CN114863707A - Vehicle information processing method and device, storage medium and vehicle - Google Patents
Vehicle information processing method and device, storage medium and vehicle Download PDFInfo
- Publication number
- CN114863707A CN114863707A CN202210495790.XA CN202210495790A CN114863707A CN 114863707 A CN114863707 A CN 114863707A CN 202210495790 A CN202210495790 A CN 202210495790A CN 114863707 A CN114863707 A CN 114863707A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- lane line
- information
- image information
- determining
- 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.)
- Pending
Links
- 230000010365 information processing Effects 0.000 title claims abstract description 17
- 238000003672 processing method Methods 0.000 title abstract description 10
- 238000000034 method Methods 0.000 claims abstract description 31
- 238000012545 processing Methods 0.000 claims description 13
- 238000005516 engineering process Methods 0.000 description 6
- 238000012549 training Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000000605 extraction Methods 0.000 description 3
- 239000003086 colorant Substances 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 230000004888 barrier function Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- 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
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/09626—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages where the origin of the information is within the own vehicle, e.g. a local storage device, digital map
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
- G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Atmospheric Sciences (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a vehicle information processing method and device, a storage medium and a vehicle. Wherein, the method comprises the following steps: acquiring image information acquired by a vehicle on a road section; determining the type of the lane line of the road section where the vehicle is located based on the image information; and sending prompt information to the vehicle based on the lane line type and the image information, wherein the prompt information is used for determining the driving strategy data of the vehicle, and the driving strategy data is used for determining the driving strategy of the vehicle. The invention solves the technical problem that the lane line cannot be accurately identified.
Description
Technical Field
The invention relates to the field of vehicles, in particular to a vehicle information processing method, device, storage medium and vehicle.
Background
At present, intelligent driving becomes a popular technical direction in the vehicle industry, but the existing intelligent driving scheme is not perfect in function and performance, so that intelligent driving accidents are frequent. However, it is the reason for frequent driving accidents that the lane lines in different driving scenes cannot be accurately identified.
Aiming at the problem that the related technology can not accurately identify the lane line, an effective solution is not provided at present.
Disclosure of Invention
The embodiment of the invention provides a vehicle information processing method, a vehicle information processing device, a storage medium and a vehicle, and at least solves the technical problem that lane lines cannot be accurately identified.
According to an aspect of an embodiment of the present invention, there is provided a method of processing vehicle information. The method can comprise the following steps: acquiring image information acquired by a vehicle on a road section; determining the type of the lane line of the road section where the vehicle is located based on the image information; and sending prompt information to the vehicle based on the lane line type and the image information, wherein the prompt information is used for determining the driving strategy data of the vehicle, and the driving strategy data is used for determining the driving strategy of the vehicle.
Optionally, determining the lane line type based on the image information includes: extracting first lane line information from the image information, wherein the first lane line information is lane line information of a vehicle which deviates from an original position; and inputting the first lane line information into a lane line identification model to obtain the lane line type, wherein the lane line identification model is a model generated based on image characteristics.
Optionally, extracting the first lane line information in the image information includes: determining that a lane line exists in the image information, wherein the type of the lane line belongs to one of lane line types; determining an included angle between the driving direction of the vehicle and the lane line based on the image information; and responding to the included angle larger than a first preset value, and extracting first lane line information from the image information.
Optionally, sending a prompt message to the vehicle based on the lane line type and the image information, including: determining a first distance from the current position of the vehicle to the lane line and a second distance between the lane line based on the image information; and responding to the fact that the type of the lane line is the non-depressible lane line, and sending prompt information to the vehicle based on the first distance and the second distance.
Optionally, sending a prompt message to the vehicle based on the first distance and the second distance, including: determining a first value between the first distance and the second distance, wherein the first value comprises a ratio or difference of the first distance and the second distance; and responding to the first value exceeding the second preset value, and sending prompt information to the vehicle.
Optionally, after extracting the first lane line information from the image information, the method further includes: checking obstacles which are within a target threshold range away from the lane line; and responding to the obstacle existing in the radius threshold range of the lane line, and sending prompt information to the vehicle.
Optionally, after the prompt message is sent to the vehicle, the current driving state of the vehicle is adjusted.
According to another aspect of the embodiment of the invention, a vehicle information processing device is also provided. The apparatus may include: the acquisition unit is used for acquiring image information acquired by a vehicle on a road section; a determination unit for determining a lane line type of a road section where the vehicle is located based on the image information; and the sending unit is used for sending prompting information to the vehicle based on the lane line type and the image information, wherein the prompting information is used for determining the driving data of the vehicle, and the driving data is used for determining the driving strategy of the vehicle.
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium. The computer-readable storage medium may be used to execute the method of processing vehicle information of the embodiment of the invention.
According to another aspect of the embodiments of the present invention, there is also provided a processor. The processor may be configured to execute a program, wherein the program executes the method of processing vehicle information according to the embodiment of the present invention.
According to another aspect of the embodiment of the invention, a vehicle is also provided. The vehicle may be used to execute the vehicle information processing method of the embodiment of the invention.
In the embodiment of the invention, the image information acquired by the vehicle on the road section where the vehicle is located at present is acquired; determining the type of the lane line of the road section where the vehicle is located based on the image information; and sending prompt information to the vehicle based on the lane line type and the image information, wherein the prompt information is used for determining the driving strategy data of the vehicle, and the driving strategy data is used for determining the driving strategy of the vehicle. That is to say, according to the embodiment of the invention, the type of the lane line where the vehicle is located is determined according to the image information acquired based on the vehicle, and then the corresponding prompt information is sent to the vehicle, so as to achieve the purpose of determining the driving strategy for the vehicle, thereby solving the technical problem that the lane line cannot be accurately identified, and achieving the technical effect of accurately identifying the lane line.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flowchart of a processing method of vehicle information according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a vehicle information processing device system according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of a vehicle to lane line distance view according to an embodiment of the present invention;
FIG. 4 is a flow chart of a method of vehicle lane line identification warning according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a vehicle information processing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided a method for processing vehicle information, where the steps illustrated in the flowchart of the figure may be executed in a computer system such as a set of computer executable instructions, and where a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be executed in an order different from that shown.
Fig. 1 is a flowchart of a processing method of vehicle information according to an embodiment of the present invention, which may include the steps of, as shown in fig. 1:
step S101, image information collected by a vehicle on a road section is obtained.
In the technical solution provided by step S101 of the present invention, image information obtained by the vehicle collecting information of the road segment where the vehicle is currently located through the vehicle-mounted device is obtained, and the image information collected by the vehicle is transmitted to the processor unit. The vehicle-mounted device may be a device equipped for the vehicle itself to collect information, and the image information may be environmental information of a road section where the vehicle is currently located.
Optionally, the image information may be current frame image information acquired by the vehicle through a four-way fisheye camera, or may also be current frame image information acquired by the vehicle through a look-around camera, where the image information may include an identifier, an indication, an obstacle, and the like of a road section where the vehicle is currently located, and this is only for example and is not limited specifically herein.
Step S102, based on the image information, the lane line type of the road section where the vehicle is located is determined.
In the technical solution provided in step S102 of the present invention, it is determined whether a lane line exists in the current frame image information by performing distortion removal and four-way image stitching on the acquired image information, when it is determined that a lane line exists in the current frame image information, an included angle between the current vehicle driving direction and the lane line is determined, if the included angle between the driving direction and the lane line exceeds a preset threshold value, a corresponding lane line is extracted, and the extracted lane line is input into a lane line identification model to determine the type of the extracted lane line, where the type of the lane line may include a depressible lane line and a non-depressible lane line.
Optionally, if lines with different colors exist in the image information of the road segment where the vehicle is currently located, it may be determined that a lane line exists in the current frame image information, where the lines with different colors may be white/yellow/blue/orange lane lines, which is merely illustrated herein and is not specifically limited.
Optionally, if an included angle between the current vehicle driving direction and the lane line exceeds a preset threshold value, indicating that a vehicle is running with a line pressing trend, issuing a corresponding early warning signal, extracting a corresponding lane line, inputting the extracted lane line into a lane line identification model, and then outputting the type of the lane line to further determine whether the extracted lane line can be pressed.
And step S103, sending prompting information to the vehicle based on the lane line type and the image information, wherein the prompting information is used for determining the driving strategy data of the vehicle, and the driving strategy data is used for determining the driving strategy of the vehicle.
In the technical solution of the above step S103, according to the acquired image information of the road segment where the vehicle is located at present and the lane line type output based on the lane line identification model, sending a prompt message to the vehicle, based on which the driving strategy data of the vehicle at the next time can be determined, and based on the determined driving strategy, adjusting the driving state of the vehicle, where the prompt message may be the early warning message of pressing a line, and the driving strategy may be used to represent the driving state of the vehicle at the next time.
Alternatively, the driving strategy data of the vehicle may include vehicle driving speed data and steering wheel angle data, which are only used for illustration and are not specifically limited.
Optionally, when it is determined that the lane line type is an unbendable lane line, calculating a distance between the vehicle and the lane line and a distance between the lane lines, comparing a calculation result with a preset threshold, if the calculation result exceeds the preset threshold, sending a prompt message to the vehicle, and determining a driving strategy of the vehicle based on the prompt message to adjust a driving state of the vehicle and avoid pressing the line, where the prompt message may be prompted by sound or by interface display, and this is not specifically limited.
Further, when the type of the lane line is determined to be the depressible lane line, no prompt message is sent.
Through the above steps S101 to S103, the embodiment acquires the image information of the road section where the vehicle is located; determining the lane line type of a road section where a vehicle is located through a training model based on the current frame image information; and comparing the vehicle calculation parameters with a preset threshold value based on the determined lane line type and the current frame image information to send corresponding prompt information to the vehicle, wherein the prompt information is used for determining the driving strategy data of the vehicle, and the driving strategy data is used for determining the driving strategy of the vehicle. That is to say, according to the obtained current frame image information and the determined lane line type, the embodiment of the invention extracts and marks the early warning lane line information, and at the same time, discriminates the vehicle calculation parameter and the preset threshold value to send the corresponding prompt information, and adjusts the vehicle driving state according to the corresponding prompt information, thereby determining the driving strategy of the vehicle, and further solving the technical problem that the lane line cannot be accurately identified.
The above-described method of this embodiment is further described below.
As an alternative embodiment, the step S102 of determining the lane line type of the road segment where the vehicle is currently located based on the current frame image information may include: extracting first lane line information from the current frame image information, wherein the first lane line information is lane line information of a vehicle deviating from an original position; and inputting the first lane line information into a lane line identification model to obtain the lane line type of the road section where the vehicle is located currently, wherein the lane line identification model is a model generated based on the image characteristics.
In this embodiment, first lane line information is extracted from the image information, where the first lane line information may be a marked lane line, and the marked lane line may be an early warning lane line whose included angle with the current vehicle driving direction exceeds a threshold value.
Optionally, the extracted first lane line information is input into the lane line identification model, and a lane line type of a road section where the vehicle is currently located is obtained.
As an optional embodiment, extracting the first lane line information from the image information may include: determining that a lane line exists in the current frame image information, wherein the type of the lane line belongs to one of lane line types; determining an included angle between the current driving direction of the vehicle and a lane line based on the image information; and responding to the included angle larger than a first preset value, and extracting first lane line information from the current frame image information.
In the embodiment, in response to that an included angle between the current driving direction of the vehicle and a lane line is greater than a first preset value, extracting first lane line information from the current frame image information, wherein the first preset value can be a preset angle threshold value, and when the included angle between the current driving direction of the vehicle and the lane line is judged to be greater than the first preset value, issuing a lane departure early warning signal to the vehicle, and simultaneously extracting the lane line and marking the lane line; and when the included angle between the current driving direction of the vehicle and the lane line is judged to be less than or equal to the first preset value, continuing to monitor the image information of the next target frame.
For example, if the first preset value is 20 °, when an included angle between the current driving direction of the vehicle and the lane line is 30 ° and the included angle between the current driving direction of the vehicle and the lane line is greater than the first preset value, issuing a lane departure warning signal to the vehicle, and simultaneously extracting the lane line and marking the lane line; when the included angle between the current driving direction of the vehicle and the lane line is 10 degrees and the included angle between the current driving direction of the vehicle and the lane line is smaller than a first preset value, continuing to monitor the image information of the next target frame, wherein the image information of the next target frame can be the image information of the next frame of the current frame image information.
As an optional embodiment, after extracting the first lane line information from the image information, the method further includes: checking obstacles which are away from the lane line within a target threshold range; and responding to the obstacle existing in the radius threshold range of the lane line, and sending prompt information to the vehicle.
In this embodiment, an obstacle within a radius threshold range of a lane line within a target frame is determined based on the acquired current frame image information, if an obstacle exists within the radius threshold range of the lane line within the target frame, prompt information is sent to a vehicle, and if an obstacle does not exist within the radius threshold range of the lane line within the target frame, a lane line pressing warning signal is issued to the vehicle, where the prompt information may be an obstacle crossing warning signal, and the obstacle may include a pedestrian and other vehicles, which is only illustrated here and is not specifically limited.
For example, judging the obstacles within the range of 50m of the radius of the lane line in the target frame, and sending an obstacle crossing early warning signal to the vehicle when the obstacles exist within the range of 50m of the radius of the lane line in the target frame; and when no obstacle exists within the range of 50m of the radius of the lane line in the target frame, issuing a lane line pressing early warning signal to the vehicle.
As an alternative embodiment, step S103, sending the prompt message to the vehicle based on the lane line type and the image information, may include: determining a first distance from the current position of the vehicle to the lane line and a second distance between the lane line based on the image information; and responding to the fact that the type of the lane line is the non-depressible lane line, and sending prompt information to the vehicle based on the first distance and the second distance.
In this embodiment, a first distance and a second distance are determined based on the acquired image information of the road section where the vehicle is located, when the type of the lane line is determined as that the lane line cannot be pressed, the first distance and the second distance are calculated, and when the calculation result exceeds a second preset value, a prompt message is sent to the vehicle, wherein the first distance may be the distance from the front end and the rear end of the vehicle body to the lane lines on the two sides, the second distance may be the distance between the lane lines on the two sides, and the second preset value may be a preset proportional threshold value between the first distance and the second distance.
As an alternative embodiment, step S103, sending a prompt message to the vehicle based on the first distance and the second distance, includes: determining a first value between the first distance and the second distance, wherein the first value comprises a ratio or difference of the first distance and the second distance; and responding to the first value exceeding the second preset value, and sending prompt information to the vehicle.
In this embodiment, a first value is obtained by calculating a ratio or a difference between the first distance and the second distance, whether the first value exceeds a preset threshold is determined, when the first value is greater than the preset threshold, the next obstacle judgment is performed, and when the first value is less than or equal to the preset threshold, the next target frame image information is continuously monitored.
As an alternative embodiment, in step S103, after the prompt message is sent to the vehicle, the current driving state of the vehicle is adjusted.
In this embodiment, based on the prompt information sent to the vehicle, the corresponding vehicle driving strategy data is determined to achieve the purpose of adjusting the current driving state of the vehicle, where adjusting the current driving state of the vehicle may be to control the vehicle to slowly decrease the vehicle speed and to slowly decrease the steering wheel angle.
The embodiment acquires the image information acquired by the vehicle on the road section; determining the lane line type of a road section where a vehicle is located through a training model based on the current frame image information; and judging whether the vehicle calculation parameters, preset threshold values and the target frame image information have obstacles or not based on the determined lane line type and the current frame image information so as to send corresponding prompt information to the vehicle, wherein the prompt information is used for determining the driving strategy data of the vehicle, and the driving strategy data is used for determining the driving strategy of the vehicle. That is to say, according to the obtained current frame image information and the determined lane line type, the embodiment of the invention extracts and marks the early warning lane line information, simultaneously judges the barrier in the target frame image information to send the corresponding prompt information, and adjusts the vehicle driving state according to the corresponding prompt information, thereby determining the driving strategy of the vehicle and further solving the technical problem that the lane line cannot be accurately identified.
Example 2
The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.
With the concern of the industry on the automatic driving technology of the vehicle and the support of the country on the key core technology of the nationally owned enterprise, the auxiliary driving becomes a technology direction which is concerned by the industry. In recent years, Level2 (L2) intelligent driving accidents frequently occur, the number of vehicle users is increased sharply with the social development, and violation phenomena in unfamiliar road sections frequently occur to be solved urgently.
In the related technology, the auxiliary driving mainly comprises an image acquisition module and an early warning judgment module, wherein the image acquisition module acquires a forward image through a vehicle-mounted camera, the early warning judgment module judges whether an early warning signal is sent out to remind a driver, and lane line conditions in different driving scenes cannot be identified in the scheme.
In order to solve the problems, the embodiment of the invention realizes 360-degree full-coverage monitoring of the vehicle driving environment based on the fisheye looking-around camera, sends prompt information to the vehicle through the acquired current frame image information and the type of the lane line of the road section where the vehicle is located determined based on the target frame image information, and adjusts the vehicle driving state based on the received prompt information so as to achieve the purpose of determining the driving strategy for the vehicle, thereby solving the technical problem that the lane line cannot be accurately identified and achieving the technical effect of accurately identifying the lane line.
In this embodiment, fig. 2 is a schematic diagram of a vehicle-mounted line-pressing recognition early-warning device system according to an embodiment of the present invention, and as shown in fig. 2, the vehicle-mounted line-pressing recognition early-warning device system may include four fish-eye looking-around cameras 201, an image preprocessing unit 202, a vehicle body information unit 203, a center unit 204, an early-warning unit 205, and a vehicle control unit 206.
The four-way fisheye looking around camera 201 may be used to acquire image information.
The image preprocessing unit 202 may be configured to process the acquired image information, and may include a distortion removal process and a four-way image stitching.
The vehicle body information unit 203 may be used to acquire the current position of the vehicle, the traveling direction of the vehicle, and the distance of the vehicle body from the lane line.
The central unit 204 may be configured to determine whether to issue a lane departure warning signal by determining the acquired image information and the acquired vehicle body information.
The early warning unit 205 may be configured to issue a corresponding early warning signal.
The vehicle control unit 206 may be configured to adjust the vehicle driving state based on the received warning signal.
Alternatively, fig. 3 is a schematic diagram of a distance view between a vehicle and a lane line according to an embodiment of the present invention, as shown in fig. 3, a distance between a vehicle head and a lane line on two sides may be represented by d1 and d2, a distance between a vehicle tail and a lane line on two sides may be represented by d3 and d4, and a distance between lane lines on two sides may be represented by d.
Based on the acquired vehicle body-to-lane line distances d1, d2, d3, d4 and the lane width d, respectively calculating ratios d1/d, d2/d, d3/d and d4/d of the vehicle body-to-lane line distance and the lane width, judging whether the ratio of the vehicle body-to-lane line distance and the lane width exceeds a preset threshold value T, entering the next step when the ratio exceeds the preset threshold value, and continuously monitoring the next target frame image information when the ratio does not exceed the preset threshold value.
In this embodiment, fig. 4 is a flowchart of a method for identifying and warning a vehicle lane line according to an embodiment of the present invention, and as shown in fig. 4, the vehicle information processing technical solution may include:
step S401, the current frame image information obtained by the four fish-eye cameras is transmitted into the processor.
In the technical solution of step S401 in the embodiment of the present invention, the current frame image information obtained by the four fish-eye cameras is transmitted to the processor, so as to perform the next processing on the current frame image information.
In step S402, a current frame is subjected to distortion removal processing.
In the technical solution of step S402 in the embodiment of the present invention, the current frame image obtained by the four fish-eye cameras is subjected to distortion removal processing, so as to ensure the accuracy of the image information.
And step S403, carrying out image splicing on the four images of the current frame.
In the technical solution of step S403 in the embodiment of the present invention, four paths of current frame images subjected to distortion removal processing are subjected to image stitching, so as to ensure that the vehicle identification is 360 ° without dead angle and full coverage.
Step S404, judging whether a white/yellow/blue/orange lane line exists.
In the technical solution of step S404 in the embodiment of the present invention, it is determined whether the processed current frame image has a white/yellow/blue/orange lane line, and if the processed image has a white/yellow/blue/orange lane line, the next step is performed; and if the processed image has no white/yellow/blue/orange lane line, continuing to monitor the next target frame image information.
Step S405, calculating an included angle between the vehicle driving direction and the lane line.
In the technical solution of the foregoing step S405 in the embodiment of the present invention, if the processed image has a white/yellow/blue/orange lane line, an included angle between the current driving direction of the vehicle and the lane line existing in the current frame image information is calculated.
Step S406, determining whether the included angle is greater than a threshold.
In the technical solution of the above step S406 in the embodiment of the present invention, it is determined whether an included angle between the vehicle driving direction and a lane line existing in the current frame image information is greater than a preset threshold, and if the included angle between the vehicle driving direction and the lane line is greater than the preset threshold, the next step is performed; and if the included angle between the vehicle driving direction and the lane line is not greater than the preset threshold value, continuing to monitor the next target frame image information.
And step S407, issuing a lane departure early warning signal.
In the technical solution of the foregoing step S407 in the embodiment of the present invention, if an included angle between the vehicle driving direction and the lane line is greater than a preset threshold, indicating that there is a vehicle line pressing trend, a lane departure warning signal is issued to the vehicle.
And step S408, extracting the early warning lane line and marking the lane line.
In the technical scheme of step S408 in the embodiment of the present invention, a lane line whose included angle with the vehicle driving direction is greater than a preset threshold is extracted, and the early warning lane line is marked.
And step S409, putting the marked lane lines into a training model.
And step S410, judging whether the early warning lane line can not be pressed.
In the technical solution of the above step S410 in the embodiment of the present invention, the marked early warning lane line is input into a training model, and the class of the early warning lane line is output to determine whether the early warning lane line can be pressed, where the training model may be a lane line class training model. If the early warning lane line is the non-depressible lane line, entering the next step; and if the early warning lane line is not the non-depressible lane line, continuing to monitor the next target frame image information.
Step S411, entering warning time filling and stopping monitoring the next target frame image information.
Step S412, the distance from the vehicle body to the lane line is calculated.
In the technical solution of the foregoing step S412 in the embodiment of the present invention, the distance between the vehicle body and the lane line may be calculated, and may include distances between the front end and the rear end of the vehicle body and the lane lines on both sides, and may be an occupation ratio of the distance between the vehicle body and the lane line to the lane width.
In step S413, it is determined whether the distance ratio exceeds the threshold T.
In the technical solution of step S413 in the embodiment of the present invention, the determining whether the distance ratio exceeds the preset threshold T may be determining whether the ratio of the distance from the vehicle body to the lane line to the lane width exceeds the preset threshold T, entering the next step if the ratio of the distance from the vehicle body to the lane line to the lane width exceeds the preset threshold T, and continuing to monitor the next target frame image information if the ratio of the distance from the vehicle body to the lane line to the lane width does not exceed the preset threshold T.
Step S414, determine whether there is an obstacle in the forward direction.
In the technical solution of the above step S414 in the embodiment of the present invention, it is determined whether there is an obstacle in the forward radius of the current frame of the lane line, if there is a pedestrian or another vehicle in the forward radius of the frame of the lane line, an obstacle crossing warning is issued to the vehicle, and if there is no pedestrian or another vehicle in the forward radius of the frame of the lane line, a lane line pressing warning signal is issued to the vehicle, and the next step is performed.
Step S415, issuing an obstacle crossing warning.
And step S416, controlling the vehicle to slowly reduce the vehicle speed and adjusting the slow width direction.
In the technical solution of step S416 in the embodiment of the present invention, the issued corresponding warning signal is input to the control module, so as to adjust the driving state of the vehicle according to the corresponding warning signal, which may be to control the vehicle to reduce the speed of the vehicle and reduce the steering angle of the steering wheel in a gradual manner, so as to correct the traveling direction and the driving state of the vehicle.
And step S417, continuing to monitor the vehicle state until the departure early warning is released.
In step S418, the next target frame status is monitored.
The embodiment of the invention realizes 360-degree full-coverage monitoring of the vehicle driving environment based on the fisheye looking-around camera, judges the lane line condition of the road section where the vehicle is located at the current moment through the acquired image information and the determined lane line type of the road section where the vehicle is located based on the image information, sends prompt information to the vehicle according to the lane line type and the obstacle monitoring judgment result, and adjusts the vehicle driving state based on the received prompt information to achieve the purpose of determining the driving strategy for the vehicle, thereby solving the technical problem that the lane line cannot be accurately identified and achieving the technical effect of accurately identifying the lane line.
Example 3
According to the embodiment of the invention, the vehicle information processing device is also provided. It should be noted that the vehicle information processing device may be used to execute the vehicle information processing method in embodiment 1.
Fig. 5 is a schematic diagram of a vehicle information processing apparatus according to an embodiment of the present invention. As shown in fig. 5, the vehicle information processing device 50 may include: an acquisition unit 501, a determination unit 502, and a transmission unit 503.
The acquiring unit 501 is configured to acquire image information acquired by a vehicle on a road segment where the vehicle is located.
A determining unit 502 for determining a lane line type of a road section on which the vehicle is located, based on the image information;
a sending unit 503, configured to send prompt information to the vehicle based on the lane line type and the image information, where the prompt information is used to determine driving data of the vehicle, and the driving data is used to determine a driving strategy of the vehicle.
Alternatively, the determining unit 502 may include: the extraction module is used for extracting the first lane line information from the image information; and the input module is used for inputting the first lane line information into the lane line identification model to obtain the lane line type.
Optionally, the extraction module may include: the first determining submodule is used for determining that a lane line exists in the image information, wherein the type of the lane line belongs to one of lane line types; the second determining submodule is used for determining an included angle between the driving direction of the vehicle and the lane line based on the image information; and the first extraction submodule is used for extracting the first lane line information from the image information in response to the included angle being larger than a first preset value.
Optionally, the determining unit 502 may further include: the first processing module is used for extracting first lane line information from the image information and then checking obstacles which are far away from the lane line within a target threshold range; the first sending module is used for responding to the situation that an obstacle exists in the radius threshold range of the lane line and sending prompt information to the vehicle.
Alternatively, the sending unit 503 may include: the first determining module is used for determining a first distance from the current position of the vehicle to the lane line and a second distance between the lane line based on the image information; and the second sending module is used for responding to the fact that the type of the lane line is the non-depressible lane line and sending prompt information to the vehicle based on the first distance and the second distance.
Optionally, the second sending module may include: the third determining submodule is used for determining a first value between the first distance and the second distance, wherein the first value comprises a ratio or a difference value of the first distance and the second distance; and the sending submodule is used for responding to the first value exceeding the second preset value and sending prompt information to the vehicle.
Optionally, the sending unit 503 may further include: and the adjusting module is used for adjusting the current running state of the vehicle after sending the prompt message to the vehicle.
In the embodiment of the invention, the image information acquired by the vehicle on the road section is acquired through the acquisition unit; determining, by a determination unit, a lane line type of a road section on which the vehicle is located based on the image information; through the sending unit, prompt information is sent to the vehicle based on the type of the lane line and the image information, so that the technical effect of improving the recognition and early warning accuracy of the vehicle-mounted pressing line is achieved, and the technical problem that the lane line cannot be recognized accurately is solved.
Example 4
According to an embodiment of the present invention, there is also provided a computer-readable storage medium including a stored program, wherein the program executes the method for processing vehicle information described in embodiment 1.
Example 5
According to an embodiment of the present invention, there is also provided a processor for executing a program, wherein the program executes the processing method of the vehicle information described in embodiment 1 when running.
Example 6
According to an embodiment of the present invention, there is also provided a vehicle for executing the method, wherein the vehicle executes the method for processing vehicle information described in embodiment 1.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method for processing vehicle information, characterized by comprising:
acquiring image information acquired by a vehicle on a road section;
determining the type of the lane line of the road section where the vehicle is located based on the image information;
and sending prompt information to the vehicle based on the lane line type and the image information, wherein the prompt information is used for determining driving strategy data of the vehicle, and the driving strategy data is used for determining driving strategies of the vehicle.
2. The method of claim 1, wherein determining a lane line type based on the image information comprises:
extracting first lane line information from the image information, wherein the first lane line information is lane line information of the vehicle which deviates from an original position;
inputting the first lane line information into a lane line identification model to obtain the lane line type, wherein the lane line identification model is a model generated based on image characteristics.
3. The method of claim 2, wherein extracting first lane line information in the image information comprises:
determining that a lane line exists in the image information, wherein the type of the lane line belongs to one of the lane line types;
determining an included angle between the driving direction of the vehicle and the lane line based on the image information;
and responding to the fact that the included angle is larger than a first preset value, and extracting the first lane line information from the image information.
4. The method of claim 1, wherein sending a prompt to the vehicle based on the lane line type and the image information comprises:
determining a first distance from a current position of the vehicle to a lane line and a second distance between the lane line based on the image information;
and responding to the fact that the type of the lane line is the non-depressible lane line, and sending prompt information to the vehicle based on the first distance and the second distance.
5. The method of claim 4, wherein sending a prompt to the vehicle based on the first distance and the second distance comprises:
determining a first value between the first distance and the second distance, wherein the first value comprises a ratio or difference of the first distance and the second distance;
and responding to the first value exceeding a second preset value, and sending the prompt message to the vehicle.
6. The method of claim 2, wherein after extracting the first lane line information from the image information, the method further comprises:
checking obstacles which are within a target threshold range away from the lane line;
and responding to the situation that an obstacle exists in the radius threshold range of the lane line, and sending prompt information to the vehicle.
7. The method of claim 1, further comprising:
and after the prompt information is sent to the vehicle, adjusting the current running state of the vehicle.
8. A vehicle information processing apparatus, characterized by comprising:
the acquisition unit is used for acquiring image information acquired by a vehicle on a road section;
a determination unit configured to determine a lane line type of a road segment on which the vehicle is located, based on the image information;
and the sending unit is used for sending prompt information to the vehicle based on the lane line type and the image information, wherein the prompt information is used for determining the driving data of the vehicle, and the driving data is used for determining the driving strategy of the vehicle.
9. A computer-readable storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the method of any one of claims 1 to 7.
10. A vehicle, characterized in that it is adapted to carrying out the method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210495790.XA CN114863707A (en) | 2022-05-07 | 2022-05-07 | Vehicle information processing method and device, storage medium and vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210495790.XA CN114863707A (en) | 2022-05-07 | 2022-05-07 | Vehicle information processing method and device, storage medium and vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114863707A true CN114863707A (en) | 2022-08-05 |
Family
ID=82637640
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210495790.XA Pending CN114863707A (en) | 2022-05-07 | 2022-05-07 | Vehicle information processing method and device, storage medium and vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114863707A (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102785661A (en) * | 2012-08-20 | 2012-11-21 | 深圳先进技术研究院 | Lane departure control system and lane departure control method |
| US20150294165A1 (en) * | 2011-07-27 | 2015-10-15 | Gentex Corporation | System and method for periodic lane marker identification and tracking |
| CN105882515A (en) * | 2015-11-11 | 2016-08-24 | 乐卡汽车智能科技（北京）有限公司 | Information processing method and device applied to automobile data recorder and automobile data recorder |
| CN106256606A (en) * | 2016-08-09 | 2016-12-28 | 浙江零跑科技有限公司 | A kind of lane departure warning method based on vehicle-mounted binocular camera |
| CN109147368A (en) * | 2018-08-22 | 2019-01-04 | 北京市商汤科技开发有限公司 | Intelligent driving control method device and electronic equipment based on lane line |
| CN109872413A (en) * | 2017-12-01 | 2019-06-11 | 比亚迪股份有限公司 | Driving behavior record and analysis system, method |
| CN109866684A (en) * | 2019-03-15 | 2019-06-11 | 江西江铃集团新能源汽车有限公司 | Lane departure warning method, system, readable storage medium storing program for executing and computer equipment |
| CN111469860A (en) * | 2020-06-28 | 2020-07-31 | 江铃汽车股份有限公司 | Lane departure early warning method and device, storage medium and automobile data recorder |
| CN113212454A (en) * | 2021-05-20 | 2021-08-06 | 中国第一汽车股份有限公司 | Method and device for adjusting vehicle running state, computer equipment and storage medium |
| CN114332821A (en) * | 2021-12-31 | 2022-04-12 | 苏州智加科技有限公司 | Decision information acquisition method, device, terminal and storage medium |
-
2022
- 2022-05-07 CN CN202210495790.XA patent/CN114863707A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150294165A1 (en) * | 2011-07-27 | 2015-10-15 | Gentex Corporation | System and method for periodic lane marker identification and tracking |
| CN102785661A (en) * | 2012-08-20 | 2012-11-21 | 深圳先进技术研究院 | Lane departure control system and lane departure control method |
| CN105882515A (en) * | 2015-11-11 | 2016-08-24 | 乐卡汽车智能科技（北京）有限公司 | Information processing method and device applied to automobile data recorder and automobile data recorder |
| CN106256606A (en) * | 2016-08-09 | 2016-12-28 | 浙江零跑科技有限公司 | A kind of lane departure warning method based on vehicle-mounted binocular camera |
| CN109872413A (en) * | 2017-12-01 | 2019-06-11 | 比亚迪股份有限公司 | Driving behavior record and analysis system, method |
| CN109147368A (en) * | 2018-08-22 | 2019-01-04 | 北京市商汤科技开发有限公司 | Intelligent driving control method device and electronic equipment based on lane line |
| CN109866684A (en) * | 2019-03-15 | 2019-06-11 | 江西江铃集团新能源汽车有限公司 | Lane departure warning method, system, readable storage medium storing program for executing and computer equipment |
| CN111469860A (en) * | 2020-06-28 | 2020-07-31 | 江铃汽车股份有限公司 | Lane departure early warning method and device, storage medium and automobile data recorder |
| CN113212454A (en) * | 2021-05-20 | 2021-08-06 | 中国第一汽车股份有限公司 | Method and device for adjusting vehicle running state, computer equipment and storage medium |
| CN114332821A (en) * | 2021-12-31 | 2022-04-12 | 苏州智加科技有限公司 | Decision information acquisition method, device, terminal and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111815959B (en) | Vehicle violation detection method and device and computer readable storage medium | |
| CN108765945A (en) | A kind of vehicle peccancy recognition methods and system | |
| CN111209780A (en) | Lane line attribute detection method and device, electronic device and readable storage medium | |
| US20180211121A1 (en) | Detecting Vehicles In Low Light Conditions | |
| CN111209777A (en) | Lane line detection method and device, electronic device and readable storage medium | |
| JP2015022499A (en) | Driving characteristic determination system | |
| CN111144330A (en) | Deep learning-based lane line detection method, device and equipment | |
| CN110379172A (en) | The generation method and device of traffic rules, storage medium, electronic device | |
| CN109872413A (en) | Driving behavior record and analysis system, method | |
| CN105654561A (en) | Multilane free flow vehicle matching method | |
| CN110969843B (en) | Traffic sign identification alarm method with inhibition strategy | |
| CN114495520B (en) | Counting method and device for vehicles, terminal and storage medium | |
| JP4735430B2 (en) | Confluence support device | |
| CN113176778A (en) | Control method and control device for unmanned vehicle and unmanned vehicle | |
| CN114863707A (en) | Vehicle information processing method and device, storage medium and vehicle | |
| US20170092121A1 (en) | Method and System for Determining and Using Property Associations | |
| CN111833621A (en) | Lane guide line generation method and device, storage medium and computer equipment | |
| CN113071494A (en) | Vehicle control method and device and automatic driving vehicle | |
| CN113147792A (en) | Vehicle control method and device and automatic driving vehicle | |
| JP2015022124A (en) | Driving characteristic determination system | |
| CN113147791A (en) | Vehicle control method and device and automatic driving vehicle | |
| CN113593239A (en) | Method and server for monitoring violation among vehicles and vehicle | |
| CN112232312A (en) | Automatic driving method and device based on deep learning and electronic equipment | |
| CN113283335B (en) | Construction area recognition method, construction area recognition device, vehicle, electronic device, and storage medium | |
| CN112270830B (en) | Method and device for determining parking position of vehicle and automatic driving vehicle |
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 |