CN107521500A - Information acquisition method and device - Google Patents
Information acquisition method and device Download PDFInfo
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- CN107521500A CN107521500A CN201710792535.0A CN201710792535A CN107521500A CN 107521500 A CN107521500 A CN 107521500A CN 201710792535 A CN201710792535 A CN 201710792535A CN 107521500 A CN107521500 A CN 107521500A
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- 238000000034 method Methods 0.000 title claims abstract description 61
- 230000015654 memory Effects 0.000 claims description 8
- 238000004422 calculation algorithm Methods 0.000 claims description 5
- 238000004590 computer program Methods 0.000 claims description 5
- 230000007774 longterm Effects 0.000 claims 1
- 239000010426 asphalt Substances 0.000 description 13
- 230000006399 behavior Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 238000010801 machine learning Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000007787 long-term memory Effects 0.000 description 2
- 230000005291 magnetic effect Effects 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 241000218691 Cupressaceae Species 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 239000010639 cypress oil Substances 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 239000003921 oil Substances 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000006403 short-term memory Effects 0.000 description 1
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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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
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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
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/05—Type of road, e.g. motorways, local streets, paved or unpaved roads
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Abstract
This application discloses information acquisition method and device.One embodiment of this method includes：The sound generated during the traveling of collection vehicle, the feature of the sound that the vehicle collected generates in the process of moving and vehicle traveling road feature it is associated；The sound and roadway characteristic identification model generated in the process of moving based on the vehicle collected, obtain vehicle traveling road feature, wherein, the corresponding relation between the feature of roadway characteristic identification model instruction sound and the feature of road.Realize using roadway characteristic identification model in the case where the position of vehicle need not be determined, obtain vehicle traveling road current pavement behavior.
Description
Technical field
The application is related to vehicular field, and in particular to environment sensing field, more particularly to information acquisition method and device.
Background technology
At present, as sensor is increasingly being applied in vehicle so that vehicle is more and more intelligent, and vehicle can be with intelligence
Can ground perception running environment.During vehicle perceives running environment, the perception for the pavement behavior of road is crucial ring
One of section.At present, the mode of generally use is：Manually in advance on the electronic map to the road surface of the road in each section
Situation is labeled, and the position of vehicle is determined according to GPS, determines the section where the position of vehicle, then, from electronic map
The pavement behavior of the road in the section where the position of the vehicle of acquisition mark.
But, on the one hand, the section of gps signal can not be got because gps signal is interfered at some, car can not be determined
Position where section, lead to not get the road surface shape in the section where the position of the vehicle marked in electronic map
Condition.On the other hand, in the case where the pavement behavior of the road in some sections changes, by the mark road surface of electronic map
The pavement behavior in the section that situation changes, the current pavement behavior in the section that pavement behavior changes.
Invention information
This application provides a kind of information acquisition method and device, for solving technology existing for above-mentioned background section
Problem.
In a first aspect, this application provides information acquisition method, this method includes：Generated during the traveling of collection vehicle
Sound, the feature of the sound that the vehicle collected generates in the process of moving and vehicle traveling road feature it is related
Connection；The sound and roadway characteristic identification model generated in the process of moving based on the vehicle collected, obtain vehicle traveling
The feature of road, wherein, the corresponding relation between the feature of roadway characteristic identification model instruction sound and the feature of road.
Second aspect, this application provides information acquisition device, the device includes：Collecting unit, it is configured to collecting vehicle
Traveling during the sound that generates, feature and the vehicle traveling of the sound that the vehicle collected generates in the process of moving exist
The feature of road be associated；Recognition unit, be configured to the sound that is generated in the process of moving based on the vehicle collected and
Roadway characteristic identification model, obtain vehicle traveling road feature, wherein, the spy of roadway characteristic identification model instruction sound
Corresponding relation between sign and the feature of road.
The information acquisition method and device that the application provides, by the sound generated during the traveling of collection vehicle, are adopted
The feature for the sound that the vehicle collected generates in the process of moving and vehicle travel road feature it is associated；Based on collection
To the sound that generates in the process of moving of vehicle and roadway characteristic identification model, obtain vehicle traveling road feature,
Wherein, the corresponding relation between the feature of roadway characteristic identification model instruction sound and the feature of road.Realize and utilize road
Feature recognition model in the case where the position of vehicle need not be determined, obtain vehicle traveling road current road surface shape
Condition.
Brief description of the drawings
By reading the detailed description made to non-limiting example made with reference to the following drawings, the application's is other
Feature, objects and advantages will become more apparent upon：
Fig. 1 shows the exemplary system architecture of the information acquisition method or device that can apply to the application；
Fig. 2 shows the flow chart of one embodiment of the information acquisition method according to the application；
Fig. 3 shows the structural representation of one embodiment of the information acquisition device according to the application；
Fig. 4 shows a hardware architecture diagram of the vehicle suitable for the application.
Embodiment
The application is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched
The specific embodiment stated is used only for explaining related invention, rather than the restriction to the invention.It also should be noted that in order to
Be easy to describe, illustrate only in accompanying drawing to about the related part of invention.
It should be noted that in the case where not conflicting, the feature in embodiment and embodiment in the application can phase
Mutually combination.Describe the application in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
Fig. 1 shows the example system frame of the embodiment of the information acquisition method that can apply to the application or device
Structure.
System architecture includes vehicle 101, network 102 and server 103.Network 102 is in vehicle 101 and server
The medium of communication link is provided between 103.Network 102 can use wireless communication link.
Vehicle 101 can utilize the sound generated during the traveling of microphone collection vehicle 101, and vehicle 101 can be transported
Row is by between the feature that the sound generated on the road of type and the road of type are travelled for learning vehicle of Primary Construction
Corresponding relation machine learning model.Vehicle 101 can collect according to when being travelled on the road of multiple different features
Sound and road feature, the machine learning model on vehicle 101 is trained.
Vehicle 101 can also send the sound collected on the road of multiple different features to server 103.Clothes
Business device 103 can run the road for learning the vehicle sound that is generated on the road of type of traveling and type feature it
Between corresponding relation machine learning model, sound that server 103 can collect according to vehicle 101 and when collecting sound
Vehicle 101 travel road feature, machine learning model is trained, by after training machine learning model send
To vehicle 101.
Fig. 2 is refer to, it illustrates the flow of one embodiment of the information acquisition method according to the application.Need to illustrate
, Overall Steps or part steps in the information acquisition method that the embodiment of the present application is provided can be by vehicle (such as Fig. 1
In vehicle 101) perform.This method comprises the following steps：
Step 201, the sound generated during the traveling of collection vehicle.
In the present embodiment, the sound that collection vehicle generates in the process of moving can be that collection vehicle crosses in current line
Cheng Zhong, the tire of vehicle of the sound source near the tire of vehicle and road contact and the sound that generates.The vehicle collected is expert at
The sound generated during sailing and vehicle current driving road feature it is associated.
For example, waveform of the feature of sound for the sound wave of sound, the feature of road is the type on the road surface of road, such as cypress
Oil circuit, sandstone road.When vehicle traveling is when on road, for vehicle when being travelled on the road of different road surface types, sound source is in car
Tire near the waveform of sound wave of sound be associated with the frictional force on road surface with tire, correspondingly, collect
The waveform of the sound wave of sound and vehicle travel road feature it is associated.
In the present embodiment, it can utilize what is generated during the traveling of the microphone collection vehicle of vehicle bottom
Sound.For example, it can utilize during the traveling for the microphone collection vehicle that the bottom of vehicle is installed close to the position of tire
The sound of generation.
In some optional implementations of the present embodiment, the feature of road includes：The road surface types of road, road
Flatness.The sound that vehicle generates in the process of moving and vehicle travel the road surface types of road, road flatness phase
Association.
Step 202, based on the sound and roadway characteristic identification model collected, the feature of road is obtained.
In the present embodiment, after the sound generated during the traveling by step 201 collection vehicle, can be based on
The sound and roadway characteristic identification model collected, obtain vehicle traveling road feature i.e. vehicle current driving road
The feature on road.
For example, the feature of the sound generated during the traveling of the vehicle collected includes：The sound wave of the sound collected
Waveform, the crest of waveform, the numerical value etc. of trough, vehicle traveling the feature of road include：Road surface types, the road of road
Flatness etc..Vehicle on identical road surface types but the different road of flatness when travelling, the traveling of the vehicle collected
During the waveform of sound wave, the crest of waveform, the numerical value of trough of the sound that generate be also different.Vehicle is identical in flatness
But when being travelled on the different road of road surface types, the waveform of the sound wave of the sound generated during the traveling of the vehicle collected,
The crest of waveform, the numerical value of trough are also different.
In the present embodiment, roadway characteristic identification model can indicate the sound wave for the sound that vehicle traveling generates on road
Waveform, the crest of waveform, the road surface types of the feature such as numerical value of trough and road, the corresponding relation of the feature such as flatness.
For example, including multiple items of information in roadway characteristic identification model, each item of information includes the ripple of the sound wave of sound
Shape, the crest of waveform, the waveform of sound wave of the numerical value of trough and the sound, the crest of waveform, trough numerical value corresponding to road
Road surface types, flatness.
Can the sound that is generated on the road of type of collection vehicle traveling respectively in advance, the spy of the road of different types
At least one feature in sign is different.For example, the road of two different types can be that road surface types are identical but flatness not
Same road, the road of two different types can be the road that flatness is identical but road surface types are different.Vehicle can divide
Do not travelled on identical road surface types but the different road of flatness, collection traveling is in identical road surface types but smooth respectively
The sound generated is spent on different roads.Vehicle can travel on identical in flatness but different road surface types road respectively,
Collection travels the sound generated on road identical in flatness but different road surface types respectively.It will can each time collect car
The feature of the sound that is generated on the road of a type of traveling and the road of the type is added to as an item of information
In the feature recognition model of road.
In the present embodiment, the sound generated during the traveling of the vehicle collected by step 201 can be extracted
Feature, it is then possible to find out the sound generated in the process of moving with the vehicle collected in roadway characteristic identification model
The feature of the characteristic similarity highest sound of sound, it is then possible to further obtain in roadway characteristic identification model with collection
To the feature of the characteristic similarity highest sound of sound that generates in the process of moving of vehicle corresponding to road feature, can
With the corresponding road of the feature of the characteristic similarity highest sound for the sound that will be generated in the process of moving with the vehicle collected
The feature on road as vehicle travel road feature be vehicle current driving road feature.
In some optional implementations of the present embodiment, using roadway characteristic identification model based on the car collected
The sound generated in the process of moving judge vehicle traveling road feature before, can be to roadway characteristic identification model
It is trained.Vehicle can be travelled on the road of different types in advance, and collection vehicle is travelled in multiple types respectively in advance
Road on the sound that generates.
Can based on the vehicle traveling collected multiple types road on the feature of sound that generates and multiple classes
The feature of the road of type, roadway characteristic identification model is trained.For example, vehicle can be in advance respectively in the high cypress of flatness
Travelled on the road of low three types of gravel road of the low asphalt road of oil circuit, flatness, flatness, collection vehicle is in three types
Road on travel the sound of generation.Travelled using the vehicle collected on the road of three types generation sound and three
The feature of the road of type, roadway characteristic identification model is trained.
For the road of a type, the sound generated on the road of the type can be travelled with multi collect vehicle, obtained
The sound generated to multiple vehicles traveling on the road of the type, is travelled in the road of the type using multiple vehicles collected
The sound and the feature of the road of the type generated on road, to being trained to roadway characteristic identification model.
In a training process, the vehicle collected can be utilized to travel the road of a type in multiple types
The feature of the sound of upper generation and the feature of the road of the type are trained to roadway characteristic identification model.It can generate respectively
Corresponding to input vector corresponding to the sound that the vehicle traveling collected generates on the road of the type and the road of the type
Roadway characteristic vector.Corresponding one of each component in input vector is on the road that the vehicle collected travels in the type
The feature of the sound of generation, the feature of the road of corresponding the type of each component in roadway characteristic vector.Once
In training process, the input vector can be input to roadway characteristic identification model, obtain predict output vector, prediction output to
One spy of the road of the type that each representation in components roadway characteristic identification model in amount is predicted based on input vector
Sign.The prediction output vector and the difference of roadway characteristic vector that can be exported based on roadway characteristic identification model, using under gradient
Algorithm is dropped, adjusts the model parameter of roadway characteristic identification model, so as to complete the once training to roadway characteristic identification model
Journey.
For example, the waveform of sound wave of the feature of the sound collected comprising the sound collected, the crest of waveform, trough
Numerical value, the vehicle asphalt road in flatness 80%, the asphalt road of flatness 50%, the gravel road three of flatness 30% respectively in advance
Travelled on the road of individual type, collect the sound that vehicle travels generation on the road of three types respectively.
It can generate respectively defeated corresponding to the sound that the vehicle traveling collected generates on the asphalt road of flatness 80%
Incoming vector, the vehicle collected travel input vector corresponding to the sound generated on the asphalt road of flatness 50%, collected
The sound that is generated on the gravel road of the gravel road of flatness 30% of vehicle traveling corresponding to input vector.The vehicle collected
Travel input vector corresponding to the sound generated on the asphalt road of flatness 80% and include expression vehicle traveling in flatness
The component of the waveform of the sound wave of the sound generated on 80% asphalt road, the crest of waveform numerical value component, the numerical value of trough
Component, accordingly, roadway characteristic vector corresponding to the asphalt road of flatness 80% is comprising representing the component of asphalt road, represent flat
The component of whole degree 80%.Input vector corresponding to the sound that the vehicle traveling collected generates on the asphalt road of flatness 50%
The component of the waveform of the sound wave of the sound generated comprising expression vehicle traveling on the asphalt road of flatness 50%, the crest of waveform
The component of numerical value, trough numerical value component.Accordingly, roadway characteristic vector includes corresponding to the asphalt road of flatness 50%
Represent the component of asphalt road, represent the component of flatness 50%.The sound generated on the gravel road of the flatness 30% collected
Corresponding input vector includes the waveform for the sound wave for representing the sound that vehicle traveling generates on the gravel road of flatness 30%
Component, the component of numerical value of crest of waveform, trough numerical value component.Accordingly, the gravel road of flatness 30% includes table
Show the component of gravel road, represent the component of flatness 30%.
Aforesaid way can be used to be travelled using the vehicle collected on the road of each type in multiple types
The feature of the sound of generation and the feature of road are repeatedly trained to roadway characteristic identification model respectively.In multiple training process
Afterwards, roadway characteristic identification model can be with the feature of instruction sound and the feature corresponding relation of road.
In some optional implementations of the present embodiment, roadway characteristic identification model can be LSTM (Long
Short-Term Memory, shot and long term memory network) model.LSTM models are serializing model, have what input length differed
Serialize feature.The input of LSTM mnemons is LSTM hidden layer, and the input of LSTM hidden layers is LSTM input layer.
The hidden layer of LSTM models, the output of mnemon is also all sequence.
In a training process, the vehicle collected can be utilized to travel the road of a type in multiple types
The feature of the sound of upper generation and the feature of the road of the type are trained to LSTM models.It can generate what is collected respectively
The input vector of LSTM models corresponding to the sound that vehicle traveling generates on the road of the type and the road of the type are corresponding
Roadway characteristic vector.Corresponding one of each component in the input vector of LSTM models is travelled at this in the vehicle collected
The feature of the sound generated on the road of type, one of the road of each representation in components the type in roadway characteristic vector
Feature.In a training process, the input vector can be input to LSTM models, and using the roadway characteristic vector as
The target output vector of LSTM models.After the input vector is input into LSTM models, it can obtain predicting output vector, in advance
The road of the type that each the representation in components roadway characteristic identification model surveyed in output vector is predicted based on input vector
A feature.Roadway characteristic vector corresponding to the prediction output vector and the road of the type that can be exported based on LSTM models
Difference, using gradient descent algorithm, the model parameter of LSTM models is adjusted, so as to complete the once training to LSTM models
Process.
Aforesaid way can be used to be travelled using the vehicle collected on the road of each type in multiple types
The feature of the sound of generation and the feature of road are repeatedly trained to LSTM models respectively.After multiple training process,
LSTM models can be with the feature of instruction sound and the feature corresponding relation of road.
In some optional implementations of the present embodiment, using roadway characteristic identification model based on the car collected
The sound generated in the process of moving judge vehicle traveling road feature when, the vehicle collected can be extracted and be expert at
The feature of the sound generated during sailing, generate inputted corresponding to the sound that the vehicle collected generates in the process of moving to
Amount, wherein, a spy of the sound that the vehicle that each representation in components in input vector collects generates in the process of moving
Sign.It is then possible to input vector corresponding to the sound that the vehicle collected is generated in the process of moving is input to roadway characteristic
Identification model, obtain output vector, wherein, each representation in components vehicle in output vector traveling road be that vehicle is worked as
It is preceding traveling road a feature.So as to, according to the vehicle of each representation in components traveling road be that vehicle is current
Travel road a feature, can obtain vehicle traveling the road surface types of road, all features such as flatness.
Fig. 3 is refer to, as the realization to method shown in above-mentioned each figure, this application provides a kind of information acquisition device
One embodiment, the device embodiment are corresponding with the embodiment of the method shown in Fig. 2.
As shown in figure 3, information acquisition device includes：Collecting unit 301, recognition unit 302.Wherein, collecting unit 301 is matched somebody with somebody
The sound generated during the traveling for collection vehicle is put, the feature for the sound that the vehicle collected generates in the process of moving
With vehicle traveling road feature it is associated；Recognition unit 302 is configured to running over journey based on the vehicle collected
The sound and roadway characteristic identification model of middle generation, obtain vehicle traveling road feature, wherein, roadway characteristic identification mould
Corresponding relation between the feature of type instruction sound and the feature of road.
In some optional implementations of the present embodiment, the feature of road includes：The road surface types of road, road
Flatness.
In some optional implementations of the present embodiment, information acquisition device also includes：Training unit, it is configured to
Before the sound generated during the traveling of collection vehicle, collection vehicle traveling generates on the road of multiple types respectively
Sound, wherein, the road of each type in multiple types has at least one spy differed with other kinds of road
Sign；The spy of the feature of the sound generated based on the vehicle traveling collected on the road of multiple types and the road of multiple types
Sign, is trained to roadway characteristic identification model.
In some optional implementations of the present embodiment, training unit is further configured to：What generation collected
Input vector corresponding to the sound generated on the road of a type of the vehicle traveling in the road of multiple types, wherein, it is defeated
The feature of each one sound of representation in components in incoming vector；Generate roadway characteristic corresponding to the road of the type to
Amount, wherein, a feature of the road of each representation in components the type in roadway characteristic vector；Input vector is input to
Roadway characteristic identification model, obtain predicting output vector, wherein, predict each representation in components roadway characteristic in output vector
One feature of the road of the type that identification model is predicted based on input vector；It is special based on prediction output vector and the road
The difference of vector is levied, the model parameter of roadway characteristic identification model is adjusted using gradient descent algorithm.
In some optional implementations of the present embodiment, recognition unit includes：Model Identification subelement, is configured to
The feature for the sound that the vehicle collected generates in the process of moving is extracted, the vehicle collected is generated and generates in the process of moving
Sound corresponding to input vector, wherein, the vehicle that each representation in components in input vector collects is in the process of moving
One feature of the sound of generation；Input vector is input to roadway characteristic identification model, obtains output vector, wherein, output
In vector each representation in components vehicle traveling road a feature.
In some optional implementations of the present embodiment, roadway characteristic identification model is shot and long term memory network mould
Type.
Fig. 4 is refer to, it illustrates the vehicle suitable for the application a hardware architecture diagram.
As shown in figure 4, vehicle includes CPU401, memory 402, microphone 403, GPS404, microphone 403 can be set
In the bottom of vehicle close to the position of the tire of vehicle.CPU401, memory 402, microphone 403, GPS404 pass through bus 405
It is connected with each other.Computer program may be implemented as according to the information acquisition method of the application, comprising upper in the computer program
State the instruction of the operation described in embodiment.Computer program can be stored in memory 402.The CPU 401 of vehicle passes through
The computer program stored in memory 402 is called, the sound generated in the process of moving according to vehicle, determines that vehicle traveling exists
Road feature.
Present invention also provides a kind of vehicle, the vehicle can be configured with one or more processors；Memory, for depositing
One or more programs are stored up, can be included in one or more programs to perform the operation described in above-mentioned steps 201-202
Instruction.When one or more programs are executed by one or more processors so that one or more processors perform above-mentioned
Operation described in step 201-202.
Present invention also provides a kind of computer-readable medium, the computer-readable medium can be included in vehicle
's；Can also be individualism, without in supplying vehicle.Above computer computer-readable recording medium carries one or more program,
When one or more program is performed by vehicle so that vehicle：The sound generated during the traveling of collection vehicle, is collected
The feature of sound that generates in the process of moving of vehicle and vehicle traveling road feature it is associated；Based on what is collected
The sound and roadway characteristic identification model that vehicle generates in the process of moving, obtain vehicle traveling road feature, wherein,
Corresponding relation between the feature of roadway characteristic identification model instruction sound and the feature of road.
It should be noted that computer-readable medium described herein can be computer-readable signal media or meter
Calculation machine readable storage medium storing program for executing either the two any combination.Computer-readable recording medium can for example include but unlimited
In the system of electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor, device or device, or any combination above.Computer can
Reading the more specifically example of storage medium can include but is not limited to：Electrically connecting with one or more wires, portable meter
Calculation machine disk, hard disk, random access storage device (RAM), read-only storage (ROM), erasable programmable read only memory
(EPROM or flash memory), optical fiber, portable compact disc read-only storage (CD-ROM), light storage device, magnetic memory device or
The above-mentioned any appropriate combination of person.In this application, computer-readable recording medium can be any includes or storage program
Tangible medium, the program can be commanded execution system, device either device use or it is in connection.And in this Shen
Please in, computer-readable signal media can include in a base band or as carrier wave a part propagation data-signal, its
In carry computer-readable program code.The data-signal of this propagation can take various forms, and include but is not limited to
Electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be computer-readable
Any computer-readable medium beyond storage medium, the computer-readable medium can send, propagate or transmit for by
Instruction execution system, device either device use or program in connection.The journey included on computer-readable medium
Sequence code can be transmitted with any appropriate medium, be included but is not limited to：Wirelessly, electric wire, optical cable, RF etc., or it is above-mentioned
Any appropriate combination.
Flow chart and block diagram in accompanying drawing, it is illustrated that according to the system of the various embodiments of the application, method and computer journey
Architectural framework in the cards, function and the operation of sequence product.At this point, each square frame in flow chart or block diagram can generation
The part of one module of table, program segment or code, the part of the module, program segment or code include one or more use
In the executable instruction of logic function as defined in realization.It should also be noted that marked at some as in the realization replaced in square frame
The function of note can also be with different from the order marked in accompanying drawing generation.For example, two square frames succeedingly represented are actually
It can perform substantially in parallel, they can also be performed in the opposite order sometimes, and this is depending on involved function.Also to note
Meaning, the combination of each square frame and block diagram in block diagram and/or flow chart and/or the square frame in flow chart can be with holding
Function as defined in row or the special hardware based system of operation are realized, or can use specialized hardware and computer instruction
Combination realize.
Being described in unit involved in the embodiment of the present application can be realized by way of software, can also be by hard
The mode of part is realized.Described unit can also be set within a processor, for example, can be described as：A kind of processor bag
Include collecting unit, recognition unit.Wherein, the title of these units does not form the limit to the unit in itself under certain conditions
It is fixed, for example, collecting unit is also described as " being used for during the traveling of collection vehicle the unit of sound generated ".
Above description is only the preferred embodiment of the application and the explanation to institute's application technology principle.People in the art
Member should be appreciated that invention scope involved in the application, however it is not limited to the technology that the particular combination of above-mentioned technical characteristic forms
Scheme, while should also cover in the case where not departing from the inventive concept, carried out by above-mentioned technical characteristic or its equivalent feature
Other technical schemes that any combination is closed and formed.Such as features described above have with (but not limited to) disclosed herein it is similar
The technical scheme that the technical characteristic of function is replaced mutually and formed.
Claims (12)
1. a kind of information acquisition method, it is characterised in that methods described includes：
The sound generated during the traveling of collection vehicle, the feature of the sound and vehicle traveling road feature it is related
Connection；
Based on the sound and roadway characteristic identification model, the feature of the road is obtained, wherein, the roadway characteristic identifies mould
Corresponding relation between the feature of type instruction sound and the feature of road.
2. according to the method for claim 1, it is characterised in that the feature of road includes：The road surface types of road, road
Flatness.
3. according to the method for claim 2, it is characterised in that the sound generated during the traveling of collection vehicle it
Before, methods described also includes：
The sound that collection vehicle traveling generates on the road of multiple types respectively, wherein, each type in multiple types
Road and other kinds of road there is at least one feature differed；
The feature of sound that is generated based on the vehicle traveling collected on the road of multiple types and the road of multiple types
Feature, roadway characteristic identification model is trained.
4. according to the method for claim 3, it is characterised in that the road in multiple types is travelled based on the vehicle collected
The feature of the road of the feature of the sound of upper generation and multiple types, roadway characteristic identification model is trained including：
The vehicle collected is generated to travel corresponding to the sound generated on the road of a type in the road of multiple types
Input vector, wherein, a feature of sound described in each representation in components in the input vector；
Roadway characteristic vector corresponding to the road of the type is generated, wherein, each component in the roadway characteristic vector
Represent a feature of the road of the type；
The input vector is input to roadway characteristic identification model, obtains predicting output vector, wherein, predict in output vector
Predicted based on the input vector one of the road of the type of each representation in components roadway characteristic identification model
Feature；
Difference based on prediction output vector and roadway characteristic vector, using gradient descent algorithm adjustment roadway characteristic identification
The model parameter of model.
5. according to the method for claim 4, it is characterised in that based on the sound and roadway characteristic identification model, obtain
The feature of the road includes：
The feature of the sound is extracted, generates input vector corresponding to the sound, wherein, each in the input vector
One feature of sound described in representation in components；
The input vector is input to roadway characteristic identification model, obtains output vector, wherein, it is every in the output vector
One-component represents a feature of the road.
6. according to the method described in one of claim 1-5, it is characterised in that the roadway characteristic identification model is remembered for shot and long term
Recall network model.
7. a kind of information acquisition device, it is characterised in that described device includes：
Collecting unit, is configured to the sound generated during the traveling of collection vehicle, and feature and the vehicle of the sound travel
The feature of road be associated；
Recognition unit, it is configured to be based on the sound and roadway characteristic identification model, obtains the feature of the road, wherein,
Corresponding relation between the feature of the roadway characteristic identification model instruction sound and the feature of road.
8. device according to claim 7, it is characterised in that described device also includes：
Training unit, it is configured to before the sound that is generated during the traveling of collection vehicle, collection vehicle traveling exists respectively
The sound generated on the road of multiple types, wherein, the road of each type in multiple types and other kinds of road
With at least one feature differed；The spy of the sound generated based on the vehicle traveling collected on the road of multiple types
The feature of the road for multiple types of seeking peace, is trained to roadway characteristic identification model.
9. device according to claim 8, it is characterised in that training unit is further configured to：What generation collected
Input vector corresponding to the sound generated on the road of a type of the vehicle traveling in the road of multiple types, wherein, institute
State a feature of sound described in each representation in components in input vector；It is special to generate road corresponding to the road of the type
Sign vector, wherein, a feature of the road of type described in each representation in components in the roadway characteristic vector；By described in
Input vector is input to roadway characteristic identification model, obtains predicting output vector, wherein, predict each point in output vector
Amount represents a feature of the road for the type that roadway characteristic identification model is predicted based on the input vector；Based on pre-
Output vector and the difference of roadway characteristic vector are surveyed, the model of roadway characteristic identification model is adjusted using gradient descent algorithm
Parameter.
10. device according to claim 9, it is characterised in that recognition unit includes：
Model Identification subelement, it is configured to extract the feature of the sound, generates input vector corresponding to the sound, its
In, a feature of sound described in each representation in components in the input vector；The input vector is input to road
Feature recognition model, obtains output vector, wherein, a spy of road described in each representation in components in the output vector
Sign.
A kind of 11. vehicle, it is characterised in that including：
One or more processors；
Memory, for storing one or more programs,
When one or more of programs are by one or more of computing devices so that one or more of processors
Realize the method as described in any in claim 1-6.
A kind of 12. computer-readable recording medium, it is characterised in that be stored thereon with computer program, it is characterised in that the journey
The method as described in any in claim 1-6 is realized when sequence is executed by processor.
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| CN107521500B (en) | 2019-11-05 |
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