CN114987448A - Automatic parking method, device and equipment based on voice and storage medium - Google Patents
Automatic parking method, device and equipment based on voice and storage medium Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/06—Automatic manoeuvring for parking
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
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Abstract
The application discloses a voice-based automatic parking method, a voice-based automatic parking device, voice-based automatic parking equipment and a voice-based automatic parking storage medium, wherein the method comprises the following steps: when a vehicle is in an automatic parking state, acquiring a first parking space number of a parking space; the parking space is present in the surrounding environment of the vehicle; outputting the first parking space number and receiving a voice instruction input by a user aiming at the first parking space number; identifying a second digit number in the voice message; and controlling the vehicle to park in the parking space corresponding to the second parking space number. According to the method and the device, the vehicle is automatically controlled to park in the parking space corresponding to the second parking space number through the second parking space number in the voice information, and the user does not need to park the vehicle beside the parking space, so that the time spent by the user in the parking process is reduced.
Description
Technical Field
The present application relates to the field of automatic parking technologies, and in particular, to a method, an apparatus, a device, and a storage medium for automatic parking based on voice.
Background
With the development of vehicle intelligence, more and more vehicles are applying the automatic parking technology.
At present, when a user uses an automatic parking function of a vehicle, the user needs to park the vehicle beside a parking space which the user wants to park, so that automatic parking is realized. However, this is particularly unfriendly to drivers with poor vehicle control or to novice drivers, who may need to adjust the position of the vehicle in order to park it beside the parking space, making the parking process take a long time.
Disclosure of Invention
The application mainly aims to provide a voice-based automatic parking method, a voice-based automatic parking device, voice-based automatic parking equipment and a voice-based automatic parking storage medium, and aims to solve the technical problem of reducing time spent in a parking process of a user.
In order to achieve the above object, the present application provides a voice-based automatic parking method, including:
when a vehicle is in an automatic parking state, acquiring a first parking space number of a parking space; the parking space is present in the surrounding environment of the vehicle;
outputting the first parking space number, and receiving a voice instruction input by a user aiming at the first parking space number;
identifying a second digit number in the voice message;
and controlling the vehicle to park in the parking space corresponding to the second parking space number.
Illustratively, when the vehicle is in an automatic parking state, before acquiring the first parking space number of the parking space, the method includes:
when the speed of the vehicle is smaller than or equal to a preset speed threshold value, when the distance between the vehicle and the parking space is smaller than a preset distance threshold value or when the gear is in a reverse gear, outputting prompt information to prompt a user whether to use an automatic parking function;
and receiving a confirmation instruction input by the user aiming at the prompt message, and controlling the vehicle to start automatic parking.
Before outputting the prompt message when the speed of the vehicle is less than or equal to a preset speed threshold, when the distance between the vehicle and the parking space is less than a preset distance threshold, or when the gear is in a reverse gear, the method includes:
acquiring a parking space image acquired by a camera arranged on the vehicle;
inputting the parking space image into a preset parking space feature identification model to obtain the edge feature of the parking space; the preset parking space feature recognition model is obtained by performing iterative training on a first model to be trained based on a first preset training data set;
determining a distance of the vehicle from the parking space based on the edge feature.
Illustratively, acquire the first parking stall number of parking stall includes:
inputting the parking space image into a preset parking space number identification model to obtain a first parking space number of a parking space; and the preset parking space number identification model is obtained by performing iterative training on a second model to be trained based on a second preset training data set.
For example, the first parking space number includes a first parking space number or a plurality of first parking space numbers, and the controlling the vehicle to park in the parking space corresponding to the second parking space number includes:
when the first parking space number comprises a first parking space number, if the first parking space number is the same as the second parking space number, controlling the vehicle to park in a parking space corresponding to the second parking space number; or the like, or, alternatively,
and when the first parking space number comprises a plurality of first parking space numbers, if the second parking space number exists in the plurality of first parking space numbers, controlling the vehicle to park in a parking space corresponding to the second parking space number.
Illustratively, the identifying a second digit number in the speech information includes:
acquiring a voice segment corresponding to the second parking space number;
and matching the voice segments from the voice information.
Exemplarily, the inputting the parking space image into a preset parking space feature recognition model, before obtaining the edge feature of the parking space, includes:
acquiring the first preset training data set and the first model to be trained;
performing iterative training on the first model to be trained based on the first preset training data set to obtain an updated first model to be trained, and determining whether the updated first model to be trained meets a preset iteration end condition;
if the updated first model to be trained meets the preset iteration end condition, taking the updated first model to be trained as the preset parking space feature recognition model;
and if the updated first model to be trained does not meet the preset iteration ending condition, returning to the step of performing iterative training on the first model to be trained based on the first preset training data set until the updated first model to be trained meets the preset iteration ending condition.
In addition, to achieve the above object, the present application also provides a voice-based automatic parking apparatus, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a first parking space number of a parking space when a vehicle is in an automatic parking state; the parking space is present in the surroundings of the vehicle;
the output module is used for outputting the first parking space number and receiving a voice instruction input by a user aiming at the first parking space number;
the identification module is used for identifying a second car position number in the voice information;
and the first control module is used for controlling the vehicle to park in the parking space corresponding to the second parking space number.
In addition, in order to achieve the above object, the present application also provides a voice-based automatic parking apparatus, which includes a memory, a processor, and a voice-based automatic parking program stored in the memory and executable on the processor, wherein the voice-based automatic parking program, when executed by the processor, implements the steps of the voice-based automatic parking method described above.
In addition, to achieve the above object, the present application further provides a computer-readable storage medium having a voice-based automatic parking program stored thereon, where the voice-based automatic parking program, when executed by a processor, implements the steps of the voice-based automatic parking method as described above.
Compared with the prior art that in order to enable a vehicle to park beside a parking space, the position of the vehicle may need to be adjusted, and therefore the parking process takes a long time, the method and the device automatically acquire a first parking space number of the parking space and output the first parking space number to a user when the vehicle is in an automatic parking state, so that the user inputs a second parking space number of the parking space which is desired to park according to the first parking space number, and finally automatically controls the vehicle to park in the parking space corresponding to the second parking space number. It can be understood that the vehicle is automatically controlled to be parked at the parking space corresponding to the second parking space number through the second parking space number in the voice message, and a user is not required to park the vehicle beside the parking space, so that the time spent by the user in the parking process is reduced.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a first embodiment of a voice-based automatic parking method of the present application;
FIG. 2 is a schematic diagram of a position relationship between a vehicle and a parking space according to a first embodiment of the automatic parking method based on voice;
fig. 3 is a schematic structural diagram of a hardware operating environment according to an embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
The application provides an automatic parking method based on voice, and referring to fig. 1, fig. 1 is a schematic flow chart of a first embodiment of the automatic parking method based on voice.
While the embodiments of the present application provide an example of a voice-based method for automatic parking, it should be noted that although a logical order is shown in the flow chart, in some cases, the steps shown or described may be performed in an order different from that shown. The automatic parking method based on voice is applied to the vehicle-mounted terminal. For convenience of description, the following omits the execution of the subject to describe the respective steps of the voice-based automatic parking method. The automatic parking method based on voice comprises the following steps:
step S10, when the vehicle is in the automatic parking state, acquiring a first parking space number of the parking space; the parking space is present in the surroundings of the vehicle.
Automatic parking is used to assist the driver in controlling the accelerator, brake, and steering wheel, thereby helping the driver park the vehicle in or out of the parking space.
It can be understood that each parking space has its unique parking space number, and generally, the parking space number is used for managing the parking space, and in this embodiment, the parking space number is used for the user to designate the parking space that the vehicle needs to park into.
A space, which may be used for parking the vehicle, comprises one or more spaces, is present in the surroundings of the vehicle, i.e. the vehicle is beside the space.
When the vehicle is in the automatic parking state, before obtaining the first parking space number of the parking space, the method includes:
step a, when the speed of a vehicle is smaller than or equal to a preset speed threshold value, when the distance between the vehicle and the parking space is smaller than a preset distance threshold value or when a gear is in a reverse gear, outputting prompt information to prompt a user whether to use an automatic parking function.
Whether the parking requirement exists for the user can be judged by the following modes: and judging whether the speed of the vehicle is less than or equal to a preset speed threshold value, whether the distance between the vehicle and the parking space is less than a preset distance threshold value or whether the gear is in a reverse gear.
Judging whether the speed of the vehicle is smaller than or equal to a preset speed threshold value, whether the distance between the vehicle and the parking space is smaller than a preset distance threshold value or whether the gear is in a reverse gear, and if so, determining that the parking requirement exists for the user; if not, determining that the user does not have the parking requirement. It can be understood that the speed of the vehicle is necessarily lower for convenient parking before the user parks the vehicle, and correspondingly, the position of the vehicle is closer to that of the parking space for parking the vehicle in the parking space, and correspondingly, since the parking space generally limits the vehicle from parking in or out in the same direction, the user needs to place the gear in the reverse gear before the user parks the vehicle for convenient vehicle taking.
For example, the preset speed threshold may be set according to a driving habit of the user (for example, when the user likes to drive at an average speed of 5km/h when looking for a parking space, the preset speed threshold may be set to 5km/h), and the embodiment is not limited.
For example, the preset distance threshold may be set as needed, and the embodiment is not limited.
Illustratively, the prompt message includes a voice prompt message, a text prompt message, and the like, wherein the voice prompt message may be output through a speaker provided in the vehicle, and the text prompt message may be output through a display provided in an in-vehicle terminal of the vehicle.
And b, receiving a confirmation instruction input by the user aiming at the prompt information, and controlling the vehicle to start automatic parking.
Accordingly, the confirmation instruction may be a voice confirmation instruction, a gesture confirmation instruction, or the like, wherein the voice confirmation instruction may be collected by a microphone provided in the vehicle, and the gesture confirmation instruction may be collected by the display (for example, a user performs a click operation on the display, and the click operation clicks a virtual key "confirmation" on the display).
Before outputting the prompt message when the speed of the vehicle is less than or equal to a preset speed threshold, when the distance between the vehicle and the parking space is less than a preset distance threshold, or when the gear is in a reverse gear, the method includes:
step c, acquiring a parking space image acquired by a camera arranged on the vehicle;
step d, inputting the parking space image into a preset parking space feature identification model to obtain the edge feature of the parking space; and the preset parking space feature recognition model is obtained by performing iterative training on a first model to be trained based on a first preset training data set.
The preset parking space feature recognition model can recognize the edge features of the parking space from the parking space image, and the edge features can represent the features of the parking space, namely the rectangular frame of the parking space. It should be noted that, when the parking space image is input into the preset parking space feature recognition model, the form of the parking space image is a feature vector, and the process of recognizing the edge feature of the parking space by the preset parking space feature recognition model is a process of calculating the feature vector and obtaining a calculation result.
For example, the first model to be trained may be constructed by Neural Network algorithms such as CNN (Convolutional Neural Network), DNN (Deep Neural Network), and the like.
Illustratively, the first preset training data set is a labeled sample image data set, that is, the sample image data set is labeled with edge features of the parking space.
And e, determining the distance between the vehicle and the parking space based on the edge characteristics.
Since the edges of the vehicle space are characterized by rectangular borders, the distance between the vehicle and the vehicle space can be the distance between the center of the vehicle and the center of the rectangle, or the distance between the side of the rectangle closest to the vehicle and the center of the vehicle.
Illustratively, acquire the first parking stall number of parking stall includes:
step f, inputting the parking space image into a preset parking space number identification model to obtain a first parking space number of a parking space; and the preset parking space number identification model is obtained by performing iterative training on a second model to be trained based on a second preset training data set.
Illustratively, the specific implementation modes of the preset parking space number recognition model, the second preset training data set and the second model to be trained are basically the same as the specific implementation modes of the preset parking space feature recognition model, the first preset training data set and the first model to be trained, and are not described again here.
And step S20, outputting the first vehicle position number and receiving a voice instruction input by a user aiming at the first vehicle position number.
The specific implementation of outputting the first vehicle location number is substantially the same as the specific implementation of outputting the prompt message, and is not described herein again.
It can be understood that the purpose of outputting the first parking space number is to inform the driver of which parking spaces can be used for parking, where the parking spaces may be one or multiple parking spaces (as shown in fig. 2, fig. 2 is a schematic diagram of a position relationship between a vehicle and a parking space, where a110, a111, and a112 are parking space numbers of three parking spaces respectively), and when a parking space is one, if the driver needs to park the vehicle into the parking space, the driver needs to include the first parking space number of the parking space in the voice instruction; when the parking spaces are multiple, the driver may select one parking space from the multiple parking spaces to park the vehicle, at this time, the voice command includes the first parking space number of the parking space selected by the driver, as shown in fig. 2, if the driver selects a111, the voice command includes a 111.
Step S30, recognizing a second digit number in the voice message;
illustratively, the identifying a second digit number in the speech information includes:
step g, acquiring a voice segment corresponding to the second parking lot number;
and h, matching the voice fragment from the voice information.
The voice segment is the voice of the driver recorded in advance, the voice segment corresponding to the second seat number is the voice of the recorded driver reading the second seat number, for example, the second seat number is 44, and the voice segment is the voice of the recorded driver reading "44".
The recognition process can also be implemented based on Neural Network algorithms such as CNN (Convolutional Neural Network), DNN (Deep Neural Network), and the like, the training process of the corresponding model is similar to the training process of the first model to be trained and the second model to be trained, and the data sets involved in the training process are labeled voice data sets. The specific training process and the using process of the model are not described herein again.
Step S40, controlling the vehicle to park in the parking space corresponding to the second parking space number;
illustratively, the first parking space number includes one first parking space number or a plurality of first parking space numbers, and the controlling the vehicle to park in the parking space corresponding to the second parking space number includes:
step i, when the first parking space number comprises a first parking space number, if the first parking space number is the same as the second parking space number, controlling the vehicle to park in a parking space corresponding to the second parking space number; or the like, or, alternatively,
and when the first parking space number comprises a plurality of first parking space numbers, if the second parking space number exists in the plurality of first parking space numbers, controlling the vehicle to park in a parking space corresponding to the second parking space number.
It can be understood that when the first parking space number includes a first parking space number, the vehicle can be controlled to park in the parking space corresponding to the second parking space number, and also the parking space corresponding to the first parking space number, because, in general, the two parking space numbers are the same unless the driver listens to the wrong prompt message and/or gives a wrong voice command. When the driver listens to the wrong prompt message and/or gives a wrong voice instruction, the first prompt message can be output to remind the driver of listening to the wrong prompt message and/or giving the wrong voice instruction, and remind the driver of inputting a new voice instruction.
When the first parking space number comprises a plurality of first parking space numbers, compared with the situation that the first parking space number comprises one first parking space number, the situation that the second parking space number is matched from the plurality of first parking space numbers is increased, and if the matching is successful, namely the second vehicle number exists in the plurality of first parking space numbers, the vehicle can be controlled to park in the parking space corresponding to the second parking space number; if the matching fails, it indicates that the driver listens to the wrong prompt message and/or gives an incorrect voice instruction, and at this time, second prompt message can be output to prompt the driver to listen to the wrong prompt message and/or give the incorrect voice instruction and prompt the driver to input a new voice instruction.
Exemplarily, the inputting the parking space image into a preset parking space feature recognition model, before obtaining the edge feature of the parking space, includes:
step j, acquiring the first preset training data set and the first model to be trained;
step k, performing iterative training on the first model to be trained based on the first preset training data set to obtain an updated first model to be trained, and determining whether the updated first model to be trained meets a preset iteration end condition; if the updated first model to be trained meets the preset iteration end condition, taking the updated first model to be trained as the preset parking space feature recognition model; and if the updated first model to be trained does not meet the preset iteration ending condition, returning to the step of performing iterative training on the first model to be trained based on the first preset training data set until the updated first model to be trained meets the preset iteration ending condition.
And performing iterative training on the first model to be trained through the first preset training data set to obtain an updated first model to be trained. After obtaining the updated first model to be trained each time, determining whether the updated first model to be trained meets a preset iteration end condition, if the updated first model to be trained meets the preset iteration end condition, ending the iteration, and taking the last updated first model to be trained as a preset parking space feature recognition model; and if the updated first model to be trained does not meet the preset iteration ending condition, the updated first model to be trained does not meet the use condition, and the updated first model to be trained is continuously subjected to iterative training and updating until the updated first model to be trained meets the iteration ending condition.
It should be noted that the iterative training is a process of training the first model to be trained through the first preset training data set for multiple times, and generally, the preset parking space feature recognition model obtained by the first model to be trained needs to be updated through multiple rounds of training. It should be noted that the preset iteration end condition is that the iteration is ended when the model prediction accuracy of the first model to be trained or the updated first model to be trained reaches the preset accuracy threshold, or when the iteration number reaches the preset iteration number.
For example, the preset accuracy threshold and the preset iteration number may be set as needed, and this embodiment is not particularly limited.
It should be noted that the specific implementation of the preset parking space number recognition model obtained by the training and the model for voice recognition obtained by the training is basically the same as the specific implementation of the preset parking space feature recognition model obtained by the training, and is not described herein again.
Compared with the prior art that in order to enable a vehicle to park beside a parking space, the position of the vehicle may need to be adjusted, and therefore the parking process takes a long time, the method and the device automatically acquire a first parking space number of the parking space and output the first parking space number to a user when the vehicle is in an automatic parking state, so that the user inputs a second parking space number of the parking space which is desired to park according to the first parking space number, and finally automatically controls the vehicle to park in the parking space corresponding to the second parking space number. It can be understood that the vehicle is automatically controlled to be parked at the parking space corresponding to the second parking space number through the second parking space number in the voice message, and a user is not required to park the vehicle beside the parking space, so that the time spent by the user in the parking process is reduced.
In addition, the present application also provides a voice-based automatic parking apparatus including:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a first parking space number of a parking space when a vehicle is in an automatic parking state; the parking space is present in the surrounding environment of the vehicle;
the output module is used for outputting the first parking space number and receiving a voice instruction input by a user aiming at the first parking space number;
the identification module is used for identifying a second car position number in the voice information;
and the first control module is used for controlling the vehicle to park in the parking space corresponding to the second parking space number.
Illustratively, the voice-based automatic parking device further includes:
the output module is used for outputting prompt information when the speed of a vehicle is less than or equal to a preset speed threshold value, the distance between the vehicle and the parking space is less than a preset distance threshold value or a gear is in a reverse gear so as to prompt a user whether to use the automatic parking function or not;
and the second control module is used for receiving a confirmation instruction input by the user aiming at the prompt information and controlling the vehicle to start automatic parking.
Illustratively, the voice-based automatic parking device further includes:
the first acquisition module is used for acquiring a parking space image acquired by a camera arranged on the vehicle;
the input module is used for inputting the parking space image into a preset parking space feature identification model to obtain the edge feature of the parking space; the preset parking space feature recognition model is obtained by performing iterative training on a first model to be trained based on a first preset training data set;
and the determining module is used for determining the distance between the vehicle and the parking space based on the edge characteristics.
Illustratively, the first obtaining module is specifically configured to:
inputting the parking space image into a preset parking space number identification model to obtain a first parking space number of a parking space; and the preset parking space number identification model is obtained by performing iterative training on a second model to be trained based on a second preset training data set.
Illustratively, the first vehicle space number includes one first vehicle space number or a plurality of first vehicle space numbers, and the control module is specifically configured to:
when the first parking space number comprises a first parking space number, if the first parking space number is the same as the second parking space number, controlling the vehicle to park in a parking space corresponding to the second parking space number; or the like, or, alternatively,
and when the first parking space number comprises a plurality of first parking space numbers, if the second parking space number exists in the plurality of first parking space numbers, controlling the vehicle to park in a parking space corresponding to the second parking space number.
Illustratively, the identification module is specifically configured to:
acquiring a voice segment corresponding to the second parking lot number;
and matching the voice segments from the voice information.
Illustratively, the voice-based automatic parking device further includes:
the second acquisition module is used for acquiring the first preset training data set and the first model to be trained;
the training module is used for carrying out iterative training on the first model to be trained based on the first preset training data set to obtain an updated first model to be trained, and determining whether the updated first model to be trained meets a preset iteration end condition; if the updated first model to be trained meets the preset iteration end condition, taking the updated first model to be trained as the preset parking space feature recognition model; and if the updated first model to be trained does not meet the preset iteration ending condition, returning to the step of performing iterative training on the first model to be trained based on the first preset training data set until the updated first model to be trained meets the preset iteration ending condition.
The specific implementation of the automatic parking device based on voice is basically the same as that of the above embodiments of the automatic parking method based on voice, and is not described herein again.
In addition, the application also provides automatic parking equipment based on voice. As shown in fig. 3, fig. 3 is a schematic structural diagram of a hardware operating environment according to an embodiment of the present application.
It should be noted that fig. 3 is a schematic structural diagram of a hardware operating environment of the automatic parking device based on voice.
As shown in fig. 3, the voice-based automatic parking apparatus may include: a processor 3001, e.g., a CPU, memory 3005, a user interface 3003, a network interface 3004, a communication bus 3002. The communication bus 3002 is used to realize connection communication between these components. The user interface 3003 may include a Display screen (Display), an input unit such as a keyboard (keyboard), and the optional user interface 3003 may also include a standard wired interface, a wireless interface. The network interface 3004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 3005 may be a high-speed RAM memory or a non-volatile memory, such as a disk memory. The memory 3005 may alternatively be a storage device separate from the processor 3001.
Alternatively, the voice-based automatic parking apparatus may further include an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like.
Those skilled in the art will appreciate that the configuration of the voice-based automatic parking apparatus illustrated in fig. 3 does not constitute a limitation of the voice-based automatic parking apparatus, and may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components.
As shown in fig. 3, the memory 3005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a voice-based automatic parking program. The operating system is a program for managing and controlling hardware and software resources of the voice-based automatic parking device, and supports the operation of a voice-based automatic parking program and other software or programs.
In the automatic parking apparatus based on voice shown in fig. 3, the user interface 3003 is mainly used for connecting a terminal and performing data communication with the terminal, such as receiving user signaling data sent by the terminal; the network interface 3004 is mainly used for a background server and performs data communication with the background server; the processor 3001 may be configured to invoke the voice-based auto park program stored in the memory 3005 and perform the steps of the voice-based auto park method as described above.
The specific implementation of the automatic parking device based on voice is basically the same as the embodiments of the automatic parking method based on voice, and is not described herein again.
In addition, an embodiment of the present application further provides a computer-readable storage medium, where a voice-based automatic parking program is stored on the computer-readable storage medium, and the voice-based automatic parking program, when executed by a processor, implements the steps of the voice-based automatic parking method described above.
The specific implementation manner of the computer-readable storage medium of the present application is substantially the same as that of the foregoing embodiments of the automatic parking method based on voice, and is not described herein again.
In addition, to achieve the above object, the present application also provides a computer program product comprising: a computer program which, when being executed by a processor, carries out the steps of the voice-based automatic parking method as described above.
The specific implementation of the computer program product of the present application is substantially the same as the embodiments of the automatic parking method based on voice, and is not further described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes: the instructions are used to enable a terminal device (which may be a mobile phone, a computer, a server, a device, or a network device) to perform the method described in the embodiments of the present application.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. A method for voice-based automatic parking, the method comprising:
when a vehicle is in an automatic parking state, acquiring a first parking space number of a parking space; the parking space is present in the surrounding environment of the vehicle;
outputting the first parking space number and receiving a voice instruction input by a user aiming at the first parking space number;
identifying a second car position number in the voice information;
and controlling the vehicle to park in the parking space corresponding to the second parking space number.
2. The method of claim 1, wherein obtaining the first lot number of the lot while the vehicle is in the auto park state comprises:
when the speed of the vehicle is smaller than or equal to a preset speed threshold value, when the distance between the vehicle and the parking space is smaller than a preset distance threshold value or when the gear is in a reverse gear, outputting prompt information to prompt a user whether to use an automatic parking function;
and receiving a confirmation instruction input by the user aiming at the prompt information, and controlling the vehicle to start automatic parking.
3. The method of claim 2, wherein before outputting the prompt when the speed of the vehicle is less than or equal to a preset speed threshold, when the distance between the vehicle and the space is less than a preset distance threshold, or when the gear is in reverse, comprising:
acquiring a parking space image acquired by a camera arranged on the vehicle;
inputting the parking space image into a preset parking space feature identification model to obtain the edge feature of the parking space; the preset parking space feature recognition model is obtained by performing iterative training on a first model to be trained based on a first preset training data set;
determining a distance of the vehicle from the parking space based on the edge feature.
4. The method of claim 3, wherein said obtaining a first lot number for a lot comprises:
inputting the parking space image into a preset parking space number identification model to obtain a first parking space number of a parking space; and the preset parking space number identification model is obtained by performing iterative training on a second model to be trained based on a second preset training data set.
5. The method of claim 1, wherein the first space number comprises a first space number or a plurality of first space numbers, and wherein controlling the vehicle to park in the space corresponding to the second space number comprises:
when the first parking space number comprises a first parking space number, if the first parking space number is the same as the second parking space number, controlling the vehicle to park in a parking space corresponding to the second parking space number; or the like, or, alternatively,
and when the first parking space number comprises a plurality of first parking space numbers, if the second parking space number exists in the plurality of first parking space numbers, controlling the vehicle to park in a parking space corresponding to the second parking space number.
6. The method of claim 1, wherein the identifying a second digit number in the voice message comprises:
acquiring a voice segment corresponding to the second parking lot number;
and matching the voice segments from the voice information.
7. The method of claim 3, wherein the step of inputting the parking space image into a preset parking space feature recognition model before obtaining the edge feature of the parking space comprises:
acquiring the first preset training data set and the first model to be trained;
performing iterative training on the first model to be trained based on the first preset training data set to obtain an updated first model to be trained, and determining whether the updated first model to be trained meets a preset iteration end condition;
if the updated first model to be trained meets the preset iteration end condition, taking the updated first model to be trained as the preset parking space feature recognition model;
and if the updated first model to be trained does not meet the preset iteration ending condition, returning to the step of performing iterative training on the first model to be trained based on the first preset training data set until the updated first model to be trained meets the preset iteration ending condition.
8. A voice-based automatic parking device, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a first parking space number of a parking space when a vehicle is in an automatic parking state; the parking space is present in the surrounding environment of the vehicle;
the output module is used for outputting the first parking space number and receiving a voice instruction input by a user aiming at the first parking space number;
the identification module is used for identifying a second car position number in the voice information;
and the first control module is used for controlling the vehicle to park in the parking space corresponding to the second parking space number.
9. A voice-based automatic parking device, characterized in that the voice-based automatic parking device comprises a memory, a processor and a voice-based automatic parking program stored on the memory and executable on the processor, wherein the voice-based automatic parking program, when executed by the processor, implements the steps of the voice-based automatic parking method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that a voice-based automatic parking program is stored on the computer-readable storage medium, and the voice-based automatic parking program, when executed by a processor, implements the steps of the voice-based automatic parking method according to any one of claims 1 to 7.
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| CN202210572434.3A CN114987448A (en) | 2022-05-24 | 2022-05-24 | Automatic parking method, device and equipment based on voice and storage medium |
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