CN114332913A - Pedestrian prompt tone control method and device for electric automobile and electronic equipment - Google Patents
Pedestrian prompt tone control method and device for electric automobile and electronic equipment Download PDFInfo
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Abstract
The invention discloses a pedestrian prompt tone control method, a device and electronic equipment of an electric automobile, wherein the method comprises the steps of collecting a shot image in the driving direction, and identifying a target pedestrian in a target area of the shot image; acquiring a current gear of the electric automobile, and determining a standard prompt tone frequency corresponding to the current speed based on the current gear; and determining the crowd category corresponding to the target pedestrian, adjusting the standard prompt tone frequency based on the crowd category to obtain the adjusted prompt tone frequency, and playing the prompt tone based on the adjusted prompt tone frequency. According to the method and the device, after the standard prompt tone frequency is determined according to the current vehicle condition of the electric vehicle, the crowd category of the target pedestrian is judged in an image recognition mode, the standard prompt tone frequency is correspondingly adjusted according to different crowd categories, and the fact that the target pedestrian is not frightened while the target pedestrian can be reminded by the finally played prompt tone is guaranteed.
Description
Technical Field
The application relates to the technical field of electric automobile control, in particular to a pedestrian prompt tone control method and device of an electric automobile and electronic equipment.
Background
When an electric vehicle (a pure electric vehicle, a hybrid electric vehicle, a fuel cell vehicle and the like) runs at a low speed in a pure electric mode, the noise outside the vehicle is obviously reduced compared with an internal combustion engine vehicle, so that other users of a road, including pedestrians, bicycles and the like, are not easy to perceive the approach of the vehicle, and traffic accidents are easily caused. For the above reasons, the electric vehicle having the pure electric driving mode needs to be equipped with a device capable of emitting a warning sound during low-speed driving. In order to prevent the pedestrian from being scared by sudden loud sound during the actual driving process, the volume of the warning sound should be adjusted according to the difference between the vehicle speed and the vehicle condition. Because different pedestrians have different acceptance degrees to the volume, the current prompt tone has poor regulation and control effect on the volume, still easily scares the pedestrians, or cannot warn the pedestrians in time.
Disclosure of Invention
In order to solve the above problem, an embodiment of the application provides a pedestrian warning tone control method and device for an electric vehicle, and an electronic device.
In a first aspect, an embodiment of the present application provides a pedestrian warning tone control method for an electric vehicle, where the method includes:
acquiring a shot image in a driving direction, and identifying a target pedestrian in a target area of the shot image;
acquiring a current gear of the electric automobile, and determining a standard prompt tone frequency corresponding to the current speed based on the current gear;
and determining the crowd category corresponding to the target pedestrian, adjusting the standard prompt tone frequency based on the crowd category to obtain an adjusted prompt tone frequency, and playing a prompt tone based on the adjusted prompt tone frequency.
Preferably, the acquiring of the shot image of the driving direction includes:
acquiring the wheel rotation direction and the wheel rotation angle of the electric automobile;
determining an angle range corresponding to the wheel rotation angle, and determining a driving direction based on the angle range and the wheel rotation direction;
and acquiring shot images shot by the camera corresponding to the driving direction.
Preferably, the recognizing a target pedestrian in the target area of the captured image includes:
determining a target area in the shot image based on the wheel rotation angle and the wheel rotation direction;
identifying a target pedestrian within the target area.
Preferably, the determining the crowd category corresponding to the target pedestrian and adjusting the standard hint audio frequency based on the crowd category includes:
acquiring facial feature information of the target pedestrian, calculating the facial feature information based on a preset neural network model, and determining a crowd category corresponding to the target pedestrian;
and acquiring a frequency adjustment parameter corresponding to the crowd category, and adjusting the standard prompt audio frequency based on the frequency adjustment parameter.
Preferably, after playing the alert tone based on the adjusted alert tone frequency, the method further includes:
continuously collecting the shot images, and monitoring the facial expression characteristic change value of the target pedestrian;
and determining prompt tone feedback data based on the facial expression characteristic change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data.
Preferably, after the continuously acquiring the shot image and monitoring the facial expression feature change value of the target pedestrian, the method further includes:
when at least two target pedestrians in the same category exist, calculating a feature difference value of facial expression feature change values of the same category corresponding to the target pedestrians in the same category;
determining prompt tone feedback data based on the facial expression feature change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data, wherein the method comprises the following steps:
when at least two target pedestrians in the same category exist, comparing the characteristic difference value with a preset difference value;
when the feature difference value is not larger than a preset difference value, calculating an average facial expression feature change value of each facial expression feature change value of the same category, determining prompt tone feedback data based on the average facial expression feature change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data;
and when the characteristic difference is larger than a preset difference, the prompt tone feedback data is not determined.
In a second aspect, an embodiment of the present application provides a pedestrian prompting sound control device for an electric vehicle, the device including:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a shot image in the driving direction and identifying a target pedestrian in a target area of the shot image;
the acquisition module is used for acquiring the current gear of the electric automobile and determining the standard prompt tone frequency corresponding to the current speed based on the current gear;
and the adjusting module is used for determining the crowd category corresponding to the target pedestrian, adjusting the standard prompt tone frequency based on the crowd category to obtain an adjusted prompt tone frequency, and playing a prompt tone based on the adjusted prompt tone frequency.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method as provided in the first aspect or any one of the possible implementation manners of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method as provided in the first aspect or any one of the possible implementations of the first aspect.
The invention has the beneficial effects that: after the standard prompt tone frequency is determined according to the current vehicle condition of the electric vehicle, the crowd category of the target pedestrian is judged in an image recognition mode, the standard prompt tone frequency is correspondingly adjusted according to different crowd categories, and the fact that the target pedestrian is not frightened when the target pedestrian can be reminded by the finally played prompt tone is guaranteed.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flow chart of a pedestrian warning tone control method of an electric vehicle according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a pedestrian prompting sound control device of an electric vehicle according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
In the following description, the terms "first" and "second" are used for descriptive purposes only and are not intended to indicate or imply relative importance. The following description provides embodiments of the present application, where different embodiments may be substituted or combined, and thus the present application is intended to include all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes feature A, B, C and another embodiment includes feature B, D, then this application should also be considered to include an embodiment that includes one or more of all other possible combinations of A, B, C, D, even though this embodiment may not be explicitly recited in text below.
The following description provides examples, and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements described without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For example, the described methods may be performed in an order different than the order described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
Referring to fig. 1, fig. 1 is a schematic flow chart of a pedestrian warning tone control method of an electric vehicle according to an embodiment of the present application. In an embodiment of the present application, the method includes:
s101, acquiring a shot image in the driving direction, and identifying a target pedestrian in a target area of the shot image.
The execution main body of the application can be a vehicle control unit of an electric automobile.
In the embodiment of the application, one or more cameras can be respectively arranged at the front end and the rear end of the electric automobile, and the images shot in the driving direction of the electric automobile are shot through the cameras. The vehicle control unit collects the shot images and identifies the shot images so as to distinguish and confirm the target pedestrians in the target area in the shot images. In practical applications, in the case of an electric vehicle, the objects to be reminded are not all pedestrians around the vehicle, but pedestrians on the driving path. Even if the shot images shot by the cameras corresponding to the driving directions are processed, the covered position areas of the shot images are still wide, so that target areas are set in the shot images, and only target pedestrians are identified in the target areas, so that the finally identified target pedestrians are pedestrians who really need prompt tone reminding.
In one embodiment, the capturing of the captured image of the driving direction includes:
acquiring the wheel rotation direction and the wheel rotation angle of the electric automobile;
determining an angle range corresponding to the wheel rotation angle, and determining a driving direction based on the angle range and the wheel rotation direction;
and acquiring shot images shot by the camera corresponding to the driving direction.
In the embodiment of the application, the driving direction can be divided into a left direction, a front direction and a right direction, and one camera can be respectively arranged at the left front part, the right front part and the right front part of the electric automobile, namely, the driving direction is determined to determine which camera is used for acquiring the image at this time. Specifically, the vehicle control unit acquires the wheel rotation direction and the wheel rotation angle of the electric vehicle through sensors arranged at various positions of a vehicle body, determines the angle range of the electric vehicle according to the wheel rotation angle, further determines the driving direction, and finally acquires a shot image according to a camera at the driving direction. The reason for determining the angle range corresponding to the wheel rotation angle is that, in some cases, the vehicle may only rotate the wheels at a small angle to allow the vehicle to move to the side in the forward process, and at this time, the driving direction of the vehicle should still be the front direction. Therefore, the angle range can be divided into two ranges of 0-45 degrees and 45-90 degrees, and the driving direction can be further judged.
Illustratively, when the wheel rotation angle is in the range of 0-45 °, the direction of travel is forward regardless of whether the wheel rotation direction is left or right. When the wheel rotation angle is 45-90 °, if the wheel rotation direction is the left direction, the running direction is the left direction, and if the wheel rotation direction is the right direction, the running direction is the right direction.
In one embodiment, the identifying a target pedestrian in a target area of the captured image includes:
determining a target area in the shot image based on the wheel rotation angle and the wheel rotation direction;
identifying a target pedestrian within the target area.
In the embodiment of the present application, the specific position of the target area in the captured image should be determined according to the wheel rotation angle and the wheel rotation direction. Specifically, when the wheel rotation direction is the left direction, the larger the wheel rotation angle, the closer the target region should be to the left edge of the captured image. When the wheel rotation direction is the right direction, the larger the wheel rotation angle, the closer the target region should be to the right edge of the captured image.
S102, obtaining a current gear of the electric automobile, and determining a standard prompt tone frequency corresponding to a current speed based on the current gear.
In the embodiment of the application, the national standard provides the limit value standard of GBT 37153-.
S103, determining the crowd category corresponding to the target pedestrian, adjusting the standard prompt tone frequency based on the crowd category to obtain an adjusted prompt tone frequency, and playing a prompt tone based on the adjusted prompt tone frequency.
The crowd categories in the embodiment of the present application can be understood as different categories divided according to the age hierarchy of pedestrians, including teenagers, adolescents, middle-aged people and elderly people.
In the embodiment of the application, after the target pedestrian is successfully identified, the corresponding crowd category can be determined through further analysis of the appearance characteristics of the target pedestrian, the vehicle control unit correspondingly adjusts the standard prompt tone frequency according to different crowd categories to obtain the adjustment prompt tone frequency, and finally the target pedestrian is warned by adjusting the prompt tone frequency and playing the prompt tone. For example, for a target pedestrian with a crowd category of teenagers, the target pedestrian is sensitive to the environment, so a higher warning tone may frighten the pedestrian, and the standard warning tone frequency needs to be reduced. For the target pedestrian with the old people in the population category, the target pedestrian may not be sensitive to the environment or even hear normal warning sound along with the aging and the degradation of organs, so the frequency of the standard warning sound needs to be increased to ensure that the target pedestrian can hear the warning sound.
In one possible implementation, the determining the crowd category corresponding to the target pedestrian and adjusting the standard cue audio frequency based on the crowd category includes:
acquiring facial feature information of the target pedestrian, calculating the facial feature information based on a preset neural network model, and determining a crowd category corresponding to the target pedestrian;
and acquiring a frequency adjustment parameter corresponding to the crowd category, and adjusting the standard prompt audio frequency based on the frequency adjustment parameter.
In the embodiment of the application, the specific mode of identifying the crowd category corresponding to the target pedestrian can be to acquire the facial feature information of the target pedestrian by shooting an image, and calculate the facial feature information according to a preset neural network model, so as to judge the estimated age of the target pedestrian according to the output result of the neural network model, and further determine the crowd category according to the age range corresponding to the estimated age. Different frequency adjustment parameters are preset for different crowd categories, so that the vehicle control unit can directly adjust the frequency of the standard prompt tone according to the frequency adjustment parameters after acquiring the corresponding frequency adjustment parameters.
In one possible implementation, after playing the alert tone based on the adjusted alert tone frequency, the method further includes:
continuously collecting the shot images, and monitoring the facial expression characteristic change value of the target pedestrian;
and determining prompt tone feedback data based on the facial expression characteristic change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data.
In the embodiment of the application, after the prompt tone is played, the camera can continuously acquire the shot image, so that the facial expression characteristics of the target pedestrian are continuously identified, and the facial expression characteristics are processed and calculated according to the neural network model to obtain the change value of the facial expression characteristics. If the change value of the facial expression characteristics is too large, the target pedestrian is considered to have large facial expression change after hearing the warning tone, and the target pedestrian is probably frightened due to too large volume of the warning tone, so that the frequency adjustment parameters are optimized according to the warning tone feedback data, and the frequency adjustment parameters are reduced. If the facial expression characteristic change value is too small, the target pedestrian is considered to have no change in the facial expression change after hearing the warning tone, possibly the volume of the warning tone is too small, and the warning effect is not played for the target pedestrian, so that the frequency adjustment parameter is optimized according to the warning tone feedback data, and the frequency adjustment parameter is increased.
In one implementation, after continuously acquiring the captured image and monitoring the change value of the facial expression feature of the target pedestrian, the method further includes:
when at least two target pedestrians in the same category exist, calculating a feature difference value of facial expression feature change values of the same category corresponding to the target pedestrians in the same category;
determining prompt tone feedback data based on the facial expression feature change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data, wherein the method comprises the following steps:
when at least two target pedestrians in the same category exist, comparing the characteristic difference value with a preset difference value;
when the feature difference value is not larger than a preset difference value, calculating an average facial expression feature change value of each facial expression feature change value of the same category, determining prompt tone feedback data based on the average facial expression feature change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data;
and when the characteristic difference is larger than a preset difference, the prompt tone feedback data is not determined.
In the embodiment of the application, if more than two target pedestrians in the same crowd category are identified and found to exist, feature difference values are calculated for the facial expression feature change values of the target pedestrians. In expectation, the responses of target pedestrians in the same crowd category should be the same, that is, the difference in facial expression changes is not large, so the feature difference value is compared with the preset difference value, if the feature difference value does not exceed the preset difference value, the data is considered to have higher reliability, the average value of the feature change values is calculated, and the warning tone feedback data is determined to optimize the frequency adjustment parameter. If the characteristic difference value exceeds the preset difference value, the reaction difference of different target pedestrians in the same crowd category to the warning sound is considered to be large, the data does not have reliability, and the frequency adjustment parameters cannot be optimized at this time.
The pedestrian prompting sound control device of the electric vehicle provided by the embodiment of the application will be described in detail with reference to fig. 2. It should be noted that, the pedestrian prompting sound control apparatus of the electric vehicle shown in fig. 2 is used for executing the method of the embodiment shown in fig. 1 of the present application, and for convenience of description, only the part related to the embodiment of the present application is shown, and details of the technology are not disclosed, please refer to the embodiment shown in fig. 1 of the present application.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a pedestrian prompting sound control device of an electric vehicle according to an embodiment of the present application. As shown in fig. 2, the apparatus includes:
the system comprises an acquisition module 201, a control module and a display module, wherein the acquisition module is used for acquiring a shot image in the driving direction and identifying a target pedestrian in a target area of the shot image;
the obtaining module 202 is configured to obtain a current gear of the electric vehicle, and determine a standard prompt tone frequency corresponding to a current vehicle speed based on the current gear;
the adjusting module 203 is configured to determine a crowd category corresponding to the target pedestrian, adjust the standard prompt tone frequency based on the crowd category to obtain an adjusted prompt tone frequency, and play a prompt tone based on the adjusted prompt tone frequency.
In one possible implementation, the acquisition module 201 includes:
the first acquisition unit is used for acquiring the wheel rotation direction and the wheel rotation angle of the electric automobile;
a first determination unit configured to determine an angle range corresponding to the wheel turning angle, and determine a driving direction based on the angle range and a wheel turning direction;
and the first acquisition unit is used for acquiring the shot image shot by the camera corresponding to the driving direction.
In one possible implementation, the acquisition module 201 further includes:
a second determination unit configured to determine a target area in the captured image based on the wheel rotation angle and the wheel rotation direction;
and the identification unit is used for identifying the target pedestrian in the target area.
In one possible implementation, the adjusting module 203 includes:
the second acquisition unit is used for acquiring the facial feature information of the target pedestrian, calculating the facial feature information based on a preset neural network model, and determining the crowd category corresponding to the target pedestrian;
and the third acquisition unit is used for acquiring the frequency adjustment parameter corresponding to the crowd category and adjusting the standard prompting audio frequency based on the frequency adjustment parameter.
In one embodiment, the adjusting module 203 further comprises:
the monitoring unit is used for continuously acquiring the shot images and monitoring the facial expression characteristic change value of the target pedestrian;
and the optimization unit is used for determining prompt tone feedback data based on the facial expression characteristic change value and optimizing the frequency adjustment parameter according to the prompt tone feedback data.
In one embodiment, the adjusting module 203 further comprises:
the characteristic difference value calculating unit is used for calculating the characteristic difference value of the facial expression characteristic change value of the same category corresponding to each target pedestrian of the same category when at least two target pedestrians of the same category exist;
the optimization unit comprises:
the comparison element is used for comparing the characteristic difference value with a preset difference value when at least two target pedestrians in the same category exist;
the first judgment element is used for calculating the average facial expression characteristic change value of the facial expression characteristic change values of the same category when the characteristic difference value is not larger than a preset difference value, determining prompt tone feedback data based on the average facial expression characteristic change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data;
and the second judgment element is used for not determining the prompt tone feedback data when the characteristic difference is larger than a preset difference.
It is clear to a person skilled in the art that the solution according to the embodiments of the present application can be implemented by means of software and/or hardware. The "unit" and "module" in this specification refer to software and/or hardware that can perform a specific function independently or in cooperation with other components, where the hardware may be, for example, a Field-Programmable Gate Array (FPGA), an Integrated Circuit (IC), or the like.
Each processing unit and/or module in the embodiments of the present application may be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or may be implemented by software that executes the functions described in the embodiments of the present application.
Referring to fig. 3, a schematic structural diagram of an electronic device according to an embodiment of the present application is shown, where the electronic device may be used to implement the method in the embodiment shown in fig. 1. As shown in fig. 3, the electronic device 300 may include: at least one central processor 301, at least one network interface 304, a user interface 303, a memory 305, at least one communication bus 302.
Wherein a communication bus 302 is used to enable the connection communication between these components.
The user interface 303 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 303 may further include a standard wired interface and a wireless interface.
The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
The central processor 301 may include one or more processing cores. The central processor 301 connects various parts within the entire electronic device 300 using various interfaces and lines, and performs various functions of the terminal 300 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305 and calling data stored in the memory 305. Alternatively, the central Processing unit 301 may be implemented in at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The CPU 301 may integrate one or a combination of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the cpu 301, but may be implemented by a single chip.
The Memory 305 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable medium. The memory 305 may be used to store instructions, programs, code sets, or instruction sets. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described above, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 305 may alternatively be at least one storage device located remotely from the central processor 301. As shown in fig. 3, memory 305, which is a type of computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.
In the electronic device 300 shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user to obtain data input by the user; the cpu 301 may be configured to call the pedestrian alert tone control application program of the electric vehicle stored in the memory 305, and specifically perform the following operations:
acquiring a shot image in a driving direction, and identifying a target pedestrian in a target area of the shot image;
acquiring a current gear of the electric automobile, and determining a standard prompt tone frequency corresponding to the current speed based on the current gear;
and determining the crowd category corresponding to the target pedestrian, adjusting the standard prompt tone frequency based on the crowd category to obtain an adjusted prompt tone frequency, and playing a prompt tone based on the adjusted prompt tone frequency.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some service interfaces, devices or units, and may be an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of 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 application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program, which is stored in a computer-readable memory, and the memory may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above description is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure should not be limited thereby. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure are intended to be included within the scope of the present disclosure. Embodiments of the present disclosure will be readily apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (9)
1. A pedestrian warning tone control method of an electric vehicle, characterized by comprising:
acquiring a shot image in a driving direction, and identifying a target pedestrian in a target area of the shot image;
acquiring a current gear of the electric automobile, and determining a standard prompt tone frequency corresponding to the current speed based on the current gear;
and determining the crowd category corresponding to the target pedestrian, adjusting the standard prompt tone frequency based on the crowd category to obtain an adjusted prompt tone frequency, and playing a prompt tone based on the adjusted prompt tone frequency.
2. The method of claim 1, wherein said capturing a captured image of a direction of travel comprises:
acquiring the wheel rotation direction and the wheel rotation angle of the electric automobile;
determining an angle range corresponding to the wheel rotation angle, and determining a driving direction based on the angle range and the wheel rotation direction;
and acquiring shot images shot by the camera corresponding to the driving direction.
3. The method of claim 2, wherein the identifying a target pedestrian in a target area of the captured image comprises:
determining a target area in the shot image based on the wheel rotation angle and the wheel rotation direction;
identifying a target pedestrian within the target area.
4. The method of claim 1, wherein the determining the crowd category corresponding to the target pedestrian and the adjusting the standard cue audio frequency based on the crowd category comprises:
acquiring facial feature information of the target pedestrian, calculating the facial feature information based on a preset neural network model, and determining a crowd category corresponding to the target pedestrian;
and acquiring a frequency adjustment parameter corresponding to the crowd category, and adjusting the standard prompt audio frequency based on the frequency adjustment parameter.
5. The method of claim 4, wherein after playing an alert tone based on the adjusted alert tone frequency, further comprising:
continuously collecting the shot images, and monitoring the facial expression characteristic change value of the target pedestrian;
and determining prompt tone feedback data based on the facial expression characteristic change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data.
6. The method of claim 5, wherein after continuously acquiring the captured images and monitoring the change value of the facial expression feature of the target pedestrian, further comprising:
when at least two target pedestrians in the same category exist, calculating a feature difference value of facial expression feature change values of the same category corresponding to the target pedestrians in the same category;
determining prompt tone feedback data based on the facial expression feature change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data, wherein the method comprises the following steps:
when at least two target pedestrians in the same category exist, comparing the characteristic difference value with a preset difference value;
when the feature difference value is not larger than a preset difference value, calculating an average facial expression feature change value of each facial expression feature change value of the same category, determining prompt tone feedback data based on the average facial expression feature change value, and optimizing the frequency adjustment parameter according to the prompt tone feedback data;
and when the characteristic difference is larger than a preset difference, the prompt tone feedback data is not determined.
7. A pedestrian notification sound control apparatus for an electric vehicle, the apparatus comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a shot image in the driving direction and identifying a target pedestrian in a target area of the shot image;
the acquisition module is used for acquiring the current gear of the electric automobile and determining the standard prompt tone frequency corresponding to the current speed based on the current gear;
and the adjusting module is used for determining the crowd category corresponding to the target pedestrian, adjusting the standard prompt tone frequency based on the crowd category to obtain an adjusted prompt tone frequency, and playing a prompt tone based on the adjusted prompt tone frequency.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1-6 are implemented when the computer program is executed by the processor.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114715030A (en) * | 2022-04-29 | 2022-07-08 | 镁佳(北京)科技有限公司 | Audio frequency adjusting method and device, storage medium and electronic equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114715030A (en) * | 2022-04-29 | 2022-07-08 | 镁佳(北京)科技有限公司 | Audio frequency adjusting method and device, storage medium and electronic equipment |
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