CN106126960A - Driving safety appraisal procedure and device - Google Patents
Driving safety appraisal procedure and device Download PDFInfo
- Publication number
- CN106126960A CN106126960A CN201610586266.8A CN201610586266A CN106126960A CN 106126960 A CN106126960 A CN 106126960A CN 201610586266 A CN201610586266 A CN 201610586266A CN 106126960 A CN106126960 A CN 106126960A
- Authority
- CN
- China
- Prior art keywords
- driving
- data
- driver
- current
- score
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Abstract
The application proposes a kind of driving safety appraisal procedure and device, and wherein, driving safety appraisal procedure includes: obtaining the personal information data that driver is up-to-date, described personal information data include: master data, health data, mood data and driving data；The current driving risk score of described driver and driving style is determined according to described master data, health data, mood data and driving data；According to described current driving risk score and driving style, determine the driving safety grade that described driver is current.The driving safety appraisal procedure provided by the application and device, achieve the various personal information according to driver, the driving safety that driver is current is carried out reliable assessment, make assessment result more accurate, thus the safe driving for driver provides reference and guidance, can effectively improve traffic safety.
Description
Technical field
The application relates to technical field of transportation, particularly relates to a kind of driving safety appraisal procedure and device.
Background technology
Along with expanding economy and society progress, vehicle population is also gradually being incremented by, synchronize be incremented by also include
The Subhealthy Status of people.
Generally, the personal health of driver not only relation individual and family's wellbeing, affect social public security equally.
In actual driving procedure, the driving technology of driver and health, mental status have great impact to driving safety.Cause
How this according to the individual factors of driver, carry out accurate evaluation to drive safety, it has also become the focus of current research.
Summary of the invention
One of technical problem that the application is intended to solve in correlation technique the most to a certain extent.
To this end, the first of the application purpose is to propose a kind of driving safety appraisal procedure, the method achieve basis
The various personal information of driver, carry out reliable assessment to the driving safety that driver is current so that assessment result is more accurate, from
And be that the safe driving of driver provides reference and guidance, can effectively improve traffic safety.
Second purpose of the application is to propose a kind of driving safety apparatus for evaluating.
For reaching above-mentioned purpose, the application first aspect embodiment proposes a kind of driving safety appraisal procedure, including:
Obtaining the up-to-date personal information data of driver, described personal information data include: master data, health data,
Mood data and driving data；
The driving that described driver is current is determined according to described master data, health data, mood data and driving data
Risk score and driving style；
According to described current driving risk score and driving style, determine the driving safety etc. that described driver is current
Level.
The driving safety appraisal procedure of the embodiment of the present application, first obtains the personal information data that driver is up-to-date, described
Personal information data include: master data, health data, mood data and driving data；Then according to described master data, it is good for
Health data, mood data and driving data determine the current driving risk score of described driver and driving style；Further according to institute
State current driving risk score and driving style, determine the driving safety grade that described driver is current.Hereby it is achieved that root
According to the various personal information of driver, the driving safety that driver is current is carried out reliable assessment so that assessment result is more accurate,
Thus the safe driving for driver provides reference and guidance, can effectively improve traffic safety.
For reaching above-mentioned purpose, the application second aspect embodiment proposes a kind of driving safety apparatus for evaluating, including:
Acquisition module, for obtaining the personal information data that driver is up-to-date, described personal information data include: basic number
According to, health data, mood data and driving data；
First determines module, described for determining according to described master data, health data, mood data and driving data
Driving risk score that driver is current and driving style；
Second determines module, for according to described current driving risk score and driving style, determines described driver
Current driving safety grade.
The driving safety apparatus for evaluating of the embodiment of the present application, first obtains the personal information data that driver is up-to-date, described
Personal information data include: master data, health data, mood data and driving data；Then according to described master data, it is good for
Health data, mood data and driving data determine the current driving risk score of described driver and driving style；Further according to institute
State current driving risk score and driving style, determine the driving safety grade that described driver is current.Hereby it is achieved that root
According to the various personal information of driver, the driving safety that driver is current is carried out reliable assessment so that assessment result is more accurate,
Thus the safe driving for driver provides reference and guidance, can effectively improve traffic safety.
Accompanying drawing explanation
The present invention above-mentioned and/or that add aspect and advantage will become from the following description of the accompanying drawings of embodiments
Substantially with easy to understand, wherein:
Fig. 1 is the flow chart of the driving safety appraisal procedure of one embodiment of the application；
Fig. 2 is the flow chart of the driving safety appraisal procedure of another embodiment of the application；
Fig. 3 is the structural representation of the driving safety apparatus for evaluating of one embodiment of the application；
Fig. 4 is the structural representation of the driving safety apparatus for evaluating of another embodiment of the application.
Detailed description of the invention
Embodiments herein is described below in detail, and the example of described embodiment is shown in the drawings, the most from start to finish
Same or similar label represents same or similar element or has the element of same or like function.Below with reference to attached
The embodiment that figure describes is exemplary, it is intended to be used for explaining the application, and it is not intended that restriction to the application.
Below with reference to the accompanying drawings driving safety appraisal procedure and the device of the embodiment of the present application are described.
Fig. 1 is the flow chart of the driving safety appraisal procedure of one embodiment of the application.
As it is shown in figure 1, this driving safety appraisal procedure includes:
Step 101, obtains the up-to-date personal information data of driver, and described personal information data include: master data, strong
Health data, mood data and driving data.
Concrete, the executive agent of the driving safety appraisal procedure that the embodiment of the present application provides is driving safety assessment dress
Putting, this device can be configured in and any or can be set directly at the control system of vehicle with the terminal unit of vehicle communication
In system.
Wherein, master data specifically includes that the sex of driver, age, height, body weight, vision etc.；Health data is main
Including: blood pressure, blood glucose, recent disease condition, taking medicine situation in the recent period, wherein, the time that " in the recent period " is corresponding can be selected as required
Select, such as select one week, 10 days, two weeks or one month etc.；Mood data is mainly used in characterizing the emotional state of driver, than
Such as anxiety, indignation, depression, energy, fatigue, flurried etc.；Driving data specifically includes that driving age, driving range etc., wherein, drives
Mileage can be the driving range that driver is total, it is also possible to refer to the driving range of driver's every day, and this is not limited by the present embodiment
Fixed.
It addition, in driving data, it is also possible to include that driver violation travels or the number of times of vehicle accident occurs, such as drive
The number of times etc. that the number of times that makes a dash across the red light of member, driver drive over the speed limit.
Specifically, driving safety apparatus for evaluating, the personal information data of driver can be obtained in several ways.I.e.
Above-mentioned steps 101, including: at least one side in manually typing, Internet of Things collection, application tracking or the collection of vehicle net
Formula, obtains the personal information data that driver is up-to-date, so that the personal information of the driver obtained is more comprehensively so that according to
Result after driver is analyzed by the information obtained is more accurate.
For example, the driving age of driver, total driving range, the driving range of average every day can be obtained by vehicle net
Deng driving data；Or by Internet of Things, obtain the medical information that driver is nearest, the blood pressure of such as driver, blood glucose, recently
The health datas such as ill information, nearest a week, 10 days or 1 month interior medicining condition that a week, 10 days or 1 month are interior；
By driver's actively typing or be tracked by the application that driver is used, the acquisition sex of driver, the age, height,
The master data such as body weight, vision；By the emotion questionnaire survey that driver is participated in or test etc., obtain the emotion of driver
Data, such as driver are the most nervous, angry, depressed, tired or flurried.
According to described master data, health data, mood data and driving data, step 102, determines that described driver works as
Front driving risk score and driving style.
In actual driving procedure, the age of driver, sex, blood pressure, the most ill, emotion and driving age etc. all can affect
The safety driven, therefore, in the embodiment of the present application, according to master data, health data, mood data and the driving of driver
Data determine the driving situation that driver is current.
Concrete, can determine that the current driving risk of described driver obtains according to C=l × B+m × H+n × P+k × D
Point.
Wherein, C is for driving risk score, and B is the score value that master data is corresponding, and H is the score value that health data is corresponding, and P is
The score value that mood data is corresponding, D is the score value that driving data is corresponding, and l, m, n, k are respectively proportionality constant.
It should be noted that owing to every kind of data include many index, the score value of such data is affected by each index
Difference, the score value that therefore each data are corresponding, the size of each index that needs include according to such data and the power of correspondence
Heavily determine.
For example, the score value B that master data is corresponding, can be determined by following formula:
B=a1×b1+a2×b2+……+an×bn
Wherein, aiRepresent i-th index b in master data indexiWeight coefficient, each weight coefficient can be 0 to 1
Between value, and according to biThe size that affects of driving safety is determined, for example, for this index of age, age value is too
Little or too big, all may can affect the safety of driving, the most different age value then can corresponding different value；And for
For sex, then can be the corresponding different weight coefficient of different sexes, and for this index of sex, can arrange
The b that different sexes is corresponding varies in size, if being the 1st index than sex, when sex is female, and b1=4,5,6 or 7 etc.,
When sex is man, b1=5,6,7 or 8 etc., this is not construed as limiting by the present embodiment.
Such as, if weight coefficient corresponding to sex is 0.3, weight coefficient corresponding to age is 0.5, the weight that height is corresponding
The weight coefficient that coefficient is 0.1, body weight is corresponding is 0.2, and weight coefficient corresponding to vision is 0.7, and driver's age is at 18-40
During year, corresponding b value is 10, driver's age 16-18 year time, the b value of correspondence is 8, driver's age 41-50 year time,
Corresponding b value is 7, driver's age 50-55 year time, the b value of correspondence is 6；When driver's sex is female, corresponding b value is
4, when driver's sex is man, corresponding b value is 6；When driver's height is less than 1.5 meters, corresponding b value is 4, driver's height
During higher than 1.5 meters and less than 1.6 meters, corresponding b value is 6, when driver's height is higher than 1.6 meters and less than 1.7 meters, and the b of correspondence
Value is 7, and when driver's height is higher than 1.7 meters and less than 1.8 meters, corresponding b value is 7；Driver's body weight is less than 50 kilograms (Kg)
Time, corresponding b value is 4, and driver's body weight is higher than 50 kilograms (Kg), and during less than 75kg, corresponding b value is 7；Driver sight is just
Chang Shi, corresponding b value is 9, and when driver sight is between 1.2-1.5, corresponding b value is 7, and driver sight is at 1.0-1.2
Between time, corresponding b value is 6, and when driver sight is less than 1.0, the b value of correspondence is 4.
So include in the master data receiving a driver: 36 years old, male, body weight 70kg, height 1.75m, vision 1.2
Time, can determine that the master data of this driver is divided into according to above-mentioned formula:
B=0.5 × 10+0.3 × 6+0.2 × 7+0.1 × 7+0.7 × 7=13.8
The score value that other class data are corresponding, it would however also be possible to employ the mode that the score value corresponding with above-mentioned master data is similar is true
Fixed.
It should be noted that can be to drive risk score to divide different intervals, corresponding different driving condition be interval,
Such as, driving risk score in 81 points～100 timesharing, expression driving condition interval is: suitably drive；Drive risk score 61
Divide～80 timesharing, represent that driving condition interval is: need to improve；Drive risk score and drive shape in 31 points～60 timesharing, expression
State interval is: dangerous driving；Driving risk score in 0 point～30 timesharing, expression driving condition interval is: be not suitable for driving etc..
It addition, driving style can determine in the following manner:
Obtain the set of N group proportionality constant corresponding to the N kind driving style preset；
According to Si=ji×B+fi×P+ti× D, determines under N kind driving style successively, current N number of of described driver
Point, wherein, SiBeing the score of i-th kind of driving style, B is the score value that master data is corresponding, and P is the score value that mood data is corresponding, D
For the score value that driving data is corresponding, ji、fi、tiBeing respectively the element in i-th group of proportionality constant set, i is more than or equal to 1 and little
In the integer equal to N；
According under described N kind driving style, the score that described driver is current, determine the driving that described driver is current
Style.
Wherein, driving style specifically includes that risk taking type, indignation, anxiety type, safe type etc., to every kind of driving style
For, the factor affecting it is different, and every kind of factor on such style to affect size the most different, therefore in the present embodiment, can
Affect coefficient with pre-set that various factors drives wind to every kind, i.e. pre-set the ratio that various driving style is respectively corresponding
Constant set, thus use different proportionality constant set, i.e. can determine that the score of driver's difference driving style.
For example, the set of the proportionality constant that risk taking type driving style is corresponding can be 0.6,0.5,0.4}, indignation type
The set of the proportionality constant that driving style is corresponding can be 0.6,0.7,0.2}, proportionality constant that safe type driving style is corresponding
Set can be 0.6,0.3,0.7} etc., thus determining score value B corresponding to the current master data of driver, emotion
After score value P that data are corresponding and score value D corresponding to driving data, the collection of the proportionality constant that the various driving style of reselection is corresponding
Close, i.e. can get under various driving style, the score of driver.
In addition, it is necessary to explanation, the different indexs in mood data, may be relatively big on different driving style impacts,
Such as, for risk taking type driving style, the driving style of the type is affected by " energy " index in its emotion may be relatively
Greatly, thus during emotion score in determining risk taking type driving style, can be the weight coefficient that " energy " Distribution Indexes is bigger,
And for indignation type driving style, the driving style of the type is affected by " angry " index in its emotion may be relatively big,
Thus determine indignation type driving style in emotion score time, can be the weight coefficient that " angry " Distribution Indexes is bigger.I.e.
For different driving styles, the score of mood data therein can use different proportionality constants to obtain.
By above-mentioned analysis, when determining the score driven under risk score and each driving style of driver, can
Think different data targets, distribute different proportionality constants, not only make the angle diversification to driver evaluation, Er Qiegen
The size affected driver according to all angles, uses different coefficients to be estimated driver, further increases and comment
Estimate accuracy and the reliability of result.
Further, after the score determining all kinds of driving style, can determine drive according to the score of all kinds of driving styles
The driving style that the person of sailing currently is partial to.Such as, by under described N kind driving style, the highest in the score that described driver is current
Divide corresponding driving style, be defined as the driving style that described driver is current.
For example, if being determined by calculating, the current angry type driving style of driver must be divided into 60 points, and risk taking type is driven
Sailing lattice must be divided into 40 points, and anxiety type driving style must be divided into 50 points, and safe type driving style must be divided into 20 points, then may determine that
The driving style of highest scoring is the driving style that driver is current.Due to the driving style of highest scoring, driving more can be reflected
The state that member is currently most inclined to, so that the assessment to driver is more accurate.
Step 103, according to described current driving risk score and driving style, determines the driving that described driver is current
Safe class.
Concrete, driving safety apparatus for evaluating can shift to an earlier date preset driving risk score and driving style and driving safety
The mapping relations of grade, afterwards, after determining current driving risk score and driving style, can be preset by inquiry
Mapping relations, i.e. can determine that current driving safety grade, and then the safe driving for driver provides guidance.
For example, drive risk score and be 81 points～100 points and time driving style is safe type, corresponding driving peace
Congruence level is safety；Drive risk score and be 81 points～100 points and time driving style is anxiety type, corresponding driving safety etc.
Level is Generally Recognized as safe；Drive risk score and be 61 points～80 points and time driving style is anxiety type, corresponding driving safety grade
For there being certain potential safety hazard；Drive risk score and be 61 points～80 points and time driving style is risk taking type, corresponding driving safety
Grade is dangerous；Drive risk score and be 31 points～60 points and time driving style is risk taking type, corresponding driving safety grade
For the most dangerous；Drive risk score be 31 points～60 points and driving style for indignation type time, corresponding driving safety grade
For danger etc..If so driving safety apparatus for evaluating is according to the personal information of driver, determine the driving risk score of driver
It is 61 points～80 points and time driving style is anxiety type, the mapping relations can preset by inquiry, determine that this driver is current
Driving safety grade for there being certain potential safety hazard.And then certain driving safety Improving advice can be provided the user.
The driving safety appraisal procedure of the embodiment of the present application, first obtains the personal information data that driver is up-to-date, described
Personal information data include: master data, health data, mood data and driving data；Then according to described master data, it is good for
Health data, mood data and driving data determine the current driving risk score of described driver and driving style；Further according to institute
State current driving risk score and driving style, determine the driving safety grade that described driver is current.Hereby it is achieved that root
According to the various personal information of driver, the driving safety that driver is current is carried out reliable assessment so that assessment result is more accurate,
Thus the safe driving for driver provides reference and guidance, can effectively improve traffic safety.
Fig. 2 is the flow chart of the driving safety appraisal procedure of another embodiment of the application.
As in figure 2 it is shown, this driving safety appraisal procedure may comprise steps of:
Step 201, at least one side in manually typing, Internet of Things collection, application tracking or the collection of vehicle net
Formula, obtains the personal information data that driver is up-to-date.
Step 202, according to C=l × B+m × H+n × P+k × D, determines the driving risk score that described driver is current.
Wherein, C is for driving risk score, and B is the score value that master data is corresponding, and H is the score value that health data is corresponding, and P is
The score value that mood data is corresponding, D is the score value that driving data is corresponding, and l, m, n, k are respectively proportionality constant.
Step 203, obtains the set of N group proportionality constant corresponding to the N kind driving style preset.
Step 204, according to Si=ji×B+fi×P+ti× D, determines under N kind driving style, the N of described driver successively
Individual score.
Wherein, SiBeing the score of i-th kind of driving style, B is the score value that master data is corresponding, and P is that mood data is corresponding
Score value, D is the score value that driving data is corresponding, ji、fi、tiBeing the element in i-th group of proportionality constant set, i is more than or equal to 1, and
Integer less than or equal to N；
Step 205, by under described N kind driving style, the driving that in the score that described driver is current, top score is corresponding
Style, is defined as the driving style that described driver is current.
Step 206, according to described current driving risk score and driving style, determines the driving that described driver is current
Safe class.
Step 207, according to default rule, sends and described current driving risk score and driving style to driver
Corresponding assisting automobile driver message.
Concrete, in driving safety apparatus for evaluating, preset assisting automobile driver message can be shifted to an earlier date and drive risk score and drive
The mapping relations of sailing lattice, thus in the personal information according to driver, after determining the driving safety grade that driver is current, i.e.
Different reminder message can be pushed for driver according to the current driving safety grade of driver.
For example, however, it is determined that the driving style of driver is " depressive type ", and according to driving risk score risk is determined
Relatively big, then can remind driver in the recent period it is noted that loosen, do more physical exercises, participate in friend's party or many viewing comedy routine etc.,
Suitably regulate mood；Or, however, it is determined that the driving style of driver is " risk taking type ", then driver can be reminded to increase and family
The time etc. that people gets along.
It should be noted that driving safety apparatus for evaluating can also be according to the sex of driver, age, driving age, BMI index
(body weight (kg) ÷ height ^2 (m)) difference, pushes different points for attention for driver, such as, determines that driver has trouble in the recent period
Sick or MAR, then can be that driver pushes points for attention during ill, medication；Or determine driver's recent emotion number
According to poor, then can be that driver pushes negative emotions Improving advice；Or, determine that driver style is problematic, then may be used
Think that driver pushes driving Improving advice etc..
The driving safety appraisal procedure of the embodiment of the present application, first pass through be manually entered, Internet of Things collection, application follow the trail of or
At least one mode in the collection of person's vehicle net, obtains the personal information data that driver is up-to-date, described personal information packet
Include: master data, health data, mood data and driving data；Then according to the computing mode preset, according to described basic number
According to, health data, mood data and driving data determine the current driving risk score of described driver and driving style respectively；
Further according to described current driving risk score and driving style, determine the driving safety grade that described driver is current, then
Assisting automobile driver message is sent to driver.Thus, obtain the personal information of driver in several ways, and according to driver's
Various personal information, use different angle, the driving safety that driver is current are carried out reliable assessment so that assessment result is more
Accurately, thus provide reference and guidance for the safe driving of driver, can effectively improve traffic safety.
In order to realize above-described embodiment, the application also proposes a kind of driving safety apparatus for evaluating.
Fig. 3 is the structural representation of the driving safety apparatus for evaluating of one embodiment of the application.
As it is shown on figure 3, this driving safety apparatus for evaluating, including:
Acquisition module 31, for obtaining the personal information data that driver is up-to-date, described personal information data include: basic
Data, health data, mood data and driving data；
First determines module 32, for determining institute according to described master data, health data, mood data and driving data
State the current driving risk score of driver and driving style；
Second determines module 33, for according to described current driving risk score and driving style, determines described driving
The driving safety grade that member is current.
Concrete, the driving safety apparatus for evaluating of the embodiment of the present application offer, for performing driving of above-described embodiment offer
Sail safety evaluation method.
Wherein, described acquisition module 31, specifically for:
At least one mode in manually typing, Internet of Things collection, application tracking or the collection of vehicle net, acquisition is driven
The personal information data that the person of sailing is up-to-date.
Further, described first determines module 32, specifically for:
According to C=l × B+m × H+n × P+k × D, determine the driving risk score that described driver is current；
Wherein, C is for driving risk score, and B is the score value that master data is corresponding, and H is the score value that health data is corresponding, and P is
The score value that mood data is corresponding, D is the score value that driving data is corresponding, and l, m, n, k are respectively proportionality constant.
In a kind of possible way of realization of the present embodiment, described first determines module 32, also particularly useful for:
Obtain the set of N group proportionality constant corresponding to the N kind driving style preset；
According to Si=ji×B+fi×P+ti× D, determines under N kind driving style successively, N number of score of described driver, its
In, SiBeing the score of i-th kind of driving style, B is the score value that master data is corresponding, and P is the score value that mood data is corresponding, and D is for driving
Sail the score value that data are corresponding, ji、fi、tiBeing respectively the element in i-th group of proportionality constant set, i is more than or equal to 1, and is less than
Integer in N；
According to the score of the current various driving styles of described driver, determine the driving style that described driver is current.
Further, above-mentioned first determines module, specifically for:
By under described N kind driving style, the driving style that in the score that described driver is current, top score is corresponding, determine
For the driving style that described driver is current.
It should be noted that the explanation of the driving safety appraisal procedure of above-described embodiment offer, it is also applied for this embodiment
The driving safety apparatus for evaluating provided, here is omitted.
The driving safety apparatus for evaluating of the embodiment of the present application, first obtains the personal information data that driver is up-to-date, described
Personal information data include: master data, health data, mood data and driving data；Then according to described master data, it is good for
Health data, mood data and driving data determine the current driving risk score of described driver and driving style；Further according to institute
State current driving risk score and driving style, determine the driving safety grade that described driver is current.Hereby it is achieved that root
According to the various personal information of driver, the driving safety that driver is current is carried out reliable assessment so that assessment result is more accurate,
Thus the safe driving for driver provides reference and guidance, can effectively improve traffic safety.
Fig. 4 is the structure chart of the driving safety apparatus for evaluating of another embodiment of the application.
As shown in Figure 4, on the basis of shown in above-mentioned Fig. 3, this driving safety apparatus for evaluating, also include:
Sending module 41, for according to preset rule, to driver send with described current driving risk score and
The assisting automobile driver message that driving style is corresponding.
Concrete, in driving safety apparatus for evaluating, preset assisting automobile driver message can be shifted to an earlier date and drive risk score and drive
The mapping relations of sailing lattice, thus in the personal information according to driver, after determining the driving safety grade that driver is current, i.e.
Different reminder message can be pushed for driver according to the current driving safety grade of driver.
For example, however, it is determined that the driving style of driver is " depressive type ", and according to driving risk score risk is determined
Relatively big, then can remind driver in the recent period it is noted that loosen, do more physical exercises, participate in friend's party or many viewing comedy routine etc.,
Suitably regulate mood；Or, however, it is determined that the driving style of driver is " risk taking type ", then driver can be reminded to increase and family
The time etc. that people gets along.
It should be noted that driving safety apparatus for evaluating can also be according to the sex of driver, age, driving age, BMI index
(body weight (kg) ÷ height ^2 (m)) difference, pushes different points for attention for driver, such as, determines that driver has trouble in the recent period
Sick or MAR, then can be that driver pushes points for attention during ill, medication；Or determine driver's recent emotion number
According to poor, then can be that driver pushes negative emotions Improving advice；Or, determine that driver style is problematic, then may be used
Think that driver pushes driving Improving advice etc..
The driving safety appraisal procedure of the embodiment of the present application, first pass through be manually entered, Internet of Things collection, application follow the trail of or
At least one mode in the collection of person's vehicle net, obtains the personal information data that driver is up-to-date, described personal information packet
Include: master data, health data, mood data and driving data；Then according to the computing mode preset, according to described basic number
According to, health data, mood data and driving data determine the current driving risk score of described driver and driving style respectively；
Further according to described current driving risk score and driving style, determine the driving safety grade that described driver is current, then
Assisting automobile driver message is sent to driver.Thus, obtain the personal information of driver in several ways, and according to driver's
Various personal information, use different angles, the driving safety that driver is current are carried out reliable assessment so that assessment result is more accurate
Really, thus provide reference and guidance for the safe driving of driver, can effectively improve traffic safety.
In the description of this specification, reference term " embodiment ", " some embodiments ", " example ", " specifically show
Example " or the description of " some examples " etc. means to combine this embodiment or example describes specific features, structure, material or spy
Point is contained at least one embodiment or the example of the application.Additionally, term " first ", " second " are only used for describing purpose,
And it is not intended that indicate or imply relative importance or the implicit quantity indicating indicated technical characteristic.
Should be appreciated that each several part of the application can realize by hardware, software, firmware or combinations thereof.Above-mentioned
In embodiment, the software that multiple steps or method in memory and can be performed by suitable instruction execution system with storage
Or firmware realizes.Such as, if realized with hardware, with the most the same, available well known in the art under
Any one or their combination in row technology realize: have the logic gates for data signal realizes logic function
Discrete logic, there is the special IC of suitable combination logic gate circuit, programmable gate array (PGA), on-the-spot
Programmable gate array (FPGA) etc..
Those skilled in the art are appreciated that and realize all or part of step that above-described embodiment method is carried
Suddenly the program that can be by completes to instruct relevant hardware, and described program can be stored in a kind of computer-readable storage medium
In matter, this program upon execution, including one or a combination set of the step of embodiment of the method.
Storage medium mentioned above can be read only memory, disk or CD etc..Although having shown that above and retouching
State embodiments herein, it is to be understood that above-described embodiment is exemplary, it is impossible to be interpreted as the limit to the application
System, above-described embodiment can be changed, revise, replace and become in scope of the present application by those of ordinary skill in the art
Type.
Claims (12)
1. a driving safety appraisal procedure, it is characterised in that comprise the following steps:
Obtaining the personal information data that driver is up-to-date, described personal information data include: master data, health data, emotion
Data and driving data；
The driving risk that described driver is current is determined according to described master data, health data, mood data and driving data
Score and driving style；
According to described current driving risk score and driving style, determine the driving safety grade that described driver is current.
2. the method for claim 1, it is characterised in that described according to described master data, health data, mood data
And driving data determines the driving risk score that described driver is current, including:
According to C=l × B+m × H+n × P+k × D, determine the driving risk score that described driver is current；
Wherein, C is for driving risk score, and B is the score value that master data is corresponding, and H is the score value that health data is corresponding, and P is emotion
The score value that data are corresponding, D is the score value that driving data is corresponding, and l, m, n, k are respectively proportionality constant.
3. the method for claim 1, it is characterised in that described according to described master data, health data, mood data
And driving data determines the driving style that described driver is current, including:
Obtain the set of N group proportionality constant corresponding to the N kind driving style preset；
According to Si=ji×B+fi×P+ti× D, determines under N kind driving style successively, N number of score that described driver is current, its
In, SiBeing the score of i-th kind of driving style, B is the score value that master data is corresponding, and P is the score value that mood data is corresponding, and D is for driving
Sail the score value that data are corresponding, ji、fi、tiBeing the element in i-th group of proportionality constant set, i is more than or equal to 1, and less than or equal to N
Integer；
According under described N kind driving style, the score that described driver is current, determine the driving style that described driver is current.
4. method as claimed in claim 3, it is characterised in that described according under described N kind driving style, described driver works as
Front score, determines the driving style that described driver is current, including:
By under described N kind driving style, the driving style that in the score that described driver is current, top score is corresponding, it is defined as institute
State the driving style that driver is current.
5. the method as described in claim 1-4 is arbitrary, it is characterised in that described according to described current driving risk score and
Driving style, after determining the driving safety grade that described driver is current, also includes:
According to default rule, send the driving corresponding with described current driving risk score and driving style to driver and carry
Awake message.
6. the method as described in claim 1-4 is arbitrary, it is characterised in that the personal information number that described acquisition driver is up-to-date
According to, including:
At least one mode in manually typing, Internet of Things collection, application tracking or the collection of vehicle net, obtains driver
Up-to-date personal information data.
7. a driving safety apparatus for evaluating, it is characterised in that including:
Acquisition module, for obtaining the personal information data that driver is up-to-date, described personal information data include: master data,
Health data, mood data and driving data；
First determines module, for determining described driving according to described master data, health data, mood data and driving data
The current driving risk score of member and driving style；
Second determines module, for according to described current driving risk score and driving style, determines that described driver is current
Driving safety grade.
8. device as claimed in claim 7, it is characterised in that described first determines module, specifically for:
According to C=l × B+m × H+n × P+k × D, determine the driving risk score that described driver is current；
Wherein, C is for driving risk score, and B is the score value that master data is corresponding, and H is the score value that health data is corresponding, and P is emotion
The score value that data are corresponding, D is the score value that driving data is corresponding, and l, m, n, k are respectively proportionality constant.
9. device as claimed in claim 7, it is characterised in that described first determines module, specifically for:
Obtain the set of N group proportionality constant corresponding to the N kind driving style preset；
According to Si=ji×B+fi×P+ti× D, determines under N kind driving style successively, N number of score that described driver is current, its
In, SiBeing the score of i-th kind of driving style, B is the score value that master data is corresponding, and P is the score value that mood data is corresponding, and D is for driving
Sail the score value that data are corresponding, ji、fi、tiBeing respectively the element in i-th group of proportionality constant set, i is more than or equal to 1, and is less than
Integer in N；
According under described N kind driving style, the score that described driver is current, determine the driving style that described driver is current.
10. method as claimed in claim 9, it is characterised in that described first determines module, specifically for:
By under described N kind driving style, the driving style that in the score that described driver is current, top score is corresponding, it is defined as institute
State the driving style that driver is current.
11. devices as described in claim 7-10 is arbitrary, it is characterised in that also include:
Sending module, is used for, according to the rule preset, sending and described current driving risk score and driving wind to driver
The assisting automobile driver message that lattice are corresponding.
12. devices as described in claim 7-10 is arbitrary, it is characterised in that described acquisition module, specifically for:
At least one mode in manually typing, Internet of Things collection, application tracking or the collection of vehicle net, obtains driver
Up-to-date personal information data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610586266.8A CN106126960A (en) | 2016-07-25 | 2016-07-25 | Driving safety appraisal procedure and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610586266.8A CN106126960A (en) | 2016-07-25 | 2016-07-25 | Driving safety appraisal procedure and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106126960A true CN106126960A (en) | 2016-11-16 |
Family
ID=57289394
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610586266.8A Pending CN106126960A (en) | 2016-07-25 | 2016-07-25 | Driving safety appraisal procedure and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106126960A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106530712A (en) * | 2016-12-16 | 2017-03-22 | 上海斐讯数据通信技术有限公司 | Big data-based system and method for pre-estimation of traffic casualty accident rates |
| CN106651162A (en) * | 2016-12-09 | 2017-05-10 | 思建科技有限公司 | Big data-based driving risk assessment method |
| CN106952002A (en) * | 2017-04-05 | 2017-07-14 | 南京人人保网络技术有限公司 | Driving methods of risk assessment and device based on driving behavior |
| CN109784188A (en) * | 2018-12-18 | 2019-05-21 | 深圳壹账通智能科技有限公司 | Driving fatigue degree evaluation method, device, computer equipment and storage medium |
| WO2019137373A1 (en) * | 2018-01-10 | 2019-07-18 | 华为技术有限公司 | Method and device for acquiring automatic driving track |
| CN110816542A (en) * | 2018-07-23 | 2020-02-21 | 罗伯特·博世有限公司 | Method for providing driver assistance |
| CN110875937A (en) * | 2018-08-31 | 2020-03-10 | 北京嘀嘀无限科技发展有限公司 | Information pushing method and system |
| WO2020108219A1 (en) * | 2018-11-30 | 2020-06-04 | 江苏智通交通科技有限公司 | Traffic safety risk based group division and difference analysis method and system |
| CN113222458A (en) * | 2021-05-31 | 2021-08-06 | 上海工程技术大学 | Urban rail transit driver safety risk assessment model and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1873722A (en) * | 2006-04-07 | 2006-12-06 | 中山大学 | Safety caution system for driving automobile |
| CN101030316A (en) * | 2007-04-17 | 2007-09-05 | 北京中星微电子有限公司 | Safety driving monitoring system and method for vehicle |
| CN101236695A (en) * | 2008-03-05 | 2008-08-06 | 中科院嘉兴中心微系统所分中心 | Driver status estimation system based on vehicle mounted sensor network |
| CN101593425A (en) * | 2009-05-06 | 2009-12-02 | 深圳市汉华安道科技有限责任公司 | A kind of fatigue driving monitoring method and system based on machine vision |
| CN101756705A (en) * | 2008-11-14 | 2010-06-30 | 北京宣爱智能模拟技术有限公司 | System and method for testing driving accident proneness |
| US9183176B2 (en) * | 2012-04-25 | 2015-11-10 | Electronics And Telecommunications Research Institute | Method and apparatus for providing driver-customized vehicle service |
-
2016
- 2016-07-25 CN CN201610586266.8A patent/CN106126960A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1873722A (en) * | 2006-04-07 | 2006-12-06 | 中山大学 | Safety caution system for driving automobile |
| CN101030316A (en) * | 2007-04-17 | 2007-09-05 | 北京中星微电子有限公司 | Safety driving monitoring system and method for vehicle |
| CN101236695A (en) * | 2008-03-05 | 2008-08-06 | 中科院嘉兴中心微系统所分中心 | Driver status estimation system based on vehicle mounted sensor network |
| CN101756705A (en) * | 2008-11-14 | 2010-06-30 | 北京宣爱智能模拟技术有限公司 | System and method for testing driving accident proneness |
| CN101593425A (en) * | 2009-05-06 | 2009-12-02 | 深圳市汉华安道科技有限责任公司 | A kind of fatigue driving monitoring method and system based on machine vision |
| US9183176B2 (en) * | 2012-04-25 | 2015-11-10 | Electronics And Telecommunications Research Institute | Method and apparatus for providing driver-customized vehicle service |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106651162A (en) * | 2016-12-09 | 2017-05-10 | 思建科技有限公司 | Big data-based driving risk assessment method |
| CN106530712A (en) * | 2016-12-16 | 2017-03-22 | 上海斐讯数据通信技术有限公司 | Big data-based system and method for pre-estimation of traffic casualty accident rates |
| CN106530712B (en) * | 2016-12-16 | 2019-09-13 | 上海斐讯数据通信技术有限公司 | The system and method for vehicular casualty rate is estimated by big data |
| CN106952002A (en) * | 2017-04-05 | 2017-07-14 | 南京人人保网络技术有限公司 | Driving methods of risk assessment and device based on driving behavior |
| WO2019137373A1 (en) * | 2018-01-10 | 2019-07-18 | 华为技术有限公司 | Method and device for acquiring automatic driving track |
| CN110816542A (en) * | 2018-07-23 | 2020-02-21 | 罗伯特·博世有限公司 | Method for providing driver assistance |
| CN110875937A (en) * | 2018-08-31 | 2020-03-10 | 北京嘀嘀无限科技发展有限公司 | Information pushing method and system |
| WO2020108219A1 (en) * | 2018-11-30 | 2020-06-04 | 江苏智通交通科技有限公司 | Traffic safety risk based group division and difference analysis method and system |
| CN109784188A (en) * | 2018-12-18 | 2019-05-21 | 深圳壹账通智能科技有限公司 | Driving fatigue degree evaluation method, device, computer equipment and storage medium |
| CN113222458A (en) * | 2021-05-31 | 2021-08-06 | 上海工程技术大学 | Urban rail transit driver safety risk assessment model and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106126960A (en) | Driving safety appraisal procedure and device | |
| Bitkina et al. | Identifying traffic context using driving stress: A longitudinal preliminary case study | |
| Lyu et al. | Driver’s cognitive workload and driving performance under traffic sign information exposure in complex environments: A case study of the highways in China | |
| Li et al. | Estimating driver’s lane-change intent considering driving style and contextual traffic | |
| Wang et al. | Human-like lane change decision model for autonomous vehicles that considers the risk perception of drivers in mixed traffic | |
| Barrett et al. | Can the ABILHAND handle manual ability in MS? | |
| Xu et al. | An overview of eco-driving theory, capability evaluation, and training applications | |
| Feldstein | Impending collision judgment from an egocentric perspective in real and virtual environments: a review | |
| Qin et al. | Influence of vehicle speed on the characteristics of driver’s eye movement at a highway tunnel entrance during day and night conditions: a pilot study | |
| Almadi et al. | A fuzzy-logic approach based on driver decision-making behavior modeling and simulation | |
| Zontone et al. | Stress evaluation in simulated autonomous and manual driving through the analysis of skin potential response and electrocardiogram signals | |
| Magaña et al. | Beside and behind the wheel: Factors that influence driving stress and driving behavior | |
| Chamberlain et al. | Evaluating the barrier effects of charge point trauma on UK electric vehicle growth | |
| Massoud et al. | IoT sensing for reality-enhanced serious games, a fuel-efficient drive use case | |
| Poliak et al. | Driver response time and age impact on the reaction time of drivers: a driving simulator study among professional-truck drivers | |
| Wang et al. | Examination of driver visual and cognitive responses to billboard elicited passive distraction using eye-fixation related potential | |
| Pan et al. | Effectiveness evaluation of optical illusion deceleration markings for a V-shaped undersea tunnel based on the set pair analysis method and the technique for order preference by similarity to ideal solution theory | |
| Xue et al. | Young novice drivers’ cognitive distraction detection: Comparing support vector machines and random forest model of vehicle control behavior | |
| Campos-Ferreira et al. | Vehicle and driver monitoring system using on-board and remote sensors | |
| Tarafder et al. | Drowsiness detection using ocular indices from EEG signal | |
| Liu et al. | The relationship of the information quantity of urban roadside traffic signs and drivers’ visibility based on information transmission | |
| Lea | Digitizing Diagnosis: Medicine, Minds, and Machines in Twentieth-Century America | |
| Xi et al. | Detection model on fatigue driving behaviors based on the operating parameters of freight vehicles | |
| Lloyd et al. | Explaining map-reading performance efficiency: gender, memory, and geographic information | |
| Chen et al. | Modeling lane-changing behaviors in merging areas of urban expressways in Nanjing, China |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161116 |
|
| RJ01 | Rejection of invention patent application after publication |