CN108446824A - A kind of methods of risk assessment of driving behavior, device, equipment and storage medium - Google Patents
A kind of methods of risk assessment of driving behavior, device, equipment and storage medium Download PDFInfo
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- CN108446824A CN108446824A CN201810129494.1A CN201810129494A CN108446824A CN 108446824 A CN108446824 A CN 108446824A CN 201810129494 A CN201810129494 A CN 201810129494A CN 108446824 A CN108446824 A CN 108446824A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
Abstract
Applicable data processing technology field of the present invention, providing a kind of methods of risk assessment of driving behavior, device, equipment and storage medium, this method includes：When the request for receiving the driving behavior progress risk assessment to target user, acquire the running data that target user drives, the driving behavior of target user is analyzed according to collected running data, to obtain the driving behavior data of target user, according to the driving behavior data of target user, the driving behavior data and preset risk assessment algorithm of user in the blacklist library pre-established, risk analysis is carried out to the driving behavior of target user, to obtain the risk evaluation result of target user's driving behavior, so that the assessment of vehicle business risk for insurance is more perfect, it is more scientific, and then improve the premium accuracy of vehicle.
Description
Technical field
The invention belongs to technical field of data processing more particularly to a kind of methods of risk assessment of driving behavior, device, set
Standby and storage medium.
Background technology
User after buying vehicle, be typically necessary for vehicle buy insure, user in addition to the compulsory insurance for traffic accident of motor-drivenvehicle for having to pay,
Purchase others business insurance that usually can also be additional, currently, traditional insurance products mainly use car insurance in the market
The static data of vehicle assesses premium of vehicle, such as the model of vehicle, producer, vehicle age etc., but risk be often people because
Caused by element, and individual risk's factor complexity is various, and information asymmetry just becomes common problem.For example, insurance is public
Department can not learn the driving behavior of driver, and insurer may hide personal information to acquire an advantage.At home, 82.5%
It is the car owner for being law-abiding, driving with caution, they check for the 17.5% often client that is in danger, therefore traditional insurance product is determined
Valence pattern is very unreasonable.
With the development of car networking, car networking technology is more and more applied in insurance industry, therefore, is based on UBI
The innovation insurance products of (Usage Based Insurance) occur, but UBI products are mainly or based on " from vehicle " at present
Risk factors calculate premium, only considered part " from row " risk factors, therefore the premium accuracy for the vehicle being calculated
It is relatively low.
Invention content
The purpose of the present invention is to provide a kind of methods of risk assessment of driving behavior, device, equipment and storage medium, purports
It is solving that due to the prior art a kind of method effectively carrying out risk assessment to driving behavior can not be provided, is leading to vehicle business
Risk for insurance assesses incomplete problem.
On the one hand, the present invention provides a kind of methods of risk assessment of driving behavior, the method includes following step：
When the request for receiving the driving behavior progress risk assessment to target user, acquires the target user and drive
Running data；
The driving behavior that the target user is analyzed according to the collected running data, to obtain the target user
Driving behavior data；
According to the driving behavior data of user in the driving behavior data of the target user, the blacklist library pre-established
And preset risk assessment algorithm, risk analysis is carried out to the driving behavior of the target user, to obtain the mesh
Mark the risk evaluation result of user's driving behavior.
On the other hand, the present invention provides a kind of risk assessment device of driving behavior, described device includes：
Running data collecting unit, for when the request for receiving the driving behavior progress risk assessment to target user
When, acquire the running data that the target user drives；
Behavioral data obtaining unit, the driving row for analyzing the target user according to the collected running data
For to obtain the driving behavior data of the target user；And
Risk analysis unit, for according in the driving behavior data of the target user, the blacklist library pre-established
The driving behavior data and preset risk assessment algorithm of user carry out risk to the driving behavior of the target user
Analysis, to obtain the risk evaluation result of target user's driving behavior.
On the other hand, the present invention also provides a kind of computing device, including memory, processor and it is stored in described deposit
In reservoir and the computer program that can run on the processor, the processor are realized such as when executing the computer program
The step of preceding the method.
On the other hand, the present invention also provides a kind of computer readable storage medium, the computer readable storage mediums
It is stored with computer program, the step of computer program realizes method as previously described when being executed by processor.
When the request for receiving the driving behavior progress risk assessment to target user, acquisition target user drives the present invention
The running data sailed analyzes the driving behavior of target user according to collected running data, to obtain the driving of target user
Behavioral data, according to the driving behavior data of user in the driving behavior data of target user, the blacklist library pre-established with
And preset risk assessment algorithm, risk analysis is carried out to the driving behavior of target user, to obtain target user's driving behavior
Risk evaluation result and then improve the guarantor of vehicle so that the assessment of vehicle business risk for insurance is more perfect, more scientific
Take accuracy.
Description of the drawings
Fig. 1 is the implementation flow chart of the methods of risk assessment for the driving behavior that the embodiment of the present invention one provides；
Fig. 2 is the structural schematic diagram of the risk assessment device of driving behavior provided by Embodiment 2 of the present invention；
Fig. 3 is the structural schematic diagram of the risk assessment device for the driving behavior that the embodiment of the present invention three provides；And
Fig. 4 is the structural schematic diagram for the computing device that the embodiment of the present invention four provides.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The specific implementation of the present invention is described in detail below in conjunction with specific embodiment：
Embodiment one：
Fig. 1 shows the implementation process of the methods of risk assessment for the driving behavior that the embodiment of the present invention one provides, in order to just
In explanation, illustrate only with the relevant part of the embodiment of the present invention, details are as follows：
In step S101, when the request for receiving the driving behavior progress risk assessment to target user, mesh is acquired
Mark the running data that user drives.
The embodiment of the present invention is suitable for computing device, for example, personal computer, smart mobile phone, tablet etc..Target user drives
The running data sailed include speed, total mileage, single stroke mileage number, stroke complete duration, stop frequency, parking duration,
Speed acceleration amplitude etc..Preferably, the running data driven to collected target user is handled, first, completion stroke
The previous stroke end of origin information, i.e., adjacent two data is latter start of a run, later, according to stroke mileage number or
Person is ranked up on the traveling date, such as how much mileage number carries out descending sort, later, when according to the end time of stroke and beginning
Between calculate stroke and complete duration, finally, filter out mileage number or stroke and complete the stroke that duration is equal to 0, and by the space of traveling
Longitude and latitude numerical value is converted to the coordinate of the point in plane right-angle coordinate, to purify running data so that subsequently uses target
The risk evaluation result of family driving behavior is more acurrate.
Preferably, before the running data that acquisition target user drives, blacklist library is first established, first, according to adopting
The insurance data of the driving vehicle of collection obtains be in danger number and the amount for which loss settled of driving vehicle, later, when the number that is in danger reaches pre-
If number or amount for which loss settled when being more than the preset amount of money, blacklist library is added in driving vehicle user, to establish blacklist
Library, to provide foundation for the risk assessment of succeeding target user's driving behavior.
It is further preferred that when determining driving vehicle user addition blacklist library, by the driving of driving vehicle user
The basic attribute data of behavioral data, the basic attribute data of driving vehicle user and driving vehicle is associated, to make
It obtains subsequently more acurrate to the risk evaluation result of target user's driving behavior.
In step s 102, the driving behavior that target user is analyzed according to collected running data, to obtain target use
The driving behavior data at family.
In embodiments of the present invention, the driving behavior that target user is analyzed according to collected running data, as example
The driving behavior on ground, target user includes：Such as, if hypervelocity, whether fatigue driving, whether wide-angle deflecting, whether substantially
It whether excessively high spends acceleration or deceleration, acceleration and the conversion frequency of deceleration, is obtained according to the driving behavior of target user and drive row
For data, as illustratively, for example, hundred kilometers of anxious deceleration numbers, hundred kilometers of anxious acceleration times, velocity standard are poor, conversion driving
Duration, conversion mileage, hundred kilometers of zig zag numbers, fatigue driving number, night running duration, idling ratio, dwell times, roads
The strange degree in road, non-green go out line frequency and deduction of points violating the regulations.
In step s 103, it is driven according to user in the driving behavior data of target user, the blacklist library pre-established
Behavioral data and preset risk assessment algorithm are sailed, risk analysis is carried out to the driving behavior of target user, to obtain target
The risk evaluation result of user's driving behavior.
In embodiments of the present invention, it is used according in the driving behavior data of target user, the blacklist library pre-established
The driving behavior data and preset risk assessment algorithm at family carry out risk analysis to the driving behavior data of target user
When, it is preferable that first, the weight coefficient of each dimension is calculated according to preset assessment dimension and preset weight calculation algorithm,
Then, the blacklist library for calculating target user according to the weight coefficient being calculated and preset distance algorithm and pre-establishing
The weighted euclidean distance is finally compared analysis, to obtain target by the weighted euclidean distance of middle user with preset threshold value
The risk evaluation result of user's driving behavior, to improve the accuracy of target user's driving behavior risk evaluation result.
In embodiments of the present invention, specifically, first, maximum most using removal when calculating the weight coefficient of each dimension
User is in the index from people, from vehicle and from each dimension of driving behavior in the small method calculating blacklist library for calculating arithmetic mean later
The average of value and target user calculate each index value of user in blacklist later in the average of the index value of same dimension
Relative number with the variable quantity of each index value of target user compared with each index value of target user, finally, according to the relative number calculate from
People, the weight coefficient from vehicle and from each dimension of driving behavior.
In embodiments of the present invention, in calculating target user and the blacklist library that pre-establishes user weighted Euclidean away from
From when, it is preferable that first, the user for taking 10 distance objective users nearest in blacklist library is as neighbour user, later, root
Formula is normalized according to minimaxBy each dimension index value of neighbour user and target user's respective dimensions index
Value is normalized, wherein viIndicate i-th of original index value, v 'iThe index value after standardization is indicated, later, according to formulaThe weighted euclidean distance of neighbour user in target user and the blacklist library pre-established is calculated,
Wherein, (x1,x2,…,xn) and (y1,y2,…,yn) indicate i-th of dimension of user two point coordinates, ωiIndicate i-th dimension
The weighted euclidean distance is compared analysis, to obtain target user's driving behavior by weight coefficient with preset threshold value later
Risk evaluation result, for example, when the weighted euclidean distance be less than or equal to preset threshold value when, illustrate the user be high risk use
Family, to improve the accuracy of risk evaluation result.
In embodiments of the present invention, it when the request for receiving the driving behavior progress risk assessment to target user, adopts
Collect the running data that target user drives, the driving behavior data of target user is analyzed according to collected running data, to obtain
The driving behavior data for obtaining target user, are used according in the driving behavior data of the target user, the blacklist library pre-established
The driving behavior data and preset risk assessment algorithm at family carry out risk analysis to the driving behavior of target user, with
To the risk evaluation result of target user's driving behavior, so that the assessment of vehicle business risk for insurance is more perfect, more scientific,
And then improve the premium accuracy of vehicle.
Embodiment two：
Fig. 2 shows the structures of the risk assessment device of driving behavior provided by Embodiment 2 of the present invention, for the ease of saying
It is bright, illustrate only with the relevant part of the embodiment of the present invention, including：
Running data collecting unit 21, for when the request for receiving the driving behavior progress risk assessment to target user
When, the running data of acquisition target user's driving.
The embodiment of the present invention is suitable for computing device, for example, personal computer, smart mobile phone, tablet etc..Target user drives
The running data sailed include speed, total mileage, single stroke mileage number, stroke complete duration, stop frequency, parking duration,
Speed acceleration amplitude etc..Preferably, the running data driven to collected target user is handled, first, completion stroke
The previous stroke end of origin information, i.e., adjacent two data is latter start of a run, later, according to stroke mileage number or
Person is ranked up on the traveling date, such as how much mileage number carries out descending sort, later, when according to the end time of stroke and beginning
Between calculate stroke and complete duration, finally, filter out mileage number or stroke and complete the stroke that duration is equal to 0, and by the space of traveling
Longitude and latitude numerical value is converted to the coordinate of the point in plane right-angle coordinate, to purify running data so that subsequently uses target
The risk evaluation result of family driving behavior is more acurrate.
Behavioral data obtaining unit 22, the driving behavior for analyzing target user according to collected running data, with
Obtain the driving behavior data of target user.
In embodiments of the present invention, the driving behavior that target user is analyzed according to collected running data, as example
The driving behavior on ground, target user includes：Such as, if hypervelocity, whether fatigue driving, whether wide-angle deflecting, whether substantially
It whether excessively high spends acceleration or deceleration, acceleration and the conversion frequency of deceleration, is obtained according to the driving behavior of target user and drive row
For data, as illustratively, for example, hundred kilometers of anxious deceleration numbers, hundred kilometers of anxious acceleration times, velocity standard are poor, conversion driving
Duration, conversion mileage, hundred kilometers of zig zag numbers, fatigue driving number, night running duration, idling ratio, dwell times, roads
The strange degree in road, non-green go out line frequency and deduction of points violating the regulations.
Risk analysis unit 23, for being used according in the driving behavior data of target user, the blacklist library pre-established
The driving behavior data and preset risk assessment algorithm at family carry out risk analysis to the driving behavior of target user, with
To the risk evaluation result of target user's driving behavior.
In embodiments of the present invention, each unit of the risk assessment device of driving behavior can be by corresponding hardware or software list
Member realizes that each unit can be independent soft and hardware unit, can also be integrated into a soft and hardware unit, herein not limiting
The system present invention.
Embodiment three：
Fig. 3 shows the structure of the risk assessment device for the driving behavior that the embodiment of the present invention three provides, for the ease of saying
It is bright, illustrate only with the relevant part of the embodiment of the present invention, including：
Insurance data acquiring unit 31 is used for the insurance data of the driving vehicle according to acquisition, obtains going out for driving vehicle
Dangerous number and amount for which loss settled.
Unit 32 is established in blacklist library, for being more than preset when the number that is in danger reaches preset number or amount for which loss settled
When the amount of money, blacklist library is added in driving vehicle user, to establish blacklist library.
The embodiment of the present invention is suitable for computing device, for example, personal computer, smart mobile phone, tablet etc..Preferably, exist
It determines when blacklist library is added in driving vehicle user, by the driving behavior data of driving vehicle user, driving vehicle user
The basic attribute data of basic attribute data and driving vehicle is associated, so that subsequently to target user's driving behavior
Risk evaluation result it is more acurrate.
Running data collecting unit 33, for when the request for receiving the driving behavior progress risk assessment to target user
When, the running data of acquisition target user's driving.
In embodiments of the present invention, the running data that target user drives includes speed, total mileage, single stroke mileage
Number, stroke complete duration, stop frequency, parking duration, speed acceleration amplitude etc..Preferably, collected target user is driven
The running data sailed is handled, first, completion start of a run information, i.e., after the previous stroke end of adjacent two data is
One stroke starting point is ranked up, such as how much mileage number carries out descending row later according to the mileage number or traveling date of stroke
Sequence calculates stroke completion duration according to the end time of stroke and time started and finally filters out mileage number or stroke later
The stroke that duration is equal to 0 is completed, and the space longitude and latitude numerical value of traveling is converted to the coordinate of the point in plane right-angle coordinate,
To purify running data so that subsequently more acurrate to the risk evaluation result of target user's driving behavior.
Behavioral data obtaining unit 34, the driving behavior for analyzing target user according to collected running data, with
Obtain the driving behavior data of target user.
In embodiments of the present invention, the driving behavior that target user is analyzed according to collected running data, as example
The driving behavior on ground, target user includes：Such as, if hypervelocity, whether fatigue driving, whether wide-angle deflecting, whether substantially
It whether excessively high spends acceleration or deceleration, acceleration and the conversion frequency of deceleration, is obtained according to the driving behavior of target user and drive row
For data, as illustratively, for example, hundred kilometers of anxious deceleration numbers, hundred kilometers of anxious acceleration times, velocity standard are poor, conversion driving
Duration, conversion mileage, hundred kilometers of zig zag numbers, fatigue driving number, night running duration, idling ratio, dwell times, roads
The strange degree in road, non-green go out line frequency and deduction of points violating the regulations.
Risk analysis unit 35, for being used according in the driving behavior data of target user, the blacklist library pre-established
The driving behavior data and preset risk assessment algorithm at family carry out risk analysis to the driving behavior of target user, with
To the risk evaluation result of target user's driving behavior.
In embodiments of the present invention, it is used according in the driving behavior data of target user, the blacklist library pre-established
The driving behavior data and preset risk assessment algorithm at family, it is excellent when carrying out risk analysis to the driving behavior of target user
Selection of land calculates the weight coefficient of each dimension according to preset assessment dimension and preset weight calculation algorithm first, then,
It is calculated in target user and the blacklist library that pre-establishes and is used according to the weight coefficient being calculated and preset distance algorithm
The weighted euclidean distance is finally compared analysis, to obtain target user by the weighted euclidean distance at family with preset threshold value
The risk evaluation result of driving behavior, to improve the accuracy of target user's driving behavior risk evaluation result.
In embodiments of the present invention, specifically, first, maximum most using removal when calculating the weight coefficient of each dimension
User is in the index from people, from vehicle and from each dimension of driving behavior in the small method calculating blacklist library for calculating arithmetic mean later
The average of value and target user calculate each index value of user in blacklist later in the average of the index value of same dimension
Relative number with the variable quantity of each index value of target user compared with each index value of target user, finally, according to the relative number calculate from
People, the weight coefficient from vehicle and from each dimension of driving behavior.
In embodiments of the present invention, in calculating target user and the blacklist library that pre-establishes user weighted Euclidean away from
From when, it is preferable that first, the user for taking 10 distance objective users nearest in blacklist library is as neighbour user, later, root
Formula is normalized according to minimaxBy each dimension index value of neighbour user and target user's respective dimensions index
Value is normalized, wherein viIndicate i-th of original index value, v 'iThe index value after standardization is indicated, later, according to formulaThe weighted euclidean distance of neighbour user in target user and the blacklist library pre-established is calculated,
Wherein, (x1,x2,…,xn) and (y1,y2,…,yn) indicate i-th of dimension of user two point coordinates, ωiIndicate i-th dimension
The weighted euclidean distance is compared analysis, to obtain target user's driving behavior by weight coefficient with preset threshold value later
Risk evaluation result, for example, when the weighted euclidean distance be less than or equal to preset threshold value when, illustrate the user be high risk use
Family, to improve the accuracy of risk evaluation result.
It is therefore preferred that wherein, blacklist library establishes unit 32 and includes：
Parameter association unit 321 is used for the basic category of the driving behavior data of driving vehicle user, driving vehicle user
The basic attribute data of property data and driving vehicle is associated.
Risk analysis unit 35 includes：
Weight-coefficient calculating unit 351, for being calculated according to preset assessment dimension and preset weight calculation algorithm
The weight coefficient of each dimension；
Euclidean distance computing unit 352, for being calculated according to the weight coefficient and preset distance algorithm that are calculated
The weighted euclidean distance of target user and user in the blacklist library pre-established；And
Risk analysis subelement 353, for weighted euclidean distance to be compared analysis with preset threshold value, to obtain mesh
Mark the risk evaluation result of user's driving behavior.
In embodiments of the present invention, each unit of the risk assessment device of driving behavior can be by corresponding hardware or software list
Member realizes that each unit can be independent soft and hardware unit, can also be integrated into a soft and hardware unit, herein not limiting
The system present invention.
Example IV：
Fig. 4 shows the structure for the computing device that the embodiment of the present invention four provides, and for convenience of description, illustrates only and this
The relevant part of inventive embodiments.
The computing device 4 of the embodiment of the present invention includes processor 40, memory 41 and is stored in memory 41 and can
The computer program 42 run on processor 40.The processor 40 realizes above-mentioned each driving row when executing computer program 42
For methods of risk assessment embodiment in step, such as step S101 to S103 shown in FIG. 1.Alternatively, processor 40 executes
The function of each unit in above-mentioned each device embodiment, such as the function of unit 21 to 23 shown in Fig. 2 are realized when computer program 42.
In embodiments of the present invention, it when the request for receiving the driving behavior progress risk assessment to target user, adopts
Collect the running data that target user drives, the driving behavior of target user is analyzed according to collected running data, to obtain mesh
The driving behavior data for marking user are driven according to user in the driving behavior data of target user, the blacklist library pre-established
Behavioral data and preset risk assessment algorithm are sailed, risk analysis is carried out to the driving behavior of target user, to obtain target
The risk evaluation result of user's driving behavior, so that vehicle business risk for insurance assesses more perfect, more scientific, Jin Erti
The high premium accuracy of vehicle.
The computing device of the embodiment of the present invention can be personal computer, mobile phone and tablet.It is handled in the computing device 4
The step of being realized when the methods of risk assessment for realizing driving behavior when device 40 executes computer program 42 can refer to preceding method reality
The description of example is applied, details are not described herein.
Embodiment five：
In embodiments of the present invention, a kind of computer readable storage medium is provided, which deposits
Computer program is contained, which realizes that the methods of risk assessment of above-mentioned each driving behavior is real when being executed by processor
The step in example is applied, for example, step S101 to S103 shown in FIG. 1.Alternatively, the computer program is realized when being executed by processor
The function of each unit in above-mentioned each device embodiment, for example, unit 21 to 23 shown in Fig. 2 function.
In embodiments of the present invention, it when the request for receiving the driving behavior progress risk assessment to target user, adopts
Collect the running data that target user drives, the driving behavior of target user is analyzed according to collected running data, to obtain mesh
The driving behavior data for marking user are driven according to user in the driving behavior data of target user, the blacklist library pre-established
Behavioral data and preset risk assessment algorithm are sailed, risk analysis is carried out to the driving behavior of target user, to obtain target
The risk evaluation result of user's driving behavior, so that vehicle business risk for insurance assesses more perfect, more scientific, Jin Erti
The high premium accuracy of vehicle.
The computer readable storage medium of the embodiment of the present invention may include can carry computer program code any
Entity or device, recording medium, for example, the memories such as ROM/RAM, disk, CD, flash memory.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement etc., should all be included in the protection scope of the present invention made by within refreshing and principle.
Claims (10)
1. a kind of methods of risk assessment of driving behavior, which is characterized in that the method includes following step：
When the request for receiving the driving behavior progress risk assessment to target user, the row that the target user drives is acquired
Sail data；
The driving behavior that the target user is analyzed according to the collected running data, to obtain driving for the target user
Sail behavioral data；
According to the driving behavior data of user in the driving behavior data of the target user, the blacklist library pre-established and
Preset risk assessment algorithm carries out risk analysis to the driving behavior of the target user, is used with obtaining the target
The risk evaluation result of family driving behavior.
2. the method as described in claim 1, which is characterized in that the step of acquiring the running data that the target user drives it
Before, the method further includes：
According to the insurance data of the driving vehicle of acquisition, be in danger number and the amount for which loss settled of driving vehicle are obtained；
When the number that is in danger reaches preset number or the amount for which loss settled is more than the preset amount of money, by the Travel vehicle
The blacklist library is added in user, to establish the blacklist library.
3. method as claimed in claim 2, which is characterized in that when the number that is in danger reaches preset number or the reason
When paying for the amount of money more than the preset amount of money, further include by the step of driving vehicle user addition blacklist library：
By the driving behavior data of the driving vehicle user, the basic attribute data of the driving vehicle user and the row
The basic attribute data for sailing vehicle is associated.
4. the method as described in claim 1, which is characterized in that carry out risk point to the driving behavior of the target user
Analysis, to further include the step of obtaining the risk evaluation result of target user's driving behavior：
The weight coefficient of each dimension is calculated according to preset assessment dimension and preset weight calculation algorithm；
The target user is calculated according to the weight coefficient being calculated and preset distance algorithm to build in advance with described
The weighted euclidean distance of user in vertical blacklist library；
The weighted euclidean distance is compared analysis with preset threshold value, to obtain the wind of target user's driving behavior
Dangerous assessment result.
5. a kind of risk assessment device of driving behavior, which is characterized in that described device includes：
Running data collecting unit, for when receiving driving behavior to target user and carrying out the request of risk assessment, adopting
Collect the running data that the target user drives；
Behavioral data obtaining unit, the driving behavior for analyzing the target user according to the collected running data,
To obtain the driving behavior data of the target user；And
Risk analysis unit, for according to user in the driving behavior data of the target user, the blacklist library pre-established
Driving behavior data and preset risk assessment algorithm, risk point is carried out to the driving behavior of the target user
Analysis, to obtain the risk evaluation result of target user's driving behavior.
6. device as claimed in claim 5, which is characterized in that described device further includes：
Insurance data acquiring unit is used for the insurance data of the driving vehicle according to acquisition, obtains the number that is in danger of driving vehicle
And amount for which loss settled；And
Unit is established in blacklist library, for being more than default when the number that is in danger reaches preset number or the amount for which loss settled
The amount of money when, the blacklist library is added in the driving vehicle user, to establish the blacklist library.
7. device as claimed in claim 6, which is characterized in that the blacklist library establishes unit and includes：
Parameter association unit, for by the driving behavior data of the driving vehicle user, the driving vehicle user it is basic
The basic attribute data of attribute data and the driving vehicle is associated.
8. device as claimed in claim 5, which is characterized in that the risk analysis unit further includes：
Weight-coefficient calculating unit, for calculating each dimension according to preset assessment dimension and preset weight calculation algorithm
Weight coefficient；
Euclidean distance computing unit, described in being calculated according to the weight coefficient and preset distance algorithm that are calculated
The weighted euclidean distance of target user and user in the blacklist library pre-established；And
Risk analysis subelement, it is described to obtain for the weighted euclidean distance to be compared analysis with preset threshold value
The risk evaluation result of target user's driving behavior.
9. a kind of computing device, including memory, processor and it is stored in the memory and can be on the processor
The computer program of operation, which is characterized in that the processor realizes such as Claims 1-4 when executing the computer program
The step of any one the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, feature to exist
In when the computer program is executed by processor the step of any one of such as Claims 1-4 of realization the method.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN109447127A (en) * | 2018-09-29 | 2019-03-08 | 深圳市元征科技股份有限公司 | Data processing method and device |
| CN111249691A (en) * | 2018-11-30 | 2020-06-09 | 百度在线网络技术（北京）有限公司 | Athlete training method and system based on body shape recognition |
| CN109800984A (en) * | 2019-01-16 | 2019-05-24 | 平安科技（深圳）有限公司 | Driving ability appraisal procedure, device, computer equipment and storage medium |
| CN109800984B (en) * | 2019-01-16 | 2024-03-01 | 平安科技（深圳）有限公司 | Driving level evaluation method, driving level evaluation device, computer device, and storage medium |
| CN109885033A (en) * | 2019-03-18 | 2019-06-14 | 百度在线网络技术（北京）有限公司 | The method and device of safe processing of vehicle control instruction |
| CN110163762A (en) * | 2019-04-15 | 2019-08-23 | 深圳壹账通智能科技有限公司 | Vehicle insurance premium method of adjustment, device, computer equipment and storage medium |
| CN110334696A (en) * | 2019-07-31 | 2019-10-15 | 爱驰汽车有限公司 | Cockpit pseudo-experience system, method, equipment and storage medium |
| CN110968839A (en) * | 2019-12-05 | 2020-04-07 | 深圳鼎然信息科技有限公司 | Driving risk assessment method, device, equipment and storage medium |
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| CN112183984A (en) * | 2020-09-21 | 2021-01-05 | 长城汽车股份有限公司 | Driving behavior processing method and device, storage medium and electronic equipment |
| CN112288334A (en) * | 2020-11-27 | 2021-01-29 | 上海评驾科技有限公司 | Lightgbm-based car networking risk factor extraction method |
| CN112288334B (en) * | 2020-11-27 | 2024-04-16 | 上海评驾科技有限公司 | Method for extracting Internet of vehicles risk factors based on lightgbm |
| CN112597835A (en) * | 2020-12-11 | 2021-04-02 | 国汽(北京)智能网联汽车研究院有限公司 | Driving behavior evaluation method and device, electronic equipment and readable storage medium |
| CN113255815A (en) * | 2021-06-10 | 2021-08-13 | 平安科技（深圳）有限公司 | User behavior abnormity analysis method, device, equipment and storage medium |
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