CN107600072A - A kind of acquisition methods and system of the common preference parameter of more passengers - Google Patents
A kind of acquisition methods and system of the common preference parameter of more passengers Download PDFInfo
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- CN107600072A CN107600072A CN201710772191.7A CN201710772191A CN107600072A CN 107600072 A CN107600072 A CN 107600072A CN 201710772191 A CN201710772191 A CN 201710772191A CN 107600072 A CN107600072 A CN 107600072A
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Abstract
This application discloses a kind of acquisition methods of more common preference parameters of passenger, including：Feature recognition operation is performed to occupant using vehicle-mounted identification equipment, obtains the interior location, quantity and identity information of occupant；Inquired about in the historical data using identity information, obtain vehicle personalization parameter corresponding to identity information；Judge whether the quantity of occupant exceedes predetermined number, if so, then carrying out integrating preference calculating to obtained each data using deep learning algorithm, obtain common preference parameter；Vehicle-mounted personalization equipment is adjusted using common preference parameter.Driver can not only be individually for proprietary vehicle personalization parameter is provided, additionally it is possible to when passenger exceedes predetermined number in the car, common preference parameter is calculated using deep learning algorithm synthesis, improves the ride experience of all passengers so that vehicle is more intelligent.The application further simultaneously discloses a kind of acquisition system of the common preference parameter of more passengers, has above-mentioned beneficial effect.
Description
Technical field
The application is related to technical field of vehicle, the acquisition methods of more particularly to a kind of common preference parameter of more passengers and is
System.
Background technology
With the development of the technologies such as internet, big data, Internet of Things, people is improve itself driving experience, to automobile
Intellectuality proposes higher and higher requirement, it is intended to carries out intelligent tune to each mobile unit by the personalizing parameters of setting
Section.
In the prior art, it is contemplated that most of vehicle is that driver individually drives, and mainly the identity information of driver is entered
Row collection, extraction characteristic information, and the vehicle personalization parameter after obtaining driver regulation is recorded, for example, preserving the side of obtaining
The parameters such as seat position that just driver is observed outside driving vehicle, reversing mirror angle, door mirror angle, and again
It is secondary judge for same driver when, load the vehicle personalization parameter that preserves before.But in addition to driver, also exist
During other passengers, or when vehicle stops that driver is outgoing only to stay passenger, it can not just be adjusted correspondingly, cause remaining to multiply
Visitor is less satisfied, is especially mainly on the vehicle of passenger services in taxi etc..
So how under more passenger conditions, the personalizing parameters of different passengers are considered, and it is specific according to passenger
Difference, there is provided a kind of securing mechanism of more common preference parameters of passenger is those skilled in the art's urgent problem to be solved.
The content of the invention
The purpose of the application is to provide a kind of acquisition methods and system of the common preference parameter of more passengers, and it can not only
It is individually for driver and proprietary vehicle personalization parameter is provided, additionally it is possible to when passenger exceedes predetermined number in the car, utilizes depth
Learning algorithm COMPREHENSIVE CALCULATING obtains common preference parameter, improves the ride experience of all passengers so that vehicle is more intelligent.
In order to solve the above technical problems, the application provides a kind of acquisition methods of more common preference parameters of passenger, the acquisition
Method includes：
Feature recognition operation is performed to occupant using vehicle-mounted identification equipment, obtains the in-car position of the occupant
Put, quantity and identity information；
Inquired about using the identity information in the historical data that server preserves, obtain the identity information pair
The vehicle personalization parameter answered；
Judge whether the quantity of the occupant exceedes predetermined number, if so, then using deep learning algorithm to each institute
State the corresponding interior location of occupant, quantity and vehicle personalization parameter to carry out integrating preference calculating, obtain common preference
Parameter；
Vehicle-mounted personalization equipment is adjusted using the common preference parameter.
Optionally, feature recognition operation is performed to occupant using vehicle-mounted identification equipment, obtains the occupant's
Interior location, quantity and identity information, including：
Judge that in-car each seat whether there is corresponding passenger using infrared sensor, obtain the quantity of the occupant
And the interior location of each occupant；Wherein, the infrared sensor is present multiple, and is arranged on each seat
Front；
The face of the occupant is shot using camera, obtains face face-image；
Facial feature extraction operation is performed to the face face-image, obtains identity information.
Optionally, inquired about using the identity information in the historical data that server preserves, obtain the identity
Vehicle personalization parameter corresponding to information, including：
The identity information is sent to the server by T-BOX communication modules；
The server is inquired about the identity information received in the historical data of record, is inquired about
As a result；
Judge whether the Query Result exceedes threshold value；
If the Query Result exceedes the threshold value, judge in the historical data that the server is recorded exist pair
The vehicle personalization parameter answered, and obtain the vehicle personalization parameter.
Optionally, using deep learning algorithm to each occupant corresponding interior location, quantity and the vehicle
Property parameter integrate preference calculating, obtain common preference parameter, including：
It is excellent to vehicle personalization parameter execution by weights allocation algorithm according to the quantity and the interior location
First level identification operation, obtains each each self-corresponding weights of the vehicle personalization parameter；
It is that corresponding vehicle personalization parameter is weighted using the weights, obtains each weighting parameters value；
Common preference parameter is calculated by preset algorithm model in each weighting parameters value.
Optionally, the acquisition methods also include：
When the Query Result is not less than the threshold value, judges to be not present in the historical data and believe with the identity
Vehicle personalization parameter corresponding to breath；
The identity information is stored in the server；
The instruction of vehicle personalization parameter acquisition is generated, and the vehicle personalization parameter acquisition is instructed via the T-
BOX communication modules are issued to in-car each controller so that each controller by the vehicle personalization parameter newly collected via
The T-BOX communication modules are recorded in the server.
Optionally, the acquisition methods also include：
Judge that can the T-BOX communication modules normally be connected to the server；
If cannot connect to the server, the identity information and corresponding vehicle personalization parameter are preserved
Among the vehicle-mounted memory card of local, directly to obtain the vehicle personalization parameter from the vehicle-mounted memory card to each institute
Controller is stated to be adjusted.
Present invention also provides a kind of acquisition system of more common preference parameters of passenger, the acquisition system includes：
Information extraction unit, for performing feature recognition operation to occupant using vehicle-mounted identification equipment, obtain described
Interior location, quantity and the identity information of occupant；
Parameter query unit, for being inquired about using the identity information in the historical data that server preserves, obtain
To vehicle personalization parameter corresponding to the identity information；
Judge and processing unit, for whether judging the quantity of the occupant more than 1 people, if so, then utilizing depth
Learning algorithm carries out integrating preference meter to each occupant corresponding interior location, quantity and the vehicle personalization parameter
Calculate, obtain common preference parameter；
Equipment adjustment unit, for vehicle-mounted personalization equipment to be adjusted using the common preference parameter.
Optionally, described information extraction unit includes：
Infrared identification subelement, for judging that in-car each seat whether there is corresponding passenger using infrared sensor, obtain
The quantity of the occupant and the interior location of each occupant；Wherein, the infrared sensor is present multiple,
And it is arranged on the front at each seat；
Subelement is imaged, for being shot using camera to the face of the occupant, obtains face face figure
Picture；
Identity information obtains subelement, for performing facial feature extraction operation to the face face-image, obtains body
Part information.
Optionally, the parameter query unit includes：
Transmission sub-unit, for the identity information to be sent to the server by T-BOX communication modules；
Subelement is inquired about, enters the identity information received in the historical data of record for the server
Row inquiry, obtains Query Result；
Threshold decision subelement, for judging whether the Query Result exceedes threshold value；
Personalizing parameters obtain subelement, exist in the historical data recorded for judging the server corresponding
Vehicle personalization parameter, and obtain the vehicle personalization parameter.
Optionally, the judgement and processing unit include：
Weights obtain subelement, for passing through weights allocation algorithm according to the quantity and the interior location
The vehicle personalization parameter execution priority is identified and operated, it is each self-corresponding to obtain each vehicle personalization parameter
Weights；
Weighted calculation subelement, for being that corresponding vehicle personalization parameter is weighted using the weights, obtain
To each weighting parameters value；
Common preference parameter generation subelement, for each weighting parameters value to be calculated by preset algorithm model
To common preference parameter.
The acquisition methods of a kind of more common preference parameters of passenger provided herein, using vehicle-mounted identification equipment to car
Interior personnel perform feature recognition operation, obtain the interior location, quantity and identity information of the occupant；Using described
Identity information is inquired about in the historical data that server preserves, and is obtained vehicle personalization corresponding to the identity information and is joined
Number；Judge whether the quantity of the occupant exceedes predetermined number, if so, then using deep learning algorithm to each car
Interior personnel corresponding interior location, quantity and vehicle personalization parameter carry out integrating preference calculating, obtain common preference ginseng
Number；Vehicle-mounted personalization equipment is adjusted using the common preference parameter.
Obviously, by technical scheme provided herein, driver can not only be individually for proprietary vehicle is provided
Property parameter, additionally it is possible to when passenger exceedes predetermined number in the car, common preference is calculated using deep learning algorithm synthesis
Parameter, considered with reference to actual scene, improve the ride experience of all passengers so that vehicle is more intelligent.This Shen
A kind of acquisition system of the common preference parameter of more passengers is please additionally provided simultaneously, and there is above-mentioned beneficial effect, it is no longer superfluous herein
State.
Brief description of the drawings
In order to illustrate more clearly of the embodiment of the present application or technical scheme of the prior art, below will to embodiment or
The required accompanying drawing used is briefly described in description of the prior art, it should be apparent that, drawings in the following description are only
Embodiments herein, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to the accompanying drawing of offer.
A kind of flow chart of the acquisition methods for more common preference parameters of passenger that Fig. 1 is provided by the embodiment of the present application；
The flow chart of the acquisition methods for another more common preference parameters of passenger that Fig. 2 is provided by the embodiment of the present application；
The flow chart of the acquisition methods for another more common preference parameter of passenger that Fig. 3 is provided by the embodiment of the present application；
The flow chart of the acquisition methods for another more common preference parameter of passenger that Fig. 4 is provided by the embodiment of the present application；
A kind of structured flowchart of the acquisition system for more common preference parameters of passenger that Fig. 5 is provided by the embodiment of the present application；
A kind of in-car hardware of the acquisition system for more common preference parameters of passenger that Fig. 6 is provided by the embodiment of the present application
Arrangement and illustrative view of functional configuration；
A kind of in-car monitoring of the acquisition system for more common preference parameters of passenger that Fig. 7 is provided by the embodiment of the present application
The infrared light filling radiation areas schematic diagram of device；
The structural frames of the acquisition system for another more common preference parameters of passenger that Fig. 8 is provided by the embodiment of the present application
Figure；
A kind of flow chart for parameter acquiring that Fig. 9 is provided by the embodiment of the present application；
A kind of parameter that Figure 10 is provided by the embodiment of the present application preserves and the flow chart of renewal；
The flow chart that a kind of more passenger parameters that Figure 11 is provided by the embodiment of the present application are obtained and preserved；
The flow chart that a kind of more passenger parameters that Figure 12 is provided by the embodiment of the present application are obtained, preserve and updated；
A kind of flow chart for the common preference parameter of the more passengers of push that Figure 13 is provided by the embodiment of the present application；
The another kind that Figure 14 is provided by the embodiment of the present application pushes the flow chart of more common preference parameters of passenger.
Embodiment
The core of the application is to provide a kind of acquisition methods and system of the common preference parameter of more passengers, can not only be single
Proprietary vehicle personalization parameter is solely provided for driver, additionally it is possible to when passenger exceedes predetermined number in the car, utilize depth
Practise algorithm synthesis and common preference parameter is calculated, considered with reference to actual scene, improve the seating of all passengers
Experience so that vehicle is more intelligent.
To make the purpose, technical scheme and advantage of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In accompanying drawing, the technical scheme in the embodiment of the present application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, rather than whole embodiments.Based on the embodiment in the application, ordinary skill people
All other embodiment that member is obtained under the premise of creative work is not made, belong to the scope of the application protection.
Below in conjunction with Fig. 1, a kind of acquisition side for more common preference parameters of passenger that Fig. 1 is provided by the embodiment of the present application
The flow chart of method.
It specifically includes following steps：
S101：Feature recognition operation is performed to occupant using vehicle-mounted identification equipment, obtains the in-car position of occupant
Put, quantity and identity information；
This step is intended to perform current occupant feature recognition operation using vehicle-mounted identification equipment, to obtain in-car
The range of information of personnel, including the total quantity of each occupant, the respective body of which position and each occupant in the car
Part information.
Wherein, vehicle-mounted identification equipment includes a lot, for example, can identify to obtain target location using infrared sensor
Whether passenger is had；It can judge to whether there is passenger on seat using the pressure sensor below each seat is placed in；Can also
Recognition of face is carried out using camera, obtains the quantity of occupant, and according to carried out by the said equipment obtains each occupant
Which seat, you can to obtain which seat operator seat, copilot, operator seat dead astern, copilot dead astern etc. are specially on
Passenger be present, and judge that passenger is specifically personnel of the driver still in addition to driver according to passenger position.
And identity information is to represent the identity characteristic of occupant, can enough identity informations uniquely refer to some and multiply
Visitor, specific manifestation mode have a lot, for example, being obtained by carrying out facial feature extraction to the face image of each occupant
To face feature information, and in this, as identity information, pupil iris etc. can also be utilized, Fingerprint Identification Unit can also be set
Finger print information etc. is obtained in the place of steering wheel or other convenient extractions, herein and is not specifically limited, concrete condition should be regarded
Consider with reference to automobile model, the design style of manufacturing firm and with the presence or absence of particular/special requirement etc..
S102：Inquired about, obtained corresponding to identity information in the historical data that server preserves using identity information
Vehicle personalization parameter；
On the basis of S101, this step is intended to using obtained identity information in the historical data that server preserves
Inquired about, to obtain vehicle personalization parameter corresponding with the identity information.
Wherein, the parameter of the in-car adjustable apparatus collected before historical data refers to by in-car each controller,
And these parameters and the identity information of occupant at that time are bound what is obtained, and parameter corresponding to same identity information
There may be several at different moments, for example, some parameters adapted to before are because a variety of causes is no longer suitable, it is natural
To be adjusted again, and the parameter after adjusting can also be selected flexibly, you can to select to cover original parameter, ensure to deposit always
In parameter corresponding to one group；It can also be that same identity information establishes multiple parameters, and remind passenger corresponding to the identity information
Different parameters is named to be distinguish between, also allows for carrying out selecting suitable parameter to be adjusted again.
And server is also the storage device of a store historical data, it is contemplated that different vehicular applications are different, note
The data volume of record is also different, and server can flexibly be set, and the server storage that car owner can also flexibly buy suitable capacity is empty
Between.When server sets are in distance access ports, it can be established and connected by vehicle-mounted wireless communication module and the server,
Such as common vehicle-mounted T-BOX modules, it is of course possible to the connection of server is implemented in by other wireless communication modules, herein
And it is not specifically limited, the comprehensive selection such as difference, price, module performance and demand of the model that should be got off depending on actual conditions.
Further, when identity information can not be established and connected in server by wireless communication module, for example, by
Tunnel, nearby without the reason such as base station, wireless communication module be abnormal, can now rely on the in-car storage card set to analyze should
The vehicle personalization parameter obtained after the identity information that passenger obtains, and passenger regulation is maintained in the storage card, and
When needing to read, judge whether cannot connect to the parameter on server, inquired about if it can not connect in storage card
And load.
S103：Judge whether the quantity of occupant exceedes predetermined number；
On the basis of S102, whether occupant's quantity that this step is intended to judge to obtain exceedes predetermined number, institute
Whether to judge more than predetermined number occupant's quantity, driven because being different from prior art and having taken into consideration only
The person of sailing does not have the actual conditions considered under more passengers, therefore the quantity that this step is intended to judge to obtain occupant is more than default
During quantity, the flow of triggering following, depth calculation is carried out using deep learning algorithm to more passengers, to obtain common preference
Set, rather than only consider driver.
Wherein, the predetermined number can adjust according to the difference of vehicle, the difference of setting custom, such as family's sedan-chair
The predetermined number can be arranged to 1 people or 2 people by car, i.e., just activation is follow-up when quantity is at least two people or three people in the car walks
Suddenly；The predetermined number can also be arranged to 30 or so the percent of standard carrying personnel, herein simultaneously in manned car
It is not specifically limited, concrete condition should be regarded and made a concrete analysis of, it is specifically chosen.
S104：The corresponding interior location of each occupant, quantity and vehicle personalization are joined using deep learning algorithm
Number carries out integrating preference calculating, obtains common preference parameter；
The foundation of this step exceedes in the quantity that S103 judged result is occupant on the basis of predetermined number, it is intended to
The corresponding interior location of occupant, quantity and vehicle personalization parameter are carried out integrating preference using deep learning algorithm
Calculate, obtain common preference parameter.Wherein, the deep learning algorithm is that the situation of presence is analyzed using big data, comprehensive
The parameter that other people are set, obtains the higher common preference parameter of a satisfaction rate.
For example, in the case of driver and copilot being in the car present, identification can be combined according to face feature information and calculated
Method judges the sex of two people, age, and according to the result combination deep learning algorithm judged is calculated one and meets and work as
The common preference parameter of preceding scene.We can assume that driver is the man of 30 years old or so, copilot be one 5 years old
The spadger of left and right, after judging above- mentioned information, it is possible to which it is probably that father takes the kids with outgoing feelings to obtain current
Scape, may judge to need to consider child emphatically by deep learning algorithm herein, i.e., according to child analyze to obtain it is a series of partially
It is good to set, for example find and obtain the music that age bracket child likes listening, the appropriate conduct height for adjusting copilot, angle etc.,
Make it that vehicle is more intelligent.
Certainly, considerable other scenes also be present, because server can be opening Design, be easy to deep learning
Algorithm combination big data carries out scenario analysis, and obtains relatively reasonable preference and set, and specific situation is not done specifically herein
Limit, whether should be opened depending on actual conditions, server and data acquisition source etc. considers.
S105：Vehicle-mounted personalization equipment is adjusted using common preference parameter.
On the basis of S104 analyzes to obtain common preference parameter, this step is intended to load the common preference ginseng on vehicle
Number, to realize the reproduction of purpose scene, realizes final purpose.
Specifically, in the case where that can not be communicated with server, possibly can not be counted by deep learning algorithm to big
According to being analyzed to obtain suitable common preference parameter, need to can realize communicated with server when, carry out S104 step
Suddenly, and the common preference parameter that calculates is issued to corresponding vehicle, so that each controller of the vehicle is common inclined according to this
Good parameter is loaded.
Wherein, in-car each controller is different according to the difference, the difference of price, Brand Design of vehicle model, may bag
Include：Door mirror angle controller, side mirror angle controller, height of seat angle controller, player controller, amusement
At least one of in central control system controller etc., herein and it is not specifically limited.
Based on above-mentioned technical proposal, a kind of acquisition methods for more common preference parameters of passenger that the embodiment of the present application provides,
Driver can not only be individually for proprietary vehicle personalization parameter is provided, additionally it is possible to when passenger exceedes predetermined number in the car,
Common preference parameter is calculated using deep learning algorithm synthesis, is considered with reference to actual scene, improves all
The ride experience of passenger so that vehicle is more intelligent.
Below in conjunction with Fig. 2, the acquisition for another more common preference parameters of passenger that Fig. 2 is provided by the embodiment of the present application
The flow chart of method.
The present embodiment be directed in a upper embodiment how to perform in S101 and S102 feature recognition operation and how profit
Made one is inquired about with identity information specifically to limit, other steps are substantially the same with a upper embodiment, same section
Reference can be made to upper embodiment relevant portion, will not be repeated here.
It specifically includes following steps：
S201：Judge that in-car each seat whether there is corresponding passenger using infrared sensor, obtain the quantity of occupant
And the interior location of each occupant；
S202：The face of occupant is shot using camera, obtains face face-image；
S203：Facial feature extraction operation is performed to face face-image, obtains identity information；
S201, S202 and S203 are to whether there is passenger on induction targets seat using infrared sensor, and according to
Infrared sensor set predeterminated position, i.e., correspond to the numbering at seat etc., come directly judge occupant quantity and respectively
Position where occupant, and judge according to position the property of occupant, such as, it is be sitting in position of driver silent
Think driver, copilot station is exactly copilot etc..
After the quantity and interior location of occupant is obtained by infrared sensor, by vehicle-mounted camera come to each
The face of occupant is shot, and obtains the face face-image of each occupant, and perform face to the face face-image
Portion's feature extraction operation, the unique identity information using obtained face feature information as each occupant of identification, in order to
In follow-up process car is relatively suitably applied in using same identity information come the historical data that is preserved before obtaining, this method
Interior space is big, seat is set among the vehicle of stacking.
Certainly, vehicle-mounted camera can also be used only in actual applications, by the way that camera is set in place
Carry out covering environment inside car as big as possible, and the face characteristic in image is carried out by the in-car image captured by camera
Identification, i.e., occupant's quantity in image, position and extraction are obtained using a series of recognizers and obtains theirs
Identity information, relatively it is suitably applied in compact car.
Can be according to the vehicle under actual conditions, identification accuracy requirement, customer demand and Car design method come comprehensive
Conjunction is selected.
S204：Identity information is sent to server by T-BOX communication modules；
S205：Server is inquired about the identity information received in the historical data of record, obtains inquiry knot
Fruit；
S204 and S205 be intended to using conventional onboard wireless communication module T-BOX by the identity information of acquisition send to
The server on backstage, facilitate the use the historical data that server is stored and carry out matching inquiry, because inquiry is to utilize face
The identity information that characteristic information serves as, usual query process are the process of a match hit in fact, and set one reasonably
Threshold value, since it is considered that face feature information is not a unalterable information, various factors is for example injured, band glasses
Or the face feature information that other reasons can all cause to identify obtained unification user every time is not quite similar, now can
Using a threshold value of setting to judge whether successful match, such as the threshold value is set to 85%, as long as that is, when the face obtained
When characteristic information remains above 85% uniformity with the face feature information in historical data, it is taken as same user's
Identity information, and then regard as same people.
S206：Judge whether Query Result exceedes threshold value；
On the basis of S205, it is default that this step is intended to judge whether the uniformity numerical value that Query Result obtains exceedes
Threshold value, the threshold value can be according to matching empirical one suitable ratio for a long time or according to matching algorithm
Some existing leaks and set, error can also be had according to the shooting precision of camera and set, do not done and have herein
Body limits, and should regard concrete condition and make a concrete analysis of, specific setting.
S207：Corresponding vehicle personalization parameter in the historical data that determining server is recorded be present, and obtain vehicle
Personalizing parameters；
This step establish S206 judged result for Query Result exceed threshold value on the basis of, it is intended to directly according to clothes
The historical data of business device storage obtains vehicle personalization parameter corresponding to the identity information, i.e., the user is to in-car each adjustable
What equipment was made meets the adjusting parameter of itself custom.
S208：Vehicle personalization parameter corresponding with identity information is not present in historical data, and identity information is preserved
In the server；
S209：The instruction of vehicle personalization parameter acquisition is generated, and vehicle personalization parameter acquisition is instructed via T-BOX
Communication module is issued to in-car each controller.
S208 establish S206 judged result for Query Result not less than threshold value on the basis of, it can be assumed that being the use
The identity information at family can not be found in the historical data of server record, that is to say, that the user is probably to be held for the first time
Row recognizer, and in the absence of corresponding historical data,, can should after the completion of judgement for the user of this first time
Identity information corresponding to user is stored in server, and issues corresponding parameter acquisition instruction, to complete the identity of user letter
Cease the binding step with corresponding personalizing parameters.
Below in conjunction with Fig. 3, the acquisition for another more common preference parameter of passenger that Fig. 3 is provided by the embodiment of the present application
The flow chart of method.
The present embodiment is to be directed in a upper embodiment in S103 how using deep learning algorithm to obtain common preference parameter
The specific restriction made, other steps are substantially the same with a upper embodiment, and same section can be found in an embodiment phase
Part is closed, will not be repeated here.
It specifically includes following steps：
S301：Quantity and interior location are identified by weights allocation algorithm to the execution priority of vehicle personalization parameter
Operation, obtains each self-corresponding weights of each vehicle personalization parameter；
This step is intended to quantity, the difference of interior location according to occupant, using weights allocation algorithm to getting
The respective vehicle personalization parameter of the occupant more than predetermined number carry out the identification operation of priority, to obtain each
Corresponding weights.
The father being previously mentioned using embodiment one and the example of child, in this case, the priority of child be certain to compared with
Height, therefore weights also can be of a relatively high, that is to say, that, should be using child as center of gravity under such a situation, with due regard to father
.Certainly, weights may be inconsistent under different scenes, and this can utilize open service according to deep learning algorithm
Device considers, to obtain a rational weights.
S302：It is that corresponding vehicle personalization parameter is weighted using weights, obtains each weighting parameters value；
S303：Common preference parameter is calculated by preset algorithm model in each weighting parameters value.
After weights corresponding to obtaining each occupant according to weights allocation algorithm, it is necessary to using weights to respective
Vehicle personalization parameter is weighted, and further, in the process, new conjunction can also be obtained according to deep learning algorithm
The vehicle personalization parameter of reason, is adjusted in order to adapt to scene, to finally give common preference parameter.
Wherein, the form of expression of preset algorithm is a lot, scene combination algorithm, external environment recognizer and passenger's heart
Feelings recognizer etc. may be by, and herein and be not specifically limited, and it is next specifically chosen should to regard concrete condition.
Below in conjunction with Fig. 4, the acquisition for another more common preference parameter of passenger that Fig. 4 is provided by the embodiment of the present application
The flow chart of method.
It specifically includes following steps：
S401：Facial feature extraction operation is performed to face face-image, obtains identity information；
S402：Can T-BOX communication modules normally be connected to server；
S403：Identity information is sent to server by T-BOX communication modules；
S404：Identity information and corresponding vehicle personalization parameter are stored among local vehicle-mounted memory card, with
Vehicle personalization parameter is obtained directly from vehicle-mounted memory card to be adjusted each controller.
The present embodiment is intended to judge when needing T-BOX wireless communication modules to send identity information etc. to server,
Can normally be connected to server under real-time external condition, due to various factors that may be present, for example, module it is abnormal,
Cross tunnel, nearby without reasons such as base stations, and propose when cannot connect to server, using vehicle-mounted memory card by relevant information
Local is stored in, and temporarily never calls deep learning algorithm and carries out scene calculating.
Based on above-mentioned technical proposal, a kind of acquisition methods for more common preference parameters of passenger that the embodiment of the present application provides,
Driver can not only be individually for proprietary vehicle personalization parameter is provided, additionally it is possible to when passenger exceedes predetermined number in the car,
Common preference parameter is calculated using deep learning algorithm synthesis, is considered with reference to actual scene, improves all
The ride experience of passenger so that vehicle is more intelligent.
Because situation is complicated, it can not enumerate and be illustrated, those skilled in the art should be able to recognize more the application
The basic skills principle combination actual conditions of offer may have many examples, in the case where not paying enough creative works,
Should be in the protection domain of the application.
Fig. 5, a kind of acquisition for more common preference parameters of passenger that Fig. 5 is provided by the embodiment of the present application are referred to below
The structured flowchart of system.
The acquisition system can include：
Information extraction unit 100, for performing feature recognition operation to occupant using vehicle-mounted identification equipment, obtain
Interior location, quantity and the identity information of occupant；
Parameter query unit 200, for being inquired about using identity information in the historical data that server preserves, obtain
To vehicle personalization parameter corresponding to identity information；
Judge and processing unit 300, for whether judging the quantity of occupant more than 1 people, if so, then utilizing depth
Learning algorithm carries out integrating preference calculating to the corresponding interior location of each occupant, quantity and vehicle personalization parameter, obtains
To common preference parameter；
Equipment adjustment unit 400, for vehicle-mounted personalization equipment to be adjusted using common preference parameter.
Wherein, information extraction unit 100 can include：
Infrared identification subelement, for judging that in-car each seat whether there is corresponding passenger using infrared sensor, obtain
The quantity of occupant and the interior location of each occupant；Wherein, infrared sensor is present multiple, and is arranged on each seat
The front of position；
Subelement is imaged, for being shot using camera to the face of occupant, obtains face face-image；
Identity information obtains subelement, for performing facial feature extraction operation to face face-image, obtains identity letter
Breath.
Wherein, parameter query unit 200 can include：
Transmission sub-unit, for identity information to be sent to server by T-BOX communication modules；
Subelement is inquired about, the identity information received is inquired about in the historical data of record for server, obtained
To Query Result；
Threshold decision subelement, for judging whether Query Result exceedes threshold value；
Personalizing parameters obtain subelement, corresponding vehicle in the historical data recorded for determining server be present
Personalizing parameters, and obtain vehicle personalization parameter.
Wherein, judge and processing unit 300 can include：
Weights obtain subelement, for individual to vehicle by weights allocation algorithm according to quantity and interior location
Property parameter execution priority identification operation, obtain each self-corresponding weights of each vehicle personalization parameter；
Weighted calculation subelement, for being that corresponding vehicle personalization parameter is weighted using weights, obtain each
Weighting parameters value；
Common preference parameter generation subelement, for each weighting parameters value to be calculated altogether by preset algorithm model
Same preference parameter.
Refer to Fig. 6 to Fig. 8, a kind of acquisition for more common preference parameters of passenger that Fig. 6 is provided by the embodiment of the present application
The in-car hardware layout and illustrative view of functional configuration of system；A kind of more passengers that Fig. 7 is provided by the embodiment of the present application are jointly inclined
The infrared light filling radiation areas schematic diagram of the in-car supervising device of the acquisition system of good parameter；Fig. 8 is carried by the embodiment of the present application
The structured flowchart of the acquisition system of another more common preference parameters of passenger of confession.
Above each unit can apply in the specific concrete instance of following one：
In Fig. 6,1 is pilot set, and 2 be driver；3 be driver side door handle, and 4 be steering wheel, and 5 be outer backsight
Mirror, 6 be instrument, and 7 be the supervising device based on camera, 8 entertainment systems main frames, and 9 be air outlet of automobile air-conditioning system, 10
It is the passenger side door handle for glove compartment, 11,12 be the passenger side passenger, and 13 be the passenger side seat, and 14 be back seat, and 15 multiply for heel row
Visitor.
Wherein, pilot set 1 and the passenger side seat are the motorized adjustment seat with memory；Outside rear-view mirror 5, it is a kind of
It is electrically adjusted the rearview mirror of lens angle；Instrument 6, it is a kind of liquid crystal type instrument；Entertainment systems 8 are a kind of with voice friendship
The middle control entertainment systems of mutual function and liquid crystal display, the size of LCDs is between 6 inches to 20 inches；In-car prison
Device 7 is controlled, is a kind of monitoring system based on wide-angle 2D gray scale cameras, the present apparatus is installed on vehicle front middle section, borrowed
Help 3 groups of infrared light filling units, can be achieved in-car driver, the passenger side passenger and heel row middle position passenger are detected, identity
Push of record, identification and personalized service etc..
In Fig. 7,7 be in-car supervising device, and 70 be the first infrared light filling unit, and 71 be the second infrared light filling unit, and 72 are
3rd infrared light filling unit.Wherein, the first infrared 70 and second infrared light filling unit 71 of light filling unit is same watt level
Supplementary lighting module, operating seat headrest area is respectively facing in 7 normal work of supervising device and vice operator's seat position headrest area is shone
Penetrate, effective light filling scope is at 1 meter or so；3rd infrared light filling unit 72 is directed towards the irradiation of heel row central seat headrest positions
Light filling unit, effective light filling scope is 2 meters or so (relative to the first and second light filling units, more powerful).
In Fig. 8, mainly include：In-car supervising device, automatic seat module, driven rearview mirrors module, liquid crystal instrument and joy
Music system main frame, liquid crystal instrument, perfume system, atmosphere lamp, car body control module, T-BOX modules and backstage and server.
Wherein, in-car supervising device is in-car supervising device 7, is a kind of monitoring system based on camera, mainly includes
Camera module, infrared LED light filling unit, CPU and CAN interface unit.Specifically, camera is a kind of
2D gray scale cameras；Infrared light filling unit is made up of the infrared LED of more 850nm or 940nm wavelength；Central processing list
Member is typically as its main operational processor by ARM kernels, DSP or FPGA；CAN interface unit is to be used for and other vehicle-mounted moulds
The interface of communication between block.
Perfume system is disposed in glove compartment, draws the perfume fragrance in scent flask by electrodynamic pump, and pass through conduit
Introduce a kind of device of air-conditioner air outlet；Atmosphere lamp is a kind of based on monochromatic or the LED of multiple color and the lamp of light guide structure part
Electro-optical device, it is a kind of device of the aesthetic feeling and regulation visual effect that strengthen automotive trim；Car body control module is one kind to crowd
The central module that more car electrics are controlled, is generally included：Power window control, centrally controrlled locking system control, driven rearview mirrors control
System, signal light control etc..
Referring also to Fig. 9 to Figure 14, wherein, a kind of flow for parameter acquiring that Fig. 9 is provided by the embodiment of the present application
Figure；A kind of parameter that Figure 10 is provided by the embodiment of the present application preserves and the flow chart of renewal；Figure 11 is the embodiment of the present application institute
The flow chart that a kind of more passenger parameters provided are obtained and preserved；A kind of more passengers that Figure 12 is provided by the embodiment of the present application
Parameter acquiring, preservation and the flow chart of renewal；It is jointly inclined that one kind that Figure 13 is provided by the embodiment of the present application pushes more passengers
The flow chart of good parameter；The another kind that Figure 14 is provided by the embodiment of the present application pushes the flow of more common preference parameters of passenger
Figure.
The specific present apparatus gathers driver's sample and remembers the seat adjusting position of driver, rearview mirror adjusts angle,
The personalization equipment such as instrument and entertainment systems state, the mode of parameter are as shown in flow chart 9；
The personalization equipment such as specific present apparatus collection the passenger side occupant sample and the seat adjusting position of memory the passenger side occupant
State, the mode of parameter are as shown in flow chart 10；
Specific the system detection, identification driver and the passenger side occupant sample simultaneously adjust the personalizations such as seat position in real time
Equipment state, the mode of parameter are as illustrated in flow chart figure 11；
For the identity recognition device based on face, the system can also periodically or intelligent updating driver and the passenger side multiply
The sample of visitor, so that the discrimination of system is effectively ensured, not with the change at user's age, not with hair style or cosmetic mode etc.
Change and it is impacted.Specific the system automatically updates the mode of driver and the passenger side occupant's sample as shown in flow chart 12；
Localization is achievable function except more than, and the system can also pass through T-BOX moulds with backstage Cloud Server
Block, real-time communication is carried out, and give passenger's active push " service ", it is farthest intelligent to realize.Specifically, this
System upload data to backstage Cloud Server mechanism as shown in flow chart 13；
Backstage Cloud Server uses deep learning algorithm, the historical data information that Current vehicle uploads is carried out intelligent
Analysis and study, draw the usage scenario of the vehicle and the Personalized Service Model of matching；When backstage, Cloud Server, which is got, works as
When having driver or occupant in vehicle in front, current scene can intelligently be classified, and active push may need in real time
" service ".
Such as：(1) driver is middle-aging male, and push UI styles are ripe, steady type；
(2) driver is women, pushes UI styles, the Young vogue type that women likes；
(3) in-car multiple passengers, driver is male, and passenger is women, and push atmosphere lamp is opened, perfume system is opened
Etc. function；
(4) in-car has children, reminds the volume of music played excessive；
(5) in-car has driver and more than 1 occupant, the song that comprehensive hobby push is liked jointly etc..
Specifically, backstage Cloud Server, according to the social function theory of in-car current scene active push " service ", such as schemes
Shown in 14.
Each embodiment is described by the way of progressive in specification, what each embodiment stressed be and other
The difference of embodiment, between each embodiment identical similar portion mutually referring to.For device disclosed in embodiment
For, because it is corresponded to the method disclosed in Example, so description is fairly simple, related part is referring to method part
Explanation.
Professional further appreciates that, with reference to the list of each example of the embodiments described herein description
Member and algorithm steps, it can be realized with electronic hardware, computer software or the combination of the two, it is hard in order to clearly demonstrate
The interchangeability of part and software, the composition and step of each example are generally described according to function in the above description.
These functions are performed with hardware or software mode actually, application-specific and design constraint depending on technical scheme.
Professional and technical personnel can realize described function using distinct methods to each specific application, but this reality
Now it is not considered that exceeding scope of the present application.
Specific case used herein is set forth to the principle and embodiment of the application, above example
Illustrate that being only intended to help understands the present processes and its core concept.It should be pointed out that the common skill for the art
For art personnel, on the premise of the application principle is not departed from, some improvement and modification can also be carried out to the application, these
Improve and modification is also fallen into the application scope of the claims.
It should also be noted that, in this manual, such as first and second or the like relational terms be used merely to by
One entity or operation make a distinction with another entity or operation, and not necessarily require or imply these entities or behaviour
Any this actual relation or order between work be present.Moreover, term " comprising ", "comprising" or its any other change
Body is intended to including for nonexcludability, so that process, method, article or equipment including a series of elements are not only
Including those key elements, but also other key elements including being not expressly set out, or also include for this process, method, thing
Product or the intrinsic key element of equipment.In the absence of more restrictions, wanted by what sentence "including a ..." limited
Element, it is not excluded that other identical element in the process including key element, method, article or equipment also be present.
Claims (10)
- A kind of 1. acquisition methods of the common preference parameter of more passengers, it is characterised in that including：Feature recognition operation is performed to occupant using vehicle-mounted identification equipment, obtains interior location, the number of the occupant Amount and identity information；Inquired about using the identity information in the historical data that server preserves, obtain car corresponding to the identity information Personalizing parameters；Judge whether the quantity of the occupant exceedes predetermined number, if so, then using deep learning algorithm to each car Interior personnel corresponding interior location, quantity and vehicle personalization parameter carry out integrating preference calculating, obtain common preference parameter；Vehicle-mounted personalization equipment is adjusted using the common preference parameter.
- 2. acquisition methods according to claim 1, it is characterised in that spy is performed to occupant using vehicle-mounted identification equipment Sign identification operation, obtains the interior location, quantity and identity information of the occupant, including：Judge that in-car each seat whether there is corresponding passenger using infrared sensor, obtain the quantity and respectively of the occupant The interior location of the occupant；Wherein, the infrared sensor is present multiple, and is arranged on the front at each seat；The face of the occupant is shot using camera, obtains face face-image；Facial feature extraction operation is performed to the face face-image, obtains identity information.
- 3. acquisition methods according to claim 2, it is characterised in that gone through using the identity information what server preserved Inquired about in history data, obtain vehicle personalization parameter corresponding to the identity information, including：The identity information is sent to the server by T-BOX communication modules；The server is inquired about the identity information received in the historical data of record, obtains Query Result；Judge whether the Query Result exceedes threshold value；If the Query Result exceedes the threshold value, judge corresponding car in the historical data that the server is recorded be present Personalizing parameters, and obtain the vehicle personalization parameter.
- 4. according to the acquisition methods described in any one of claims 1 to 3, it is characterised in that using deep learning algorithm to each institute State the corresponding interior location of occupant, quantity and vehicle personalization parameter to carry out integrating preference calculating, obtain common preference Parameter, including：According to the quantity and the interior location by weights allocation algorithm to the vehicle personalization parameter execution priority Identification operation, obtains each each self-corresponding weights of the vehicle personalization parameter；It is that corresponding vehicle personalization parameter is weighted using the weights, obtains each weighting parameters value；Common preference parameter is calculated by preset algorithm model in each weighting parameters value.
- 5. acquisition methods according to claim 4, it is characterised in that also include：When the Query Result is not less than the threshold value, judge in the historical data in the absence of corresponding with the identity information Vehicle personalization parameter；The identity information is stored in the server；The instruction of vehicle personalization parameter acquisition is generated, and the vehicle personalization parameter acquisition is instructed and led to via the T-BOX News module is issued to in-car each controller so that each controller by the vehicle personalization parameter newly collected via the T- BOX communication modules are recorded in the server.
- 6. acquisition methods according to claim 5, it is characterised in that also include：Judge that can the T-BOX communication modules normally be connected to the server；If cannot connect to the server, the identity information and corresponding vehicle personalization parameter are stored in local Vehicle-mounted memory card among, directly to obtain the vehicle personalization parameter from the vehicle-mounted memory card to each controller It is adjusted.
- A kind of 7. acquisition system of the common preference parameter of more passengers, it is characterised in that including：Information extraction unit, for performing feature recognition operation to occupant using vehicle-mounted identification equipment, obtain the in-car Interior location, quantity and the identity information of personnel；Parameter query unit, for being inquired about using the identity information in the historical data that server preserves, obtain institute State vehicle personalization parameter corresponding to identity information；Judge and processing unit, for whether judging the quantity of the occupant more than 1 people, if so, then utilizing deep learning Algorithm carries out integrating preference calculating to each occupant corresponding interior location, quantity and the vehicle personalization parameter, obtains To common preference parameter；Equipment adjustment unit, for vehicle-mounted personalization equipment to be adjusted using the common preference parameter.
- 8. acquisition system according to claim 7, it is characterised in that described information extraction unit includes：Infrared identification subelement, for judging that in-car each seat whether there is corresponding passenger using infrared sensor, obtain described The quantity of occupant and the interior location of each occupant；Wherein, the infrared sensor is present multiple, and sets In the front at each seat；Subelement is imaged, for being shot using camera to the face of the occupant, obtains face face-image；Identity information obtains subelement, for performing facial feature extraction operation to the face face-image, obtains identity letter Breath.
- 9. acquisition system according to claim 8, it is characterised in that the parameter query unit includes：Transmission sub-unit, for the identity information to be sent to the server by T-BOX communication modules；Subelement is inquired about, is looked into the identity information received in the historical data of record for the server Ask, obtain Query Result；Threshold decision subelement, for judging whether the Query Result exceedes threshold value；Personalizing parameters obtain subelement, corresponding vehicle in the historical data recorded for judging the server be present Property parameter, and obtain the vehicle personalization parameter.
- 10. the acquisition system according to any one of claim 7 to 9, it is characterised in that the judgement and processing unit bag Include：Weights obtain subelement, for according to the quantity and the interior location by weights allocation algorithm to described Vehicle personalization parameter execution priority identification operation, obtain each self-corresponding priority power of each vehicle personalization parameter Value；Weighted calculation subelement, for being that corresponding vehicle personalization parameter is weighted using the weights, obtain each Weighting parameters value；Common preference parameter generation subelement, for each weighting parameters value to be calculated jointly by preset algorithm model Preference parameter.
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| CN113934203A (en) * | 2020-07-09 | 2022-01-14 | 奥迪股份公司 | Method, apparatus and storage medium for controlling autonomous vehicle |
| WO2022193470A1 (en) * | 2021-03-17 | 2022-09-22 | 博泰车联网科技(上海)股份有限公司 | User preference query method and device for cloud platform, and storage medium and terminal |
| CN113276890A (en) * | 2021-07-14 | 2021-08-20 | 国汽智控(北京)科技有限公司 | Automatic control method and device for vehicle and vehicle |
| CN113602159A (en) * | 2021-08-17 | 2021-11-05 | 广汽本田汽车有限公司 | Method, system and device for automatically adjusting automobile seat and storage medium |
| CN114771442A (en) * | 2022-04-29 | 2022-07-22 | 中国第一汽车股份有限公司 | Vehicle personalized setting method and vehicle |
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