CN115465285A - Vehicle voice control method based on driving process and related device - Google Patents
Vehicle voice control method based on driving process and related device 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
- 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
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
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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
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/06—Direction of travel
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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
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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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
- B60W2554/00—Input parameters relating to objects
- B60W2554/40—Dynamic objects, e.g. animals, windblown objects
- B60W2554/406—Traffic density
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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
- B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
- B60W2555/20—Ambient conditions, e.g. wind or rain
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Abstract
The application discloses a vehicle voice control method and a related device based on a driving process, comprising the following steps: determining a state expected value according to the running information by acquiring the current running information of the target vehicle; acquiring current environment information and generating a driving scene by combining the state expected value; judging the driving scene according to preset conditions, and if the driving scene passes the preset conditions, acquiring a voice reminding strategy corresponding to the driving scene, so that when a voice broadcasting requirement is received, generating a voice message according to the voice reminding strategy; the driving scene is generated by collecting the driving information and the current environment information, the driving scene is judged according to preset conditions, and a corresponding voice reminding strategy is generated after the judgment is passed so as to realize the reminding function of safe driving of the automobile.
Description
Technical Field
The present application relates to the field of voice control, and in particular, to a vehicle voice control method and related apparatus based on a driving process.
Background
With the rapid development of science and technology, automobiles become an indispensable part of more and more people's lives. With the vigorous development of the automobile industry in China, automobile safety also becomes a significant problem. In the current technical environment, when a vehicle runs, safety prompt of road conditions is mainly performed to people in the vehicle in a mode of in-vehicle navigation or navigation software. For complex driving environments and different driving scenes, the capability of generating corresponding voice prompts is unavailable.
Therefore, how to achieve reasonable planning and generate voice prompts based on the driving process becomes a technical problem to be solved urgently.
Disclosure of Invention
In order to generate reasonable voice reminding messages according to different conditions of a vehicle in the driving process, the application provides a vehicle voice control method and a related device based on the driving process.
In a first aspect, the vehicle voice control method based on the driving process provided by the application adopts the following technical scheme:
a vehicle voice control method based on a driving process comprises the steps of obtaining current driving information of a target vehicle, and determining a state expected value according to the current driving information;
acquiring current environment information, and generating a driving scene by combining the state expected value;
judging whether the driving scene meets a preset condition or not;
if so, acquiring a voice reminding strategy corresponding to the driving scene;
and when a voice broadcasting requirement is detected, generating a voice message by combining the voice reminding strategy.
Optionally, the obtaining current driving information of the target vehicle, and determining the expected state value according to the current driving information includes:
acquiring current driving information of a target vehicle, wherein the current driving information comprises: vehicle speed information, vehicle driving duration, vehicle driver information, and vehicle trip information;
determining a journey type according to the vehicle journey information;
and determining a state expected value according to the current running information and the travel type.
Optionally, the determining the trip type according to the vehicle trip information includes:
determining a starting point position and a navigation end point position according to the vehicle travel information;
traversing the starting point position and the navigation end point position in a preset label set;
acquiring a logical relation between a starting point label and an end point label in a traversal result;
and determining the type of the trip according to the logical relation.
Optionally, the obtaining current environment information and generating a driving scene in combination with the expected state value include:
acquiring current environment information, wherein the current environment information comprises: current driving external weather information, current road condition information and current time information;
generating an environment scene according to the current driving outside weather information and the current time information;
generating a road condition scene according to real-time road condition information and specified information in the road condition information;
and generating a driving scene according to the environment scene and the road condition scene.
Optionally, the determining whether the driving scene meets a preset condition includes:
acquiring historical driving scene generation records;
and acquiring judgment information corresponding to preset conditions in the historical driving scene generation record, and judging the effectiveness of the driving scene according to the judgment information.
Optionally, the obtaining determination information corresponding to a preset condition from the historical driving scene generation record, and performing validity judgment on the driving scene according to the determination information includes:
acquiring average driving time length information in the historical driving scene generation record;
when the driving duration information in the driving scene is greater than the average driving duration information, matching a historical driving scene closest to the driving scene from the historical driving scene generation records;
and judging the effectiveness according to the historical driving scene and the driving scene.
Optionally, when a voice broadcast demand is detected, after generating a voice message in combination with the voice prompt policy, the method further includes:
after the fact that the execution of the behavior corresponding to the voice reminding strategy is completed is detected;
acquiring current driving information and current environment information, and judging whether a current driving scene needs to be updated or not;
and if so, executing the step of acquiring the current running information of the target vehicle and determining the state expected value according to the current running information.
In a second aspect, the present application provides a vehicle voice control apparatus based on a driving process, comprising:
the expected value acquisition module is used for acquiring the current running information of the target vehicle and determining a state expected value according to the current running information;
the scene generation module is used for acquiring current environment information and generating a driving scene by combining the state expected value;
the condition judgment module is used for judging whether the driving scene meets a preset condition or not;
the strategy acquisition module is used for acquiring a voice reminding strategy corresponding to the driving scene if the driving scene exists;
and the voice generating module is used for generating a voice message by combining the voice reminding strategy when the voice broadcasting requirement is detected.
In a third aspect, the present application provides a computer apparatus, the apparatus comprising: a memory, a processor that, when executing computer instructions stored by the memory, performs a method as described above.
In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the method as described above.
In summary, the present application includes the following advantageous technical effects:
the method comprises the steps of obtaining current running information of a target vehicle, and determining a state expected value according to the running information; acquiring current environment information and generating a driving scene by combining the state expected value; judging the driving scene according to preset conditions, and if the driving scene passes the preset conditions, acquiring a voice reminding strategy corresponding to the driving scene, so that when a voice broadcast demand is received, generating a voice message according to the voice reminding strategy; the driving scene is generated by collecting the driving information and the current environment information, the driving scene is judged according to preset conditions, and a corresponding voice reminding strategy is generated after the judgment is passed so as to realize the reminding function of safe driving of the automobile.
Drawings
FIG. 1 is a schematic diagram of a computer device architecture of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating a first embodiment of a voice control method for a vehicle according to the present invention based on a driving process;
FIG. 3 is a flow chart illustrating a second embodiment of the voice control method for a vehicle based on driving of the invention;
fig. 4 is a block diagram showing the configuration of a first embodiment of the voice control apparatus for a vehicle according to the present invention based on the running course.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a computer device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the computer device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement connection communication among these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of a computer device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and a vehicle voice control program based on a driving course.
In the computer device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the computer device of the present invention may be provided in a computer device that calls the vehicle voice control program based on the running course stored in the memory 1005 through the processor 1001 and executes the vehicle voice control method based on the running course provided by the embodiment of the present invention.
The embodiment of the invention provides a vehicle voice control method based on a driving process, and referring to fig. 2, fig. 2 is a flowchart illustrating a first embodiment of the vehicle voice control method based on the driving process.
In this embodiment, the vehicle voice control method based on the driving process includes the following steps:
and S10, acquiring the current running information of the target vehicle, and determining a state expected value according to the current running information.
It should be noted that the execution main body of the embodiment may be a computing service device with data processing, network communication and program running functions, such as a smart phone, a tablet computer, a personal computer, and the like, or may be other devices capable of implementing the above functions, which is not limited in the embodiment.
It is understood that the current driving information refers to data related to the driving of the vehicle, which is acquired by preset sensors or other data monitoring devices, and the driving data includes: vehicle speed, current vehicle conditions, driver information, and direction of travel. The vehicle speed can be directly obtained through a vehicle instrument panel, and the current vehicle condition of the vehicle comprises the vehicle energy consumption condition and the vehicle health condition. The driver information is further improved by establishing a corresponding driver profile in advance and recording the form habits of the driver. And (4) uniformly adopting default driving habits for the condition of the new driver. The direction of travel includes forward and reverse.
It is understood that the determination of the expected state value according to the current driving information means that the expected state value is determined by obtaining the above parameters in the current driving information and substituting the parameters into a vehicle state model for calculation. And the vehicle state model consists of a preset state and recorded parameters. Different vehicle states and interval ranges of corresponding parameters are set, and the current target vehicle is estimated by combining actual running information to obtain a current state expected value.
In specific implementation, the current running information of the target vehicle is acquired, the running information of the current vehicle is acquired according to the current running information, the running information and the vehicle state model are subjected to expected value operation, the corresponding state expected value is matched from the preset state, and finally the state of the current vehicle is determined.
Step S20: and acquiring current environment information, and generating a driving scene by combining the expected value of the state.
It should be noted that the current environment information refers to objective environment information outside the current vehicle, and may include driving time, driving weather, driving road condition, and travel information. And acquiring data of the overall environment of the vehicle by acquiring the current environment information of the vehicle.
It can be understood that the driving scene is a driving scene corresponding to the driving of the vehicle, and the driving scene is formed by presetting tags. The composition of a driving scene is composed of at least two preset labels. Traversing in different label sets, acquiring labels in the label sets according to the traversing result, and combining all the acquired labels to generate a driving scene. For example: the method comprises the steps that a preset label set a, a preset label set b, a preset label set c and a preset label set d exist, through traversal is sequentially conducted on the four sets, a label a1 is obtained from the set a, and a label b3 is obtained from the set b, and the two sets cd do not have traversal results meeting conditions. The corresponding driving scene is therefore a rack-mounted scene composed of a1b 3.
In specific implementation, the current environment information is obtained, the driving scene is generated by combining the state expected value through obtaining external information of current vehicle driving, generating label traversal conditions according to the external information and the state expected value, obtaining all label sets, traversing in all the label sets through the label traversal conditions, and forming the traversal result into the driving scene.
Further, in order to reduce an error of the driving scenario generation, the obtaining the current environment information and generating the driving scenario in combination with the expected state value includes: acquiring current environment information, wherein the current environment information comprises: current driving external weather information, current road condition information and current time information; generating an environment scene according to the current driving outside weather information and the current time information; generating a road condition scene according to real-time road condition information and specified information in the road condition information; and generating a driving scene according to the environment scene and the road condition scene.
It should be noted that the driving outside weather can be acquired by using the internet; the current road condition information can be obtained from traffic report broadcasting or internet real-time road condition information; the current time information can be read directly by the internal clock. Further, according to actual use needs, a daytime driving period and a night driving period can be set before the current time information is acquired, and which driving period is currently determined automatically after the time information is acquired.
It can be understood that, generating the environmental scene according to the current driving outside weather information and the current time information means that the environmental scene is generated correspondingly according to the weather information and the current time information, and the environmental scene is a self-defined term used for integrating the weather information and the time information.
It should be noted that the traffic scene is generated according to the real-time traffic information and the specified information in the traffic information, that is, the traffic information and the traffic control information before driving are acquired, and the traffic scene is a self-defined noun and is used for showing the traffic information before driving. For example: the congestion 2 kilometers ahead is known on a certain highway by acquiring information, and temporary control is implemented on high speed due to fog. Therefore, the road condition scene is generated according to the two conditions.
In specific implementation, the generation of the driving scene according to the environment scene and the road condition scene is to combine the tag contents corresponding to the environment scene and the road condition scene to generate the driving scene, that is, a set of all the tags.
Step S30: and judging whether the driving scene meets a preset condition or not.
Further, in order to set a reasonable preset condition to determine a driving scene, the determining whether the driving scene meets the preset condition includes: acquiring historical driving scene generation records; and acquiring judgment information corresponding to preset conditions in the historical driving scene generation record, and judging the effectiveness of the driving scene according to the judgment information.
In a specific implementation, the obtaining of the determination information corresponding to the preset condition from the historical driving scene generation record and the determining of the validity of the driving scene according to the determination information includes: acquiring average driving time length information in the historical driving scene generation record; when the driving duration information in the driving scene is greater than the average driving duration information, matching a historical driving scene closest to the driving scene from the historical driving scene generation records; and judging the effectiveness according to the historical driving scene and the driving scene.
It should be noted that, the judgment of the validity of the driving scene means that the driving scene needs to be generated correctly only when a certain driving time is met, and if the average driving time is 10 minutes, all the driving scenes generated by the vehicle within 10 minutes of driving are considered to be invalid.
It is understood that the historical driving record generation record is log information corresponding to the historical scene generation record.
In a specific implementation, the historical driving scene closest to the driving scene is matched from the historical driving scene generation record by acquiring the label information in the driving scene and matching the historical driving scene closest to the label information in the driving scene in the historical driving scene generation record.
Step S40: and if so, acquiring a voice reminding strategy corresponding to the driving scene.
In specific implementation, if the driving scene does not meet the validity judgment corresponding to the preset condition under the condition of no, the information corresponding to the driving scene generation needs to be collected again.
Step S50: and when a voice broadcasting requirement is detected, generating a voice message by combining a voice reminding strategy.
In specific implementation, when a voice broadcasting requirement is detected, generating a voice message by combining a voice reminding strategy means detecting whether a link requiring voice prompt, such as a vehicle overspeed, vehicle position navigation, a vehicle bluetooth call request and other messages, exists. The voice reminding strategy is obtained and the voice message is generated, namely the corresponding voice reminding strategy is obtained, for example, when the driving scene of the vehicle is a dangerous scene, all incoming call reminders are uniformly muted and not prompted. And for the prompting situation about driving, the volume is increased to attract the attention of the driver.
Further, in order to cope with the change of the environmental scene in the driving process of the vehicle, when the voice broadcast requirement is detected, after the voice message is generated by combining the voice prompt strategy, the method further includes: after the fact that the execution of the behavior corresponding to the voice reminding strategy is completed is detected; acquiring current driving information and current environment information, and judging whether a current driving scene needs to be updated or not; and if so, executing the step of acquiring the current running information of the target vehicle and determining the expected state value according to the current running information.
The method comprises the steps of determining a state expected value according to the running information by acquiring the current running information of a target vehicle; acquiring current environment information and generating a driving scene by combining the state expected value; judging the driving scene according to preset conditions, and if the driving scene passes the preset conditions, acquiring a voice reminding strategy corresponding to the driving scene, so that when a voice broadcast demand is received, generating a voice message according to the voice reminding strategy; the driving scene is generated by acquiring the driving information and the current environment information, the driving scene is judged according to preset conditions, and a corresponding voice reminding strategy is generated after the judgment is passed so as to realize a reminding function of safe driving of the automobile.
Referring to fig. 3, fig. 3 is a flow chart illustrating a vehicle voice control method based on a driving process according to a second embodiment of the present invention.
Based on the first embodiment, the step S10 of the vehicle voice control method based on the driving process of the present embodiment further includes:
step S101: acquiring current running information of a target vehicle, wherein the current running information comprises: vehicle speed information, vehicle driving duration, vehicle driver information, and vehicle trip information.
In a specific implementation, the driving information corresponding to the vehicle is acquired by interfacing with a vehicle information interface, and the vehicle driver information can be judged according to a pressure sensor of a vehicle seat or judged by a fingerprint identification device.
Step S102: and determining the travel type according to the vehicle travel information.
In particular implementations, a start point and an end point of a current trip of a vehicle are obtained. And performing position analysis on the starting point positioning information and the end point positioning information, and reading whether a travel type preset by a driver exists after the analysis. For example: delivering children, daily shopping, etc.
Step S103: and determining the expected state value according to the current running information and the travel type.
In specific implementation, the expected state value is determined according to the current running information and the travel type by acquiring vehicle running data in the current running information and calculating in an expected value calculation model corresponding to the travel type to determine the expected state value.
Further, in order to be more accurate in determining the expected value of the state, the determining the trip type according to the vehicle trip information includes: determining a starting point position and a navigation end point position according to the vehicle travel information; traversing the starting point position and the navigation end point position in a preset label set; acquiring a logical relation between a starting point label and an end point label in a traversal result; and determining the type of the trip according to the logical relation.
The present embodiment obtains the current driving information of the target vehicle, where the current driving information includes: vehicle speed information, vehicle driving duration, vehicle driver information, and vehicle trip information; determining a travel type according to the vehicle travel information; determining a state expected value according to the current running information and the travel type; the method for obtaining the vehicle travel information determines the travel type through the travel information in the travel information, and combines the travel information to generate the expected state value, so that the technical effect of accurately generating the voice control method according to the vehicle travel is further realized.
Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, in which a program for vehicle voice control based on a driving process is stored, and the program for vehicle voice control based on a driving process, when executed by a processor, implements the steps of the method for vehicle voice control based on a driving process as described above.
Referring to fig. 4, fig. 4 is a block diagram illustrating a first embodiment of a voice control apparatus for a vehicle according to the present invention.
As shown in fig. 4, a vehicle voice control apparatus based on a driving process according to an embodiment of the present invention includes:
the expected value acquisition module 10 is used for acquiring the current running information of the target vehicle and determining a state expected value according to the current running information;
the scene generation module 20 is configured to obtain current environment information and generate a driving scene by combining the state expected value;
the condition judgment module 30 is used for judging whether the driving scene meets a preset condition or not;
the strategy obtaining module 40 is configured to obtain a voice reminding strategy corresponding to the driving scene if the driving scene is determined to be the driver's driving scene;
and the voice generating module 50 is configured to generate a voice message by combining the voice reminding strategy when a voice broadcasting requirement is detected.
It should be understood that the above is only an example, and the technical solution of the present invention is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited in this respect.
The embodiment determines the expected state value according to the running information by acquiring the current running information of the target vehicle; acquiring current environment information and generating a driving scene by combining the state expected value; judging the driving scene according to preset conditions, and if the driving scene passes the preset conditions, acquiring a voice reminding strategy corresponding to the driving scene, so that when a voice broadcast demand is received, generating a voice message according to the voice reminding strategy; the driving scene is generated by collecting the driving information and the current environment information, the driving scene is judged according to preset conditions, and a corresponding voice reminding strategy is generated after the judgment is passed so as to realize the reminding function of safe driving of the automobile.
In an embodiment, the expected value obtaining module 10 is further configured to obtain current driving information of the target vehicle, where the current driving information includes: vehicle speed information, vehicle driving duration, vehicle driver information, and vehicle travel information; determining a travel type according to the vehicle travel information; and determining a state expected value according to the current running information and the travel type.
In an embodiment, the expected value obtaining module 10 is further configured to determine a starting point position and a navigation end point position according to the vehicle travel information; traversing the starting point position and the navigation end point position in a preset label set; acquiring a logical relation between a starting point label and an end point label in a traversal result; and determining the travel type according to the logical relation.
In an embodiment, the scene generating module 20 is further configured to obtain current environment information, where the current environment information includes: current driving external weather information, current road condition information and current time information; generating an environment scene according to the current driving outside weather information and the current time information; generating a road condition scene according to real-time road condition information and specified information in the road condition information; and generating a driving scene according to the environment scene and the road condition scene.
In an embodiment, the condition determining module 30 is further configured to obtain a historical driving scene generation record; and acquiring judgment information corresponding to preset conditions in the historical driving scene generation record, and judging the effectiveness of the driving scene according to the judgment information.
In an embodiment, the condition determining module 30 is further configured to obtain average driving time length information in the historical driving scene generation record; when the driving duration information in the driving scene is greater than the average driving duration information, matching a historical driving scene closest to the driving scene from the historical driving scene generation records; and judging the effectiveness according to the historical driving scene and the driving scene.
In an embodiment, the voice generating module 50 is further configured to, after detecting that the execution of the behavior corresponding to the voice reminding policy is completed; acquiring current driving information and current environment information, and judging whether a current driving scene needs to be updated or not; and if so, executing the step of acquiring the current running information of the target vehicle and determining the state expected value according to the current running information.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may be referred to a method for controlling a vehicle by voice based on a driving process according to any embodiment of the present invention, and are not described herein again.
Furthermore, 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 system 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 system. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages 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 solutions of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. a Read Only Memory (ROM)/RAM, a magnetic disk, and an optical disk), and includes several instructions for enabling a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A vehicle voice control method based on a driving process is characterized by comprising the following steps:
acquiring current running information of a target vehicle, and determining a state expected value according to the current running information;
acquiring current environment information, and generating a driving scene by combining the state expected value;
judging whether the driving scene meets a preset condition or not;
if so, acquiring a voice reminding strategy corresponding to the driving scene;
and when a voice broadcasting requirement is detected, generating a voice message by combining the voice reminding strategy.
2. The vehicle voice control method based on the driving process according to claim 1, wherein the acquiring current driving information of a target vehicle, and the determining a state expectation value according to the current driving information includes:
acquiring current driving information of a target vehicle, wherein the current driving information comprises: vehicle speed information, vehicle driving duration, vehicle driver information, and vehicle travel information;
determining a journey type according to the vehicle journey information;
and determining a state expected value according to the current running information and the travel type.
3. The vehicle voice control method based on the driving process according to claim 2, wherein the determining the trip type according to the vehicle trip information includes:
determining a starting point position and a navigation end point position according to the vehicle travel information;
traversing the starting point position and the navigation end point position in a preset label set;
acquiring a logical relation between a starting point label and an end point label in a traversal result;
and determining the type of the trip according to the logical relation.
4. The vehicle voice control method based on the driving process according to claim 1, wherein the obtaining the current environment information and generating the driving scene in combination with the expected state value comprises:
acquiring current environment information, wherein the current environment information comprises: current driving external weather information, current road condition information and current time information;
generating an environment scene according to the current driving outside weather information and the current time information;
generating a road condition scene according to real-time road condition information and specified information in the road condition information;
and generating a driving scene according to the environment scene and the road condition scene.
5. The vehicle voice control method based on the driving process according to claim 1, wherein the judging whether the driving scene meets a preset condition comprises:
acquiring a historical driving scene generation record;
and acquiring judgment information corresponding to preset conditions in the historical driving scene generation record, and judging the effectiveness of the driving scene according to the judgment information.
6. The vehicle voice control method based on the driving process according to claim 5, wherein the obtaining of the determination information corresponding to the preset condition in the historical driving scene generation record and the validity judgment of the driving scene according to the determination information comprises:
acquiring average driving time length information in the historical driving scene generation record;
when the driving duration information in the driving scene is greater than the average driving duration information, matching a historical driving scene closest to the driving scene from the historical driving scene generation records;
and judging the effectiveness according to the historical driving scene and the driving scene.
7. The vehicle voice control method based on the driving process according to claim 1, wherein after generating the voice message in combination with the voice prompt policy when the voice broadcast requirement is detected, the method further comprises:
after the fact that the execution of the behavior corresponding to the voice reminding strategy is completed is detected;
acquiring current driving information and current environment information, and judging whether a current driving scene needs to be updated or not;
and if so, executing the step of acquiring the current running information of the target vehicle and determining the expected state value according to the current running information.
8. A travel process-based vehicle speech control apparatus, characterized by comprising:
the expected value acquisition module is used for acquiring the current running information of the target vehicle and determining a state expected value according to the current running information;
the scene generation module is used for acquiring current environment information and generating a driving scene by combining the state expected value;
the condition judgment module is used for judging whether the driving scene meets a preset condition or not;
the strategy acquisition module is used for acquiring a voice reminding strategy corresponding to the driving scene if the driving scene is the driving scene;
and the voice generation module is used for generating a voice message by combining the voice reminding strategy when the voice broadcasting requirement is detected.
9. A computer device, the device comprising: a memory, a processor that, when executing computer instructions stored by the memory, performs the method of any of claims 1-7.
10. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the method of any one of claims 1 to 7.
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| CN202211074449.3A CN115465285A (en) | 2022-09-03 | 2022-09-03 | Vehicle voice control method based on driving process and related device |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117922580A (en) * | 2024-03-08 | 2024-04-26 | 东莞本凡网络技术有限公司 | Intelligent driving supervision method and system based on artificial intelligence |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117922580A (en) * | 2024-03-08 | 2024-04-26 | 东莞本凡网络技术有限公司 | Intelligent driving supervision method and system based on artificial intelligence |
| CN117922580B (en) * | 2024-03-08 | 2024-09-27 | 东莞本凡网络技术有限公司 | Intelligent driving supervision method and system based on artificial intelligence |
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Application publication date: 20221213 |