CN105701123B - The recognition methods of man-vehicle interface and device - Google Patents
The recognition methods of man-vehicle interface and device Download PDFInfo
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Abstract
This application discloses a kind of recognition methods of man-vehicle interface and devices.Wherein the recognition methods of the man-vehicle interface includes: the space-time data of the space-time data and vehicle according to people, calculates the relative coefficient of each personal vehicle combination；Each personal vehicle combination is traversed, judges whether the relative coefficient is more than or equal to relative coefficient threshold value；If so, combining people's vehicle as man-vehicle interface to be identified；Using default rule, the man-vehicle interface to be identified is identified as man-vehicle interface of the vehicle to a people or a vehicle to more people.Using method provided by the present application, it can be according to the space-time data of people and the space-time data of vehicle, man-vehicle interface is identified as man-vehicle interface of the vehicle to a people or a vehicle to more people, since the data cover of the space-time data of the space-time data and vehicle of the people of collection is wide, so as to identify the wide man-vehicle interface of comparison.
Description
Technical field
This application involves the field of data mining, and in particular to a kind of recognition methods of man-vehicle interface and device.
Background technique
Currently, all trades and professions are all widely collecting user data, and searched out from a large amount of data by algorithm hidden
It is hidden in useful information therein, it may be assumed that data mining.How limited data to be utilized, as much as possible the also scene, more smart of original subscriber
The real demand for capturing user quasi-ly has become various industries, the important research problem in field.
How the above problem is presented as using limited data in automobile consumption field, goes back the associated scene of protoplast's vehicle,
The problem of identifying man-vehicle interface.In digitization operation, assets assessment, it is often necessary to judge whether someone has vehicle.It is existing
People's vehicle recognition methods mainly includes following two:
1) it is identified based on people's vehicle register information.
This type of information is the most accurate, will do it registration because only that user really possesses vehicle.In this way, can be with
Directly obtain the relationship between User Identity, vehicles identifications.However, this type of information only have vehicle administration office, sale of automobile website,
Automobile 4s service shop has been likely to, since information is more sensitive, it is difficult to and the open other industry that is shared with uses, such as: electric business, society
Hand over the industries such as platform.
2) it is identified based on people in the Automobile Products consumer record of electric business platform.
In the user of electric business platform purchase Automobile Products, it is more likely that possess automobile, this type of information can also compare
Accurately identify the relationship of people, vehicle, it might even be possible to according to the Automobile Products of purchase, identify the model of automobile.However, due to purchase
The difference of habit is bought, many people buy Automobile Products not by electric business platform, and buy to the automobile 4s service shop under line, because
This, the disadvantages of the method are as follows people, car data coverage area be not wide.
In summary, on the one hand, vehicle administration office, sale of automobile website, automobile 4s service shop have the associated data of people's vehicle, but
Data sensitive seldom discloses, and can not use for other industry high-volume.On the other hand, since people, vehicle are independent entities, and
The on-line systems such as electric business platform, social platform can only obtain the very limited amount of associated data of people's vehicle when collecting data.
Therefore, the prior art, which exists, to identify man-vehicle interface according to a limited number of, true people's vehicle associated data
Problem.
Summary of the invention
The application provides recognition methods and the device of a kind of man-vehicle interface, can only be according to quantity to solve that the prior art exists
The problem of limited, true people's vehicle associated data identification man-vehicle interface.
The application provides a kind of recognition methods of man-vehicle interface, comprising:
According to the space-time data of the space-time data of people and vehicle, the relative coefficient of each personal vehicle combination is calculated；
Each personal vehicle combination is traversed, judges whether the relative coefficient is more than or equal to relative coefficient threshold value；If so,
It combines people's vehicle as man-vehicle interface to be identified；
Using default rule, the man-vehicle interface to be identified is identified as people of the vehicle to a people or a vehicle to more people
Vehicle relationship.
Optionally, in the space-time data of the space-time data according to people and vehicle, the correlation of each personal vehicle combination is calculated
Before coefficient, further includes:
Obtain the space-time data of the people and the space-time data of vehicle.
Optionally, the space-time data of the people includes identity, longitude, latitude and time；The space-time data of the vehicle
Including navigation equipment mark, longitude, latitude and time；The relative coefficient refers to that time and geographical location are equal between people and Che
Identical number.
Optionally, in the space-time data of the space-time data according to people and vehicle, the correlation of each personal vehicle combination is calculated
Before coefficient, further includes:
The every a pair longitude and latitude data of the space-time data of the space-time data of the people and vehicle are converted to
The character string of geohash coding.
Optionally, the digit of the geohash coding is adjustable.
Optionally, the space-time data of the space-time data and vehicle of the people refers to flat within the scope of preset time interval
Equal geographical location.
Optionally, in the space-time data of the space-time data according to people and vehicle, the correlation of each personal vehicle combination is calculated
Before coefficient, further includes:
POI data according to the map, by the space-time data of the space-time data of the people and vehicle with specific geographic position phase
The data of pass are deleted；The map POI data includes title, classification, longitude and latitude.
Optionally, described according to the space-time data of people and the space-time data of vehicle, calculate the correlation system of each personal vehicle combination
Number includes:
According to the space-time data of the space-time data of people and vehicle, the combination of owner's vehicle is generated；
Each personal vehicle combination is traversed, obtains and combines the space-time data of relevant people and the space-time data of vehicle with people's vehicle, and
According to the space-time data of the space-time data of the relevant people and vehicle, the relative coefficient of people's vehicle combination is calculated.
Optionally, described to use default rule, the man-vehicle interface to be identified is identified as a vehicle to a people or one
Vehicle includes: to the man-vehicle interface of more people
If people in the man-vehicle interface to be identified is only with a vehicle there are man-vehicle interface, and the people to be identified
Only there are man-vehicle interfaces with a people for vehicle in vehicle relationship, then determine that the man-vehicle interface to be identified is people of the vehicle to a people
Vehicle relationship；
If there are man-vehicle interfaces to be identified between more vehicles respectively by the people in the man-vehicle interface to be identified, or
There are man-vehicle interfaces to be identified between multiple people respectively for vehicle in the man-vehicle interface to be identified, then determine the correlation
The maximum man-vehicle interface to be identified of property coefficient is man-vehicle interface of the vehicle to a people；
If the vehicle in the man-vehicle interface to be identified is sentenced respectively between multiple people there are man-vehicle interface to be identified
It is a vehicle between the fixed vehicle and the multiple people to the man-vehicle interface of more people.
Optionally, the relative coefficient threshold value is generated using following steps:
In the space-time data of the people, the people with vehicle and mobile device of the first predetermined number is chosen, as first
Sample；
According to the first sample, in the space-time data of the people and the space-time data of vehicle, the first sample is obtained
In everyone the people space-time data and the space-time data of vehicle that possesses of the people, as the first data to be calculated；
Calculate the relative coefficient of each of described first data to be calculated He each car；
The average value for calculating the relative coefficient of each of described first data to be calculated and each car, as described
Relative coefficient threshold value.
Optionally, the relative coefficient threshold value is generated using following steps:
In the space-time data of the people, the people with vehicle and mobile device of the first predetermined number is chosen, as first
Sample；
According to the first sample, in the space-time data of the people and the space-time data of vehicle, the first sample is obtained
In everyone the people space-time data and the space-time data of vehicle that possesses of the people, as the first data to be calculated；
Calculate the relative coefficient of each of described first data to be calculated He each car；
The average value for calculating the relative coefficient of each of described first data to be calculated and each car, as first
Average correlation coefficient；
In the space-time data of the people, the only people with mobile device without vehicle of the second predetermined number is chosen,
As the second sample；
According to second sample, in the space-time data of the people, everyone institute in acquisition second sample
The space-time data for stating people, using its space-time data with the vehicle as the second data to be calculated；
Calculate the relative coefficient of each of described second data to be calculated He each car；
In the relative coefficient of each of described second data to be calculated and each car, relative coefficient is chosen most
The relative coefficient of high preset ratio, as relative coefficient to be calculated；And by the relative coefficient to be calculated
Average value adds third predetermined number, as the second average correlation coefficient；
The maximum value in the first average correlation coefficient and the second average correlation coefficient is chosen, as the correlation
Property coefficient threshold value.
Optionally, the space-time data of the vehicle further includes vehicle model and license plate number.
The application also provides a kind of identification device of man-vehicle interface, comprising:
Computing unit, for calculating the correlation of each personal vehicle combination according to the space-time data of people and the space-time data of vehicle
Coefficient；
Judging unit judges whether the relative coefficient is more than or equal to correlation system for traversing each personal vehicle combination
Number threshold value；If so, combining people's vehicle as man-vehicle interface to be identified；
Identify unit, for using default rule, by the man-vehicle interface to be identified be identified as a vehicle to a people or
Man-vehicle interface of one vehicle to more people.
Optionally, further includes:
Acquiring unit, for obtaining the space-time data of the people and the space-time data of vehicle.
Optionally, further includes:
Transcoding units, for turning every a pair of of the longitude and latitude data of the space-time data of the space-time data of the people and vehicle
It is changed to the character string of geohash coding.
Optionally, further includes:
Delete unit, for POI data according to the map, by the space-time data of the space-time data of the people and vehicle with spy
Determine the relevant data in geographical location to delete；The map POI data includes title, classification, longitude and latitude.
Optionally, the computing unit includes:
Subelement is combined, for generating the combination of owner's vehicle according to the space-time data of people and the space-time data of vehicle；
Computation subunit, for traversing each personal vehicle combination, obtain the space-time data that relevant people is combined with people's vehicle and
The space-time data of vehicle, and according to the space-time data of the space-time data of the relevant people and vehicle, calculate the correlation of people's vehicle combination
Property coefficient.
Optionally, the mark unit includes:
First identifier subelement, if only there are people Che Guan with a vehicle for the people in the man-vehicle interface to be identified
System, and only there are man-vehicle interfaces with a people for the vehicle in the man-vehicle interface to be identified, then determine the people to be identified
Vehicle relationship is man-vehicle interface of the vehicle to a people；
Second identifier subelement, if existed between more vehicles respectively for the people in the man-vehicle interface to be identified
There are people to be identified between multiple people respectively for vehicle in man-vehicle interface or the man-vehicle interface to be identified to be identified
Vehicle relationship then determines that the maximum man-vehicle interface to be identified of the relative coefficient is man-vehicle interface of the vehicle to a people；
Third identifies subelement, if existed between multiple people respectively for the vehicle in the man-vehicle interface to be identified
Man-vehicle interface to be identified then determines the man-vehicle interface between the vehicle and the multiple people for a vehicle to more people.
Compared with prior art, the application has the following advantages:
The recognition methods of man-vehicle interface provided by the present application and device are based on by collector respectively, the location information of vehicle
The identification of space-time obtains the relationship of people and vehicle.
The space-time data of the recognition methods of man-vehicle interface provided by the present application and device, space-time data and vehicle to people carries out
Data mining, by calculating the relative coefficient of each personal vehicle combination, and by each relative coefficient and relative coefficient threshold value
It is compared, default rule can be used, the man-vehicle interface that relative coefficient is more than or equal to relative coefficient threshold value is identified
For a vehicle to a people or a vehicle to the man-vehicle interface of more people, due to the data of the space-time data of the space-time data and vehicle of the people of collection
Broad covered area, so as to identify the wide man-vehicle interface of comparison.
Detailed description of the invention
Fig. 1 is the flow chart of the recognition methods embodiment of the man-vehicle interface of the application；
Fig. 2 is the specific flow chart that the space-time data of people is generated in the recognition methods embodiment of the man-vehicle interface of the application；
Fig. 3 is the specific flow chart of step S101 in the recognition methods embodiment of the man-vehicle interface of the application；
Fig. 4 is the detailed process that relative coefficient threshold value is generated in the recognition methods embodiment of the man-vehicle interface of the application
Figure；
Fig. 5 is the specific flow chart of step S103 in the recognition methods embodiment of the man-vehicle interface of the application；
Fig. 6 is the schematic diagram of the identification device embodiment of the man-vehicle interface of the application.
Specific embodiment
In the following description, numerous specific details are set forth in order to facilitate a full understanding of the present invention.But the present invention can be with
Much it is different from other way described herein to implement, those skilled in the art can be without prejudice to intension of the present invention the case where
Under do similar popularization, therefore the present invention is not limited to the specific embodiments disclosed below.
In this application, recognition methods and the device of a kind of man-vehicle interface are provided.In the following embodiments one by one into
Row is described in detail.
Referring to FIG. 1, its flow chart for the recognition methods embodiment of the man-vehicle interface of the application.The method includes such as
Lower step:
Step S101: according to the space-time data of the space-time data of people and vehicle, the relative coefficient of each personal vehicle combination is calculated.
Existing man-vehicle interface information perhaps due to too it is sensitive cannot share use or due to covering surface is small cannot be wide
General use.The recognition methods of man-vehicle interface provided by the present application can carry out man-vehicle interface according to a large amount of people truck position information
Identification, existing man-vehicle interface data are supplemented from the angle of data mining.
Data mining (Data Mining, DM) is the hot issue of current artificial intelligence and database area research, so-called
Data mining refers to disclose implicit, not previously known and has potential value from the mass data of database by algorithm
The non-trivial process of information.Data mining is a kind of decision support processes, it is based primarily upon artificial intelligence, machine learning, mode
Identification, statistics, database, visualization technique etc. analyze the data of enterprise increasingly automatedly, make the reasoning of inductive,
Potential mode is therefrom excavated, aid decision making person adjusts market strategy, reduces risks, make correct decision.
Knowledge Discovery process is made of following three phases: (1) data preparation, (2) data mining, (3) results expression and
It explains.Data mining can be interacted with user or knowledge base.Data mining is sought from mass data by analyzing each data
The technology for looking for its rule mainly has data preparation, rule searching and rule to indicate 3 steps.Data preparation is from relevant number
According to choosing required data in source and be integrated into the data set for data mining；It is with some way by data set that rule, which is found,
Contained rule is found out；Rule indicates it is to indicate the rule found out (as visualized) as far as possible in such a way that user is intelligible
Out.
It the relevant analysis of the task of data mining, clustering, classification analysis, anomaly analysis, special cohort analysis and drills
Variation analysis etc..The recognition methods of man-vehicle interface provided by the present application, is a kind of method of typical data mining, and task is
According to a large amount of people truck position information, analysis is associated to people and Che, to obtain a people to a vehicle or a vehicle to more people's
Man-vehicle interface.
In the present embodiment, in the space-time data of the space-time data according to people and vehicle, each personal vehicle combination is calculated
Before relative coefficient, further includes:
Step S100: the space-time data of the people and the space-time data of vehicle are obtained.
For the recognition methods for implementing man-vehicle interface provided by the present application, it is necessary first to carry out Data Preparation, obtain number
According to the object of excavation, it may be assumed that the data set of the space-time data of the space-time data and vehicle of people.
The space-time data of people described in the embodiment of the present application is mainly derived from smart phone.The coverage of smart phone is
Through being covered with the whole world, because of the full touching that smart phone has outstanding operating system, can freely install all kinds of softwares, complete large-size screen monitors
This three big characteristic of screen formula operation sense, so the keyboard-type mobile phone to have terminated completely several years ago.Currently, most people are owned by intelligence
Mobile phone.With the development of mobile internet, the application based on mobile Internet is also increasing, such as: network finance, mobile purchase
Object, social media, e-commerce, instant messaging etc., various mobile phones, which are applied, provides colourful service for user.Wherein,
The client of certain application program of mobile phone can be collected into the location information of people, for example, Tencent QQ, Taobao can collect user
Geographical location information.Become increasingly abundant along with what the extensive use of smart phone and mobile phone were applied, people got used to
When done shopping, chatted using smart phone everywhere, client all incessantly record user location information, for example, with
When family is driven, client background is also in the location information that record user dumbly.Therefore, it can be collected by smart phone
The original position-information of a large amount of people.These original position-informations include but is not limited to the device number or user identity mark of mobile phone
The information such as knowledge, longitude, latitude and time.
After being collected into the original position-information of people, for the identification side for executing man-vehicle interface provided by the embodiments of the present application
Method, it is also necessary to data preparation work be carried out to the original position-information of people, in order to obtain the data set of standardization.For example, such as
The not instead of User Identity that fruit is collected into, cell phone apparatus number (are specifically as follows international mobile subscriber identity or advertisement
Identifier), then use of the corresponding people of the equipment in corresponding application program of mobile phone can be identified by user's identifying system
Family identity, such as: Taobao user id, Alipay user id etc..According to the User Identity of acquisition, standardization is generated
The location information of people.The location information of the people of standardization is denoted as user [userID, lat, log, time], the meaning indicated
Are as follows: the information of user's longitude and latitude locating for some specific time.
In the present embodiment, the space-time data of the people includes identity, longitude, latitude and time.Referring to FIG. 2,
Its for the application man-vehicle interface recognition methods embodiment in generate people space-time data specific flow chart, the people when
Empty data are generated using following steps:
Step S201: the space-time data of original people is acquired；The space-time data of the original people includes mobile terminal
At least one and longitude of device number and the User Identity of application program, latitude and time.
Step S202: judge the original people space-time data whether include the application program user identity mark
Know.
Step S203: if it is not, then according to the device number of the device number of the mobile terminal and mobile terminal and applying journey
The incidence relation of the User Identity of sequence obtains the user identity with the associated application program of device number of the mobile terminal
Mark.
Step S204: according to the user identity mark of the space-time data of the original people and the associated application program
Know, generates the space-time data of the people.
Step S205: the space-time data of the people is stored.
In the present embodiment, the space-time data of the vehicle includes navigation equipment mark, longitude, latitude and time.The application
The space-time data of vehicle described in embodiment is mainly derived from automobile navigation instrument.Since most private car is all configured with navigation
Instrument, in vehicle traveling process, if having used navigation routine or will record traveling road in crossing, important monitoring section etc.
The log information of line.Such as: high moral navigation can collect the daily record data in vehicle traveling process, since navigation equipment is built-in
In automobile, thus navigation can approximation be equal to automobile, navigation equipment mark approximation is equal to automobile logo.It is set by navigation
The standby automobile log information being collected into includes but is not limited to navigation equipment mark, longitude, latitude and time, is denoted as car
[carID, lat, log, time], the meaning indicated are as follows: the information of automobile longitude and latitude locating for some specific time.
The recognition methods of man-vehicle interface provided by the embodiments of the present application, by equipment such as smart phone and automobile navigation instruments,
The location information of a large amount of people, vehicle can be obtained.Since the data cover of collection is wide, so can recognize that the wide people of comparison
Vehicle relation data, to compensate for people's car data covering that the on-line systems such as electric business platform, social platform are collected in the prior art
The small defect in face.
When carrying out Data Preparation, it should be noted that the timeliness of data, the validity of the timeliness of data with data
Equally, decide the analysis result of data mining.In practical applications, need to confirm according to different needs the timeliness of data
Property, out-of-date thing will not have an impact decision having analyzed next.For man-vehicle interface, this timeliness is
Vital, reason is that the relationship between people and vehicle may change, and the industries such as electric business need basis to collect
The space-time data of people and Che quickly analyze effective as a result, to bring bigger interests to electric business.Therefore, it executes
The recognition methods of man-vehicle interface provided by the embodiments of the present application, the time range of the space-time data of the space-time data and vehicle of the people
It is adjustable, for example, object of the nearest 365 days data as data mining can be taken, really has to quickly recognize
Effect ground man-vehicle interface.
The space-time data of people and the space-time data of vehicle are got by step S100, i.e., executable step S101, according to people
Space-time data and vehicle space-time data, calculate the relative coefficient of each personal vehicle combination.Relative coefficient described herein
Refer to the number all the same of time and geographical location between people and Che, i.e. the space-time registration of people and Che.To obtain man-vehicle interface,
It needs to calculate separately the relative coefficient between them to the combination of every a pair of of people and Che.When calculating relative coefficient, need
The time of people and Che, geographical location are compared.
The ground in the space-time data of people and the space-time data of vehicle directly acquired respectively by smart phone and navigation equipment
Managing location information is longitude and latitude data.The recognition methods of man-vehicle interface provided by the embodiments of the present application, both can be directly right
Longitude and latitude data compare, and first can also switch to indicate by longitude and latitude data using different coding modes
After the one-dimensional character string in geographical location, then one-dimensional character string is compared again, so as to more efficiently be calculated,
Obtain the relative coefficient of people's vehicle combination.For example, geohash coding mode can be used, first longitude and latitude data are switched to
After one-dimensional character string, then one-dimensional character string is compared.These above-mentioned different calculations, all only specific embodiment
Change, all without departing from the core of the application, therefore all within the scope of protection of this application.
Based on above-mentioned analysis, to reach higher calculating speed, in the present embodiment, in the space-time data according to people
With the space-time data of vehicle, before the relative coefficient for calculating each personal vehicle combination, further includes: by the space-time data and vehicle of the people
Space-time data every a pair longitude and latitude data be converted to geohash coding character string.
Geohash is the algorithm that two-dimensional longitude and latitude is converted into one-dimensional character string, each character string represents certain
One rectangular area.The simplest explanation of geohash is exactly: by a latitude and longitude information, be converted into one can sort, can be with
The string encoding compared.The algorithm is used primarily in the address searching of map at present, can be in database using the algorithm
Index is established in address, and the speed of map data retrieval is greatly improved.Geohash coding digit be it is adjustable, character string
Digit is more, and the rectangular area represented is smaller, so that the geographical location indicated is more accurate.In the present embodiment, due to vapour
Vehicle is mobile fast, a region is indicated with 6 geohash codings (about 0.34 sq-km), as the smallest mikey.
The people in each geographical location and the space-time data of Che can be acquired at any time by navigation equipment and smart phone, wrapped
It includes: parking lot, bustling business block.Parking lot and the business block of prosperity are all the crowded regions of wagon flow, these
The data in region are relatively difficult to navigate to specific vehicle, people, such as: it is according to the man-vehicle interface that the data in these places analyze
One people is to more vehicles or a vehicle to the relationship of more people, and actual conditions are really not so.Therefore, for the analysis of man-vehicle interface, by it
It is considered as interference data or noise data.For this purpose, can with POI according to the map (Point of Interest) coordinate, by people and
Parking lot involved in the space-time data of vehicle, bustling block location information weed out, in order to avoid the validity of impact analysis result.
In the present embodiment, in the space-time data of the space-time data according to people and vehicle, each personal vehicle combination is calculated
Before relative coefficient, further includes: POI data according to the map, by the space-time data of the space-time data of the people and vehicle with
The relevant data in specific geographic position are deleted.
In GIS-Geographic Information System, a POI can be a house, a retail shop, a mailbox, a bus station
Deng.Each POI includes four aspect information, title, classification, longitude, latitude.Therefore, the space-time of the space-time data and vehicle of very important person
Geographical location in data is overlapped with the specific geographic position of map POI coordinates logo, can reject the data.Pass through map
The classification information of POI, it is possible to specify specific geographic position, such as: classification is the POI in parking lot, bustling block.
Referring to FIG. 3, it is the specific flow chart of step S101 in recognition methods embodiment of the man-vehicle interface of the application.
In the present embodiment, described according to the space-time data of people and the space-time data of vehicle, calculate the relative coefficient of each personal vehicle combination
Include:
Step S1011: according to the space-time data of the space-time data of people and vehicle, the combination of owner's vehicle is generated.
In step S1011, first according to the space-time data of the space-time data of people and vehicle, all people in data set are obtained
With all vehicles, then people and Che are combined one by one, generate the combination of all people's vehicle.Such as: if the number of people is M,
The number of vehicle is N, then the number of people's vehicle combination is M*N.
Step S1012: each personal vehicle combination of traversal, obtain the space-time data and vehicle that relevant people is combined with people's vehicle when
Empty data, and according to the space-time data of the space-time data of the relevant people and vehicle, calculate the relative coefficient of people's vehicle combination.
In step S1012, for above-mentioned every a pair of of people Che Zuhe, in the space-time data of people and the space-time data of vehicle into
Row inquiry to obtain all space-time datas of people and all space-time datas of vehicle in the combination of people's vehicle, and calculates the people and is somebody's turn to do
Time and geographical location number all the same between vehicle, obtain relative coefficient.
The recognition methods of man-vehicle interface provided by the embodiments of the present application is to calculate correlation system to the combination of each personal vehicle
Number, therefore computation complexity is O (M*N), wherein M is the data volume of the space-time data of people, and N is the data of the space-time data of vehicle
Amount.The space-time data of the people of original collection and the space-time data of vehicle, application client and navigation depending on smart phone
The record time setting options of equipment, and open the time of application client and navigation equipment.Therefore, original collection
The space-time data of people and the space-time data of vehicle and non-temporal equally distributed data, the time of a part of data may be very close
Collection, and the time of another part data may be very loose.Importantly, original data volume is great.Therefore, if root
The relative coefficient that people's vehicle is calculated according to initial data will lead to huge calculation amount, and occupy more system resource.It considers
The movement characteristic of people and Che, except the space-time data of the above-mentioned people according to original collection and the space-time data of vehicle carry out calculating correlation
It, can also be according to the space-time data of the people of the average geographic location within the scope of preset time interval and the space-time of vehicle outside coefficient
Data are calculated, and in order to reduce calculation amount, improve calculating speed, and flat within the scope of the time interval being rationally arranged
The space-time data of people and the space-time data of vehicle in equal geographical location are capable of the motion profile of representative and Che.It is above-mentioned that these are different
Calculation, all only change of specific embodiment, all without departing from the core of the application, therefore all in the protection model of the application
Within enclosing.
In the present embodiment, for every a pair of of people Che Zuhe, according to the average geography within the scope of preset time interval
The space-time data of the people of position and the space-time data of vehicle calculate time all the same of time and geographical location between the people and the vehicle
Number.Specifically: by the time using 10 minutes as the smallest chronomere, the average bit that every 10 minutes people's vehicles occur is calculated
It sets, including two steps: according to the preset time interval, the space-time data of the space-time data of the people of original collection and vehicle being carried out
Segmentation；The average geographic location of each section initial data after calculating segmentation.When calculating mean place, can be used
The string representation position of geohash coding, then calculation result data is car [carID, geohash6, timeID], user
[userID, geohash6, timeID] respectively indicates vehicle and the event of people.
Step S102: each personal vehicle combination of traversal judges whether the relative coefficient is more than or equal to relative coefficient threshold
Value；If so, combining people's vehicle as man-vehicle interface to be identified.
Relative coefficient described herein refers to the number between people's vehicle with identical event, relative coefficient
Numerical value is bigger, then the correlation of people's vehicle is bigger.Relative coefficient threshold value described herein is one and passes through a large amount of regression trainings
The threshold value of acquired relative coefficient, the threshold value table are leted others have a look at the minimum value of the relative coefficient between vehicle, it may be assumed that as people Che Zhi
Between relative coefficient be more than or equal to relative coefficient threshold value when, determine people Che Xiangguan；When the relative coefficient between people's vehicle is small
When being equal to relative coefficient threshold value, then people Che Wuguan is determined.Relevant people's vehicle may be a vehicle to a people, a vehicle to a people or
One vehicle is to more people.In the specific implementation process, reasonably assessment relative coefficient threshold value is very crucial.It is obtained by regression training
When taking relative coefficient threshold value, feasible regression training mode includes the regression training mode of linear model, i.e. linear regression is calculated
Method.
The recognition methods of man-vehicle interface provided by the embodiments of the present application generates relative coefficient threshold value using following steps:
In the space-time data of the people, the people with vehicle and mobile device of the first predetermined number is chosen, as first sample；According to
The first sample obtains in the first sample everyone in the space-time data of the people and the space-time data of vehicle
The space-time data for the vehicle that the space-time data of the people and the people possess, as the first data to be calculated；Described first is calculated wait count
The relative coefficient for each of evidence and each car of counting；Calculate each of described first data to be calculated and each car
Relative coefficient average value, as the relative coefficient threshold value.
The recognition methods of man-vehicle interface provided by the embodiments of the present application, when generating relative coefficient threshold value, the of selection
Each of one sample all has vehicle or smart phone, it may be assumed that calculates relative coefficient threshold value from positive angle estimator.First
The number of sample should be sufficiently large, and the number of sample is more, and obtained relative coefficient threshold value is more accurate, such as: first sample
Number be greater than 100.Based on the considerations of data age, the present embodiment chooses people in first sample data, car data is most
Nearly 365 days data, it may be assumed that the first data to be calculated are specially data in preset time range.Pass through step S401 to step
Rapid S404 can obtain the average correlation coefficient for having people's vehicle combination of smart phone again with vehicle, by relative coefficient
Average value is as relative coefficient threshold value.
When assessing relative coefficient threshold value, to obtain more accurate assessment result, preferred assessment mode is from front
Comprehensive assessment is carried out with two angles of reverse side.Referring to FIG. 4, raw in its recognition methods embodiment for the man-vehicle interface of the application
At the specific flow chart of relative coefficient threshold value.In the present embodiment, the relative coefficient threshold value is generated using following steps:
Step S401: in the space-time data of the people, choosing the people with vehicle and mobile device of the first predetermined number,
As first sample.
Step S402: according to the first sample, in the space-time data of the people and the space-time data of vehicle, described in acquisition
The space-time data for the vehicle that the space-time data of everyone people and the people possess in first sample, as the first number to be calculated
According to.
Step S403: the relative coefficient of each of described first data to be calculated and each car is calculated.
Step S404: being averaged for the relative coefficient of each of described first data to be calculated and each car is calculated
Value, as the first average correlation coefficient.
First average correlation coefficient described herein refers to being averaged for the relative coefficient of the people and vehicle that possess vehicle
Value.In the present embodiment, assessment calculating is carried out from front first, each of first sample has vehicle, smart phone.Pass through
Step S401 to step S404 can obtain the average correlation coefficient for having people's vehicle combination of smart phone again with vehicle.Example
Such as: it chooses 100 and really possesses the people of vehicle as first sample, these people relative coefficient between its vehicle for possessing respectively
Average value be 10 times.
Step S405: in the space-time data of the people, that chooses the second predetermined number only has mobile device without having
There is the people of vehicle, as the second sample.
Step S406: it according to second sample, in the space-time data of the people, obtains each in second sample
The space-time data of the personal people, using its space-time data with the vehicle as the second data to be calculated.
Step S407: the relative coefficient of each of described second data to be calculated and each car is calculated.
Step S408: in the relative coefficient of each of described second data to be calculated and each car, phase is chosen
The relative coefficient for closing the highest preset ratio of property coefficient, as relative coefficient to be calculated；And by the phase to be calculated
The average value for closing property coefficient adds third predetermined number, as the second average correlation coefficient.
Step S405 to step S408 is to carry out assessment calculating from the negative, in the second sample of selection per capita without vehicle,
But there is smart phone.It in proprietary space-time data, obtains and belongs to the part data of people in the second sample, and by collection
The space-time data of data and whole vehicles carries out relative coefficient calculating, finds out the correlation system of each personal vehicle combination of the second sample
Number.In the present embodiment, the relative coefficient of people's vehicle of numerical value highest 20% is chosen, the average value of these relative coefficients is calculated,
And average value is added into third predetermined number as the second average correlation coefficient.Such as: choose 100 people for not possessing vehicle
As the second sample, relative coefficient of these people respectively between vehicle, highest to relative coefficient 20% people's vehicle are calculated
Relative coefficient, averaged be 7 times, if third predetermined number be 1, the second average correlation coefficient be 8 times.
In the present embodiment, the number of the first, second sample should be sufficiently large, and the number of sample is more, obtained correlation
Property coefficient threshold value is more accurate, such as: the number of the first, second sample is all larger than 100.
Based on the considerations of data age, the present embodiment chooses people in the first, second sample data, car data is nearest
365 days data, it may be assumed that the first, second data to be calculated are specially data in preset time range.
Third predetermined number described in the embodiment of the present application refers to the relative coefficient if between a people and a vehicle
Less than or equal to the average value of the relative coefficient to be calculated, then man-vehicle interface is not present between the people and the vehicle；If one
Relative coefficient between a personal and vehicle is more than or equal to the average value of the relative coefficient to be calculated and third is preset
The sum of number, then there are man-vehicle interfaces between the people and the vehicle.Third predetermined number be it is adjustable, can take whole greater than 0
Number, such as: third predetermined number is set as 1 or 2 etc..
Step S409: choosing the maximum value in the first average correlation coefficient and the second average correlation coefficient, makees
For the relative coefficient threshold value.
From front, assessment obtains the first average correlation coefficient, and assessment obtains the second average correlation coefficient from the negative, by
It lets others have a look at the minimum value of the relative coefficient between vehicle in relative coefficient threshold value table, therefore the first average correlation system should be chosen
Maximum value in several and the second average correlation coefficient, as relative coefficient threshold value.Such as: the first average correlation coefficient is
10, the second average correlation coefficient is 8, then relative coefficient threshold value is 10.
Step S103: default rule is used, the man-vehicle interface to be identified is identified as a vehicle to a people or a vehicle
To the man-vehicle interface of more people.
By step S102, people's vehicle that relative coefficient in the combination of owner's vehicle is more than or equal to relative coefficient threshold value is obtained
Combination, the relationship of these people's vehicles combination include a variety of different people of the vehicle to a people, a vehicle to more people and more vehicles to a people
Vehicle relationship, described in detail below:
1) man-vehicle interface of the vehicle to a people: the people in these man-vehicle interfaces is only corresponding with a vehicle, in turn, these
Vehicle in man-vehicle interface is also only corresponding with a people, it may be assumed that is one-to-one relationship between people and Che.Therefore, as judgement
Man-vehicle interface is man-vehicle interface of the vehicle to a people.
2) man-vehicle interface of the vehicle to more people: same vehicle in these man-vehicle interfaces is corresponding with multiple people, it may be assumed that people and
It is many-to-one relationship between vehicle.Therefore, such man-vehicle interface can be merged into a new man-vehicle interface, new people's vehicle
Artificial multiple people in relationship, vehicle are the vehicle that these people share, and are determined as a vehicle to the people of more people new man-vehicle interface
Vehicle relationship.Due to the vehicle of many types be for public trip service, such as: regular bus, school bus, officer's car etc., therefore will appear
The case where multiple people correspond to the same vehicle.
In practical applications, man-vehicle interface of the vehicle to more people can also be carried out further thin as the case may be
Point, a portion man-vehicle interface is determined as that a vehicle to the man-vehicle interface of more people, and another part man-vehicle interface is determined as
Man-vehicle interface of one vehicle to a people.Specifically: first to any one vehicle, search whether that there are N number of above people is associated therewith
Property coefficient is more than or equal to relative coefficient threshold value, and N may be set according to actual conditions, in the present embodiment using N >=5, if
There are N number of above people, these man-vehicle interfaces can be determined as a vehicle to the man-vehicle interface of more people；If only less than N's
People, then choose the maximum value in the vehicle and everyone relative coefficient, and people that maximal correlation property coefficient is related to and Che are sentenced
It is set to a vehicle to the man-vehicle interface of a people.For example, three people in one family co-own a vehicle, then determine most-often used
There is one-to-one man-vehicle interface between the people of the vehicle and the vehicle.These above-mentioned different judgment rules are all only embodied
The change of mode, all without departing from the core of the application, therefore all within the scope of protection of this application.
3) man-vehicle interface of more vehicles to a people: the same person in these man-vehicle interfaces is corresponding with multiple vehicles, it may be assumed that people and
It is one-to-many relationship between vehicle.Therefore, such man-vehicle interface can be merged into a new man-vehicle interface, new people's vehicle
An artificial people in relationship, vehicle are the more vehicles that this people possesses, and are determined as more vehicles to the people of a people new man-vehicle interface
Vehicle relationship.In the present embodiment, due to geohash character string identification be a region, this region may be recognized
Vehicle is all someone, both the corresponding people of more vehicles, this practical partial data is " dirty data ", can according to the specific time and
This partial data is found out, and is rejected in position.Such as: in the same time, the data that someone corresponds to multiple vehicles are " dirty
Data ".
Since the case where more vehicles are to a people, is complex, such as: when a people is in unit, it is likely to be obtained its and corresponds to more vehicles
The case where, these are not man-vehicle interface of the real more vehicles to a people.Therefore, man-vehicle interface provided by the embodiments of the present application
Recognition methods does not identify man-vehicle interface of more vehicles to a people specifically.
In conclusion needing as the case may be, to pre-establish some judgment rules, various man-vehicle interfaces are identified
Come.Referring to FIG. 5, it is the specific flow chart of step S103 in recognition methods embodiment of the man-vehicle interface of the application.At this
It is described to use default rule in embodiment, the man-vehicle interface to be identified is identified as a vehicle to a people or a vehicle to more
The man-vehicle interface of people includes:
Step S1031: and described if people in the man-vehicle interface to be identified is only with a vehicle there are man-vehicle interface
Only there are man-vehicle interfaces with a people for vehicle in man-vehicle interface to be identified, then determine that the man-vehicle interface to be identified is a vehicle
To the man-vehicle interface of a people.
Step S1032: if there are people to be identified between more vehicles respectively by the people in the man-vehicle interface to be identified
Vehicle in vehicle relationship or the man-vehicle interface to be identified is sentenced respectively between multiple people there are man-vehicle interface to be identified
The fixed maximum man-vehicle interface to be identified of relative coefficient is man-vehicle interface of the vehicle to a people.
Step S1033: if there are people to be identified between multiple people respectively for the vehicle in the man-vehicle interface to be identified
Vehicle relationship then determines the man-vehicle interface between the vehicle and the multiple people for a vehicle to more people.
In the present embodiment, the space-time data of the vehicle obtained by navigation equipment further includes vehicle model and license plate number
Code.The industries such as electric business, not only can basis after the relationship for obtaining people's vehicle according to the recognition methods of man-vehicle interface provided by the present application
Man-vehicle interface carries out relevant shopping guide's business, and further relevant promotion etc. can also be carried out according to vehicle model and license plate number
Activity.
The space-time data of the recognition methods of man-vehicle interface provided by the present application, space-time data and vehicle to people carries out data digging
Pick by calculating the relative coefficient of each personal vehicle combination, and each relative coefficient and relative coefficient threshold value is compared
Compared with, can use default rule, by relative coefficient be more than or equal to relative coefficient threshold value man-vehicle interface be identified as a vehicle
To a people or a vehicle to the man-vehicle interface of more people, due to the data cover face of the space-time data of the space-time data and vehicle of the people of collection
Extensively, so as to identifying the wide man-vehicle interface of comparison.
In the above-described embodiment, a kind of recognition methods of man-vehicle interface is provided, corresponding, the application also mentions
For a kind of identification device of man-vehicle interface.Fig. 5 is please referred to, is the signal of the identification device embodiment of the man-vehicle interface of the application
Figure.Since Installation practice is substantially similar to embodiment of the method, so describing fairly simple, related place is implemented referring to method
The part explanation of example.Installation practice described below is only schematical.
A kind of identification device of the man-vehicle interface of the present embodiment, comprising:
Computing unit 101, for calculating the correlation of each personal vehicle combination according to the space-time data of people and the space-time data of vehicle
Property coefficient judging unit 102 judges whether the relative coefficient is more than or equal to correlation system for traversing each personal vehicle combination
Number threshold value；If so, combining people's vehicle as man-vehicle interface to be identified；Unit 103 is identified, for using preset rule
Then, the man-vehicle interface to be identified is identified as man-vehicle interface of the vehicle to a people or a vehicle to more people.
Optionally, further includes:
Acquiring unit, for obtaining the space-time data of the people and the space-time data of vehicle.
Optionally, further includes:
Transcoding units, for turning every a pair of of the longitude and latitude data of the space-time data of the space-time data of the people and vehicle
It is changed to the character string of geohash coding.
Optionally, further includes:
Delete unit, for POI data according to the map, by the space-time data of the space-time data of the people and vehicle with spy
Determine the relevant data in geographical location to delete；The map POI data includes title, classification, longitude and latitude.
Optionally, the computing unit 101 includes:
Subelement is combined, for generating the combination of owner's vehicle according to the space-time data of people and the space-time data of vehicle；
Computation subunit, for traversing each personal vehicle combination, obtain the space-time data that relevant people is combined with people's vehicle and
The space-time data of vehicle, and according to the space-time data of the space-time data of the relevant people and vehicle, calculate the correlation of people's vehicle combination
Property coefficient.
Optionally, the mark unit 103 includes:
First identifier subelement, if only there are people Che Guan with a vehicle for the people in the man-vehicle interface to be identified
System, and only there are man-vehicle interfaces with a people for the vehicle in the man-vehicle interface to be identified, then determine the people to be identified
Vehicle relationship is man-vehicle interface of the vehicle to a people；
Second identifier subelement, if existed between more vehicles respectively for the people in the man-vehicle interface to be identified
There are people to be identified between multiple people respectively for vehicle in man-vehicle interface or the man-vehicle interface to be identified to be identified
Vehicle relationship then determines that the maximum man-vehicle interface to be identified of the relative coefficient is man-vehicle interface of the vehicle to a people；
Third identifies subelement, if existed between multiple people respectively for the vehicle in the man-vehicle interface to be identified
Man-vehicle interface to be identified then determines the man-vehicle interface between the vehicle and the multiple people for a vehicle to more people.
Although the present invention is disclosed as above with preferred embodiment, it is not for limiting the present invention, any this field skill
Art personnel without departing from the spirit and scope of the present invention, can make possible variation and modification, therefore guarantor of the invention
Shield range should be subject to the range that the claims in the present invention are defined.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
1, computer-readable medium can be by any side including permanent and non-permanent, removable and non-removable media
Method or technology realize that information stores.Information can be computer readable instructions, data structure, the module of program or other numbers
According to.The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory
(SRAM), dynamic random access memory (DRAM), other kinds of random access memory (RAM), read-only memory
(ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory techniques, CD-ROM are read-only
Memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or
Other magnetic storage devices or any other non-transmission medium, can be used for storage can be accessed by a computing device information.According to
Herein defines, and computer-readable medium does not include non-temporary computer readable media (transitory media), such as modulates
Data-signal and carrier wave.
2, it will be understood by those skilled in the art that embodiments herein can provide as the production of method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It can be used moreover, the application can be used in the computer that one or more wherein includes computer usable program code
The computer program product implemented on storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Form.
Claims (18)
1. a kind of recognition methods of man-vehicle interface characterized by comprising
According to the space-time data of the space-time data of people and vehicle, the relative coefficient of each personal vehicle combination, the correlation system are calculated
Number refers to the number all the same of time and geographical location between people and Che；
Each personal vehicle combination is traversed, judges whether the relative coefficient is more than or equal to relative coefficient threshold value；If so, by institute
The combination of people's vehicle is stated as man-vehicle interface to be identified；
Using default rule, the man-vehicle interface to be identified is identified as Ren Cheguan of the vehicle to a people or a vehicle to more people
System.
2. the recognition methods of man-vehicle interface according to claim 1, which is characterized in that in the space-time data according to people
With the space-time data of vehicle, before the relative coefficient for calculating each personal vehicle combination, further includes:
Obtain the space-time data of the people and the space-time data of vehicle.
3. the recognition methods of man-vehicle interface according to claim 1, which is characterized in that the space-time data of the people includes body
Part mark, longitude, latitude and time；The space-time data of the vehicle includes navigation equipment mark, longitude, latitude and time.
4. the recognition methods of man-vehicle interface according to claim 2, which is characterized in that in the space-time data according to people
With the space-time data of vehicle, before the relative coefficient for calculating each personal vehicle combination, further includes:
The every a pair longitude and latitude data of the space-time data of the space-time data of the people and vehicle are converted to geohash to compile
The character string of code.
5. the recognition methods of man-vehicle interface according to claim 4, which is characterized in that the digit of the geohash coding
It is adjustable.
6. the recognition methods of man-vehicle interface according to claim 4, which is characterized in that the space-time data of the people and vehicle
Space-time data refers to the average geographic location within the scope of preset time interval.
7. the recognition methods of man-vehicle interface according to claim 1, which is characterized in that in the space-time data according to people
With the space-time data of vehicle, before the relative coefficient for calculating each personal vehicle combination, further includes:
POI data according to the map, will be relevant to specific geographic position in the space-time data of the space-time data of the people and vehicle
Data are deleted；The map POI data includes title, classification, longitude and latitude.
8. the recognition methods of man-vehicle interface according to claim 1, which is characterized in that the space-time data according to people and
The space-time data of vehicle, the relative coefficient for calculating each personal vehicle combination include:
According to the space-time data of the space-time data of people and vehicle, the combination of owner's vehicle is generated；
Each personal vehicle combination is traversed, obtains and combines the space-time data of relevant people and the space-time data of vehicle with people's vehicle, and according to
The space-time data of the relevant people and the space-time data of vehicle calculate the relative coefficient of people's vehicle combination.
9. the recognition methods of man-vehicle interface according to claim 1, which is characterized in that it is described to use default rule, it will
The man-vehicle interface to be identified is identified as a vehicle and includes: to the man-vehicle interface of more people to a people or a vehicle
If people in the man-vehicle interface to be identified is only with a vehicle there are man-vehicle interface, and the Ren Cheguan to be identified
Only there are man-vehicle interfaces with a people for vehicle in system, then determine that the man-vehicle interface to be identified is Ren Cheguan of the vehicle to a people
System；
If there are man-vehicle interfaces to be identified or described between more vehicles respectively by people in the man-vehicle interface to be identified
There are man-vehicle interfaces to be identified between multiple people respectively for vehicle in man-vehicle interface to be identified, then determine the correlation system
The maximum man-vehicle interface to be identified of number is man-vehicle interface of the vehicle to a people；
If the vehicle in the man-vehicle interface to be identified is respectively between multiple people there are man-vehicle interface to be identified, determining should
It is a vehicle between vehicle and the multiple people to the man-vehicle interface of more people.
10. the recognition methods of -9 described in any item man-vehicle interfaces according to claim 1, which is characterized in that the correlation system
Number threshold value is generated using following steps:
In the space-time data of the people, the people with vehicle and mobile device of the first predetermined number is chosen, as first sample；
According to the first sample, in the space-time data of the people and the space-time data of vehicle, obtain every in the first sample
The space-time data for the vehicle that the space-time data of the people of one people and the people possess, as the first data to be calculated；
Calculate the relative coefficient of each of described first data to be calculated He each car；
The average value for calculating the relative coefficient of each of described first data to be calculated and each car, as the correlation
Property coefficient threshold value.
11. the recognition methods of -9 described in any item man-vehicle interfaces according to claim 1, which is characterized in that the correlation system
Number threshold value is generated using following steps:
In the space-time data of the people, the people with vehicle and mobile device of the first predetermined number is chosen, as first sample；
According to the first sample, in the space-time data of the people and the space-time data of vehicle, obtain every in the first sample
The space-time data for the vehicle that the space-time data of the people of one people and the people possess, as the first data to be calculated；
Calculate the relative coefficient of each of described first data to be calculated He each car；
The average value for calculating the relative coefficient of each of described first data to be calculated and each car, it is average as first
Relative coefficient；
In the space-time data of the people, the only people with mobile device without vehicle of the second predetermined number is chosen, as
Second sample；
According to second sample, in the space-time data of the people, everyone people in acquisition second sample
Space-time data, using its space-time data with the vehicle as the second data to be calculated；
Calculate the relative coefficient of each of described second data to be calculated He each car；
In the relative coefficient of each of described second data to be calculated and each car, it is highest to choose relative coefficient
The relative coefficient of preset ratio, as relative coefficient to be calculated；And being averaged the relative coefficient to be calculated
Value plus third predetermined number, as the second average correlation coefficient；
The maximum value in the first average correlation coefficient and the second average correlation coefficient is chosen, as the correlation system
Number threshold value.
12. the recognition methods of -9 described in any item man-vehicle interfaces according to claim 1, which is characterized in that the space-time of the vehicle
Data further include vehicle model and license plate number.
13. a kind of identification device of man-vehicle interface characterized by comprising
Computing unit, for calculating the relative coefficient of each personal vehicle combination according to the space-time data of people and the space-time data of vehicle,
The relative coefficient refers to the number all the same of time and geographical location between people and Che；
Judging unit judges whether the relative coefficient is more than or equal to relative coefficient threshold for traversing each personal vehicle combination
Value；If so, combining people's vehicle as man-vehicle interface to be identified；
Unit is identified, for using default rule, the man-vehicle interface to be identified is identified as a vehicle to a people or a vehicle
To the man-vehicle interface of more people.
14. the identification device of man-vehicle interface according to claim 13, which is characterized in that further include:
Acquiring unit, for obtaining the space-time data of the people and the space-time data of vehicle.
15. the identification device of man-vehicle interface according to claim 13, which is characterized in that further include:
Transcoding units, for being converted to every a pair of of the longitude and latitude data of the space-time data of the space-time data of the people and vehicle
The character string of geohash coding.
16. the identification device of man-vehicle interface according to claim 13, which is characterized in that further include:
Unit is deleted, it, will be in the space-time data of the space-time data of the people and vehicle and specifically for POI data according to the map
The relevant data in position are managed to delete；The map POI data includes title, classification, longitude and latitude.
17. the identification device of man-vehicle interface according to claim 13, which is characterized in that the computing unit includes:
Subelement is combined, for generating the combination of owner's vehicle according to the space-time data of people and the space-time data of vehicle；
Computation subunit obtains the space-time data and vehicle that relevant people is combined with people's vehicle for traversing each personal vehicle combination
Space-time data, and according to the space-time data of the space-time data of the relevant people and vehicle, calculate the correlation system of people's vehicle combination
Number.
18. the identification device of man-vehicle interface according to claim 13, which is characterized in that the mark unit includes:
First identifier subelement, if for the people in the man-vehicle interface to be identified only with a vehicle there are man-vehicle interface,
And only there are man-vehicle interfaces with a people for the vehicle in the man-vehicle interface to be identified, then determine the Ren Cheguan to be identified
System is man-vehicle interface of the vehicle to a people；
Second identifier subelement, if existed between more vehicles wait mark respectively for the people in the man-vehicle interface to be identified
There are Ren Cheguan to be identified between multiple people respectively for vehicle in the man-vehicle interface of knowledge or the man-vehicle interface to be identified
System then determines that the maximum man-vehicle interface to be identified of the relative coefficient is man-vehicle interface of the vehicle to a people；
Third identifies subelement, if existed between multiple people wait mark respectively for the vehicle in the man-vehicle interface to be identified
The man-vehicle interface of knowledge then determines the man-vehicle interface between the vehicle and the multiple people for a vehicle to more people.
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