CN115675454B - Vehicle collision recognition method, vehicle-mounted terminal, vehicle, and storage medium - Google Patents
Vehicle collision recognition method, vehicle-mounted terminal, vehicle, and storage medium Download PDFInfo
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- CN115675454B CN115675454B CN202211679446.2A CN202211679446A CN115675454B CN 115675454 B CN115675454 B CN 115675454B CN 202211679446 A CN202211679446 A CN 202211679446A CN 115675454 B CN115675454 B CN 115675454B
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Abstract
According to the vehicle collision recognition method, the vehicle-mounted terminal, the vehicle and the storage medium provided by the embodiment of the invention, firstly, the track of a target vehicle and multi-frame images of side vehicles are obtained; then identifying each frame of image of the side vehicle, determining a front wheel center point and a rear wheel center point of the side vehicle close to one side of the target vehicle under each frame of image, and determining the relative speed of the side vehicle relative to the target vehicle; determining the track of the side vehicle according to the central point of the front wheel and the central point of the rear wheel under each frame of image; and finally determining a collision prediction result of the target vehicle according to the track of the target vehicle, the track of the side vehicle and the relative speed. Through the ray with the central point place of front and back wheel as the prediction orbit of side vehicle, for the mode that directly carries out the orbit prediction according to automobile body or locomotive direction among the prior art, can make the orbit of discerning more accurate to improve the degree of accuracy of collision discernment, effectively avoid the emergence of vehicle collision.
Description
Technical Field
The application belongs to the technical field of intelligent driving, and particularly relates to a vehicle collision recognition method, a vehicle-mounted terminal, a vehicle and a storage medium.
Background
With the rapid development of advanced technologies such as multi-sensor information fusion, modern control theory, artificial intelligence and large-scale integrated circuits, automobile intellectualization aiming at improving the autonomous driving capability and driving safety of vehicles has become a research focus in the field of vehicle engineering. In order to fully excavate the human-like characteristics of the intelligent vehicle, the motion prediction of surrounding vehicles in a dynamic environment and the deep research of the collision risk of the intelligent vehicle are developed, so that the intelligent degree and the safety level of the vehicle are improved.
Collision recognition generally relies on trajectory prediction of surrounding vehicles, in the prior art, the driving direction of a vehicle is generally directly recognized, and a trajectory is drawn from the head of the vehicle according to the driving direction of the vehicle, but the drawn trajectory may not be accurate due to errors in recognition of the driving direction of the vehicle, so that the accuracy of collision recognition is low.
Disclosure of Invention
In view of this, the invention provides a vehicle collision recognition method, a vehicle-mounted terminal, a vehicle and a storage medium, and aims to solve the problem of low accuracy of collision recognition in the prior art.
A first aspect of an embodiment of the present invention provides a vehicle collision recognition method, which is applied to a target vehicle, and includes:
acquiring a track of a target vehicle and multi-frame images of vehicles at the sides of the target vehicle;
identifying each frame of image of the side vehicle, determining a front wheel central point and a rear wheel central point of one side of the side vehicle close to the target vehicle under each frame of image, and determining the relative speed of the side vehicle relative to the target vehicle;
determining the track of the side vehicle according to the central point of the front wheel and the central point of the rear wheel under each frame of image;
and determining a collision prediction result of the target vehicle according to the track of the target vehicle, the track of the side vehicle and the relative speed.
A second aspect of an embodiment of the present invention provides a vehicle collision recognition apparatus applied to a target vehicle, the apparatus including:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring a track of a target vehicle and a multi-frame image of a vehicle at the side of the target vehicle;
the identification module is used for identifying each frame of image of the side vehicle, determining the center point of a front wheel and the center point of a rear wheel of the side vehicle close to one side of the target vehicle under each frame of image, and determining the relative speed of the side vehicle relative to the target vehicle;
the determining module is used for determining the track of the side vehicle according to the central point of the front wheel and the central point of the rear wheel under each frame of image;
and the prediction module is used for determining a collision prediction result of the target vehicle according to the track of the target vehicle, the track of the side vehicle and the relative speed.
A third aspect of the embodiments of the present invention provides a vehicle-mounted terminal, which includes a memory, a processor, and a computer program stored in the memory and operable on the processor, wherein the processor implements the steps of the vehicle collision recognition method according to the first aspect when executing the computer program.
A fourth aspect of an embodiment of the present invention provides a vehicle, including: an image acquisition device, a gyroscope, and the in-vehicle terminal of the third aspect.
A fifth aspect of the embodiments of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the vehicle collision recognition method of the first aspect as described above.
According to the vehicle collision recognition method, the vehicle-mounted terminal, the vehicle and the storage medium provided by the embodiment of the invention, firstly, the track of a target vehicle and a multi-frame image of a vehicle at the side of the target vehicle are obtained; then identifying each frame of image of the side vehicle, determining the center point of a front wheel and the center point of a rear wheel of one side of the side vehicle close to the target vehicle under each frame of image, and determining the relative speed of the side vehicle relative to the target vehicle; determining the track of the side vehicle according to the central point of the front wheel and the central point of the rear wheel under each frame of image; and finally determining a collision prediction result of the target vehicle according to the track of the target vehicle, the track of the side vehicle and the relative speed. Through the ray with the central point place of front and back wheel as the prediction orbit of side vehicle, for the mode that directly carries out the orbit prediction according to automobile body or locomotive direction among the prior art, the central point of wheel is the point that changes in the accurate discernment, consequently can make the orbit of discernment more accurate to improve the degree of accuracy of collision discernment, effectively avoid the emergence of vehicle collision.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a diagram of an application scenario of a vehicle collision recognition method according to an embodiment of the present invention;
FIG. 2 is a flow chart of an implementation of a vehicle collision recognition method provided by an embodiment of the invention;
FIG. 3 is a schematic diagram of a lateral vehicle trajectory;
FIG. 4 is a schematic diagram of the calculation of relative velocity;
fig. 5 is a schematic structural view of a vehicle collision recognition apparatus provided by an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an in-vehicle terminal according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
Fig. 1 is an application scenario diagram of a vehicle collision recognition method according to an embodiment of the present invention. The vehicle collision recognition method provided by the invention can be applied to the application scene, but is not limited to the application scene. In the embodiment of the present invention, the vehicle may be a passenger vehicle, such as a car, a minibus, an SUV, or the like, or may be a commercial vehicle, which is not limited herein. The vehicle includes: an image acquisition device 11, a gyroscope 12, and an in-vehicle terminal 13.
The image acquisition device 11 is arranged on the right side of the vehicle and used for shooting images on two sides of the vehicle and sending the images to the vehicle-mounted terminal 13, and the image acquisition device 11 and the gyroscope 12 are both connected with the vehicle-mounted terminal 13. The gyroscope 12 may determine the steering angle of the vehicle, the in-vehicle terminal 13 may determine the trajectory of itself from the gyroscope 12, and then the in-vehicle terminal 13 recognizes the vehicle closest to the own vehicle in the image as a side vehicle, and determines the relative speed and trajectory with the side vehicle, thereby determining whether there is a possibility of collision between the two vehicles.
Fig. 2 is a flowchart of an implementation of a vehicle collision recognition method according to an embodiment of the present invention. As shown in fig. 2, in some embodiments, a vehicle collision recognition method, applied to the target vehicle shown in fig. 1, includes:
s210, acquiring a track of the target vehicle and multi-frame images of vehicles on the sides of the target vehicle.
In the embodiment of the invention, the target vehicle can determine the inner steering angle and the outer steering angle of the vehicle according to the gyroscope arranged on the target vehicle during running, so that the track of the vehicle can be accurately predicted. During the running process of the target vehicle, images of two sides of the target vehicle are shot in real time, the vehicle closest to the target vehicle is determined as a side vehicle, and then the image of each frame of the vehicle below the side vehicle is recorded.
S220, identifying each frame of image of the side vehicle, determining a front wheel center point and a rear wheel center point of the side vehicle close to one side of the target vehicle under each frame of image, and determining the relative speed of the side vehicle relative to the target vehicle.
In the embodiment of the present invention, the identification of each frame of image of the lateral vehicle may be implemented according to a pre-established neural network model, or may be implemented according to a Single Shot multi box Detector (SSD) model, which is not limited herein.
Fig. 3 is a schematic diagram of the trajectory of a side vehicle. As shown in fig. 3, the pre-established neural network first identifies the side vehicle with the closest distance, then identifies two wheels in the target frame where the side vehicle is located, and finally determines the center points of the two wheels in the target frames where the two wheels are located. Finally, fig. 4 is a schematic diagram of the calculation of the relative velocity. As shown in fig. 4, a reference point may be selected on the target frame where the side vehicle is located, and the relative speed of the two vehicles may be determined according to the moving speed of the reference point, for example, the upper left corner of the target frame may be marked as the reference point. For example, when the moving speed of the reference point is calculated to determine the relative speed of the two vehicles, the captured images of the lateral vehicles may be divided into uniform grids, the ordinate of each grid corresponds to a preset speed a, if the ordinate of the reference point in two adjacent captures rises by 2 grids, the relative speed is 2a, if the ordinate of the reference point in two adjacent captures falls by 2 grids, the relative speed is-2 a, and if the reference points in two adjacent captures are both in the same grid, the relative speed is 0.
And S230, determining the track of the side vehicle according to the center point of the front wheel and the center point of the rear wheel under each frame of image.
In the embodiment of the invention, the central point of the rear wheel is used as a vertex, and a ray passing through the central point of the front wheel is taken, so that the track of the side vehicle can be obtained.
And S240, determining a collision prediction result of the target vehicle according to the track of the target vehicle, the track of the side vehicle and the relative speed.
In the embodiment of the invention, whether the target vehicle and the side vehicle intersect can be determined according to the track of the target vehicle and the track of the side vehicle, and if so, whether the target vehicle and the side vehicle collide at the intersection is determined according to the relative speed.
In the embodiment of the invention, the ray where the central points of the front and rear wheels are located is used as the predicted track of the side vehicle, and compared with the mode of directly predicting the track according to the direction of the vehicle body or the direction of the vehicle head in the prior art, the central points of the wheels are points which are easier to accurately identify, so that the identified track can be more accurate, the accuracy of collision identification is improved, and the occurrence of vehicle collision is effectively avoided.
In some embodiments, S220 may include: identifying the position of the side vehicle in each frame of image to obtain the position variation of the side vehicle; the relative speed of the side vehicle with respect to the target vehicle is determined based on the amount of change in the position of the side vehicle.
In the embodiment of the present invention, the distance between reference points in two adjacent shots may be directly calculated, the relative speed may also be determined according to the manner of drawing a grid in the above embodiment, and the relative speed may also be calculated according to the position change of the wheel center point in two adjacent frames of images, which is not limited herein.
In some embodiments, S240 may include: judging whether the track of the target vehicle is intersected with the track of the side vehicle; if the track of the target vehicle is intersected with the track of the side vehicle, determining collision time according to the relative speed, wherein the collision time is the time difference between the target vehicle and the side vehicle when the target vehicle and the side vehicle reach the intersection point of the intersected tracks; and determining a collision prediction result of the target vehicle according to the collision time.
In the embodiment of the invention, the distances from the target vehicle to the intersection point of the tracks of the side vehicles can be respectively calculated, then the distances are divided by the respective vehicle speeds, so that the time from the target vehicle to the intersection point of the tracks of the side vehicles can be obtained, and then the time difference can be obtained by carrying out subtraction. Wherein the vehicle speed of the side vehicle is equal to the vehicle speed of the target vehicle plus the relative speed.
In some embodiments, determining the time-to-collision based on the relative velocity comprises:
wherein, the first and the second end of the pipe are connected with each other,S s as the time of the collision,Cis the length of the trajectory of the side vehicle,r a is the turning radius of the trajectory of the target vehicle,v 1 is the speed of the target vehicle,v 2 the vehicle speed of the side vehicle is set,v 1 =v+v 2 ，vis the relative velocity.
In some embodiments, the turning radius is determined according to the following equation:
wherein the content of the first and second substances,sis the width of the rut of the target vehicle,r 0 is the scrub radius of the target vehicle,jis the distance between the steering shafts of the subject vehicle,L kt is the wheel base of the target vehicle,β i is the inboard steering angle of the subject vehicle,β ao for the theoretical value of the outside steering angle of the target vehicle,β a is the actual value of the outside steering angle of the target vehicle,β F is the steering slip angle of the target vehicle.
In some embodiments, determining a collision prediction of the target vehicle based on the time of collision includes: when the collision time is less than a first preset time, determining that the collision prediction result of the target vehicle is possible to generate collision; when the collision time is less than a second preset time, determining that the collision prediction result of the target vehicle is about to collide; the first preset time is longer than the second preset time;
correspondingly, the vehicle collision recognition method further comprises the following steps: when the collision prediction result is that collision is possible, a deceleration early warning signal is sent out; when the collision prediction result is an imminent collision, the control target vehicle is decelerated.
In the embodiment of the invention, the first preset time and the second preset time can be adjusted according to the vehicle speed, when the vehicle speed is higher, the first preset time and the second preset time can be properly increased, so that the collision risk is further reduced, and when the vehicle speed is lower, the first preset time and the second preset time are properly increased, so that repeated adjustment/early warning is avoided.
In some embodiments, prior to S240, the vehicle collision recognition method further comprises: identifying each frame image of the side vehicle, and determining the length-width ratio of the wheels of the side vehicle in each frame image; determining a turning angle of the side vehicle according to the track of the side vehicle and the length-width ratio of the wheels of the side vehicle in each frame image; correcting the track of the side vehicle according to the turning angle of the side vehicle to obtain a corrected track of the side vehicle; accordingly, S240 may include: and determining a collision prediction result of the target vehicle according to the track of the target vehicle, the corrected track of the side vehicle and the relative speed.
In the embodiment of the present invention, when the side vehicle traveling direction and the relative position between the image capturing device of the target vehicle and the side vehicle are determined, the aspect ratio of the wheels of the side vehicle is generally not changed, and if a change in the aspect ratio of the wheels is detected at this time, it indicates that the side vehicle is turning at this time, and therefore, the trajectory of the side vehicle needs to be corrected. The running direction of each side vehicle and the aspect ratio of the wheel of the side vehicle corresponding to the relative position between the image acquisition device of each target vehicle and the side vehicle under the condition of straight running can be stored in advance in a table form, then when the side vehicle is identified, the aspect ratio (namely the ratio of the horizontal direction length and the vertical direction length of the target frame where the wheel is located) of the current wheel of the side vehicle in straight running can be determined by directly looking up the table, and for the right side vehicle, if the aspect ratio is larger than the aspect ratio in straight running, the right side wheel turns left, otherwise, the right side wheel turns right.
In conclusion, the beneficial effects of the invention are as follows: whether the tracks of the target vehicle and the tracks of the side vehicles intersect can be determined according to the track of the target vehicle and the track of the side vehicles, and if the tracks of the target vehicle and the tracks of the side vehicles intersect, whether the target vehicle and the side vehicles collide at the intersection is determined according to the relative speed.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 5 is a schematic structural diagram of a vehicle collision recognition apparatus provided in an embodiment of the present invention. As shown in fig. 5, in some embodiments, a vehicle collision recognition apparatus 5, applied to a target vehicle, includes:
the acquiring module 510 is configured to acquire a track of the target vehicle and a multi-frame image of a vehicle lateral to the target vehicle.
And the identifying module 520 is used for identifying each frame of image of the side vehicle, determining a front wheel center point and a rear wheel center point of one side of the side vehicle close to the target vehicle under each frame of image, and determining the relative speed of the side vehicle relative to the target vehicle.
The determining module 530 is configured to determine a track of the side vehicle according to a center point of the front wheel and a center point of the rear wheel in each frame of image.
And the predicting module 540 is used for determining a collision predicting result of the target vehicle according to the track of the target vehicle, the track of the side vehicle and the relative speed.
Optionally, the identification module is specifically configured to identify a position of the side vehicle in each frame of image, so as to obtain a position variation of the side vehicle; the relative speed of the side vehicle with respect to the target vehicle is determined based on the amount of change in the position of the side vehicle.
Optionally, the predicting module 540 is specifically configured to: judging whether the track of the target vehicle is intersected with the track of the side vehicle; if the track of the target vehicle is intersected with the track of the side vehicle, determining collision time according to the relative speed, wherein the collision time is the time difference between the target vehicle and the side vehicle when the target vehicle and the side vehicle reach the intersection point of the intersected tracks; and determining a collision prediction result of the target vehicle according to the collision time.
Optionally, the predicting module 540 is specifically configured to:
wherein the content of the first and second substances,S s as the time of the collision,Cis the length of the trajectory of the side vehicle,r a is the turning radius of the trajectory of the target vehicle,v 1 is the speed of the target vehicle,v 2 the vehicle speed of the side vehicle is set,v 1 =v+v 2 ，vis the relative velocity.
Optionally, the turning radius is determined according to the following formula:
wherein the content of the first and second substances,sis the rut width of the target vehicle,r 0 is the scrub radius of the target vehicle,jis the distance between the steering shafts of the subject vehicle,L kt is the wheel base of the target vehicle,β i is the inboard steering angle of the subject vehicle,β ao a theoretical value of the outside steering angle of the target vehicle,β a is the actual value of the outside steering angle of the target vehicle,β F is the steering slip angle of the target vehicle.
Optionally, the predicting module 540 is specifically configured to: when the collision time is less than a first preset time, determining that the collision prediction result of the target vehicle is possible to generate collision; when the collision time is less than a second preset time, determining that the collision prediction result of the target vehicle is about to collide; the first preset time is longer than the second preset time; accordingly, the vehicle collision recognition device 5 further includes: when the collision prediction result is that collision is possible, sending a deceleration early warning signal; when the collision prediction result is an imminent collision, the control target vehicle decelerates.
Optionally, the vehicle collision recognition device 5 further includes: the correction module is used for identifying each frame of image of the side vehicle and determining the length-width ratio of wheels of the side vehicle in each frame of image; determining a turning angle of the side vehicle according to the track of the side vehicle and the length-width ratio of the wheels of the side vehicle in each frame image; the trajectory of the side vehicle is corrected according to the turning angle of the side vehicle, and a corrected trajectory of the side vehicle is obtained. Accordingly, the prediction module 540 is configured to determine a collision prediction result of the target vehicle according to the trajectory of the target vehicle, the corrected trajectory of the side vehicle, and the relative speed.
The vehicle collision recognition device provided by the embodiment can be used for executing the method embodiments, the implementation principle and the technical effect are similar, and the details are not repeated here.
Fig. 6 is a schematic structural diagram of an in-vehicle terminal according to an embodiment of the present invention. As shown in fig. 6, an embodiment of the present invention provides an in-vehicle terminal 6, where the in-vehicle terminal 6 of the embodiment includes: a processor 60, a memory 61, and a computer program 62 stored in the memory 61 and executable on the processor 60. The processor 60, when executing the computer program 62, implements the steps in the various vehicle collision recognition method embodiments described above, such as steps 210-240 shown in fig. 2. Alternatively, the processor 60, when executing the computer program 62, implements the functions of the various modules/units in the various system embodiments described above, such as the functions of the modules 510 to 540 shown in fig. 5.
Illustratively, the computer program 62 may be divided into one or more modules/units, which are stored in the memory 61 and executed by the processor 60 to implement the present invention. One or more of the modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 62 in the in-vehicle terminal 6.
The vehicle-mounted terminal 6 may be a terminal or a server, wherein the terminal may be a mobile phone, an MCU, an ECU, and the like, and is not limited herein, and the server may be a physical server, a cloud server, and the like, and is not limited herein. The in-vehicle terminal 6 may include, but is not limited to, a processor 60, a memory 61. Those skilled in the art will appreciate that fig. 6 is only an example of the in-vehicle terminal 6, and does not constitute a limitation to the in-vehicle terminal 6, and may include more or less components than those shown, or combine some components, or different components, for example, the terminal may further include an input-output device, a network access device, a bus, etc.
The Processor 60 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 61 may be an internal storage unit of the in-vehicle terminal 6, such as a hard disk or a memory of the in-vehicle terminal 6. The memory 61 may be an external storage device of the in-vehicle terminal 6, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like provided on the in-vehicle terminal 6. Further, the memory 61 may also include both an internal storage unit of the in-vehicle terminal 6 and an external storage device. The memory 61 is used for storing computer programs and other programs and data required by the terminal. The memory 61 may also be used to temporarily store data that has been output or is to be output.
Embodiments of the present invention provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned vehicle collision recognition method embodiments are implemented.
The computer-readable storage medium stores a computer program 62, the computer program 62 includes program instructions, and when the program instructions are executed by the processor 60, all or part of the processes in the method according to the above embodiments may be implemented by the computer program 62 instructing related hardware, and the computer program 62 may be stored in a computer-readable storage medium, and when the computer program 62 is executed by the processor 60, the steps of the above embodiments of the method may be implemented. The computer program 62 comprises, inter alia, computer program code, which may be in the form of source code, object code, an executable file or some intermediate form. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, software distribution medium, etc.
The computer readable storage medium may be an internal storage unit of the terminal of any of the foregoing embodiments, for example, a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk provided on the terminal, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is used for storing a computer program and other programs and data required by the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by functions and internal logic of the process, and should not limit the implementation process of the embodiments of the present invention in any way.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. For the specific working processes of the units and modules in the system, reference may be made to the corresponding processes in the foregoing method embodiments, which are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, a module or a unit may be divided into only one logical function, and may be implemented in other ways, for example, a plurality of 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, devices or units, and may be in an electrical, mechanical or other form.
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 network 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 may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method according to the embodiments of the present invention may also be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the embodiments of the method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, software distribution medium, etc.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (9)
1. A vehicle collision recognition method, applied to a target vehicle, the method comprising:
acquiring a track of a target vehicle and multi-frame images of vehicles at the sides of the target vehicle;
identifying each frame of image of the side vehicle, determining a front wheel center point and a rear wheel center point of one side, close to the target vehicle, of the side vehicle under each frame of image, and determining the relative speed of the side vehicle relative to the target vehicle;
taking the central point of the rear wheel as a vertex under each frame of image, and making a ray passing through the central point of the front wheel to obtain the track of the side vehicle under each frame of image;
identifying each frame image of the side vehicle, and determining the aspect ratio of the wheels of the side vehicle in each frame image;
according to the track of the side vehicle and the aspect ratio of the wheels of the side vehicle in each frame image,
determining the aspect ratio of the current side vehicle wheel when the side vehicle wheel moves straight by looking up a table from a pre-stored table;
determining a turning angle of the side vehicle from an aspect ratio of the wheels of the side vehicle and an aspect ratio of the wheels of the side vehicle when the wheels are traveling straight;
correcting the track of the side vehicle according to the turning angle of the side vehicle to obtain a corrected track of the side vehicle;
and determining a collision prediction result of the target vehicle according to the track of the target vehicle, the corrected track of the side vehicle and the relative speed.
2. The vehicle collision recognition method according to claim 1, wherein the determining the relative speed of the side vehicle with respect to the target vehicle includes:
identifying the position of the side vehicle in each frame of image to obtain the position variation of the side vehicle;
and determining the relative speed of the side vehicle relative to the target vehicle according to the position change amount of the side vehicle.
3. The vehicle collision recognition method according to claim 1, wherein determining the collision prediction result of the target vehicle based on the trajectory of the target vehicle, the corrected trajectory of the side vehicle, and the relative speed includes:
judging whether the track of the target vehicle is intersected with the corrected track of the side vehicle;
if the track of the target vehicle is intersected with the corrected track of the side vehicle, determining collision time according to the vehicle speed of the target vehicle and the relative speed, wherein the collision time is the time difference between the target vehicle and the side vehicle when the track of the side vehicle is intersected with the arrival track of the target vehicle;
and determining a collision prediction result of the target vehicle according to the collision time.
4. The vehicle collision recognition method according to claim 3, wherein the determining a collision time based on the vehicle speed and the relative speed of the target vehicle includes:
wherein, the first and the second end of the pipe are connected with each other,S s as the time of the collision, there is,Cis the length of the trajectory of the side vehicle,r a is the turning radius of the trajectory of the target vehicle,v 1 is the speed of the target vehicle,v 2 is the speed of the side vehicle,v 1 =v+v 2 ，vis the relative velocity.
5. The vehicle collision recognition method according to claim 4, characterized in that the turning radius is determined according to the following equation:
wherein the content of the first and second substances,sis the rut width of the target vehicle,r 0 is the scrub radius of the target vehicle,jis the distance between the steering shafts of the target vehicle,L kt is the wheel base of the target vehicle,β i is the inside steering angle of the target vehicle,β ao is a theoretical value of the outside steering angle of the target vehicle,β a is the actual value of the outside steering angle of the target vehicle,β F is the steering slip angle of the target vehicle.
6. The vehicle collision recognition method according to claim 3, wherein the determining a collision prediction result of the target vehicle according to the collision time includes:
when the collision time is less than a first preset time, determining that the collision prediction result of the target vehicle is possible to generate collision;
when the collision time is less than a second preset time, determining that the collision prediction result of the target vehicle is about to collide;
the first preset time is longer than the second preset time;
the method further comprises the following steps:
when the collision prediction result is that collision is possible, sending a deceleration early warning signal;
and when the collision prediction result is that a collision is about to occur, controlling the target vehicle to decelerate.
7. An in-vehicle terminal comprising a memory, a processor and a computer program stored in the memory and operable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the vehicle collision recognition method according to any one of claims 1 to 6 above.
8. A vehicle, characterized by comprising: image acquisition device, gyroscope and in-vehicle terminal as claimed in claim 7 above.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when being executed by a processor, carries out the steps of the vehicle collision recognition method according to any one of claims 1 to 6 above.
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| GB2518187A (en) * | 2013-09-12 | 2015-03-18 | Ford Global Tech Llc | Collision warning for a driver controlled vehicle |
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| CN108417089A (en) * | 2018-03-14 | 2018-08-17 | 杭州分数科技有限公司 | Traffic safety method for early warning, apparatus and system |
| CN113060135A (en) * | 2019-12-30 | 2021-07-02 | 厦门歌乐电子企业有限公司 | Vehicle collision prevention device and method |
| CN113362607B (en) * | 2021-08-10 | 2021-10-29 | 天津所托瑞安汽车科技有限公司 | Steering state-based blind area early warning method, device, equipment and medium |
| CN114999228B (en) * | 2022-06-01 | 2022-12-16 | 北京易航远智科技有限公司 | Anti-collision method for automatic driving vehicle in severe weather |
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