CN106781454B - The appraisal procedure and device of driving behavior - Google Patents
The appraisal procedure and device of driving behavior Download PDFInfo
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- CN106781454B CN106781454B CN201611060709.6A CN201611060709A CN106781454B CN 106781454 B CN106781454 B CN 106781454B CN 201611060709 A CN201611060709 A CN 201611060709A CN 106781454 B CN106781454 B CN 106781454B
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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Abstract
The present invention proposes the appraisal procedure and device of a kind of driving behavior, wherein the appraisal procedure of the driving behavior, comprising: obtains the vehicle operation data of stroke to be assessed, wherein the vehicle operation data includes the alert data of multiple traveling index item；The stroke to be assessed is split according to prefixed time interval, obtains at least one corresponding stroke segment of the stroke to be assessed；Based on preset assessment models, the safety trend numerical value of corresponding stroke segment is determined according to the alert data for the multiple traveling index item for including in each stroke segment；The assessment result of the stroke to be assessed according to the safety trend numerical generation of at least one stroke segment.The embodiment of the present invention keeps assessment result more accurate, improves the reasonability of assessment and the property of can refer to.
Description
Technical field
The present invention relates to vehicle drive behavioral analysis technology field, in particular to the appraisal procedure and dress of a kind of driving behavior
It sets.
Background technique
With the increasingly raising of living standard, the quantity of motor vehicles is also more and more.Meanwhile traffic accident frequency
Rate is also continuously increased.In driving vehicle processes, unsafe driving behavior brings many security risks, causes huge
The loss of property and personnel, therefore, the driving behavior for how improving driver have become a very important problem.
Currently, usually carrying out threshold by three longitudinal acceleration, transverse acceleration, normal acceleration parameters in the related technology
Value judgement, to provide the gross score of driving behavior, alternatively, providing safe or unsafe judging result.However, current comments
Valence method has that not accurate to the assessment result of driving behavior, reference value is low.
Summary of the invention
The present invention is directed to solve above-mentioned technical problem at least to a certain extent.
For this purpose, the first purpose of this invention is to propose a kind of appraisal procedure of driving behavior, keep assessment result more smart
Standard improves the reasonability of assessment and the property of can refer to.
Second object of the present invention is to propose a kind of assessment device of driving behavior.
In order to achieve the above object, embodiment proposes a kind of appraisal procedure of driving behavior according to a first aspect of the present invention, packet
Include following steps:
Obtain the vehicle operation data of stroke to be assessed, wherein the vehicle operation data includes multiple traveling index item
Alert data；
The stroke to be assessed is split according to prefixed time interval, it is corresponding at least to obtain the stroke to be assessed
One stroke segment；
Based on preset assessment models, the alert data according to the multiple traveling index item for including in each stroke segment is true
The safety trend numerical value of fixed corresponding stroke segment；
The assessment result of the stroke to be assessed according to the safety trend numerical generation of at least one stroke segment.
It is in one embodiment of the invention, described that the stroke to be assessed is split according to prefixed time interval,
Obtain at least one corresponding stroke segment of the stroke to be assessed, comprising:
Judge whether the stroke to be assessed collides event according to the vehicle operation data；
In case of collision accident, it is determined that the time point for the event that collides, and by the stroke, with the time
Point is terminal, the period that length is the prefixed time interval, as the corresponding stroke segment of the stroke to be assessed；Or
If not colliding event, the stroke to be assessed is split according to the prefixed time interval, is obtained
To multiple stroke segments.
In one embodiment of the invention, the stroke to be assessed is divided according to prefixed time interval described
It cuts, before obtaining at least one corresponding stroke segment of the stroke to be assessed, further includes:
The length of the prefixed time interval is determined according to the quantity of the input parameter of the preset assessment models.
In one embodiment of the invention, further includes:
Obtain the vehicle operation data of multiple sample strokes, wherein the vehicle operation data includes multiple traveling indexs
The sample alert data of item；
The multiple stroke is divided according to the stroke event that whether collides, obtains the first of the event of colliding
Second class stroke of class stroke and the event that do not collide；
For each first kind stroke, the time point for the event that collides in the first kind stroke is determined, and will be described
It is the period of prefixed time interval by terminal, length of the time point in first kind stroke, as the first kind stroke
Corresponding stroke segment；
For each second class stroke, the second class stroke is split according to the prefixed time interval, is obtained
Multiple stroke segments of the second class stroke；
According to the sample alert data for multiple traveling index item that the corresponding stroke segment of the multiple sample stroke includes
Model training is carried out, the assessment models are established.
In one embodiment of the invention, the safety trend numerical value of at least one stroke segment according to is raw
At the assessment result of the stroke to be assessed, comprising:
It counts at least one described stroke segment, the safety trend numerical value is the first segments of the first numerical value
Amount, and count at least one described stroke segment, the safety trend numerical value is the second number of fragments of second value；
The assessment score of the stroke to be assessed is calculated according to first number of fragments and second number of fragments.
Second aspect of the present invention embodiment proposes a kind of assessment device of driving behavior characterized by comprising
Module is obtained, for obtaining the vehicle operation data of stroke to be assessed, wherein the vehicle operation data includes more
The alert data of a traveling index item；
Segmentation module obtains described to be assessed for being split according to prefixed time interval to the stroke to be assessed
At least one corresponding stroke segment of stroke；
First determining module, for being based on preset assessment models, according to the multiple travelings for including in each stroke segment
The alert data of index item determines the safety trend numerical value of corresponding stroke segment；
Generation module, for the row to be assessed according to the safety trend numerical generation of at least one stroke segment
The assessment result of journey.
In one embodiment of the invention, the segmentation module is used for:
Judge whether the stroke to be assessed collides event according to the vehicle operation data；
In case of collision accident, it is determined that the time point for the event that collides, and by the stroke, with the time
Point is terminal, the period that length is the prefixed time interval, as the corresponding stroke segment of the stroke to be assessed；Or
If not colliding event, the stroke to be assessed is split according to the prefixed time interval, is obtained
To multiple stroke segments.
In one embodiment of the invention, further includes:
Second determining module, when for determining described default according to the quantity of the input parameters of the preset assessment models
Between the length that is spaced.
In one embodiment of the invention, further include that assessment models establish module, be used for:
Obtain the vehicle operation data of multiple sample strokes, wherein the vehicle operation data includes multiple traveling indexs
The sample alert data of item；
The multiple stroke is divided according to the stroke event that whether collides, obtains the first of the event of colliding
Second class stroke of class stroke and the event that do not collide；
For each first kind stroke, the time point for the event that collides in the first kind stroke is determined, and will be described
It is the period of prefixed time interval by terminal, length of the time point in first kind stroke, as the first kind stroke
Corresponding stroke segment；
For each second class stroke, the second class stroke is split according to the prefixed time interval, is obtained
Multiple stroke segments of the second class stroke；
According to the sample alert data for multiple traveling index item that the corresponding stroke segment of the multiple sample stroke includes
Model training is carried out, the assessment models are established.
In one embodiment of the invention, the generation module is used for:
It counts at least one described stroke segment, the safety trend numerical value is the first segments of the first numerical value
Amount, and count at least one described stroke segment, the safety trend numerical value is the second number of fragments of second value；
The assessment score of the stroke to be assessed is calculated according to first number of fragments and second number of fragments.
The appraisal procedure and device of the driving behavior of the embodiment of the present invention, by the vehicle driving number for obtaining stroke to be assessed
According to stroke to be assessed being then divided at least one stroke segment according to prefixed time interval, and be based on preset assessment mould
Type determines the safety trend numerical value of each stroke segment, according to the safety trend numerical value of the stroke segment in stroke to be assessed
The assessment result of the stroke to be assessed is generated, assessment result can be kept more accurate, and by row in conjunction with more index item
The alert data of the traveling index item of journey is temporally segmented cutting analysis, and can accurately flutter to catch leads to dangerous the reason of occurring and mistake
Journey is assessed and is reminded to vehicle operation data in real time, is improved the reasonability of assessment and the property of can refer to, is reduced traffic thing
Therefore generation, improve drive safety.
Additional aspect and advantage of the invention will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Above-mentioned and/or additional aspect of the invention and advantage will become from the description of the embodiment in conjunction with the following figures
Obviously and it is readily appreciated that, in which:
Fig. 1 is the flow chart according to the appraisal procedure of the driving behavior of one embodiment of the invention；
Fig. 2 is the flow chart according to the appraisal procedure of the driving behavior of another embodiment of the present invention；
Fig. 3 is the flow chart according to the appraisal procedure of the driving behavior of another embodiment of the present invention；
Fig. 4 is the structural schematic diagram according to the assessment device of the driving behavior of one embodiment of the invention；
Fig. 5 is the structural schematic diagram according to the assessment device of the driving behavior of another embodiment of the present invention.
Specific embodiment
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, and for explaining only the invention, and is not considered as limiting the invention.
In the description of the present invention, it is to be understood that, term " multiple " refers to two or more；Term " first ",
" second " is used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance.
Below with reference to the accompanying drawings the appraisal procedure and device of driving behavior according to an embodiment of the present invention are described.
Fig. 1 is the flow chart according to the appraisal procedure of the driving behavior of one embodiment of the invention.
As shown in Figure 1, the appraisal procedure of driving behavior according to an embodiment of the present invention, comprising:
S101 obtains the vehicle operation data of stroke to be assessed.
Specifically, the appraisal procedure of driving behavior provided in an embodiment of the present invention, executing subject mention for the embodiment of the present invention
The assessment device of the driving behavior of confession, the device can be configured in any motor vehicles, be commented with realizing vehicle travel
Point.
Wherein, vehicle operation data may include the alert data of multiple index item.
For example, the alert data of multiple index item may include collision warning, zig zag alarm, anxious alarm of slowing down,
It is anxious to accelerate alarm, anxious lane change alert, overspeed alarming, fatigue driving alarm, the alarm of long-time idling, frequent lane change alert, revolving speed
The information such as excessively high alarm, water temperature over-high alarm, neutral position sliding alarm.
Further, above-mentioned warning message can be opened by vehicle single stroke mileage travelled, main furnace building light switch, dipped headlight
Pass, side-marker lamp switch, fog lamp switch, left steering lamp switch, right turn lamp switch, dangerous lamp switch, door contact interrupter, car door lock are opened
Pass, car window switch, ECM (control unit of engine)/ECU (engine control module), ABS (anti-blocking brake system), SRS
The alarm of (electronic security(ELSEC) air bag), machine oil (pressure, temperature), maintenance alarm, wheel tyre pressure alarm, parking brake state, brake pedal, brake
Vehicle pedal relative position, gas pedal, gas pedal relative position, clutch state, seat belt status, ACC signal, key shape
The information of vehicles such as state, wiper status, air-conditioning switch gear, Engine Inlet Temperature, air-conditioning vehicle interior temperature determine.
In some embodiments of the invention, data when each index item can be alarmed are denoted as 1, do not alarm
When data be denoted as 0.
When specific implementation, mobile device, on-board automatic diagnosis system (On-Board Diagnostics, letter can be passed through
Claim OBD) or vehicle before install the equipment of standby, etc. any available vehicle operation data, obtain the vehicle of branch's journey to be evaluated
Running data.
S102 is split the stroke to be assessed according to prefixed time interval, and it is corresponding to obtain the stroke to be assessed
At least one stroke segment.
Wherein, prefixed time interval can be 10 seconds (s), 15s, 20s, etc..
Specifically, it can be configured according to the type of OBD equipment or the variation of other factors.
Alternatively, in one embodiment of the invention, for the ease of the subsequent peace for determining stroke segment according to assessment models
When full tendentiousness numerical value, it can will also be determined between the preset time according to the quantity of the input parameter of the preset assessment models
Every length.For example, above-mentioned prefixed time interval can be 15 seconds if the quantity of the input parameter of assessment models is 15,
So that the alert data of multiple index item under per second can be used as an input parameter of preset assessment models.
Assessment models are the vehicle drive data foundation previously according to great amount of samples stroke.Specific establishment process can pass through
The process of embodiment illustrated in fig. 3 is established.Wherein, the quantity of the input parameter of assessment models is by being split to sample stroke
When used prefixed time interval length determine.
When specific implementation, as shown in Fig. 2, step 102 may include step S201-S203.
S201 judges whether the stroke to be assessed collides event according to the vehicle operation data.
S202, in case of collision accident, it is determined that the time point for the event that collides, and by the stroke, with institute
The period that time point is terminal, length is the prefixed time interval is stated, as the corresponding stroke piece of the stroke to be assessed
Section.
That is, the data of 15s are as the trip pair before can colliding in stroke for the stroke to collide
The stroke segment answered.
As an example it is assumed that preset time period is 15s, in the stroke to be assessed of a 2min, collide event
Time point be the 1st point 30 seconds, then can be corresponding as stroke to be assessed using 1 point of period between 30 seconds 15 seconds to 1 point
Stroke segment.
S203 divides the stroke to be assessed according to the prefixed time interval if not colliding event
It cuts, obtains multiple stroke segments.
That is, it is prefixed time interval length that stroke can be divided into length for the stroke not collided
Multiple segments.
As an example it is assumed that preset time period is that 15s is split in the stroke to be assessed of a 2min with 15s,
Obtain 8 stroke segments.
It in one embodiment of the invention, for the ease of carrying out data preservation and calculating the purpose of, can be based on default rule
Then, the corresponding alert data of each stroke segment after segmentation is stored as to the tables of data of preset format.
Specifically, the tables of data includes M × N+1 column, Q+2 row, wherein M is the duration of prefixed time interval, and N is vehicle
The item number for the index item for including in running data, Q are the number of the corresponding stroke segment of stroke to be assessed.That is, in tables of data
The corresponding stroke segment of every row.
As an example it is assumed that the index item in the vehicle operation data of the stroke to be assessed of a 1min includes " anxious to accelerate "
" hypervelocity " 2, prefixed time interval 15s.So, the event if stroke to be assessed does not collide, after segmentation
Storable tables of data can be as shown in table 1, includes 60/15+2=6 row, 15 × 2+1=31 column.If the stroke to be assessed occurs
Collision accident, then storable tables of data can be as shown in table 2 after its segmentation, includes 1+2=3 row, 15 × 2+1=31 column.
Table 1
Table 2
S103 is based on preset assessment models, according to the alarm for the multiple traveling index item for including in each stroke segment
Data determine the safety trend numerical value of corresponding stroke segment.
Specifically, for each stroke segment, it can be by the report of corresponding each traveling index item per second in stroke segment
Input parameter of the alert data as input parameter input assessment models, exportable the trip segment after the calculating of assessment models
Safety trend numerical value.It can enter to obtain the safety trend numerical value of each stroke segment in stroke to be assessed as a result,.
Wherein, safety trend numerical value may include indicating the first numerical value (for example, can be indicated with 0) of safety and indicating dangerous
Second value (for example, can be indicated with 1).
S104, the assessment of the stroke to be assessed according to the safety trend numerical generation of at least one stroke segment
As a result.
Specifically, can be counted according to the safety trend numerical value of stroke segment each in stroke to be assessed.It obtains
Wherein safety trend total score and dangerous tendency total score, in turn, according to safety trend total score and dangerous tendency total score meter
Calculate the assessment score of entire stroke to be assessed.
In one embodiment of the invention, for the first numerical value (for example, can be indicated with 0) and table of above-mentioned expression safety
Show dangerous second value (for example, can be indicated with 1), at least one statistics available described stroke segment, the safety trend
Numerical value is the first number of fragments of the first numerical value, and is counted at least one described stroke segment, the safety trend numerical value
For the second number of fragments of second value；It is calculated according to first number of fragments and second number of fragments described to be assessed
The assessment score of stroke.
As an example it is assumed that the first number of fragments is S, the second number of fragments is D, then,
The assessment score of stroke to be assessed=S/ (S+D) × 100.
As a result, by being split to stroke, stroke segment each in stroke is carried out by being converted to the assessment of stroke
Whether An Quan classification problem, then by the classification results of each stroke segment be converted to entire stroke scoring so that scoring tie
Fruit is more accurate.
The appraisal procedure of the driving behavior of the embodiment of the present invention, by obtaining the vehicle operation data of stroke to be assessed, so
Stroke to be assessed is divided by least one stroke segment according to prefixed time interval afterwards, and is determined based on preset assessment models
The safety trend numerical value of each stroke segment, according to the safety trend numerical generation institute of the stroke segment in stroke to be assessed
The assessment result of stroke to be assessed is stated, assessment result can be kept more accurate, and pass through the row to stroke in conjunction with more index item
The alert data for sailing index item is temporally segmented cutting analysis, and can accurately flutter to catch leads to dangerous the reason of occurring and process, real
When vehicle operation data is assessed and is reminded, improve assessment reasonability and the property of can refer to, reduce traffic accident
Occur, improves drive safety.
In another embodiment of this hair invention, the appraisal procedure of above-mentioned driving behavior may also include as shown in Figure 3
Establish the process of above-mentioned assessment models.Specifically, as shown in figure 3, can comprise the following steps that
S301 obtains the vehicle operation data of multiple sample strokes.
Wherein, the vehicle operation data includes the sample alert data of multiple traveling index item.
The vehicle operation data of sample stroke can be the mass data in vehicle history driving process.
S302 divides the multiple stroke according to the stroke event that whether collides, obtains the event of colliding
First kind stroke and the event that do not collide the second class stroke.
In order to enable the assessment models trained are more accurate, sample stroke may include the first kind row of time of colliding
Second class stroke of journey and the event that do not collide.It therefore, can root first after the vehicle operation data for obtaining sample stroke
According to the event that whether collides in stroke, the sample stroke that will acquire is divided into the first kind stroke for the event of colliding and does not send out
Second class stroke of raw collision accident.
S303 determines the time point for the event that collides in the first kind stroke, and will for each first kind stroke
It is the period of prefixed time interval by terminal, length of the time point, as the first kind in the first kind stroke
The corresponding stroke segment of stroke.
Wherein, determine that the specific implementation of the corresponding stroke segment of first kind stroke can refer to Fig. 2 institute in step S303
State the specific implementation process of step S202 in embodiment.
It is analyzed as a result, by alert data before accident occurs (as collided preceding 15 seconds data) fine cut, Neng Gouzhun
It really flutters to catch and leads to dangerous the reason of occurring and process, the assessment accuracy for the assessment models that thus training obtains is higher.
S304 is split each second class stroke according to the prefixed time interval to the second class stroke,
Obtain multiple stroke segments of the second class stroke.
Wherein, determine that the specific implementation of the corresponding stroke segment of the second class stroke can refer to Fig. 1 institute in step S304
State the specific implementation process of step S203 in embodiment.
As a result, by the way that data to be temporally segmented to cutting, and it to be used for Training valuation model, the assessment mould that thus training obtains
Type can carry out behavior evaluation and prompting at regular intervals to vehicle operation data in real time, accident can be avoided to send out in time
It is raw.
Further, the mode that stroke segment can be stored in embodiment according to Fig.2, by first kind stroke and the second class
The corresponding segment of stroke is uniformly stored in a tables of data.It for example, can be as shown in table 3.
Table 3
The sample of S305, the multiple traveling index item for including according to the corresponding stroke segment of the multiple sample stroke are alarmed
Data carry out model training, establish the assessment models.
In an embodiment of the present invention, a variety of machine learning algorithms can be based on, according to the traveling index in above-mentioned data packet
The sample alert data Training valuation model of item.For example, by taking neural network algorithm as an example, an initial nerve net can be established
Network, wherein the input layer quantity in the initial neural network is 15 × index number, and hidden layer neuron quantity isOutput layer neuron quantity is 2.
Then, the data in table 3 are inputted into neural network by item, wherein each achievement data is as independent variable in 1 to 15 second
Input layer is sequentially input, the achievement data that " colliding " arranges in table is as dependent variable input and output layer neuron.
Above-mentioned neural network is trained by the vehicle drive data of the sample stroke of the magnanimity obtained as a result, most
The neural network model for assessment is obtained eventually.
Further it will be understood that vehicle operation data is not fixed and invariable in a kind of possible way of realization,
With the variation of time or other factors, vehicle operation data can also generate variation.Corresponding, default characteristic model can also generate
Change, therefore, in embodiments of the present invention, after establishing assessment models, can also include:
The vehicle operation data of the sample stroke is acquired every predetermined period；
The assessment models are updated according to the vehicle operation data of the collected sample stroke.
Wherein, predetermined period can be 1 hour, 2 hours, 1 day, 2 days, etc..By being updated to assessment models,
Assessment result can be made more acurrate.
After determining assessment models, current stroke to be assessed can be determined according to the assessment models in vehicle operation
In each stroke segment safety trend numerical value.
It should be noted that in practical applications, hiding layer number and each layer neuron number can be adjusted according to the actual situation
Amount.
Thus it is fine to cross alert data before accident occurs (as collided preceding 15 seconds data) for the assessment models that training obtains
Cutting analysis, can accurately flutter to catch leads to dangerous the reason of occurring and process, can in real time to vehicle operation data carry out every
The behavior evaluation of a period of time and prompting, can avoid accident in time, and assessment accuracy is higher.
In order to realize above-described embodiment, the present invention also proposes a kind of assessment device of driving behavior.
Fig. 4 is the structural schematic diagram according to the assessment device of the driving behavior of one embodiment of the invention.
As shown in figure 4, the assessment device of driving behavior according to an embodiment of the present invention, comprising: obtain module 10, segmentation mould
Block 20, the first determining module 30 and generation module 40.
Specifically, the vehicle operation data that module 10 is used to obtain stroke to be assessed is obtained, wherein the vehicle driving number
According to the alert data for including multiple traveling index item.
Specifically, the appraisal procedure of driving behavior provided in an embodiment of the present invention, executing subject mention for the embodiment of the present invention
The assessment device of the driving behavior of confession, the device can be configured in any motor vehicles, be commented with realizing vehicle travel
Point.
Wherein, vehicle operation data may include the alert data of multiple index item.
For example, the alert data of multiple index item may include collision warning, zig zag alarm, anxious alarm of slowing down,
It is anxious to accelerate alarm, anxious lane change alert, overspeed alarming, fatigue driving alarm, the alarm of long-time idling, frequent lane change alert, revolving speed
The information such as excessively high alarm, water temperature over-high alarm, neutral position sliding alarm.
Further, above-mentioned warning message can be opened by vehicle single stroke mileage travelled, main furnace building light switch, dipped headlight
Pass, side-marker lamp switch, fog lamp switch, left steering lamp switch, right turn lamp switch, dangerous lamp switch, door contact interrupter, car door lock are opened
Pass, car window switch, ECM (control unit of engine)/ECU (engine control module), ABS (anti-blocking brake system), SRS
The alarm of (electronic security(ELSEC) air bag), machine oil (pressure, temperature), maintenance alarm, wheel tyre pressure alarm, parking brake state, brake pedal, brake
Vehicle pedal relative position, gas pedal, gas pedal relative position, clutch state, seat belt status, ACC signal, key shape
The information of vehicles such as state, wiper status, air-conditioning switch gear, Engine Inlet Temperature, air-conditioning vehicle interior temperature determine.
In some embodiments of the invention, data when each index item can be alarmed are denoted as 1, do not alarm
When data be denoted as 0.
When specific implementation, mobile device, on-board automatic diagnosis system (On-Board Diagnostics, letter can be passed through
Claim OBD) or vehicle before install the equipment of standby, etc. any available vehicle operation data, obtain the vehicle of branch's journey to be evaluated
Running data.
Segmentation module 20 obtains described to be assessed for being split according to prefixed time interval to the stroke to be assessed
At least one corresponding stroke segment of stroke.
Wherein, prefixed time interval can be 10 seconds (s), 15s, 20s, etc..
Specifically, it can be configured according to the type of OBD equipment or the variation of other factors.
Alternatively, in one embodiment of the invention, for the ease of the subsequent peace for determining stroke segment according to assessment models
When full tendentiousness numerical value, it can will also be determined between the preset time according to the quantity of the input parameter of the preset assessment models
Every length.For example, above-mentioned prefixed time interval can be 15 seconds if the quantity of the input parameter of assessment models is 15,
So that the alert data of multiple index item under per second can be used as an input parameter of preset assessment models.
In one embodiment of the invention, segmentation module 20 can be used for:
Judge whether the stroke to be assessed collides event according to the vehicle operation data；
In case of collision accident, it is determined that the time point for the event that collides, and by the stroke, with the time
Point is terminal, the period that length is the prefixed time interval, as the corresponding stroke segment of the stroke to be assessed；
If not colliding event, the stroke to be assessed is split according to the prefixed time interval, is obtained
To multiple stroke segments.
That is, the data of 15s are as the trip pair before can colliding in stroke for the stroke to collide
The stroke segment answered.
As an example it is assumed that preset time period is 15s, in the stroke to be assessed of a 2min, collide event
Time point be the 1st point 30 seconds, then can be corresponding as stroke to be assessed using 1 point of period between 30 seconds 15 seconds to 1 point
Stroke segment.
For the stroke not collided, stroke can be divided into multiple segments that length is prefixed time interval length.
As an example it is assumed that preset time period is that 15s is split in the stroke to be assessed of a 2min with 15s,
Obtain 8 stroke segments.
It in one embodiment of the invention, for the ease of carrying out data preservation and calculating the purpose of, can be based on default rule
Then, the corresponding alert data of each stroke segment after segmentation is stored as to the tables of data of preset format.
Specifically, the tables of data includes M × N+1 column, Q+2 row, wherein M is the duration of prefixed time interval, and N is vehicle
The item number for the index item for including in running data, Q are the number of the corresponding stroke segment of stroke to be assessed.That is, in tables of data
The corresponding stroke segment of every row.
As an example it is assumed that the index item in the vehicle operation data of the stroke to be assessed of a 1min includes " anxious to accelerate "
" hypervelocity " 2, prefixed time interval 15s.So, the event if stroke to be assessed does not collide, after segmentation
Storable tables of data can be as shown in table 1, includes 60/15+2=6 row, 15 × 2+1=31 column.If the stroke to be assessed occurs
Collision accident, then storable tables of data can be as shown in table 2 after its segmentation, includes 1+2=3 row, 15 × 2+1=31 column.
First determining module 30 is used to be based on preset assessment models, according to the multiple travelings for including in each stroke segment
The alert data of index item determines the safety trend numerical value of corresponding stroke segment.
Specifically, for each stroke segment, the first determining module 30 can will be per second corresponding each in stroke segment
Input parameter of the alert data of index item as input parameter input assessment models is travelled, it can after the calculating of assessment models
Export the safety trend numerical value of the trip segment.The safety that each stroke segment in stroke to be assessed can be entered to obtain as a result, is inclined
Tropism numerical value.
Wherein, safety trend numerical value may include indicating the first numerical value (for example, can be indicated with 0) of safety and indicating dangerous
Second value (for example, can be indicated with 1).
Generation module 40 is used for be assessed according to the safety trend numerical generation of at least one stroke segment
The assessment result of stroke.
Specifically, generation module 40 can be carried out according to the safety trend numerical value of stroke segment each in stroke to be assessed
Statistics.Wherein safety trend total score and dangerous tendency total score are obtained, in turn, according to safety trend total score and dangerous tendency
Total score calculates the assessment score of entire stroke to be assessed.
In one embodiment of the invention, for the first numerical value (for example, can be indicated with 0) and table of above-mentioned expression safety
Show dangerous second value (for example, can be indicated with 1), generation module 40 can be used for: counting at least one described stroke segment,
The safety trend numerical value is the first number of fragments of the first numerical value, and is counted at least one described stroke segment, described
Safety trend numerical value is the second number of fragments of second value；According to first number of fragments and second number of fragments
Calculate the assessment score of the stroke to be assessed.
As an example it is assumed that the first number of fragments is S, the second number of fragments is D, then,
The assessment score of stroke to be assessed=S/ (S+D) × 100.
As a result, by being split to stroke, stroke segment each in stroke is carried out by being converted to the assessment of stroke
Whether An Quan classification problem, then by the classification results of each stroke segment be converted to entire stroke scoring so that scoring tie
Fruit is more accurate.
The assessment device of the driving behavior of the embodiment of the present invention, by obtaining the vehicle operation data of stroke to be assessed, so
Stroke to be assessed is divided by least one stroke segment according to prefixed time interval afterwards, and is determined based on preset assessment models
The safety trend numerical value of each stroke segment, according to the safety trend numerical generation institute of the stroke segment in stroke to be assessed
The assessment result of stroke to be assessed is stated, assessment result can be kept more accurate, and pass through the row to stroke in conjunction with more index item
The alert data for sailing index item is temporally segmented cutting analysis, and can accurately flutter to catch leads to dangerous the reason of occurring and process, real
When vehicle operation data is assessed and is reminded, improve assessment reasonability and the property of can refer to, reduce traffic accident
Occur, improves drive safety.
Fig. 5 is the structural schematic diagram according to the assessment device of the driving behavior of another embodiment of the present invention.
As shown in figure 5, the assessment device of driving behavior according to an embodiment of the present invention, comprising: obtain module 10, segmentation mould
Block 20, the first determining module 30, generation module 40, the second determining module 50, assessment models establish module 60.
Wherein, obtaining module 10, segmentation module 20, the first determining module 30 and generation module 40 can refer to shown in Fig. 4 in fact
Apply example.
Second determining module 50 is used to be determined according to the quantity of the input parameter of the preset assessment models described default
The length of time interval.
Assessment models in the embodiment of the present invention can be for previously according to the foundation of the vehicle drive data of great amount of samples stroke.
Specific establishment process can establish the foundation of module 60 by assessment models.Wherein, the quantity of the input parameter of assessment models, is by right
What the length of sample stroke used prefixed time interval when being split determined.
Assessment models are established module 60 and are used for:
Obtain the vehicle operation data of multiple sample strokes, wherein the vehicle operation data includes multiple traveling indexs
The sample alert data of item；The multiple stroke is divided according to the stroke event that whether collides, is collided
The first kind stroke of event and the second class stroke of the event that do not collide；For each first kind stroke, described first is determined
The time point for the event that collides in class stroke, and by the first kind stroke, it is pre- by terminal, length of the time point
If the period of time interval, as the corresponding stroke segment of the first kind stroke；For each second class stroke, according to institute
It states prefixed time interval to be split the second class stroke, obtains multiple stroke segments of the second class stroke；According to
The sample alert data for multiple traveling index item that the corresponding stroke segment of the multiple sample stroke includes carries out model training,
Establish the assessment models.
Wherein, the vehicle operation data includes the sample alert data of multiple traveling index item.
The vehicle operation data of sample stroke can be the mass data in vehicle history driving process.
In order to enable the assessment models trained are more accurate, sample stroke may include the first kind row of time of colliding
Second class stroke of journey and the event that do not collide.It therefore, can root first after the vehicle operation data for obtaining sample stroke
According to the event that whether collides in stroke, the sample stroke that will acquire is divided into the first kind stroke for the event of colliding and does not send out
Second class stroke of raw collision accident.
In an embodiment of the present invention, a variety of machine learning algorithms can be based on, according to the traveling index in above-mentioned data packet
The sample alert data Training valuation model of item.For example, by taking neural network algorithm as an example, an initial nerve net can be established
Network, wherein the input layer quantity in the initial neural network is 15 × index number, and hidden layer neuron quantity isOutput layer neuron quantity is 2.
Then, the data in table 3 are inputted into neural network by item, wherein each achievement data is as independent variable in 1 to 15 second
Input layer is sequentially input, the achievement data that " colliding " arranges in table is as dependent variable input and output layer neuron.
Above-mentioned neural network is trained by the vehicle drive data of the sample stroke of the magnanimity obtained as a result, most
The neural network model for assessment is obtained eventually.
After determining assessment models, current stroke to be assessed can be determined according to the assessment models in vehicle operation
In each stroke segment safety trend numerical value.
It should be noted that in practical applications, hiding layer number and each layer neuron number can be adjusted according to the actual situation
Amount.
Thus it is fine to cross alert data before accident occurs (as collided preceding 15 seconds data) for the assessment models that training obtains
Cutting analysis, can accurately flutter to catch leads to dangerous the reason of occurring and process, can in real time to vehicle operation data carry out every
The behavior evaluation of a period of time and prompting, can avoid accident in time, and assessment accuracy is higher.
Further it will be understood that vehicle operation data is not fixed and invariable in a kind of possible way of realization,
With the variation of time or other factors, vehicle operation data can also generate variation.Corresponding, default characteristic model can also generate
Therefore variation in embodiments of the present invention, after establishing assessment models, can acquire the sample stroke every predetermined period
Vehicle operation data, and the assessment models are updated according to the vehicle operation data of the collected sample stroke.
Wherein, predetermined period can be 1 hour, 2 hours, 1 day, 2 days, etc..By being updated to assessment models,
Assessment result can be made more acurrate.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiment or examples.In addition, without conflicting with each other, the skill of this field
Art personnel can tie the feature of different embodiments or examples described in this specification and different embodiments or examples
It closes and combines.
In addition, term " first ", " second " are used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance
Or implicitly indicate the quantity of indicated technical characteristic.Define " first " as a result, the feature of " second " can be expressed or
Implicitly include at least one this feature.In the description of the present invention, the meaning of " plurality " is two or more, unless separately
There is clearly specific restriction.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing specific logical function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the present invention includes other realization, wherein can not press shown or discussed suitable
Sequence, including according to related function by it is basic simultaneously in the way of or in the opposite order, Lai Zhihang function, this should be of the invention
Embodiment person of ordinary skill in the field understood.
Expression or logic and/or step described otherwise above herein in flow charts, for example, being considered use
In the order list for the executable instruction for realizing logic function, may be embodied in any computer-readable medium, for
Instruction execution system, device or equipment (such as computer based system, including the system of processor or other can be held from instruction
The instruction fetch of row system, device or equipment and the system executed instruction) it uses, or combine these instruction execution systems, device or set
It is standby and use.For the purpose of this specification, " computer-readable medium ", which can be, any may include, stores, communicates, propagates or pass
Defeated program is for instruction execution system, device or equipment or the dress used in conjunction with these instruction execution systems, device or equipment
It sets.The more specific example (non-exhaustive list) of computer-readable medium include the following: there is the electricity of one or more wirings
Interconnecting piece (electronic device), portable computer diskette box (magnetic device), random access memory (RAM), read-only memory
(ROM), erasable edit read-only storage (EPROM or flash memory), fiber device and portable optic disk is read-only deposits
Reservoir (CDROM).In addition, computer-readable medium can even is that the paper that can print described program on it or other are suitable
Medium, because can then be edited, be interpreted or when necessary with it for example by carrying out optical scanner to paper or other media
His suitable method is handled electronically to obtain described program, is then stored in computer storage.
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
It suddenly is that relevant hardware can be instructed to complete by program, the program can store in a kind of computer-readable storage medium
In matter, which when being executed, includes the steps that one or a combination set of embodiment of the method.
It, can also be in addition, each functional unit in each embodiment of the present invention can integrate in a processing module
It is that each unit physically exists alone, can also be integrated in two or more units in a module.Above-mentioned integrated mould
Block both can take the form of hardware realization, can also be realized in the form of software function module.The integrated module is such as
Fruit is realized and when sold or used as an independent product in the form of software function module, also can store in a computer
In read/write memory medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..Although having been shown and retouching above
The embodiment of the present invention is stated, it is to be understood that above-described embodiment is exemplary, and should not be understood as to limit of the invention
System, those skilled in the art can be changed above-described embodiment, modify, replace and become within the scope of the invention
Type.
Claims (8)
1. a kind of appraisal procedure of driving behavior, which comprises the following steps:
Obtain the vehicle operation data of stroke to be assessed, wherein the vehicle operation data includes the report of multiple traveling index item
Alert data；
The stroke to be assessed is split according to prefixed time interval, obtain the stroke to be assessed it is corresponding at least one
Stroke segment；
Based on preset assessment models, phase is determined according to the alert data for the multiple traveling index item for including in each stroke segment
Answer the safety trend numerical value of stroke segment；
The assessment result of the stroke to be assessed according to the safety trend numerical generation of at least one stroke segment；
Wherein, described that the stroke to be assessed is split according to prefixed time interval, it is corresponding to obtain the stroke to be assessed
At least one stroke segment, comprising:
Judge whether the stroke to be assessed collides event according to the vehicle operation data；
In case of collision accident, it is determined that time point for the event that collides, and by the stroke to be assessed, with it is described when
Between point be terminal, the period that length is the prefixed time interval, as the corresponding stroke segment of the stroke to be assessed；Or
Person
If not colliding event, the stroke to be assessed is split according to the prefixed time interval, is obtained more
A stroke segment.
2. the method as described in claim 1, which is characterized in that it is described according to prefixed time interval to the stroke to be assessed
It is split, before obtaining at least one corresponding stroke segment of the stroke to be assessed, further includes:
The length of the prefixed time interval is determined according to the quantity of the input parameter of the preset assessment models.
3. the method as described in claim 1, which is characterized in that further include:
Obtain the vehicle operation data of multiple sample strokes, wherein the vehicle operation data includes multiple traveling index item
Sample alert data；
The multiple stroke is divided according to the stroke event that whether collides, obtains the first kind row for the event of colliding
Second class stroke of journey and the event that do not collide；
For each first kind stroke, the time point for the event that collides in the first kind stroke is determined, and by described first
It is the period of prefixed time interval by terminal, length of the time point in class stroke, it is corresponding as the first kind stroke
Stroke segment；
For each second class stroke, the second class stroke is split according to the prefixed time interval, is obtained described
Multiple stroke segments of second class stroke；
The sample alert data for the multiple traveling index item for including according to the corresponding stroke segment of the multiple sample stroke carries out
Model training establishes the assessment models.
4. the method according to claim 1, which is characterized in that at least one stroke segment according to
The assessment result of stroke to be assessed described in safety trend numerical generation, comprising:
It counting at least one described stroke segment, the safety trend numerical value is the first number of fragments of the first numerical value, and
It counts at least one described stroke segment, the safety trend numerical value is the second number of fragments of second value；
The assessment score of the stroke to be assessed is calculated according to first number of fragments and second number of fragments.
5. a kind of assessment device of driving behavior characterized by comprising
Module is obtained, for obtaining the vehicle operation data of stroke to be assessed, wherein the vehicle operation data includes multiple rows
Sail the alert data of index item；
Divide module and obtains the stroke to be assessed for being split according to prefixed time interval to the stroke to be assessed
At least one corresponding stroke segment；
First determining module, for being based on preset assessment models, according to the multiple traveling indexs for including in each stroke segment
The alert data of item determines the safety trend numerical value of corresponding stroke segment；
Generation module, for the stroke to be assessed according to the safety trend numerical generation of at least one stroke segment
Assessment result；
Wherein, the segmentation module is used for:
Judge whether the stroke to be assessed collides event according to the vehicle operation data；
In case of collision accident, it is determined that time point for the event that collides, and by the stroke to be assessed, with it is described when
Between point be terminal, the period that length is the prefixed time interval, as the corresponding stroke segment of the stroke to be assessed；Or
Person
If not colliding event, the stroke to be assessed is split according to the prefixed time interval, is obtained more
A stroke segment.
6. device as claimed in claim 5, which is characterized in that further include:
Second determining module determines between the preset time for the quantity according to the input parameters of the preset assessment models
Every length.
7. device as claimed in claim 5, which is characterized in that further include that assessment models establish module, be used for:
Obtain the vehicle operation data of multiple sample strokes, wherein the vehicle operation data includes multiple traveling index item
Sample alert data；
The multiple stroke is divided according to the stroke event that whether collides, obtains the first kind row for the event of colliding
Second class stroke of journey and the event that do not collide；
For each first kind stroke, the time point for the event that collides in the first kind stroke is determined, and by described first
It is the period of prefixed time interval by terminal, length of the time point in class stroke, it is corresponding as the first kind stroke
Stroke segment；
For each second class stroke, the second class stroke is split according to the prefixed time interval, is obtained described
Multiple stroke segments of second class stroke；
The sample alert data for the multiple traveling index item for including according to the corresponding stroke segment of the multiple sample stroke carries out
Model training establishes the assessment models.
8. such as the described in any item devices of claim 5-7, which is characterized in that the generation module is used for:
It counting at least one described stroke segment, the safety trend numerical value is the first number of fragments of the first numerical value, and
It counts at least one described stroke segment, the safety trend numerical value is the second number of fragments of second value；
The assessment score of the stroke to be assessed is calculated according to first number of fragments and second number of fragments.
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| CN107730028A (en) * | 2017-09-18 | 2018-02-23 | 广东翼卡车联网服务有限公司 | A kind of car accident recognition methods, car-mounted terminal and storage medium |
| CN107766876B (en) * | 2017-09-19 | 2019-08-13 | 平安科技（深圳）有限公司 | Driving model training method, driver's recognition methods, device, equipment and medium |
| CN107704918B (en) * | 2017-09-19 | 2019-07-12 | 平安科技（深圳）有限公司 | Driving model training method, driver's recognition methods, device, equipment and medium |
| CN108389072B (en) * | 2018-01-23 | 2020-12-22 | 深圳市至尊汽车服务有限公司 | Method for managing fees in p2p vehicle renting process |
| CN110210980A (en) * | 2018-06-15 | 2019-09-06 | 腾讯科技（深圳）有限公司 | A kind of driving behavior appraisal procedure, device and storage medium |
| CN111833480B (en) * | 2019-04-12 | 2022-04-15 | 比亚迪股份有限公司 | Driving behavior detection method and device and vehicle |
| CN112734147A (en) * | 2019-10-28 | 2021-04-30 | 北京京东乾石科技有限公司 | Method and device for equipment evaluation management |
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