CN111967384A - Vehicle information processing method, device, equipment and computer readable storage medium - Google Patents
Vehicle information processing method, device, equipment and computer readable storage medium Download PDFInfo
- Publication number
- CN111967384A CN111967384A CN202010823943.XA CN202010823943A CN111967384A CN 111967384 A CN111967384 A CN 111967384A CN 202010823943 A CN202010823943 A CN 202010823943A CN 111967384 A CN111967384 A CN 111967384A
- Authority
- CN
- China
- Prior art keywords
- road
- information
- target vehicle
- vehicle
- 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.)
- Pending
Links
- 230000010365 information processing Effects 0.000 title claims abstract description 49
- 238000003672 processing method Methods 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 claims abstract description 30
- 238000004364 calculation method Methods 0.000 claims abstract description 8
- 238000001514 detection method Methods 0.000 claims description 25
- 238000012545 processing Methods 0.000 claims description 12
- 230000011218 segmentation Effects 0.000 claims description 11
- 238000010606 normalization Methods 0.000 claims description 10
- 238000007634 remodeling Methods 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 13
- 238000004891 communication Methods 0.000 description 5
- 230000006399 behavior Effects 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 230000003993 interaction Effects 0.000 description 2
- 238000012806 monitoring device Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011022 operating instruction Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- 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
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- 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
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/07—Target detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/08—Detecting or categorising vehicles
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
- Traffic Control Systems (AREA)
Abstract
The present disclosure provides a vehicle information processing method, apparatus, device, and computer-readable storage medium, the method comprising: acquiring a road surface image acquired by an image acquisition device; identifying road information in the road surface image; identifying target vehicles in the road information, and determining central point information corresponding to each target vehicle; and judging whether the target vehicle runs safely according to the central point information and a safe running area to obtain a judgment result, wherein the safe running area is determined according to the central line of the road information and a preset range threshold. Therefore, auxiliary calculation is not needed to be carried out by adopting traffic elements in other roads, such as road sign lines, traffic lights and the like, so that the method is suitable for traffic scenes of various roads, the identification operation of whether vehicles safely run under the traffic scene of a single road is effectively limited, and the traffic safety of the traffic scene of the single road is ensured.
Description
Technical Field
The present disclosure relates to the field of intelligent transportation, and in particular, to a vehicle information processing method, apparatus, device, and computer-readable storage medium.
Background
With the continuous development of traffic, vehicles on the road surface are more and more, and therefore, how to ensure traffic safety also becomes a problem to be solved urgently.
In order to judge whether a vehicle normally runs on a road, in the prior art, a deep learning technology has been widely applied in the traffic field, for example, an actual intersection scene is identified through modes of target detection, road segmentation and the like, and whether the vehicle has an illegal driving behavior is assisted and judged according to information such as a road sign line, a traffic signal lamp and the like in the intersection scene.
However, when the vehicle information processing is performed by the above method, information such as a road sign line and a traffic light is often necessary for auxiliary determination, and therefore, the method is often applied only to an intersection of a town street. For the traffic scene of the single road without the traffic information, the method cannot accurately judge whether the vehicle has illegal driving behaviors, and further cannot guarantee the traffic safety of the traffic scene of the single road.
Disclosure of Invention
The present disclosure provides a vehicle information processing method, device, and apparatus, and a computer-readable storage medium, which are used to solve the technical problem that in the prior art, it is not possible to accurately determine whether a vehicle has an illegal driving behavior, and thus it is not possible to ensure traffic safety in a traffic scene of a single road.
A first aspect of the present disclosure is to provide a vehicle information processing method including:
acquiring a road surface image acquired by an image acquisition device;
identifying road information in the road surface image;
identifying target vehicles in the road information, and determining central point information corresponding to each target vehicle;
and judging whether the target vehicle runs safely according to the central point information and a safe running area to obtain a judgment result, wherein the safe running area is determined according to the central line of the road information and a preset range threshold.
A second aspect of the present disclosure is to provide a vehicle information processing apparatus including:
the acquisition module is used for acquiring the road surface image acquired by the image acquisition device;
the identification module is used for identifying road information in the road surface image;
the determining module is used for identifying target vehicles in the road information and determining central point information corresponding to each target vehicle;
and the judging module is used for judging whether the target vehicle runs safely according to the central point information and a safe running area to obtain a judging result, wherein the safe running area is determined according to the central line of the road information and a preset range threshold.
A third aspect of the present disclosure is to provide a vehicle information processing apparatus including: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the vehicle information processing method according to the first aspect by the processor.
A fourth aspect of the present disclosure is to provide a computer-readable storage medium having stored therein computer-executable instructions for implementing the vehicle information processing method according to the first aspect when the computer-executable instructions are executed by a processor.
The vehicle information processing method, the vehicle information processing device, the vehicle information processing equipment and the computer readable storage medium are used for determining the central point information of the target vehicle in the road surface by performing image processing operation on the road surface image after the road surface image is acquired. And determining whether the current target vehicle is safely driven according to the center point information and a preset safe driving area, wherein the safe driving area is determined according to the central line of the identified road information and a preset range threshold. The method does not need to adopt traffic elements in other roads, such as road sign lines, traffic lights and the like, to carry out auxiliary calculation, thereby being suitable for traffic scenes of various roads, effectively limiting the identification operation of whether vehicles safely run under the traffic scene of a single road, and ensuring the traffic safety of the traffic scene of the single road.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 is a schematic diagram of a network architecture upon which the present disclosure is based;
FIG. 2 is a schematic flowchart of a vehicle information processing method according to a first embodiment of the disclosure;
FIG. 3 is a schematic view of a scenario provided by an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of a vehicle information processing method according to a second embodiment of the disclosure;
fig. 5 is a schematic flowchart of a vehicle information processing method according to a third embodiment of the disclosure;
FIG. 6 is a schematic center point view provided by an embodiment of the present disclosure;
fig. 7 is a schematic flowchart of a vehicle information processing method according to a fourth embodiment of the disclosure;
fig. 8 is a schematic structural diagram of a vehicle information processing apparatus according to a fifth embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of a vehicle information processing apparatus according to a sixth embodiment of the present disclosure;
fig. 10 is a schematic structural diagram of a vehicle information processing apparatus according to a seventh embodiment of the present disclosure;
fig. 11 is a schematic structural diagram of a vehicle information processing apparatus according to an eighth embodiment of the present disclosure;
fig. 12 is a schematic structural diagram of a vehicle information processing apparatus according to a ninth embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments obtained based on the embodiments in the disclosure belong to the protection scope of the disclosure.
In view of the above-mentioned technical problem that the prior art cannot accurately determine whether a vehicle has an illegal driving behavior, and thus cannot guarantee traffic safety of a traffic scene of a single road, the present disclosure provides a vehicle information processing method, apparatus, device, and computer-readable storage medium.
It should be noted that the vehicle information processing method, device, equipment and computer readable storage medium provided by the present disclosure may be applied to a scene for determining a driving state of a vehicle under various road conditions.
In order to identify whether a vehicle in a road is safely driven, in the prior art, after a road surface image is acquired, traffic elements such as a road sign line and a traffic signal lamp in the road are generally additionally adopted as auxiliary identification operations. However, the above method is only applicable to town streets provided with road marking lines and traffic lights, and is not applicable to a single road provided with road marking lines and traffic lights, and the above method cannot accurately identify the road.
In the process of solving the technical problem, the inventor finds through research that after the road surface image acquired by the image acquisition device is acquired, the road surface image can be subjected to image processing operation to determine the center point information of the target vehicle in the road surface. Therefore, whether the target vehicle safely runs in the safe running area can be judged subsequently according to the central point information and the safe running area, other traffic elements are not needed to be adopted as auxiliary calculation, and the method is suitable for various traffic scenes.
Fig. 1 is a schematic diagram of a network architecture based on the present disclosure, and as shown in fig. 1, the network architecture based on the present disclosure at least includes: the system comprises an image acquisition device 1 and a server 2, wherein the server 2 is provided with a vehicle information processing device. The vehicle information device is written by C/C + +, Java, Shell or Python and other languages; the image capturing device 1 may be any device capable of capturing images, such as a camera and a monitoring device. The image acquisition device 1 is in communication connection with the server 2, so that the two can perform information interaction.
Fig. 2 is a schematic flowchart of a vehicle information processing method according to a first embodiment of the disclosure, and as shown in fig. 2, the method includes:
The execution subject of the present embodiment is a vehicle information processing device, which may be coupled to a server. The server is in communication connection with the image acquisition device, so that information interaction can be carried out with the image acquisition device.
In this embodiment, the vehicle information processing device may acquire the road surface image acquired by the image acquisition device. The image acquisition device can be any one of a camera, a monitor and the like, is arranged on the road surface and can shoot road surface images. Accordingly, the road surface image may be an image of the road surface acquired by the monitoring device.
The image acquisition device can acquire and transmit the road surface image in real time, and can also acquire the road surface image according to a preset time threshold, which is not limited by the disclosure.
Further, on the basis of the first embodiment, after the step 101, the method further includes:
and carrying out size remodeling operation and/or gray normalization and/or brightness normalization processing on the road surface image.
In this embodiment, since there may be differences between the image capturing devices disposed on different road segments, after the road surface image is acquired, in order to improve the efficiency and accuracy of subsequent image processing, a size reshaping operation may be performed on the road surface image, so that the road surface images captured by each image capturing device have the same size. In addition, the road surface image can be subjected to operations such as gray level normalization and brightness normalization. The three different pretreatment methods can be implemented individually or in combination, and the disclosure is not limited thereto.
And 102, identifying road information in the road surface image.
In this embodiment, the road surface image acquired by the image acquisition device may include a lot of information, for example, information of trees, houses, etc. on the road side. But the above information tends to be of little use. Therefore, after the road surface image is acquired, the road information in the road surface image can be identified.
And 103, identifying target vehicles in the road information, and determining central point information corresponding to each target vehicle.
In the present embodiment, after the road information in the road surface image is recognized, the target vehicle traveling on the road can be further recognized. In addition, in order to facilitate the determination of the subsequent target vehicle position, after the target vehicles are determined, the center point information corresponding to each target vehicle may be determined, and the center point may represent the position information of the target vehicle.
And 104, judging whether the target vehicle runs safely according to the central point information and a safe running area to obtain a judgment result, wherein the safe running area is determined according to the central line of the road information and a preset range threshold.
In the present embodiment, since the center point information can accurately represent the position information of the target vehicle, it is possible to determine whether the current target vehicle is safely driven according to the center point information and the safe driving area, and obtain the determination result.
It should be noted that the safe driving area is determined based on the center line of the road information and a preset range threshold. The preset range threshold may be a range of 1/2 lanes to the left and right of the center line.
Fig. 3 is a schematic view of a scenario provided by an embodiment of the present disclosure, as shown in fig. 3, where a target vehicle travels on a road, and whether the vehicle is safely driven may be determined according to a central point 1 and a safe driving area 2. The safe driving area 2 is determined according to the center line 3 of the road and a preset range threshold.
Specifically, on the basis of the first embodiment, the step 104 specifically includes:
if the central point information is in the safe driving area, judging that the target vehicle is safely driven;
and if the central point information is not in the safe driving area, judging that the target vehicle is driven dangerously.
In this embodiment, if it is detected that the center point is within the safe driving area, it may be determined that the target vehicle is currently safely driven. On the contrary, if the central point is detected not to be in the safe driving area, it can be determined that the target vehicle is not safely driven currently.
Further, on the basis of the first embodiment, after the step 104, the method further includes:
and if the target vehicle does not safely run, sending alarm information to a law enforcement agency, and/or controlling the target vehicle to remind dangerous driving.
In this embodiment, in order to ensure traffic safety, when it is detected that the target vehicle does not safely run, an alarm message needs to be sent to a law enforcement agency, or the target vehicle may be controlled to remind the driver of dangerous driving, so that the driver can adjust the driving mode in time.
The vehicle information processing method provided by the embodiment determines the center point information of the target vehicle in the road surface by performing an image processing operation on the road surface image after acquiring the road surface image. And determining whether the current target vehicle is safely driven according to the center point information and a preset safe driving area, wherein the safe driving area is determined according to the central line of the identified road information and a preset range threshold. The method does not need to adopt traffic elements in other roads, such as road sign lines, traffic lights and the like, to carry out auxiliary calculation, thereby being suitable for traffic scenes of various roads, effectively limiting the identification operation of whether vehicles safely run under the traffic scene of a single road, and ensuring the traffic safety of the traffic scene of the single road.
Fig. 4 is a schematic flowchart of a vehicle information processing method provided in a second embodiment of the present disclosure, and on the basis of the first embodiment, as shown in fig. 4, step 102 specifically includes:
And 203, fitting the boundary information by adopting lines to obtain the road information.
In this embodiment, in order to realize the identification of the road information, a preset segmentation network may be first used to identify the road region in the road surface image. The segmentation network may be any one of pspnet, deplab, and the like, which can implement traffic scene segmentation, and the disclosure does not limit this.
Further, it is considered that a simple segmentation network is likely to cause discontinuity in the segmentation result. Therefore, the pixel communication area detection operation can be carried out on the road area, and the boundary information corresponding to the road area is obtained. And then, fitting operation can be carried out on the boundary information by adopting lines to obtain the road information.
According to the vehicle information processing method provided by the embodiment, the road area is identified through the segmentation network, and the boundary of the road area is processed, so that the road information in the road surface image can be accurately identified, and a basis is provided for identifying whether a subsequent target vehicle runs safely.
Further, on the basis of any of the above embodiments, the identifying the road information in the road surface image in step 103 specifically includes:
detecting all vehicles in the road information through a preset target detection model;
and identifying all motor vehicles as the target vehicle in all the vehicles through a preset vehicle type identification model.
In this embodiment, since vehicles such as three-wheel vehicles and two-wheel vehicles are often used as non-motor vehicles on the country road, it is necessary to further perform a screening operation on the recognized vehicle information.
Specifically, first, all the vehicles in the road information may be detected using the object detection model. Further, the vehicle type recognition model can be used for recognizing the motor vehicles in all the vehicles to obtain the target vehicle.
Fig. 5 is a schematic flow chart of a vehicle information processing method according to a third embodiment of the present disclosure, and based on any one of the embodiments, as shown in fig. 5, determining center point information corresponding to each target vehicle in step 103 includes:
step 301, detecting a preset number of pieces of key point information corresponding to each target vehicle through a preset key point detection model.
Step 302, connecting the key point information according to a preset connection rule to obtain at least two connection line information, and using the intersection point of the at least two connection lines as the center point information.
In this embodiment, after the target vehicle is identified, the center point information corresponding to the target vehicle needs to be determined. Specifically, first, a preset number of pieces of key point information corresponding to each target vehicle may be detected through a preset key point detection model. The key points may be key points on the vehicle profile, such as lighting on the vehicle tires, chassis, roof, etc. The key points can be connected according to a preset connection rule to obtain information of at least two connecting lines, and the intersection point of the connecting lines is used as a central point.
Fig. 6 is a schematic center point diagram provided in the embodiment of the present disclosure, and as shown in fig. 6, the key points may specifically be four vehicle vertexes of the target vehicle. The diagonals of the vehicle are respectively connected to obtain the intersection point, namely the central point, of the connecting lines.
According to the vehicle information processing method provided by the embodiment, the central point information which can be used for representing the position of the target vehicle can be accurately determined by identifying the key points of the target vehicle and constructing the connecting line.
Fig. 7 is a schematic flowchart of a vehicle information processing method according to a fourth embodiment of the present disclosure, and on the basis of any of the foregoing embodiments, as shown in fig. 7, after step 103, the method further includes:
And 402, calculating the running speed of the target vehicle according to the first coordinate, the second coordinate and the time interval between the previous moment and the current moment.
And step 403, judging whether the target vehicle is driven in an overspeed mode according to the running speed.
In this embodiment, since the image capturing device may send the road surface image according to the preset time interval, and the position of the same target vehicle in the road surface image may also change at two different times, the vehicle speed of the target vehicle may be calculated according to different position information and the preset time interval.
Specifically, for each target vehicle, a first coordinate (x) corresponding to the target vehicle at a previous time may be determined separately0，y0) And a second coordinate (x) of the current time1，y1). And calculating the running speed of the target vehicle according to the first coordinate, the second coordinate and the time interval between the previous moment and the current moment. The calculation formula of the running speed can be shown as formula 1:
V＝{【[x0-x1]2+[y0-y1]2】0.5}*R/t
where V is the traveling speed of the target vehicle, (x)0，y0) Is a first coordinate, (x)1，y1) And R is a second coordinate, R is a scale arranged in the monitored intersection region, and t is a preset time interval.
And it is possible to detect whether the target vehicle is speeding or not based on the running speed. Specifically, the driving speed may be compared with a preset speed threshold, and if the driving speed exceeds the preset speed threshold, the target vehicle is represented to run at an overspeed, otherwise, the target vehicle is represented to run safely. Wherein the speed threshold may be set according to a specific location, which is not limited by the present disclosure.
Further, if the target vehicle does not run safely, alarm information is sent to a law enforcement agency, and/or the target vehicle is controlled to remind driver of dangerous driving.
According to the vehicle information processing method provided by the embodiment, the running speed of the target vehicle is calculated according to the central point of the target and the preset time interval, so that whether the target vehicle runs at an overspeed or not can be accurately determined on the basis of no need of assistance of other traffic elements, and traffic safety is guaranteed.
Fig. 8 is a schematic structural diagram of a vehicle information processing device according to a fifth embodiment of the present disclosure, and as shown in fig. 9, the device includes: the device comprises an acquisition module 51, an identification module 52, a determination module 53 and a judgment module 54, wherein the acquisition module 51 is used for acquiring a road surface image acquired by an image acquisition device. And the identification module 52 is used for identifying the road information in the road surface image. And a determining module 53, configured to identify target vehicles in the road information, and determine center point information corresponding to each target vehicle. A determining module 54, configured to determine whether the target vehicle is safely driven according to the center point information and a safe driving area, and obtain a determination result, where the safe driving area is determined according to a center line of the road information and a preset range threshold.
Further, the determining module is configured to: if the central point information is in the safe driving area, judging that the target vehicle is safely driven; and if the central point information is not in the safe driving area, judging that the target vehicle is driven dangerously.
Further, the apparatus further comprises: and the preprocessing module is used for carrying out size remodeling operation and/or gray normalization and/or brightness normalization processing on the road surface image.
Further, the apparatus further comprises: and the processing module is used for sending alarm information to a law enforcement agency and/or controlling the target vehicle to remind dangerous driving if the target vehicle does not run safely.
The vehicle information processing apparatus provided by the present embodiment determines the center point information of the target vehicle in the road surface by performing an image processing operation on the road surface image after acquiring the road surface image. And determining whether the current target vehicle is safely driven according to the center point information and a preset safe driving area, wherein the safe driving area is determined according to the central line of the identified road information and a preset range threshold. The method does not need to adopt traffic elements in other roads, such as road sign lines, traffic lights and the like, to carry out auxiliary calculation, thereby being suitable for traffic scenes of various roads, effectively limiting the identification operation of whether vehicles safely run under the traffic scene of a single road, and ensuring the traffic safety of the traffic scene of the single road.
Fig. 9 is a schematic structural diagram of a vehicle information processing device according to a sixth embodiment of the present disclosure, and on the basis of the fifth embodiment, as shown in fig. 9, the identification module specifically includes: the road surface image recognition method comprises a recognition unit 61, a detection unit 62 and a fitting unit 63, wherein the recognition unit 61 is used for recognizing a road area in the road surface image through a preset segmentation network. And the detection unit 62 is configured to perform pixel connected region detection operation on the road region to obtain boundary information corresponding to the road region. And the fitting unit 63 is configured to perform fitting operation on the boundary information by using a line to obtain the road information.
Further, on the basis of any of the above embodiments, the determining module includes: the system comprises a vehicle detection unit and a target vehicle identification unit, wherein the vehicle detection unit is used for detecting all vehicles in the road information through a preset target detection model; and the target vehicle identification unit is used for identifying all motor vehicles as the target vehicles in all the vehicles through a preset vehicle type identification model.
Fig. 10 is a schematic structural diagram of a vehicle information processing device according to a seventh embodiment of the present disclosure, where on the basis of any of the foregoing embodiments, as shown in fig. 10, the determining module includes: the system comprises a key point detection unit 71 and a central point determination unit 72, wherein the key point detection unit 71 is configured to detect a preset number of pieces of key point information corresponding to each target vehicle through a preset key point detection model; the central point determining unit 72 is configured to connect the key point information according to a preset connection rule to obtain information of at least two connection lines, and use an intersection point of the at least two connection lines as the central point information.
Fig. 11 is a schematic structural diagram of a vehicle information processing device according to an eighth embodiment of the present disclosure, where on the basis of any of the foregoing embodiments, as shown in fig. 11, the device further includes: the system comprises a coordinate determination module 81, a calculation module 82 and an overspeed judgment module 83, wherein the coordinate determination module 81 is used for respectively determining a first coordinate corresponding to a previous moment of a target vehicle and a second coordinate corresponding to a current moment of the target vehicle for each target vehicle; a calculating module 82, configured to calculate a running speed of the target vehicle according to the first coordinate, the second coordinate, and a time interval between the previous time and the current time; and an overspeed judging module 83, configured to judge whether the target vehicle is driven in an overspeed manner according to the driving speed.
Fig. 12 is a schematic structural diagram of a vehicle information processing apparatus according to a ninth embodiment of the present disclosure, and as shown in fig. 12, the apparatus includes: a memory 91, a processor 92;
a memory 91; a memory 91 for storing instructions executable by the processor 92;
wherein the processor 92 is configured to execute the vehicle information processing method according to any one of the above embodiments by the processor 92.
The memory 91 stores programs. In particular, the program may include program code comprising computer operating instructions. The memory 91 may comprise a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor 92 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present disclosure.
Alternatively, in a specific implementation, if the memory 91 and the processor 92 are implemented independently, the memory 91 and the processor 92 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 3, but this does not mean only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 91 and the processor 92 are integrated on a chip, the memory 91 and the processor 92 may complete the same communication through an internal interface.
Still another embodiment of the present disclosure provides a computer-readable storage medium having stored therein computer-executable instructions for implementing the vehicle information processing method according to any one of the above embodiments when executed by a processor.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working process of the apparatus described above may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; while the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.
Claims (18)
1. A vehicle information processing method characterized by comprising:
acquiring a road surface image acquired by an image acquisition device;
identifying road information in the road surface image;
identifying target vehicles in the road information, and determining central point information corresponding to each target vehicle;
and judging whether the target vehicle runs safely according to the central point information and a safe running area to obtain a judgment result, wherein the safe running area is determined according to the central line of the road information and a preset range threshold.
2. The method of claim 1, wherein the identifying the road information in the road surface image comprises:
identifying a road area in the road surface image through a preset segmentation network;
carrying out pixel connected region detection operation on the road region to obtain boundary information corresponding to the road region;
and fitting the boundary information by adopting lines to obtain the road information.
3. The method of claim 1, wherein the identifying a target vehicle in the road information comprises:
detecting all vehicles in the road information through a preset target detection model;
and identifying all motor vehicles as the target vehicle in all the vehicles through a preset vehicle type identification model.
4. The method of claim 1, wherein the determining the center point information corresponding to each of the target vehicles comprises:
detecting a preset number of key point information corresponding to each target vehicle through a preset key point detection model;
and connecting the key point information according to a preset connection rule to obtain at least two pieces of connecting line information, and taking the intersection point of the at least two connecting lines as the central point information.
5. The method according to any one of claims 1 to 4, wherein the determining whether the target vehicle is safely driven according to the center point information and a safe driving area to obtain a determination result comprises:
if the central point information is in the safe driving area, judging that the target vehicle is safely driven;
and if the central point information is not in the safe driving area, judging that the target vehicle is driven dangerously.
6. The method according to any one of claims 1 to 4, wherein after acquiring the road surface image acquired by the image acquisition device, the method further comprises:
and carrying out size remodeling operation and/or gray normalization and/or brightness normalization processing on the road surface image.
7. The method according to any one of claims 1-4, wherein after determining the center point information corresponding to each of the target vehicles, further comprising:
respectively determining a first coordinate corresponding to the target vehicle at the previous moment and a second coordinate corresponding to the current moment for each target vehicle;
calculating the running speed of the target vehicle according to the first coordinate, the second coordinate and the time interval between the previous moment and the current moment;
and judging whether the target vehicle is driven in an overspeed mode according to the running speed.
8. The method according to any one of claims 1 to 4, wherein the determining whether the target vehicle is safely driven according to the center point information and the safe driving area further comprises:
and if the target vehicle does not safely run, sending alarm information to a law enforcement agency, and/or controlling the target vehicle to remind dangerous driving.
9. A vehicle information processing apparatus characterized by comprising:
the acquisition module is used for acquiring the road surface image acquired by the image acquisition device;
the identification module is used for identifying road information in the road surface image;
the determining module is used for identifying target vehicles in the road information and determining central point information corresponding to each target vehicle;
and the judging module is used for judging whether the target vehicle runs safely according to the central point information and a safe running area to obtain a judging result, wherein the safe running area is determined according to the central line of the road information and a preset range threshold.
10. The apparatus of claim 9, wherein the identification module comprises:
the identification unit is used for identifying a road area in the road surface image through a preset segmentation network;
the detection unit is used for carrying out pixel connected region detection operation on the road region to obtain boundary information corresponding to the road region;
and the fitting unit is used for performing fitting operation on the boundary information by adopting lines to obtain the road information.
11. The apparatus of claim 9, wherein the determining module comprises:
the vehicle detection unit is used for detecting all vehicles in the road information through a preset target detection model;
and the target vehicle identification unit is used for identifying all motor vehicles as the target vehicles in all the vehicles through a preset vehicle type identification model.
12. The apparatus of claim 9, wherein the determining module comprises:
the key point detection unit is used for detecting the key point information of a preset number corresponding to each target vehicle through a preset key point detection model;
and the central point determining unit is used for connecting the key point information according to a preset connection rule to obtain at least two pieces of connecting line information, and taking the intersection point of the at least two connecting lines as the central point information.
13. The apparatus according to any one of claims 9-12, wherein the determining module is configured to:
if the central point information is in the safe driving area, judging that the target vehicle is safely driven;
and if the central point information is not in the safe driving area, judging that the target vehicle is driven dangerously.
14. The apparatus according to any one of claims 9-12, further comprising:
and the preprocessing module is used for carrying out size remodeling operation and/or gray normalization and/or brightness normalization processing on the road surface image.
15. The apparatus according to any one of claims 9-12, further comprising:
the coordinate determination module is used for respectively determining a first coordinate corresponding to the target vehicle at the previous moment and a second coordinate corresponding to the current moment for each target vehicle;
the calculation module is used for calculating the running speed of the target vehicle according to the first coordinate, the second coordinate and the time interval between the previous moment and the current moment;
and the overspeed judging module is used for judging whether the target vehicle is subjected to overspeed driving according to the running speed.
16. The apparatus according to any one of claims 9-12, further comprising:
and the processing module is used for sending alarm information to a law enforcement agency and/or controlling the target vehicle to remind dangerous driving if the target vehicle does not run safely.
17. A vehicular information processing apparatus characterized by comprising: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the vehicle information processing method according to any one of claims 1 to 8 by the processor.
18. A computer-readable storage medium having stored therein computer-executable instructions for implementing the vehicle information processing method according to any one of claims 1 to 8 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010823943.XA CN111967384A (en) | 2020-08-17 | 2020-08-17 | Vehicle information processing method, device, equipment and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010823943.XA CN111967384A (en) | 2020-08-17 | 2020-08-17 | Vehicle information processing method, device, equipment and computer readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111967384A true CN111967384A (en) | 2020-11-20 |
Family
ID=73389592
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010823943.XA Pending CN111967384A (en) | 2020-08-17 | 2020-08-17 | Vehicle information processing method, device, equipment and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111967384A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112732859A (en) * | 2021-01-25 | 2021-04-30 | 腾讯科技（深圳）有限公司 | Prompt information generation method and device, electronic equipment and storage medium |
| CN112990114A (en) * | 2021-04-21 | 2021-06-18 | 四川见山科技有限责任公司 | Traffic data visualization simulation method and system based on AI identification |
| CN113968229A (en) * | 2021-11-30 | 2022-01-25 | 广州文远知行科技有限公司 | Road area determination method and device and electronic equipment |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102295004A (en) * | 2011-06-09 | 2011-12-28 | 中国人民解放军国防科学技术大学 | Lane departure warning method |
| CN103971521A (en) * | 2014-05-19 | 2014-08-06 | 清华大学 | Method and device for detecting road traffic abnormal events in real time |
| KR20150018988A (en) * | 2013-08-12 | 2015-02-25 | 현대모비스 주식회사 | Apparatus for monitoring state of road and system for providing safe driving service with the said apparatus |
| CN104778444A (en) * | 2015-03-10 | 2015-07-15 | 公安部交通管理科学研究所 | Method for analyzing apparent characteristic of vehicle image in road scene |
| CN107031623A (en) * | 2017-03-16 | 2017-08-11 | 浙江零跑科技有限公司 | A kind of road method for early warning based on vehicle-mounted blind area camera |
| CN108216242A (en) * | 2016-12-14 | 2018-06-29 | 现代自动车株式会社 | For the device and method that the limited road of vehicle is controlled to travel |
| CN110136254A (en) * | 2019-06-13 | 2019-08-16 | 吉林大学 | Driving assistance information display methods based on dynamic probability driving map |
| CN111540237A (en) * | 2020-05-19 | 2020-08-14 | 河北德冠隆电子科技有限公司 | Method for automatically generating vehicle safety driving guarantee scheme based on multi-data fusion |
-
2020
- 2020-08-17 CN CN202010823943.XA patent/CN111967384A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102295004A (en) * | 2011-06-09 | 2011-12-28 | 中国人民解放军国防科学技术大学 | Lane departure warning method |
| KR20150018988A (en) * | 2013-08-12 | 2015-02-25 | 현대모비스 주식회사 | Apparatus for monitoring state of road and system for providing safe driving service with the said apparatus |
| CN103971521A (en) * | 2014-05-19 | 2014-08-06 | 清华大学 | Method and device for detecting road traffic abnormal events in real time |
| CN104778444A (en) * | 2015-03-10 | 2015-07-15 | 公安部交通管理科学研究所 | Method for analyzing apparent characteristic of vehicle image in road scene |
| CN108216242A (en) * | 2016-12-14 | 2018-06-29 | 现代自动车株式会社 | For the device and method that the limited road of vehicle is controlled to travel |
| CN107031623A (en) * | 2017-03-16 | 2017-08-11 | 浙江零跑科技有限公司 | A kind of road method for early warning based on vehicle-mounted blind area camera |
| CN110136254A (en) * | 2019-06-13 | 2019-08-16 | 吉林大学 | Driving assistance information display methods based on dynamic probability driving map |
| CN111540237A (en) * | 2020-05-19 | 2020-08-14 | 河北德冠隆电子科技有限公司 | Method for automatically generating vehicle safety driving guarantee scheme based on multi-data fusion |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112732859A (en) * | 2021-01-25 | 2021-04-30 | 腾讯科技（深圳）有限公司 | Prompt information generation method and device, electronic equipment and storage medium |
| CN112732859B (en) * | 2021-01-25 | 2022-05-06 | 腾讯科技（深圳）有限公司 | Prompt information generation method and device, electronic equipment and storage medium |
| CN112990114A (en) * | 2021-04-21 | 2021-06-18 | 四川见山科技有限责任公司 | Traffic data visualization simulation method and system based on AI identification |
| CN113968229A (en) * | 2021-11-30 | 2022-01-25 | 广州文远知行科技有限公司 | Road area determination method and device and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110660254B (en) | Traffic signal lamp detection and intelligent driving method and device, vehicle and electronic equipment | |
| CN111212772B (en) | Method and device for determining a driving strategy of a vehicle | |
| CN109284674B (en) | Method and device for determining lane line | |
| CN111815959B (en) | Vehicle violation detection method and device and computer readable storage medium | |
| CN111967384A (en) | Vehicle information processing method, device, equipment and computer readable storage medium | |
| CN106647776B (en) | Method and device for judging lane changing trend of vehicle and computer storage medium | |
| JP2002083297A (en) | Object recognition method and object recognition device | |
| CN107909012B (en) | Real-time vehicle tracking detection method and device based on disparity map | |
| CN110458050B (en) | Vehicle cut-in detection method and device based on vehicle-mounted video | |
| CN112149649B (en) | Road spray detection method, computer equipment and storage medium | |
| CN111145569A (en) | Road monitoring and vehicle running control method and device and vehicle-road cooperative system | |
| CN113469115A (en) | Method and apparatus for outputting information | |
| CN110969843B (en) | Traffic sign identification alarm method with inhibition strategy | |
| WO2024098992A1 (en) | Vehicle reversing detection method and apparatus | |
| CN113297939A (en) | Obstacle detection method, system, terminal device and storage medium | |
| CN114693722B (en) | Vehicle driving behavior detection method, detection device and detection equipment | |
| CN115965926A (en) | Vehicle-mounted road sign line inspection system | |
| CN116152753A (en) | Vehicle information identification method and system, storage medium and electronic device | |
| CN115019511A (en) | Method and device for identifying illegal lane change of motor vehicle based on automatic driving vehicle | |
| CN115359438A (en) | Vehicle jam detection method, system and device based on computer vision | |
| KR20200020193A (en) | Edge-cloud system for collecting and providing data of connected car | |
| CN114998861A (en) | Method and device for detecting distance between vehicle and obstacle | |
| CN115546744A (en) | Lane detection using DBSCAN | |
| CN114494938A (en) | Non-motor vehicle behavior identification method and related device | |
| CN113591673A (en) | Method and device for recognizing traffic signs |
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 |