CN107450511A - Assess method, apparatus, equipment and the computer-readable storage medium of wagon control model - Google Patents
Assess method, apparatus, equipment and the computer-readable storage medium of wagon control model Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
Abstract
The present invention provides a kind of method, apparatus, equipment and computer-readable storage medium for assessing wagon control model, wherein assessing the method for wagon control model includes：Collection vehicle running data；The output data that wagon control model is directed to the vehicle operation data is obtained, determines to assess parameter value as model evaluation parameter value according to output data；And calculated according to vehicle operation data and assess parameter value as criterion evaluation parameter value；Using the mean square deviation corresponding to same timestamp between model evaluation parameter value and criterion evaluation parameter value, the wagon control model is assessed.By technical scheme provided by the present invention, realize it is objective, assess wagon control model exactly.
Description
【Technical field】
The present invention relates to driving technology field, more particularly to a kind of method, apparatus for assessing wagon control model, equipment and
Computer-readable storage medium.
【Background technology】
In recent years, revolution was generated with the developing rapidly of deep learning, the further investigation of artificial intelligence, auto industry
The change of property.Realize that the automatic Pilot of vehicle is a main direction of studying in driving field by deep learning, and it is how right
It is the important guarantee for realizing vehicle safety automatic Pilot that the wagon control model obtained by deep learning, which assess,.
【The content of the invention】
In view of this, the invention provides a kind of method, apparatus, equipment and computer storage for assessing wagon control model
Medium, realize it is objective, exactly assess wagon control model.
The present invention is that technical scheme is to provide a kind of method for assessing wagon control model used by solving technical problem,
Methods described includes：Collection vehicle running data；The output data that wagon control model is directed to the vehicle operation data is obtained,
Determine to assess parameter value as model evaluation parameter value according to output data；And calculated according to vehicle operation data and assess ginseng
Numerical value is as criterion evaluation parameter value；Using corresponding to same timestamp between model evaluation parameter value and criterion evaluation parameter value
Mean square deviation, assess the wagon control model.
According to one preferred embodiment of the present invention, the assessment parameter is traveling curvature, and the wagon control model is vehicle
Lateral control model, the output data are steering wheel angle.
According to one preferred embodiment of the present invention, the vehicle operation data includes：Vehicle position data and each vehicle position
Put timestamp corresponding to data.
According to one preferred embodiment of the present invention, described calculated according to vehicle operation data assesses parameter value as criterion evaluation
Parameter value includes：According to timestamp corresponding to vehicle position data and each vehicle position data, calculate corresponding to each timestamp
Travel curvature value；Interpolation calculation is carried out to travelling curvature value corresponding to each timestamp respectively, obtains list where corresponding each timestamp
Multiple traveling curvature values of position time interval；Respectively from multiple traveling curvature values of corresponding each timestamp unit one belongs to time interval
In select a traveling curvature value as corresponding each timestamp；The traveling curvature value of predetermined threshold value requirement will be met as corresponding
The criterion evaluation parameter value of each timestamp.
According to one preferred embodiment of the present invention, it is described to determine to assess parameter value as model evaluation parameter according to output data
Value includes：The steering wheel angle of corresponding each timestamp is converted to the traveling curvature value of corresponding each timestamp using preset model；
Model evaluation parameter value of the traveling curvature value as corresponding each timestamp of predetermined threshold value requirement will be met.
According to one preferred embodiment of the present invention, it is described to utilize model evaluation parameter value and standard corresponding to same timestamp
Before assessing the mean square deviation assessment wagon control model between parameter value, in addition to：Judge the model evaluation parameter value
Number whether be more than predetermined threshold value, if being more than, the model evaluation parameter value is calculated based on the timestamp and standard is commented
Estimate the mean square deviation between parameter value, otherwise do not calculate.
The present invention is to provide a kind of device for assessing wagon control model to solve the technical scheme that technical problem uses,
Described device includes：Collecting unit, for collection vehicle running data；Determining unit, it is directed to for obtaining wagon control model
The output data of the vehicle operation data, determine to assess parameter value as model evaluation parameter value according to output data；And
Calculated according to vehicle operation data and assess parameter value as criterion evaluation parameter value；Assessment unit, for utilizing same timestamp
Mean square deviation between corresponding model evaluation parameter value and criterion evaluation parameter value, assesses the wagon control model.
According to one preferred embodiment of the present invention, the assessment parameter is traveling curvature, and the wagon control model is vehicle
Lateral control model, the output data are steering wheel angle.
According to one preferred embodiment of the present invention, the vehicle operation data that the collecting unit is gathered includes：Vehicle location
Timestamp corresponding to data and each vehicle position data.
According to one preferred embodiment of the present invention, the determining unit is assessing parameter for being calculated according to vehicle operation data
It is specific to perform when value is used as criterion evaluation parameter value：According to the time corresponding to vehicle position data and each vehicle position data
Stamp, calculate traveling curvature value corresponding to each timestamp；Interpolation calculation is carried out to travelling curvature value corresponding to each timestamp respectively, is obtained
To multiple traveling curvature values of corresponding each timestamp unit one belongs to time interval；Respectively from corresponding each timestamp unit one belongs to time
A traveling curvature value as corresponding each timestamp is selected in multiple traveling curvature values in section；Predetermined threshold value requirement will be met
Criterion evaluation parameter value of the traveling curvature value as each timestamp of correspondence.
According to one preferred embodiment of the present invention, the determining unit according to output data for determining that assessing parameter value makees
For model evaluation parameter value when, it is specific to perform：The steering wheel angle of corresponding each timestamp is converted to correspondingly using preset model
The traveling curvature value of each timestamp；Model evaluation of the traveling curvature value as corresponding each timestamp of predetermined threshold value requirement will be met
Parameter value.
According to one preferred embodiment of the present invention, the assessment unit is utilizing model evaluation parameter corresponding to same timestamp
Before mean square deviation between value and criterion evaluation parameter value assesses the wagon control model, also perform：Judge that the model is commented
Whether the number for estimating parameter value is more than predetermined threshold value, if being more than, the model evaluation parameter value is calculated based on the timestamp
Mean square deviation between criterion evaluation parameter value, is not otherwise calculated.
As can be seen from the above technical solutions, the present invention is based on same timestamp, calculates criterion evaluation parameter value and mould
Type assesses the mean square deviation between parameter value, and wagon control model is assessed using resulting mean square deviation, realize it is objective, comment exactly
Estimate wagon control model.
【Brief description of the drawings】
Fig. 1 is the method flow diagram for the assessment wagon control model that one embodiment of the invention provides.
Fig. 2 is the structure drawing of device for the assessment wagon control model that one embodiment of the invention provides.
Fig. 3 is the block diagram for the computer system/server that one embodiment of the invention provides.
【Embodiment】
In order that the object, technical solutions and advantages of the present invention are clearer, below in conjunction with the accompanying drawings with specific embodiment pair
The present invention is described in detail.
The term used in embodiments of the present invention is only merely for the purpose of description specific embodiment, and is not intended to be limiting
The present invention." one kind ", " described " and "the" of singulative used in the embodiment of the present invention and appended claims
It is also intended to including most forms, unless context clearly shows that other implications.
It should be appreciated that term "and/or" used herein is only a kind of incidence relation for describing affiliated partner, represent
There may be three kinds of relations, for example, A and/or B, can be represented：Individualism A, while A and B be present, individualism B these three
Situation.In addition, character "/" herein, it is a kind of relation of "or" to typically represent forward-backward correlation object.
Depending on linguistic context, word as used in this " if " can be construed to " ... when " or " when ...
When " or " in response to determining " or " in response to detection ".Similarly, depending on linguistic context, phrase " if it is determined that " or " if detection
(condition or event of statement) " can be construed to " when it is determined that when " or " in response to determine " or " when the detection (condition of statement
Or event) when " or " in response to detecting (condition or event of statement) ".
In the present invention, on the one hand using the mean square deviation between the selected normal data for assessing parameter and model data come
Assess wagon control model, on the other hand, choose more pervasive, objective assessment parameter, so as to realize it is objective, assess exactly
Wagon control model.
If direct use direction disk angle, vehicle shift distance between center line etc. assess parameter and carry out commenting for wagon control model
When estimating, it can be influenceed by the intrinsic parameter of vehicle.In embodiments of the present invention, curvature is preferably travelled as vehicle lateral control mould
The assessment parameter of type.Traveling curvature represents the angle of turn of vehicle in the process of moving, with radius of turn in vehicle running path
Correlation, therefore by vehicle, inherently parameter is not influenceed traveling curvature, chooses traveling curvature as vehicle lateral control model
Assessment parameter can be more objective, accurate.Traveling curvature is hereinafter chosen as parameter is assessed, to vehicle lateral control model
Evaluation process be described.
Fig. 1 is the method flow diagram for the assessment wagon control model that one embodiment of the invention provides.As shown in fig. 1, institute
The method of stating includes：
In 101, collection vehicle running data.
In this step, the vehicle operation data gathered includes vehicle position data and each vehicle position data is corresponding
Timestamp.
Wherein, vehicle position data is the longitude and latitude or coordinate of vehicle present position in the process of moving；Each vehicle location
At the time of timestamp corresponding to data is that vehicle is corresponding when driving to each position.It is understood that vehicle is travelling
During be able to record passed through position and at the time of by corresponding to each position, therefore this step just can be according to vehicle
The data of record, collect the vehicle row including timestamp corresponding to vehicle position data and each vehicle position data
Sail data.
In 102, the output data that wagon control model is directed to the vehicle operation data is obtained, it is true according to output data
Accepted opinion estimates parameter value as model evaluation parameter value；And calculate assessment parameter value according to vehicle operation data and commented as standard
Estimate parameter value.
First, term involved in this step is explained：Wagon control model is vehicle lateral control model, its
For controlling the steering of vehicle；Output data is steering wheel angle；Parameter is assessed as traveling curvature, it is bent for traveling to assess parameter value
Rate value.
In this step, after obtaining wagon control model for the output data of vehicle operation data, according to acquired
Output data determines to assess parameter value as model evaluation parameter value.
Specifically, after the steering wheel angle exported when obtaining vehicle and driving to position by wagon control model,
According to acquired steering wheel angle, the steering wheel angle of corresponding each position is converted into corresponding each position using preset model
Travel curvature value.Wherein, the model for conversion direction disk corner and traveling curvature value can be Ackermann models, also may be used
Think other switching networks.Because in acquired vehicle operation data, vehicle traveling-position is corresponding with the vehicle traveling moment
, i.e. vehicle traveling-position is corresponding with timestamp, therefore the traveling curvature value for the corresponding each position being converted to is namely corresponding
The traveling curvature value of each timestamp.
After the traveling curvature value of each timestamp of correspondence exported by wagon control model is obtained, default threshold will be unsatisfactory for
The traveling curvature value of value requirement is filtered as exceptional value, and the traveling curvature value for meeting predetermined threshold value requirement is commented as model
Estimate parameter value.
In this step, calculated according to vehicle operation data and assess parameter value as criterion evaluation parameter value.
Specifically, according to timestamp corresponding to vehicle position data in vehicle operation data and each vehicle position data,
The traveling curvature value corresponding to each timestamp is calculated using preset formula.Wherein, the preset formula of vehicle traveling curvature value is calculated
It is as follows：
In above-mentioned formula：K represents traveling curvature value；X represents longitude, and y represents latitude, i.e. x, y is actual longitude and latitude warp
Obtain representing vehicle location after crossing coordinate transform；T represents timestamp.
After obtaining travelling curvature value corresponding to each timestamp, respectively to travelling curvature corresponding to resulting each timestamp
Value carries out interpolation calculation, obtains multiple traveling curvature values of corresponding each timestamp unit one belongs to time interval, then respectively from corresponding
One is selected in multiple traveling curvature values of each timestamp unit one belongs to time interval, the traveling curvature as corresponding each timestamp
Value.It is understood that change is little in unit interval section due to traveling curvature value, therefore choose obtained by interpolation calculation
Can to any one in multiple traveling curvature values.In the present invention, multiple rows obtained by interpolation calculation are preferentially chosen
Sail the traveling curvature value of second traveling curvature value timestamp (t) as corresponding in curvature value.
For example, if it is k that traveling curvature value of the vehicle at certain timestamp (t), certain position (x, y) place, which is calculated, profit
Carry out interpolation calculation with resulting traveling curvature value k, with obtain [t, t+1) multiple traveling curvature value (k in this second1,
k2,k3....kn), one is then chosen from by multiple curvature obtained by interpolation calculation as to should timestamp (t)
Curvature value is travelled, such as chooses k2For to should timestamp (t) traveling curvature value.
Wherein, the traveling curvature value of predetermined threshold value requirement will be met in the traveling curvature value of resulting each timestamp of correspondence
Filtering, it will only meet standard precompensation parameter value of the traveling curvature value as each timestamp of predetermined threshold value requirement.
For example, if the traveling curvature value for calculating obtained each timestamp of correspondence is respectively (15:36, -0.23),
(15:50,0.72) and (16:03,0.4), wherein previous item represents timestamp, latter represents traveling curvature value.It is if default
The requirement of threshold value is to travel curvature value to be less than 0.5, then will travel 0.72 filtering in curvature value, -0.23 and 0.4 is used as and is marked
Standard assesses parameter value.
In 103, using square between model evaluation parameter value and criterion evaluation parameter value corresponding to same timestamp
Difference, assess the wagon control model.
Before this step, it is also necessary to judge whether the number of acquired model evaluation parameter value meets predetermined threshold value
It is required that whether the number of i.e. judgment models assessment parameter value is more than predetermined threshold value.If the quantity of acquired model evaluation parameter value
When very few, the Evaluation accuracy of model can be influenceed because data volume is very few, it is therefore desirable to which judgment models assess the number of parameter value.
If the number of acquired model evaluation parameter value is more than predetermined threshold value, enters and commented based on the timestamp calculating model
The mean square deviation between parameter value and criterion evaluation parameter value is estimated, otherwise without calculating.Wherein, model evaluation parameter value is default
Threshold value could be arranged to the half of normal data number.
Because wagon control model belongs to regression problem, therefore the mean square deviation between observation and predicted value can be passed through
To weigh the precision of prediction of wagon control model.Therefore in this step, using criterion evaluation parameter value as observation, by model
Parameter value is assessed as predicted value, it is horizontal that the mean square deviation by calculating criterion evaluation parameter value and model evaluation parameter value assesses vehicle
To Controlling model.
In this step, the criterion evaluation parameter value and model evaluation parameter of corresponding each timestamp are first determined based on timestamp
Value, then judge under each timestamp whether and meanwhile criterion evaluation parameter value and model evaluation parameter value be present.If sometime stab
It is lower criterion evaluation parameter value and model evaluation parameter value to be present simultaneously, then by the criterion evaluation parameter value and model evaluation parameter value
Be defined as to should timestamp criterion evaluation parameter value and model evaluation parameter value, if the sometime lower only criterion evaluation of stamp
When parameter value or only model evaluation parameter value, then by the criterion evaluation parameter value or model evaluation parameter under the timestamp
Value is filtered.
For example, if sometime stamp is 15：36, to should timestamp criterion evaluation parameter value be 0.3, model is commented
It is 0.28 to estimate parameter value, then timestamp 15：Criterion evaluation parameter value corresponding to 36 is 0.3, and model evaluation parameter value is 0.28.
If under the timestamp, only exist criterion evaluation parameter value 0.3 or only exist model evaluation parameter value 0.28, then by the timestamp
Corresponding criterion evaluation parameter value or model evaluation parameter value is filtered.
Specifically, in the calculation formula for calculating the mean square deviation between criterion evaluation parameter value and model evaluation parameter value such as
Under：
In formula：MSE represents mean square deviation, and n represents data amount check, curvstandardCriterion evaluation parameter value is represented,
curvmodelRepresentative model assesses parameter value.
If according to the mean square deviation obtained by criterion evaluation parameter value and model evaluation parameter value calculation it is smaller when, show car
Lateral control model is more accurate；It is equal obtained by if parameter value calculation is assessed according to criterion evaluation parameter value and model criteria
When variance is larger, then show that vehicle lateral control model accuracy is relatively low.
Fig. 2 is the structure drawing of device for the assessment wagon control model that one embodiment of the invention provides, as shown in Figure 2, institute
Stating device includes：Collecting unit 21, determining unit 22 and assessment unit 23.
Collecting unit 21, for collection vehicle running data.
The vehicle operation data that collecting unit 21 is gathered includes vehicle position data and each vehicle position data is corresponding
Timestamp.
Wherein, vehicle position data is the longitude and latitude or coordinate of vehicle present position in the process of moving；Each vehicle location
At the time of timestamp corresponding to data is that vehicle is corresponding when driving to each position.It is understood that vehicle is travelling
During be able to record passed through position and at the time of by corresponding to each position, therefore collecting unit 21 just being capable of basis
The data of vehicle registration, collect the car including timestamp corresponding to vehicle position data and each vehicle position data
Running data.
Determining unit 22, the output data of the vehicle operation data is directed to for obtaining wagon control model, according to defeated
Go out data and determine to assess parameter value as model evaluation parameter value；And calculated according to vehicle operation data and assess parameter value work
For criterion evaluation parameter value.
First, term involved in determining unit 22 is explained：Wagon control model is vehicle lateral control mould
Type, for controlling the steering of vehicle；Output data is steering wheel angle；Parameter is assessed as traveling curvature, assesses parameter value as row
Sail curvature value.
After determining unit 22 obtains wagon control model for the output data of vehicle operation data, according to acquired defeated
Go out data and determine to assess parameter value as model evaluation parameter value.
Specifically, it is determined that the direction that unit 22 is exported when obtaining vehicle and driving to position by wagon control model
After disk corner, according to acquired steering wheel angle, the steering wheel angle of corresponding each position is converted to pair using preset model
Answer the traveling curvature value of each position.Wherein it is determined that unit 22 be used for conversion direction disk corner can be with travelling the model of curvature value
For Ackermann models, or other switching networks.Due in acquired vehicle operation data, vehicle traveling-position
Corresponding with the vehicle traveling moment, i.e. vehicle traveling-position is corresponding with timestamp, therefore the corresponding each position being converted to
Traveling curvature value namely corresponds to the traveling curvature value of each timestamp.
Determining unit 22, will not after the traveling curvature value of each timestamp of correspondence exported by wagon control model is obtained
Meet that the traveling curvature value of predetermined threshold value requirement is filtered as exceptional value, the traveling curvature value of predetermined threshold value requirement will be met
As model evaluation parameter value.
Determining unit 22 calculates according to vehicle operation data assesses parameter value as criterion evaluation parameter value.
Specifically, it is determined that unit 22 is corresponding according to vehicle position data in vehicle operation data and each vehicle position data
Timestamp, the traveling curvature value corresponding to each timestamp is calculated using preset formula.Wherein it is determined that unit 22 calculates vehicle row
The preset formula for sailing curvature value is as follows：
In above-mentioned formula：K represents traveling curvature value；X represents longitude, and y represents latitude, i.e. x, y is actual longitude and latitude warp
Obtain representing vehicle location after crossing coordinate transform；T represents timestamp.
Determining unit 22 is corresponding to resulting each timestamp respectively after obtaining travelling curvature value corresponding to each timestamp
Traveling curvature value carry out interpolation calculation, obtain multiple traveling curvature values of corresponding each timestamp unit one belongs to time interval, then
One is selected from multiple traveling curvature values of corresponding each timestamp unit one belongs to time interval respectively, as corresponding each timestamp
Traveling curvature value.It is understood that due to traveling curvature value, change is little in unit interval section, it is thus determined that unit
22 selections can by any one in multiple traveling curvature values obtained by interpolation calculation.In the present invention, determining unit 22
Second traveling curvature value timestamp (t) as corresponding in multiple traveling curvature values obtained by preferential selection interpolation calculation
Travel curvature value.
For example, however, it is determined that it is bent that traveling of the vehicle at certain timestamp (t), certain position (x, y) place is calculated in unit 22
Rate value is k, and interpolation calculation is carried out using resulting traveling curvature value k, with obtain [t, t+1) multiple travelings in this second
Curvature value (k1,k2,k3....kn), it is then determined that unit 22 chooses one from by multiple curvature obtained by interpolation calculation
As to should timestamp (t) traveling curvature value, such as choose k2For to should timestamp (t) traveling curvature value.
Wherein it is determined that unit 22 will meet predetermined threshold value requirement in the traveling curvature value of resulting each timestamp of correspondence
Curvature value filtering is travelled, will only meet standard precompensation parameter value of the traveling curvature value as each timestamp of predetermined threshold value requirement.
For example, however, it is determined that the traveling curvature value that unit 22 calculates obtained each timestamp of correspondence is respectively (15:
36, -0.23), (15:50,0.72) and (16:03,0.4), wherein previous item represents timestamp, latter represents traveling curvature
Value.If the requirement of predetermined threshold value is less than 0.5 for traveling curvature value, it is determined that 0.72 filtering that unit 22 will be travelled in curvature value,
Criterion evaluation parameter value is used as by -0.23 and 0.4.
Assessment unit 23, for utilizing corresponding to same timestamp between model evaluation parameter value and criterion evaluation parameter value
Mean square deviation, assess the wagon control model.
Assessment unit 23 is before being assessed, it is also necessary to judges whether the number of acquired model evaluation parameter value is full
Whether the number that parameter value is assessed in the requirement of sufficient predetermined threshold value, i.e. judgment models is more than predetermined threshold value.If acquired model evaluation
When the quantity of parameter value is very few, the Evaluation accuracy of model can be influenceed because data volume is very few, it is therefore desirable to which judgment models are assessed
The number of parameter value.If the number of acquired model evaluation parameter value is more than predetermined threshold value, assessment unit 23 is based on institute
The mean square deviation between the timestamp calculating model evaluation parameter value and criterion evaluation parameter value is stated, otherwise without calculating.Its
In, the predetermined threshold value of model evaluation parameter value could be arranged to the half of normal data number.
Because wagon control model belongs to regression problem, therefore the mean square deviation between observation and predicted value can be passed through
To weigh the precision of prediction of wagon control model.Therefore assessment unit 23 is using criterion evaluation parameter value as observation, by model
Parameter value is assessed as predicted value, it is horizontal that the mean square deviation by calculating criterion evaluation parameter value and model evaluation parameter value assesses vehicle
To Controlling model.
Assessment unit 23 first determines the criterion evaluation parameter value and model evaluation parameter of corresponding each timestamp based on timestamp
Value, then judge under each timestamp whether and meanwhile criterion evaluation parameter value and model evaluation parameter value be present.If sometime stab
Lower criterion evaluation parameter value and model evaluation parameter value to be present simultaneously, then assessment unit 23 is by the criterion evaluation parameter value and model
Assess parameter value be defined as to should timestamp criterion evaluation parameter value and model evaluation parameter value, if sometime stabbing lower
When having criterion evaluation parameter value or only model evaluation parameter value, then assessment unit 23 joins the criterion evaluation under the timestamp
Numerical value or model evaluation parameter value are filtered.
For example, if sometime stamp is 15：36, to should timestamp criterion evaluation parameter value be 0.3, model is commented
It is 0.28 to estimate parameter value, then timestamp 15：Criterion evaluation parameter value corresponding to 36 is 0.3, and model evaluation parameter value is 0.28.
If under the timestamp, only exist criterion evaluation parameter value 0.3 or only exist model evaluation parameter value 0.28, then by the timestamp
Corresponding criterion evaluation parameter value or model evaluation parameter value is filtered.
Specifically, assessment unit 23 is in the meter for calculating the mean square deviation between criterion evaluation parameter value and model evaluation parameter value
It is as follows to calculate formula：
In formula：MSE represents mean square deviation, and n represents data amount check, curvstandardCriterion evaluation parameter value is represented,
curvmodelRepresentative model assesses parameter value.
If assessment unit 23 is smaller according to criterion evaluation parameter value and the mean square deviation obtained by model evaluation parameter value calculation
When, then show that vehicle lateral control model is more accurate；If assessment unit 23 is commented according to criterion evaluation parameter value with model criteria
Estimate mean square deviation obtained by parameter value calculation it is larger when, then show that vehicle lateral control model accuracy is relatively low.
It is understood that according to the species to be assessed wagon control model, choosing corresponding parameter of assessing can enter
Row model evaluation.During to assess vehicle longitudinal control model, then choose car speed or vehicle acceleration be used as and assess parameter,
According to the mean square deviation between criterion evaluation parameter value and model evaluation parameter value, vehicle longitudinal control model is assessed.Also
Can be after vehicle lateral control model and vehicle longitudinal control model is assessed respectively, using the mode of weighting to wagon control
Model is assessed.The present invention is to this without limiting.
Fig. 3 shows the frame suitable for being used for the exemplary computer system/server 012 for realizing embodiment of the present invention
Figure.The computer system/server 012 that Fig. 3 is shown is only an example, function that should not be to the embodiment of the present invention and use
Range band carrys out any restrictions.
As shown in figure 3, computer system/server 012 is showed in the form of universal computing device.Computer system/clothes
The component of business device 012 can include but is not limited to：One or more processor or processing unit 016, system storage
028, the bus 018 of connection different system component (including system storage 028 and processing unit 016).
Bus 018 represents the one or more in a few class bus structures, including memory bus or Memory Controller,
Peripheral bus, graphics acceleration port, processor or the local bus using any bus structures in a variety of bus structures.Lift
For example, these architectures include but is not limited to industry standard architecture (ISA) bus, MCA (MAC)
Bus, enhanced isa bus, VESA's (VESA) local bus and periphery component interconnection (PCI) bus.
Computer system/server 012 typically comprises various computing systems computer-readable recording medium.These media can be appointed
The usable medium what can be accessed by computer system/server 012, including volatibility and non-volatile media, movably
With immovable medium.
System storage 028 can include the computer system readable media of form of volatile memory, such as deposit at random
Access to memory (RAM) 030 and/or cache memory 032.Computer system/server 012 may further include other
Removable/nonremovable, volatile/non-volatile computer system storage medium.Only as an example, storage system 034 can
For reading and writing immovable, non-volatile magnetic media (Fig. 3 is not shown, is commonly referred to as " hard disk drive ").Although in Fig. 3
Being not shown, can providing for the disc driver to may move non-volatile magnetic disk (such as " floppy disk ") read-write, and pair can
The CD drive of mobile anonvolatile optical disk (such as CD-ROM, DVD-ROM or other optical mediums) read-write.In these situations
Under, each driver can be connected by one or more data media interfaces with bus 018.Memory 028 can include
At least one program product, the program product have one group of (for example, at least one) program module, and these program modules are configured
To perform the function of various embodiments of the present invention.
Program/utility 040 with one group of (at least one) program module 042, can be stored in such as memory
In 028, such program module 042 includes --- but being not limited to --- operating system, one or more application program, other
Program module and routine data, the realization of network environment may be included in each or certain combination in these examples.Journey
Sequence module 042 generally performs function and/or method in embodiment described in the invention.
Computer system/server 012 can also with one or more external equipments 014 (such as keyboard, sensing equipment,
Display 024 etc.) communication, in the present invention, computer system/server 012 is communicated with outside radar equipment, can also be with
One or more enables a user to the equipment communication interacted with the computer system/server 012, and/or with causing the meter
Any equipment that calculation machine systems/servers 012 can be communicated with one or more of the other computing device (such as network interface card, modulation
Demodulator etc.) communication.This communication can be carried out by input/output (I/O) interface 022.Also, computer system/clothes
Being engaged in device 012 can also be by network adapter 020 and one or more network (such as LAN (LAN), wide area network (WAN)
And/or public network, such as internet) communication.As illustrated, network adapter 020 by bus 018 and computer system/
Other modules communication of server 012.It should be understood that although not shown in the drawings, computer system/server 012 can be combined
Using other hardware and/or software module, include but is not limited to：Microcode, device driver, redundant processing unit, outside magnetic
Dish driving array, RAID system, tape drive and data backup storage system etc..
Processing unit 016 is stored in program in system storage 028 by operation, so as to perform various function application with
And data processing, such as a kind of method for identifying website affinity is realized, it can include：
Collection vehicle running data；
The output data that wagon control model is directed to the vehicle operation data is obtained, determines to assess ginseng according to output data
Numerical value is as model evaluation parameter value；And calculated according to vehicle operation data and assess parameter value as criterion evaluation parameter value；
Using the mean square deviation corresponding to same timestamp between model evaluation parameter value and criterion evaluation parameter value, institute is assessed
State wagon control model.
Above-mentioned computer program can be arranged in computer-readable storage medium, i.e., the computer-readable storage medium is encoded with
Computer program, the program by one or more computers when being performed so that one or more computers are performed in the present invention
State the method flow shown in embodiment and/or device operation.For example, the method stream by said one or multiple computing devices
Journey, it can include：
Collection vehicle running data；
The output data that wagon control model is directed to the vehicle operation data is obtained, determines to assess ginseng according to output data
Numerical value is as model evaluation parameter value；And calculated according to vehicle operation data and assess parameter value as criterion evaluation parameter value；
Using the mean square deviation corresponding to same timestamp between model evaluation parameter value and criterion evaluation parameter value, institute is assessed
State wagon control model.
Over time, the development of technology, medium implication is more and more extensive, and the route of transmission of computer program is no longer limited by
Tangible medium, directly can also be downloaded from network etc..Any combination of one or more computer-readable media can be used.
Computer-readable medium can be computer-readable signal media or computer-readable recording medium.Computer-readable storage medium
Matter for example may be-but not limited to-system, device or the device of electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor, or
Combination more than person is any.The more specifically example (non exhaustive list) of computer-readable recording medium includes：With one
Or the electrical connections of multiple wires, portable computer diskette, hard disk, random access memory (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
Memory device, magnetic memory device or above-mentioned any appropriate combination.In this document, computer-readable recording medium can
Be it is any include or the tangible medium of storage program, the program can be commanded execution system, device or device use or
Person is in connection.
Computer-readable signal media can include in a base band or as carrier wave a part propagation data-signal,
Wherein carry computer-readable program code.The data-signal of this propagation can take various forms, including --- but
It is not limited to --- electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be
Any computer-readable medium beyond computer-readable recording medium, the computer-readable medium can send, propagate or
Transmit for by instruction execution system, device either device use or program in connection.
The program code included on computer-readable medium can be transmitted with any appropriate medium, including --- but it is unlimited
In --- wireless, electric wire, optical cable, RF etc., or above-mentioned any appropriate combination.Can be with one or more programmings
Language or its combination are write for performing the computer program code that operates of the present invention, described program design language include towards
The programming language of object-such as Java, Smalltalk, C++, in addition to conventional procedural programming language-all
Such as " C " language or similar programming language.Program code can perform fully on the user computer, partly with
On the computer of family perform, the software kit independent as one perform, part on the user computer part on the remote computer
Perform or performed completely on remote computer or server.In the situation of remote computer is related to, remote computer can
To pass through the network of any kind --- subscriber computer is connected to including LAN (LAN) or wide area network (WAN), or, can
To be connected to outer computer (such as passing through Internet connection using ISP).
Using technical scheme provided by the present invention, by calculating criterion evaluation parameter value and mould based on same timestamp
Type assesses the mean square deviation between parameter value, and wagon control model is assessed using resulting mean square deviation, objective, accurate so as to realize
Assess wagon control model in ground.
In several embodiments provided by the present invention, it should be understood that disclosed system, apparatus and method can be with
Realize by another way.For example, device embodiment described above is only schematical, for example, the unit
Division, only a kind of division of logic function, can there is other dividing mode when actually realizing.
The unit illustrated as separating component can be or may not be physically separate, show as unit
The part shown can be or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On NE.Some or all of unit therein can be selected to realize the mesh of this embodiment scheme according to the actual needs
's.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units it is integrated in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, can also be realized in the form of hardware adds SFU software functional unit.
The above-mentioned integrated unit realized in the form of SFU software functional unit, can be stored in one and computer-readable deposit
In storage media.Above-mentioned SFU software functional unit is stored in a storage medium, including some instructions are causing a computer
It is each that equipment (can be personal computer, server, or network equipment etc.) or processor (processor) perform the present invention
The part steps of embodiment methods described.And foregoing storage medium includes：USB flash disk, mobile hard disk, read-only storage (Read-
Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disc or CD etc. it is various
Can be with the medium of store program codes.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
God any modification, equivalent substitution and improvements done etc., should be included within the scope of protection of the invention with principle.
Claims (14)
- A kind of 1. method for assessing wagon control model, it is characterised in that methods described includes：Collection vehicle running data；The output data that wagon control model is directed to the vehicle operation data is obtained, determines to assess parameter value according to output data As model evaluation parameter value；And calculated according to vehicle operation data and assess parameter value as criterion evaluation parameter value；Using the mean square deviation corresponding to same timestamp between model evaluation parameter value and criterion evaluation parameter value, the car is assessed Controlling model.
- 2. according to the method for claim 1, it is characterised in that the assessment parameter is to travel curvature, the wagon control Model is vehicle lateral control model, and the output data is steering wheel angle.
- 3. according to the method for claim 1, it is characterised in that the vehicle operation data includes：Vehicle position data with And timestamp corresponding to each vehicle position data.
- 4. according to the method for claim 2, it is characterised in that described calculated according to vehicle operation data assesses parameter value work Include for criterion evaluation parameter value：According to timestamp corresponding to vehicle position data and each vehicle position data, traveling curvature corresponding to each timestamp is calculated Value；Interpolation calculation is carried out to travelling curvature value corresponding to each timestamp respectively, obtains corresponding each timestamp unit one belongs to time zone Between multiple traveling curvature values；When one is selected from multiple traveling curvature values of corresponding each timestamp unit one belongs to time interval respectively as corresponding to each Between the traveling curvature value that stabs；Criterion evaluation parameter value of the traveling curvature value as corresponding each timestamp of predetermined threshold value requirement will be met.
- 5. according to the method for claim 2, it is characterised in that described to determine to assess parameter value as mould according to output data Type, which assesses parameter value, to be included：The steering wheel angle of corresponding each timestamp is converted to the traveling curvature value of corresponding each timestamp using preset model；Model evaluation parameter value of the traveling curvature value as corresponding each timestamp of predetermined threshold value requirement will be met.
- 6. according to the method for claim 1, it is characterised in that described to utilize model evaluation ginseng corresponding to same timestamp Before mean square deviation between numerical value and criterion evaluation parameter value assesses the wagon control model, in addition to：Judge whether the number of the model evaluation parameter value is more than predetermined threshold value, if being more than, calculated based on the timestamp Mean square deviation between the model evaluation parameter value and criterion evaluation parameter value, is not otherwise calculated.
- 7. a kind of device for assessing wagon control model, it is characterised in that described device includes：Collecting unit, for collection vehicle running data；Determining unit, the output data of the vehicle operation data is directed to for obtaining wagon control model, according to output data It is determined that parameter value is assessed as model evaluation parameter value；And calculated according to vehicle operation data and assess parameter value as standard Assess parameter value；Assessment unit, it is square between model evaluation parameter value and criterion evaluation parameter value corresponding to same timestamp for utilizing Difference, assess the wagon control model.
- 8. device according to claim 7, it is characterised in that the assessment parameter is to travel curvature, the wagon control Model is vehicle lateral control model, and the output data is steering wheel angle.
- 9. device according to claim 7, it is characterised in that the vehicle operation data bag that the collecting unit is gathered Include：Timestamp corresponding to vehicle position data and each vehicle position data.
- 10. device according to claim 9, it is characterised in that the determining unit is for according to vehicle operation data It is specific to perform when calculating assessment parameter value as criterion evaluation parameter value：According to timestamp corresponding to vehicle position data and each vehicle position data, traveling curvature corresponding to each timestamp is calculated Value；Interpolation calculation is carried out to travelling curvature value corresponding to each timestamp respectively, obtains corresponding each timestamp unit one belongs to time zone Between multiple traveling curvature values；When one is selected from multiple traveling curvature values of corresponding each timestamp unit one belongs to time interval respectively as corresponding to each Between the traveling curvature value that stabs；Criterion evaluation parameter value of the traveling curvature value as corresponding each timestamp of predetermined threshold value requirement will be met.
- 11. device according to claim 9, it is characterised in that the determining unit according to output data for determining It is specific to perform when assessing parameter value as model evaluation parameter value：The steering wheel angle of corresponding each timestamp is converted to the traveling curvature value of corresponding each timestamp using preset model；Model evaluation parameter value of the traveling curvature value as corresponding each timestamp of predetermined threshold value requirement will be met.
- 12. device according to claim 7, it is characterised in that the assessment unit is using corresponding to same timestamp Before mean square deviation between model evaluation parameter value and criterion evaluation parameter value assesses the wagon control model, also perform：Judge whether the number of the model evaluation parameter value is more than predetermined threshold value, if being more than, calculated based on the timestamp Mean square deviation between the model evaluation parameter value and criterion evaluation parameter value, is not otherwise calculated.
- 13. a kind of equipment, it is characterised in that the equipment includes：One or more processors；Storage device, 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 are real The now method as described in any in claim 1-6.
- 14. a kind of storage medium for including computer executable instructions, the computer executable instructions are by computer disposal For performing the method as described in any in claim 1-6 when device performs.
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