, acquiring video information containing the vehicle body condition and generating early warning information, and sending the video information and the early warning information to a preset user terminal.
Optionally, the step of acquiring the type of the obstacle and the first interval distance between the obstacle and the vehicle according to the picture information, and judging whether the vehicle has a scratch risk according to the type of the obstacle and the interval distance includes:
acquiring a first interval distance between an obstacle and the vehicle, and judging whether the distance between the obstacle and the vehicle is smaller than a preset first safety distance;
if yes, determining the type of the obstacle according to a preset identification model and the picture information in the first preset range;
if the type of the obstacle is an obstacle vehicle, acquiring position information of the obstacle vehicle, and judging whether the obstacle vehicle is positioned at the side of the vehicle;
if the obstacle vehicle is positioned at the side edge of the vehicle, determining the width of the door of the obstacle vehicle according to the picture information in the first preset range;
judging whether the width is greater than a first spacing distance between an obstacle and the vehicle;
and if the width is larger than the first interval distance between the obstacle and the vehicle, judging that scratch risks exist.
Optionally, the step of determining whether the obstacle vehicle is located on the side of the vehicle includes:
if the obstacle vehicle is not positioned at the side of the vehicle, judging whether a first interval distance between the obstacle and the vehicle is smaller than a second preset safety distance;
if the interval distance is smaller than the second preset safety distance, judging that scratch risks exist, and the first preset safety distance is larger than the second preset safety distance.
Optionally, the step of determining the type of the obstacle according to the preset recognition model and the picture information within the first preset range includes:
if the type of the obstacle is other types, acquiring the moving direction of the obstacle and monitoring the interval distance between the obstacle and the vehicle in real time;
if the moving direction of the obstacle is close to the vehicle and the interval distance between the obstacle and the vehicle is smaller than the second preset safety distance, judging that the vehicle is in scratch risk.
Optionally, the step of acquiring the real-time speed of the vehicle and determining the running state of the vehicle according to the real-time speed of the vehicle includes:
if the running state of the vehicle is running, acquiring the position of the obstacle and the real-time position of the vehicle in a second preset range around the vehicle;
calculating a second interval distance between the vehicle and the obstacle according to the obstacle position and the real-time position of the vehicle in a second preset range, and judging whether the second interval distance is smaller than a third preset safety distance or not;
if yes, generating early warning information to remind the driver.
Optionally, if the vehicle has a scratch risk, the step of acquiring video information including the vehicle body condition and generating the early warning information includes:
if the vehicle is in scratch risk, acquiring video information comprising the vehicle body condition and sending out an early warning signal;
detecting whether the scratch risk disappears or not in real time according to the early warning signal;
if the scratch risk of the vehicle disappears, acquiring video information including the vehicle body condition within a preset time period after the scratch risk disappears;
if the risk of scratch of the vehicle does not disappear, executing the steps of: and detecting whether the scratch risk disappears.
Optionally, if the vehicle has a scratch risk, acquiring video information including a vehicle body condition and generating early warning information, where the step of sending the video information and the early warning information to a preset user terminal includes:
judging whether the vehicle is scratched or not according to the video information;
if yes, acquiring scratch information of a vehicle scratch position, and judging a scratch grade according to the scratch information;
searching a preset scratch solution corresponding to the scratch grade according to the scratch grade, and sending the preset scratch solution to the user terminal.
Optionally, if the vehicle has a scratch risk, acquiring video information including a vehicle body condition and generating early warning information, where the step of sending the video information and the early warning information to a preset user terminal further includes:
and sending the video information to a cloud server, so that the cloud server generates early warning information according to the video information and sends the early warning information to a user terminal.
To achieve the above object, the present invention also provides a vehicle comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the vehicle monitoring method as described above.
To achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the vehicle monitoring method as described above.
According to the vehicle monitoring method, the vehicle and the computer readable storage medium, the real-time speed of the vehicle is obtained, and the running state of the vehicle is determined according to the real-time speed of the vehicle, so that the running state of the vehicle is judged, the scratch risk in the process of the vehicle being stationary or running is further evaluated, and the accuracy of the scratch risk evaluation is improved; detecting whether an obstacle exists in a first preset range around the vehicle according to the vehicle position information and the picture information, so that the detection of the obstacle in the first preset range around the vehicle in a stationary process, namely, when the vehicle is in a parking state, is realized, the vehicle is conveniently monitored according to the obstacle, and the monitoring is more comprehensive; according to the picture information, the type of the obstacle and the first interval distance between the obstacle and the vehicle are obtained, whether the vehicle has scratch risks or not is judged according to the type of the obstacle and the interval distance, analysis and determination of the obstacle in the parking process of the vehicle are realized, whether the vehicle has scratch risks or not is evaluated according to an analysis result, and accuracy of evaluation of the external obstacle and the scratch risks of the vehicle is improved; the video information containing the car body condition is obtained, and the video information and the early warning information are sent to the preset user terminal, so that a car owner can further process according to the video information and the early warning information, the occurrence of a car scratch accident is avoided, and the economic loss of the car owner is reduced.
Drawings
FIG. 1 is a schematic diagram of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of a vehicle monitoring method according to the present invention;
FIG. 3 is a flow chart of a second embodiment of the vehicle monitoring method of the present invention;
FIG. 4 is a flow chart of a fourth embodiment of the vehicle monitoring method of the present invention;
FIG. 5 is a flowchart of a fifth embodiment of a vehicle monitoring method according to the present invention;
FIG. 6 is a flowchart of a sixth embodiment of a vehicle monitoring method according to the present invention;
fig. 7 is a flowchart of a seventh embodiment of the vehicle monitoring method according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic diagram of a hardware structure of a vehicle according to various embodiments of the present invention. The vehicle comprises a communication module 01, a memory 02, a processor 03 and the like. Those skilled in the art will appreciate that the vehicle illustrated in FIG. 1 may also include more or fewer components than shown, or may combine certain components, or a different arrangement of components. The processor 03 is connected to the memory 02 and the communication module 01, respectively, and a computer program is stored in the memory 02 and executed by the processor 03 at the same time.
The communication module 01 is connectable to an external device via a network. The communication module 01 can receive data sent by external equipment, and can also send data, instructions and information to the external equipment, wherein the external equipment can be electronic equipment such as a mobile phone, a tablet personal computer, a notebook computer, a desktop computer and the like.
The memory 02 is used for storing software programs and various data. The memory 02 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data or information created according to the use of the vehicle, or the like. In addition, memory 02 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device.
The processor 03, which is a control center of the vehicle, connects various parts of the entire vehicle using various interfaces and lines, performs various functions of the vehicle and processes data by running or executing software programs and/or modules stored in the memory 02, and calling data stored in the memory 02, thereby performing overall monitoring of the vehicle. The processor 03 may include one or more processing units; preferably, the processor 03 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, an application program, etc., and the modem processor mainly processes wireless communication. It will be appreciated that the modem processor described above may not be integrated into the processor 03.
Those skilled in the art will appreciate that the vehicle structure shown in FIG. 1 is not limiting of the vehicle and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
According to the above hardware structure, various embodiments of the method of the present invention are presented.
Referring to fig. 2, in a first embodiment of the vehicle monitoring method of the present invention, the vehicle monitoring method includes the steps of:
step S10, acquiring the real-time speed of the vehicle, and determining the running state of the vehicle according to the real-time speed of the vehicle;
the running state of the vehicle comprises a static state and a running state, and when the real-time speed of the vehicle is 0, the running state of the vehicle is judged to be static; if the real-time speed of the vehicle is not 0, judging that the running state of the vehicle is running; in addition, since the vehicle may have a speed of 0 during driving, for example, when waiting for a traffic light, whether the vehicle is in a driving state or a stationary state may be determined by determining whether the duration of the real-time speed of 0 is greater than a preset time, and if the duration of the real-time speed of 0 is greater than the preset time, the driving state of the vehicle is determined to be stationary; and if the duration time of the real-time speed of the vehicle being 0 is smaller than the preset time, judging that the running state of the vehicle is running. The real-time position information of the vehicle can be further combined to judge the running state of the vehicle, namely if the real-time position information of the vehicle does not change within the preset time, the vehicle can be judged to be in a stationary state, otherwise, the running state is judged to be running;
step S20, if the vehicle running state is stationary, acquiring vehicle position information and picture information in a first preset range around the vehicle, and detecting whether an obstacle exists in the first preset range around the vehicle according to the vehicle position information and the picture information;
in this embodiment, the first preset range is a range with a vehicle as a center and a radius of 10 meters, where the radius may also be 15 meters, 20 meters or 30 meters, and a person skilled in the art may set different radii according to actual needs, so as to achieve acquisition of picture information in the first preset range; the picture information includes a picture of an obstacle within a first preset range and a first separation distance between a vehicle obstacle and the vehicle. The picture information can be obtained according to a surrounding camera arranged on the vehicle body or a common camera arranged around the vehicle body; in addition, the obstacle in the first preset range can be obtained according to radar monitoring installed on the vehicle.
In another embodiment, after the radar installed on the vehicle body acquires that the obstacle exists in the first preset range, the camera installed on the vehicle body can be triggered to work, so that the obstacle in the first preset range is acquired.
In the embodiment, the radar is used for triggering the camera to work, so that the vehicle monitoring range can be controlled, the opening of the camera can be flexibly controlled, and the electricity consumption is reduced.
If yes, executing step S30, obtaining the type of the obstacle and the first interval distance between the obstacle and the vehicle according to the picture information, and judging whether the vehicle has scratch risk according to the type of the obstacle and the interval distance;
the types of obstacles may be classified into obstacle vehicles, i.e., the obstacles are other vehicles and other obstacle types, such as: animals, humans, stones, etc.;
step S40, if the vehicle is at risk of scratch, acquiring video information containing the vehicle body condition and generating early warning information, wherein the video information and the early warning information are sent to a preset user terminal;
the video information comprises real-time vehicle body video information and video information with the vehicle position as the center and the preset radius within 2 meters, wherein the preset radius can be 2.5 meters, 3 meters, 3.5 meters and the like, and a person skilled in the art can set different preset radii according to actual needs so as to realize the generation of the video information; the early warning information is a prompt for early warning the vehicle owner; the preset user terminal can be electronic equipment or vehicle-mounted equipment with wireless transmission functions, such as a mobile phone, a tablet and the like, which are preset by a user.
According to the vehicle monitoring method, the real-time speed of the vehicle is obtained, the running state of the vehicle is determined according to the real-time speed of the vehicle, the running state of the vehicle is judged, the scratch risk in the process of the vehicle being stationary or running is further evaluated, and the accuracy of the scratch risk evaluation is improved; detecting whether an obstacle exists in a first preset range around the vehicle according to the vehicle position information and the picture information, so that the detection of the obstacle in the first preset range around the vehicle in a stationary process, namely, when the vehicle is in a parking state, is realized, the vehicle is conveniently monitored according to the obstacle, and the monitoring is more comprehensive; according to the picture information, the type of the obstacle and the first interval distance between the obstacle and the vehicle are obtained, whether the vehicle has scratch risks or not is judged according to the type of the obstacle and the interval distance, analysis and determination of the obstacle in the parking process of the vehicle are realized, whether the vehicle has scratch risks or not is evaluated according to an analysis result, and accuracy of evaluation of the external obstacle and the scratch risks of the vehicle is improved; the video information containing the car body condition is obtained, and the video information and the early warning information are sent to the preset user terminal, so that a car owner can further process according to the video information and the early warning information, the occurrence of a car scratch accident is avoided, and the economic loss of the car owner is reduced.
Further, referring to fig. 3, in the vehicle monitoring method according to the present invention according to the first embodiment of the present invention, the present invention proposes a second embodiment, and the step S30 includes:
step S31, obtaining a first interval distance between an obstacle and the vehicle, and judging whether the distance between the obstacle and the vehicle is smaller than a preset first safety distance;
the first interval distance between the obstacle and the vehicle can be calculated according to the position between the vehicle and the obstacle, and can also be calculated according to the radar installed on the vehicle; the first preset safety distance may be 0.5 meter, 0.6 meter, 0.7 meter or 0.8 meter, etc., and a person skilled in the art may set different first preset safety distances according to actual requirements, so as to realize the judgment of the type of the obstacle.
Step S32, if yes, determining the type of the obstacle according to a preset identification model and the picture information in the first preset range;
the preset recognition model specifically comprises a neural network recognition model which is trained and completed such as a vehicle model, an animal model and a human body model, and the type of the obstacle can be output when the picture information is input into the preset recognition model.
Step S33, if the type of the obstacle is an obstacle vehicle, acquiring position information of the obstacle vehicle, and judging whether the obstacle vehicle is positioned at the side of the vehicle;
the sides of the vehicle, i.e. the right side of the vehicle and the left side of the vehicle, or are located parallel to the left and right rear sides of the vehicle.
Step S34, if the obstacle vehicle is positioned at the side edge of the vehicle, determining the width of the door of the obstacle vehicle according to the picture information in the first preset range;
in addition, after the obstacle vehicle is judged to be positioned at the side edge of the vehicle, the brand and the model of the obstacle vehicle can be searched through the Internet or a preset database according to the picture information in the first preset range, and the door width of the obstacle vehicle is acquired according to the brand and the model of the obstacle vehicle, so that the acquired door width is more accurate;
step S35, judging whether the width is larger than a first interval distance between an obstacle and the vehicle;
step S36, judging that scratch risks exist if the width is larger than a first interval distance between the obstacle and the vehicle;
when the width is larger than the first interval distance between the barrier and the vehicle, namely, the width of the vehicle door can cause scratch risk to the vehicle when the vehicle door is opened, namely, the vehicle is judged to have scratch risk.
In this embodiment, by acquiring a first interval distance between the obstacle and the vehicle, determining whether the distance between the obstacle and the vehicle is smaller than a preset first safety distance, if yes, determining the type of the obstacle according to a preset recognition model and picture information in the first preset range, so that the vehicle can determine the obstacle in the safety distance, and the accuracy of determination is improved; if the type of the obstacle is judged to be an obstacle vehicle, acquiring position information of the obstacle vehicle, judging whether the obstacle vehicle is positioned at the side edge of the vehicle, and preventing the obstacle vehicle from rubbing the vehicle when the obstacle vehicle runs at the side edge of the vehicle; through if the obstacle vehicle is located the side of vehicle, confirm the width of obstacle vehicle door according to the picture information according to first default scope to judge whether the width is greater than the obstacle with first interval distance between the vehicle, prevent that the obstacle vehicle door from being greater than the obstacle with the first interval distance between the vehicle causes the obstacle vehicle door to cut and scratch the vehicle when opening the door operation at the side of vehicle, further improved the security of vehicle in the parking process, reduced car owner economic loss.
Further, in the vehicle monitoring method according to the present invention according to the first embodiment of the present invention, the present invention provides a third embodiment, and after the step S33, the method further includes:
if the obstacle vehicle is not positioned at the side of the vehicle, judging whether a first interval distance between the obstacle and the vehicle is smaller than a second preset safety distance;
if the interval distance is smaller than the second preset safety distance, judging that scratch risks exist, and the first preset safety distance is larger than the second preset safety distance.
The second preset safety distance can be 0.4 meter, 0.5 meter or 0.6 meter, and a person skilled in the art can set different second preset safety distances according to actual requirements so as to judge scratch risks when an obstacle vehicle is not positioned at the side of the vehicle;
in this embodiment, the obstacle vehicle may be located at the rear side of the vehicle or at the front side of the vehicle or other positions except the side of the vehicle, and by determining whether the first distance between the obstacle and the vehicle is smaller than the second preset safety distance and determining the scratch risk, it is possible to prevent other obstacle vehicles from scratching the vehicle when starting or executing other operations.
Further, referring to fig. 4, in the vehicle monitoring method according to the present invention according to the first embodiment of the present invention, the present invention proposes a fourth embodiment, and after the step S33, the method further includes:
step S321, if the type of the obstacle is other, acquiring the moving direction of the obstacle and monitoring the interval distance between the obstacle and the vehicle in real time;
in step S322, if the moving direction of the obstacle is close to the vehicle and the distance between the obstacle and the vehicle is smaller than the second preset safety distance, it is determined that the vehicle is at risk of scratch.
When the obstacle is of another type, the other type may include a movable object including a person, an animal, and the like, and an immovable object including a stone, a building, a sign, and the like; when the type of the obstacle is a movable object, the position information of the obstacle can be obtained according to a radar installed on a vehicle body, when the moving direction of the object is judged to be close to the vehicle and the distance between the obstacle and the vehicle is smaller than the second safety distance, an imaging device installed on the vehicle can be triggered by the radar to carry out video shooting, and the vehicle is judged to have scratch risk;
in this embodiment, by judging the type of the obstacle, acquiring the moving direction of the obstacle, monitoring the safety distance between the obstacle and the vehicle in real time, and judging that the moving direction of the obstacle is close to the vehicle and the spacing distance between the obstacles is smaller than the second preset safety distance, the scratch risk judgment when the obstacle is a non-vehicle is realized, so that the scratch risk judgment is more accurate, and meanwhile, the vehicle can be prevented from being deliberately scratched, and the economic loss of the vehicle owner is reduced.
Further, referring to fig. 5, in the vehicle monitoring method according to the present invention according to the first embodiment of the present invention, the present invention proposes a fifth embodiment, and after the step S10, the method further includes:
step S101, if the running state of the vehicle is running, acquiring the position of the obstacle and the real-time position of the vehicle in a second preset range around the vehicle;
when the vehicle is in a running state, the second preset range is a circle with the vehicle as a center and with a radius of 2.5 meters, the radius can be 2.75 meters, 3 meters, 3.25 meters and the like, and a person skilled in the art can set the second preset ranges with different sizes according to actual needs so as to realize scratch early warning of the vehicle in the running process. The obstacle position and the real-time vehicle position within the second preset range can be obtained through a radar or a positioning tool arranged on the vehicle.
Step S102, calculating a second interval distance between the vehicle and the obstacle according to the obstacle position and the real-time vehicle position in a second preset range, and judging whether the second interval distance is smaller than a third preset safety distance;
the third preset safety distance can be specifically 2 meters, 2.5 meters or 3 meters, and a person skilled in the art can set different third preset safety distances according to actual needs so as to realize scratch early warning of the vehicle in the running process.
Step S103, if yes, generating early warning information to remind a driver;
if not, not processing;
in this embodiment, the vehicle is driven by judging the driving state of the vehicle, acquiring the position of the obstacle and the real-time position of the vehicle in the second preset range around the vehicle, and calculating to obtain the second interval distance between the vehicle and the obstacle, and generating the early warning information to remind the driver when the second interval distance is smaller than the third preset safety distance, so as to avoid the scratch accident caused by too close to the obstacle in the driving process of the vehicle, reduce the occurrence of the scratch accident, and improve the driving safety.
Further, referring to fig. 6, in the vehicle monitoring method according to the present invention according to the first embodiment of the present invention, a sixth embodiment of the present invention is provided, and the step S40 further includes:
step S41, if the vehicle is at risk of scratch, acquiring video information comprising the vehicle body condition and sending out an early warning signal;
the video information can be acquired through a camera device arranged on the vehicle body; the early warning signals can comprise early warning information sent to a vehicle owner, acousto-optic and electric signals sent by the vehicle.
Step S42, monitoring whether the scratch risk disappears or not in real time according to the early warning signal;
step S43, if the risk of scratch of the vehicle disappears, acquiring video information including the condition of the vehicle body within a preset time period after the risk of scratch of the vehicle disappears;
in this embodiment, the preset duration may be 30s, or may be 40s, 50s, or 60s, etc., and those skilled in the art may set different preset durations according to actual situations, so as to implement the vehicle monitoring method.
Step S44, if the risk of vehicle scratch is not disappeared, executing the steps of: s42, performing S42;
if the risk of vehicle scratch is not disappeared, continuously collecting video information containing the vehicle body condition until the risk of vehicle scratch is disappeared.
In the embodiment, by collecting video information including the vehicle body condition and sending out warning information, the specific condition of the vehicle body when the vehicle is scratched can be recorded, and meanwhile, warning can be provided for surrounding vehicles or other obstacles through the warning information to prevent scratch accidents; through detecting whether scratch risk disappears to gather the video information including automobile body situation in the preset duration after scratch risk disappears, can fully guarantee to record the situation information of automobile body under the existence scratch risk of vehicle, under the circumstances that the vehicle takes place to scratch, remain the evidence of scratch, effectively reduce the economic loss of car owner.
Further, referring to fig. 7, in the vehicle monitoring method according to the present invention according to the first embodiment of the present invention, the present invention proposes a seventh embodiment, and after the step S40, the method further includes:
step S401, judging whether a scratch occurs on the vehicle according to the video information;
step S402, if yes, acquiring scratch information of a vehicle scratch position, and judging a scratch grade according to the scratch information;
in this embodiment, detailed scratch information of the scratch position may be obtained according to the video information, and matching is performed according to the detailed scratch information and a preset scratch level built in the vehicle, and the scratch level is determined. For example, if the scratch information is a scratch, judging that the scratch grade is 1 grade; if the scratch grade is paint dropping, judging the grade to be grade 2; and by analogy, the more serious the scratch is, the higher the scratch grade is.
Step S403, searching a preset scratch solution corresponding to the scratch grade according to the scratch grade, and sending the preset scratch solution to the user terminal.
In this embodiment, if a vehicle is scratched, the scratch grade is determined according to scratch information of the scratch position of the vehicle, and a corresponding preset scratch solution is found according to the scratch grade, so that a user can be helped to know the scratch information at the first time, a solution is generated, and user experience is improved.
Further, in the vehicle monitoring method according to the present invention according to the first embodiment of the present invention, the present invention provides an eighth embodiment, and the step S40 further includes
And sending the video information to a cloud server, so that the cloud server generates early warning information according to the video information and sends the early warning information to a user terminal.
In this embodiment, the collected video information is sent to the cloud server, and prompt information about scratch risks can be generated to the user terminal according to the video information, so that the user can make corresponding processing according to the video information, scratch behaviors are prevented, and economic losses of the user are avoided.
The present invention also proposes a computer-readable storage medium on which a computer program is stored. The computer readable storage medium may be the Memory 02 in the vehicle of fig. 1, or may be at least one of ROM (Read-Only Memory)/RAM (Random Access Memory ), magnetic disk, optical disk, etc., and the computer readable storage medium includes a plurality of information for causing the vehicle to perform the method according to the embodiments of the present invention.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (7)
1. A vehicle monitoring method, characterized by comprising:
acquiring the real-time speed of the vehicle, and determining the running state of the vehicle according to the real-time speed of the vehicle;
if the vehicle running state is stationary, acquiring vehicle position information and picture information in a first preset range around the vehicle, and detecting whether an obstacle exists in the first preset range around the vehicle according to the vehicle position information and the picture information;
if so, acquiring the type of the obstacle and a first interval distance between the obstacle and the vehicle according to the picture information, and judging whether the vehicle is in scratch risk or not according to the type of the obstacle and the interval distance;
if the vehicle is in scratch risk, acquiring video information containing the vehicle body condition, generating early warning information, and transmitting the video information and the early warning information to a preset user terminal;
the step of obtaining the type of the obstacle and the first interval distance between the obstacle and the vehicle according to the picture information, and judging whether the vehicle has scratch risk according to the type of the obstacle and the interval distance comprises the following steps:
acquiring a first interval distance between an obstacle and the vehicle, and judging whether the distance between the obstacle and the vehicle is smaller than a preset first safety distance;
if yes, determining the type of the obstacle according to a preset identification model and the picture information in the first preset range;
if the type of the obstacle is an obstacle vehicle, acquiring position information of the obstacle vehicle, and judging whether the obstacle vehicle is positioned at the side of the vehicle;
if the obstacle vehicle is positioned at the side edge of the vehicle, determining the width of the door of the obstacle vehicle according to the picture information in the first preset range;
judging whether the width is greater than a first spacing distance between an obstacle and the vehicle;
if the width is larger than a first interval distance between the obstacle and the vehicle, judging that scratch risks exist;
if the obstacle vehicle is not positioned at the side of the vehicle, judging whether a first interval distance between the obstacle and the vehicle is smaller than a second preset safety distance;
if the interval distance is smaller than the second preset safety distance, judging that scratch risks exist, wherein the first preset safety distance is larger than the second preset safety distance;
the step of determining the type of the obstacle according to the preset recognition model and the picture information in the first preset range comprises the following steps:
if the type of the obstacle is other types, acquiring the moving direction of the obstacle and monitoring the interval distance between the obstacle and the vehicle in real time;
if the moving direction of the obstacle is close to the vehicle and the interval distance between the obstacle and the vehicle is smaller than the second preset safety distance, judging that the vehicle is in scratch risk.
2. The vehicle monitoring method according to claim 1, wherein the step of acquiring the real-time speed of the vehicle and determining the running state of the vehicle based on the real-time speed of the vehicle comprises:
if the running state of the vehicle is running, acquiring the position of the obstacle and the real-time position of the vehicle in a second preset range around the vehicle;
calculating a second interval distance between the vehicle and the obstacle according to the obstacle position and the real-time position of the vehicle in a second preset range, and judging whether the second interval distance is smaller than a third preset safety distance or not;
if yes, generating early warning information to remind the driver.
3. The vehicle monitoring method according to claim 1, wherein the step of acquiring video information including a vehicle body condition and generating early warning information if there is a risk of scratch of the vehicle includes:
if the vehicle is in scratch risk, acquiring video information comprising the vehicle body condition and sending out an early warning signal;
detecting whether the scratch risk disappears or not in real time according to the early warning signal;
if the scratch risk of the vehicle disappears, acquiring video information including the vehicle body condition within a preset time period after the scratch risk disappears;
if the risk of scratch of the vehicle does not disappear, executing the steps of: and detecting whether the scratch risk disappears.
4. The vehicle monitoring method according to claim 1, wherein if there is a scratch risk, the step of acquiring video information including a vehicle body condition and generating early warning information, and the step of transmitting the video information and the early warning information to a preset user terminal includes:
judging whether the vehicle is scratched or not according to the video information;
if yes, acquiring scratch information of a vehicle scratch position, and judging a scratch grade according to the scratch information;
searching a preset scratch solution corresponding to the scratch grade according to the scratch grade, and sending the preset scratch solution to the user terminal.
5. The method for monitoring a vehicle according to claim 4, wherein if there is a scratch risk, the step of acquiring video information including a vehicle body condition and generating early warning information, and the step of transmitting the video information and the early warning information to a preset user terminal further includes:
and sending the video information to a cloud server, so that the cloud server generates early warning information according to the video information and sends the early warning information to a user terminal.
6. A vehicle comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the vehicle monitoring method according to any one of claims 1 to 5.
7. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the vehicle monitoring method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110833635.XA CN113569698B (en) | 2021-07-22 | 2021-07-22 | Vehicle monitoring method, vehicle and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110833635.XA CN113569698B (en) | 2021-07-22 | 2021-07-22 | Vehicle monitoring method, vehicle and computer readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113569698A CN113569698A (en) | 2021-10-29 |
| CN113569698B true CN113569698B (en) | 2023-10-27 |
Family
ID=78166532
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110833635.XA Active CN113569698B (en) | 2021-07-22 | 2021-07-22 | Vehicle monitoring method, vehicle and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113569698B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114220275B (en) * | 2022-02-22 | 2022-05-24 | 浙江创泰科技有限公司 | Unattended intelligent parking management system |
| CN115915064A (en) * | 2022-10-09 | 2023-04-04 | 清研智行(北京)科技有限公司 | Vehicle sensing method, device, medium and equipment based on wireless signals |
| CN115798075A (en) * | 2022-10-20 | 2023-03-14 | 广州汽车集团股份有限公司 | Vehicle abnormality detection method, vehicle abnormality detection device, vehicle, and storage medium |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103303194A (en) * | 2012-03-13 | 2013-09-18 | 通用汽车环球科技运作有限责任公司 | Method and system for warning of potential collision of an object with a stationary vehicle door |
| CN106128089A (en) * | 2016-07-01 | 2016-11-16 | 合肥未来计算机技术开发有限公司 | A kind of vehicle accident immediate processing method based on drive recorder |
| CN107452230A (en) * | 2017-07-28 | 2017-12-08 | 明见（厦门）技术有限公司 | A kind of obstacle detection method, device, terminal device and storage medium |
| CN108482248A (en) * | 2018-03-27 | 2018-09-04 | 奇瑞汽车股份有限公司 | Park cars anti-collision reminding method, system, computer readable storage medium |
| KR20190114388A (en) * | 2018-03-30 | 2019-10-10 | 현대자동차주식회사 | Method and apparatus for preventing collisions during parking using ultra wideband radar |
| CN110549940A (en) * | 2019-08-21 | 2019-12-10 | 上海赫千电子科技有限公司 | automobile scratch prevention method and system based on vehicle-mounted Ethernet |
| CN110696714A (en) * | 2019-10-18 | 2020-01-17 | 深圳市元征科技股份有限公司 | Vehicle monitoring method, device and system and electronic equipment |
| CN111754813A (en) * | 2019-03-28 | 2020-10-09 | 上海擎感智能科技有限公司 | Driving assisting method and device |
| CN111923833A (en) * | 2020-07-23 | 2020-11-13 | 长城汽车股份有限公司 | Vehicle door opening early warning method and device, storage medium and vehicle |
| CN112519797A (en) * | 2020-12-10 | 2021-03-19 | 广州小鹏自动驾驶科技有限公司 | Vehicle safety distance early warning method, early warning system, automobile and storage medium |
-
2021
- 2021-07-22 CN CN202110833635.XA patent/CN113569698B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103303194A (en) * | 2012-03-13 | 2013-09-18 | 通用汽车环球科技运作有限责任公司 | Method and system for warning of potential collision of an object with a stationary vehicle door |
| CN106128089A (en) * | 2016-07-01 | 2016-11-16 | 合肥未来计算机技术开发有限公司 | A kind of vehicle accident immediate processing method based on drive recorder |
| CN107452230A (en) * | 2017-07-28 | 2017-12-08 | 明见（厦门）技术有限公司 | A kind of obstacle detection method, device, terminal device and storage medium |
| CN108482248A (en) * | 2018-03-27 | 2018-09-04 | 奇瑞汽车股份有限公司 | Park cars anti-collision reminding method, system, computer readable storage medium |
| KR20190114388A (en) * | 2018-03-30 | 2019-10-10 | 현대자동차주식회사 | Method and apparatus for preventing collisions during parking using ultra wideband radar |
| CN111754813A (en) * | 2019-03-28 | 2020-10-09 | 上海擎感智能科技有限公司 | Driving assisting method and device |
| CN110549940A (en) * | 2019-08-21 | 2019-12-10 | 上海赫千电子科技有限公司 | automobile scratch prevention method and system based on vehicle-mounted Ethernet |
| CN110696714A (en) * | 2019-10-18 | 2020-01-17 | 深圳市元征科技股份有限公司 | Vehicle monitoring method, device and system and electronic equipment |
| CN111923833A (en) * | 2020-07-23 | 2020-11-13 | 长城汽车股份有限公司 | Vehicle door opening early warning method and device, storage medium and vehicle |
| CN112519797A (en) * | 2020-12-10 | 2021-03-19 | 广州小鹏自动驾驶科技有限公司 | Vehicle safety distance early warning method, early warning system, automobile and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113569698A (en) | 2021-10-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113569698B (en) | Vehicle monitoring method, vehicle and computer readable storage medium | |
| CN106710291B (en) | Parking space obtaining method and device for parking lot | |
| CN107608388B (en) | Autonomous police vehicle | |
| CN108806272B (en) | Method and device for reminding multiple motor vehicle owners of illegal parking behaviors | |
| DE102016215931B4 (en) | System and method for retrievably providing and updating classification data on parking spaces | |
| CN109003455B (en) | Method and device for reminding vehicle owner of illegal parking behavior | |
| CN103824037A (en) | Vehicle anti-tracking alarm device | |
| CN108932849B (en) | Method and device for recording low-speed running illegal behaviors of multiple motor vehicles | |
| CN113470371B (en) | Method, system, and computer-readable storage medium for identifying an offending vehicle | |
| JP2020187781A (en) | Information processing apparatus, information processing method, and program | |
| CN114341962A (en) | Dangerous vehicle display system, dangerous vehicle display device, dangerous vehicle display program, computer-readable recording medium, and apparatus having recorded the program | |
| CN111243185A (en) | Charging parking space occupation determination method, device and medium | |
| CN115311894A (en) | Intelligent parking management method, system, terminal and medium based on big data analysis | |
| CN113469115A (en) | Method and apparatus for outputting information | |
| CN106781620B (en) | Violation information system and violation map construction method | |
| CN111209797A (en) | Method, device, equipment and storage medium for monitoring driving behavior | |
| CN113989715A (en) | Vehicle parking violation detection method and device, electronic equipment and storage medium | |
| CN110706115A (en) | Traffic accident fast claims settlement method, system and server | |
| DE102018210852A1 (en) | Procedure for the determination of illegal driving behavior by a vehicle | |
| CN210223044U (en) | Electric warning snapshot system of traffic signal lamp-free zebra crossing | |
| KR20140031443A (en) | System and method for providing traffic accident data | |
| CN114530057B (en) | Vehicle early warning method and device, vehicle and storage medium | |
| CN112308723A (en) | Vehicle detection method and system | |
| CN115861916A (en) | Abnormal parking behavior detection method and device, computer equipment and storage medium | |
| CN115146830A (en) | Method and system for intelligently identifying taxi taking intention of passerby and vehicle thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |