CN105095677A - Adaptive driving behavior analysis method and apparatus - Google Patents
Adaptive driving behavior analysis method and apparatus Download PDFInfo
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Abstract
The invention relates to the technical field of vehicle driving behavior analysis, in particular to an adaptive driving behavior analysis method and apparatus. Firstly, vehicle driving state parameters including rotational speed, accelerated speed and vehicle speed are acquired and calculated, and a transmission ratio is obtained; the rotational speed is divided into m rotational speed intervals, the transmission ratio is divided into n gear intervals, mean values of the transmission ratio and the acceleration of each rotational speed interval and each gear interval are calculated, a transmission ratio mean value and an accelerated speed mean value are obtained, and comparison data is obtained; and real-time vehicle driving state parameters are acquired and compared with the comparison data, and a vehicle is analyzed whether to be in a bad driving state or not. According to the adaptive driving behavior analysis method and apparatus, vehicle driving data is continuously acquired, a criterion for driving behavior analysis of a driver can be fully established, a normal driving behavior of the driver can be better reflected through more data, a bad driving behavior of the driver can be accurately compared, judgment criterions of a continuously variable transmission vehicle and a step-down variable transmission vehicle are well compatible, and the judgment precision is high.
Description
Technical field
The present invention relates to car steering behavioral analysis technology field, particularly relate to a kind of drive automatically behavior analysis method and device thereof.
Background technology
In order to accurately judge whether driver exists anxious acceleration or the anxious this kind of driving behavior being unfavorable for safety or fuel economy of slowing down, need to carry out monitor and managment to the driving behavior of driver, driving behavior is generally the roadcraft of the vehicle drive data analysis driver that basis collects by the roadcraft of collection vehicle running data analysis driver, provide in prior art " a kind of method using acceleration transducer remote real-time monitoring vehicle suddenly to accelerate or bring to a halt ", see that publication number is: 102107652A, publication date is: the Chinese patent of 2011-06-29, this method is the accekeration by detecting XYZ axle three direction, again through carrying out the component rejection of XY axle to acceleration of gravity when tilting, obtain vehicle accekeration accurately, thus judge that whether road speed is at zone of reasonableness, the urgency realizing remote real-time monitoring vehicle is accelerated or brings to a halt.
Existing car category is various, and whether vehicle, load-carrying, automatic catch, manual gear, different road conditions all can have an impact to acceleration, only calculates the driving behavior that acceleration judges driver therefore merely, and error can be caused large, and result is inaccurate.Adopt traditional determination methods cannot adapt to complicated road conditions and different vehicles.
Summary of the invention
In order to overcome prior art Problems existing, goal of the invention of the present invention is to propose a kind of wide accommodation, judges the driving behavior analysis method that precision is high.
Technical scheme of the present invention is as follows:
A kind of drive automatically behavior analysis method is provided, comprises the steps:
Step one, image data, after automobile becomes mobile status from halted state, gather the rotating speed Ω of acceleration alpha, speed of a motor vehicle ν and the engine of automobile under level road, state of giving it the gun;
Step 2, acquisition correlation data, first collect according to step one and often organize speed of a motor vehicle ν, engine speed Ω, δ is compared in the transmission that acquisition automobile is often organized, then ratio of gear δ is divided into m gear interval, rotating speed Ω is divided into n rotating speed interval, determines that automobile is interval at each gear, the average acceleration in each rotating speed interval according to the acceleration a that step one collects
then the average acceleration in each gear interval is got
maximal value, obtain peak acceleration a
max;
Step 3, Data Comparison, gather the real-time rotate speed Ω of automobile
h, real time acceleration a
h, real-time speed of a motor vehicle v
h, calculate and obtain real-time ratio of gear δ
h, by real-time ratio of gear δ
hbe matched to gear corresponding in step 2 interval, the real-time rotate speed Ω gathered
h, real time acceleration a
h, real-time speed of a motor vehicle v
hthe correlation data obtained with step 2 contrasts, and determines whether the driving behavior of automobile is suddenly accelerate driving behavior, anxious driving behavior of slowing down, collision driving behavior.
Frequency acquisition in described step one be 1 ~ 50 milli second/time, the acceleration that continuous acquisition is N time, gets the mean value of this acceleration, obtains acceleration a, N be greater than 1 natural number.
In step 3, as the real-time rotate speed Ω collected
hbe more than or equal to rotary speed threshold value Ω
mtime, determine that automobile is current and accelerate driving behavior, rotary speed threshold value Ω for anxious
mit is 3000 ~ 4000 revolutions per seconds
In described step 3, real time acceleration a
hwith the acceleration a in same gear interval
max, acceleration factor λ
1contrast, as real time acceleration a
hbe greater than acceleration factor λ
1with acceleration a
maxlong-pending, determine that automobile is current and accelerate driving behavior for anxious; Described acceleration factor λ
1be 0.5≤λ
1< 1.
In described step 3, real time acceleration a
hwith the peak acceleration a in same gear interval
max, acceleration factor λ
2contrast, as real time acceleration a
hbe greater than acceleration factor λ
2with acceleration a
maxlong-pending, determine automobile current be anxious driving behavior of slowing down, described acceleration system λ
2be 1≤λ
2< 4.
In step 3, gather real-time centripetal acceleration a
towith the peak acceleration a in same gear interval
max, acceleration factor λ
3contrast, as real-time centripetal acceleration a
tobe greater than acceleration factor λ
3with acceleration a
maxlong-pending, determine automobile current be zig zag driving behavior, described acceleration system λ
3be 1 < λ
3< 4.
In described step 3, as the real-time gas pedal degree of depth L collected
hwhen being greater than gas pedal depth threshold L, determining that automobile is current and accelerate driving behavior for anxious.
In described step 3, as the real-time brake pedal degree of depth K collected
hwhen being greater than brake pedal depth threshold K, determine automobile current be anxious driving behavior of slowing down.
Gather domatic angle θ in described step one, when domatic angle θ=0, determine that automobile is current for the driving behavior of plane road conditions.
As the real-time speed of a motor vehicle v that step 3 collects
hduring for low speed, and real time acceleration a
hchange frequency be greater than change frequency threshold value, acceleration a
hchange peak value be greater than change peak threshold time, determine automobile current be road conditions driving behavior of jolting.
As the real time acceleration a that step 3 collects
hwhen being greater than 1 acceleration of gravity, determine that automobile is collision driving behavior.
In step 3, described correlation data is recorded as at least 3 correlation datas, chooses the average acceleration in same gear interval and same rotating speed interval in each correlation data successively
contrast, the correlation data of numerical approximation is judged as the correlation data of identical transport condition, then the quantity of the correlation data of identical transport condition is contrasted, the correlation data of what the correlation data quantity of identical transport condition was maximum is automobile transport condition in the unloaded state, i.e. light condition correlation data;
Extract the average acceleration of unloaded state vs's data in same gear interval and same rotating speed interval
with the average acceleration in load condition correlation data
obtain duty ratio r.
Another object of the present invention is to provide a kind of drive automatically behavior judgment means, described driving behavior judgment means comprises:
Acquisition module, for being connected with automobile OBD interface, gathering running car data, namely gathering the running car data of automobile under level road, state of giving it the gun;
Computing module, accepts the data gathered of acquisition module, and calculates according to the data gathered, and obtains correlation data, sets up contrast matrix;
Judge module, is connected with acquisition module and computing module respectively, for receiving the automobile real time status information that acquisition module collects, contrasting, judge driving behavior with the contrast matrix in computing module.
Described driving behavior judgment means also comprises:
Signal transmission module, is connected with judge module, for receiving the bad steering behavioural information that judge module sends, and bad steering information is sent to Surveillance center;
Surveillance center, for the bad steering behavior of Received signal strength transport module, line item of going forward side by side;
GPS locating module, for locating and detect the traveling rail mark of automobile.
Technique effect of the present invention is as follows: adaptive driving behavior analysis method of the present invention, in vehicle traveling process, continuous collection running car data, the rotating speed Ω etc. of such as acceleration a, speed of a motor vehicle v and engine, comprise various transport condition, can set up the benchmark that driver driving behavior judges fully, the data of collection are more, this benchmark more can react the normal driving behavior of driver, also just can contrast the bad steering behavior of driver;
In step, each automobile all can Resurvey data after becoming mobile status from halted state, automobile is from stopping to mobile status, very likely there is the change of dead weight capacity, as empty wagon stops, starting after load-carrying, the different load condition of automobile also can be different for the judgement of driving behavior, therefore, after becoming mobile status from stopping, Resurvey data, make this method can adapt to the different load condition of automobile.
Data gathered in addition are the data of state of giving it the gun on level road, and under level road gives it the gun state, the complete connection status of whole kinematic train process, can show the most real ratio of gear, can calculate ratio of gear the most accurately.Under level road, also the most real acceleration can be shown.Therefore can collect very accurately rational car steering information under level road, be convenient to step 2 calculating and obtain correlation data accurately.
Gear is divided by ratio of gear interval in step 2, also delimit rotating speed interval simultaneously, form the judgment matrix of correlation data, correspondence goes out the value of the interval acceleration a in different rotating speeds interval of each gear, good compatibility stepless speed-change automobile and step speed change automobile, make that acceleration a is interval at each gear, rotating speed interval in have different values, the reference value of stepless speed-change automobile under free position can be reacted, the well compatible judgment standard of stepless speed-change automobile and step speed change automobile;
Step 3 gathers real time acceleration real-time rotate speed Ω
h, real time acceleration a
h, real-time speed of a motor vehicle v
h, by real-time ratio of gear δ
hbefore matching in judgment matrix, contrast, effectively improve judgement precision.
Accompanying drawing explanation
Fig. 1 is automobile force analysis schematic diagram on the slope;
Fig. 2 is driving behavior judgment means structural representation of the present invention.
In figure, 1 is automobile, and 2 for travelling plane, and 3 is surface level.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
For stepless automatic transmission car, more detailed description is done to the present invention in the present embodiment.
Embodiment 1
As shown in Figure 2, the present embodiment judges car steering behavior by car steering behavior judgment means, and driving behavior judgment means comprises:
Acquisition module, for being connected with automobile OBD interface, gather running car data, namely gather acceleration a, the speed of a motor vehicle v of automobile under level road, state of giving it the gun, the rotating speed Ω of engine, gas pedal degree of depth L, brake pedal degree of depth K, steering wheel angle;
Computing module, accepts the data gathered of acquisition module, and calculates according to the data gathered, and obtains correlation data, sets up contrast matrix.
Judge module, is connected with acquisition module and computing module respectively, for receiving the automobile real time status information that acquisition module collects, contrasting, judge driving behavior with the contrast matrix in computing module.
Signal transmission module, is connected with judge module, for receiving the bad steering behavioural information that judge module sends, and bad steering information is sent to Surveillance center;
Surveillance center, for the bad steering behavior of Received signal strength transport module, line item of going forward side by side.
GPS locating module, for locating and detect the driving trace of automobile.
The invention provides a kind of adaptive driving behavior analysis method, its step is as follows:
Step one, data acquisition, after automobile becomes mobile status from halted state, with Fixed Time Interval harvester motor vehicle data, the data gathered are the rotating speed Ω of acceleration a, speed of a motor vehicle ν and the engine of automobile under level road gives it the gun state, and filtering is carried out to gathered data, the obvious irrational data of filtration fraction;
Wherein, the data acquiring frequency of acceleration a is 1 ~ 50 milli second/time, the acceleration that continuous acquisition is N time, N be greater than 1 natural number, get the mean value of this N time acceleration, obtain acceleration a.In the present embodiment, prioritizing selection frequency acquisition is 10 millis second/time, N=50.The frequency acquisition of other data is 10 × 50=500 milli second/time, namely 0.5 second/time.
Level road be angle of inclination be in ± 3 degree between road surface.
Step 2, data processing, obtain correlation data, first collects according to step one and often organize speed of a motor vehicle ν, engine speed Ω, calculate ratio of gear
ratio of gear δ from big to small or interval from the little gear to being divided into m equal length successively, get m=5, rotating speed Ω is divided into n rotating speed interval, gets n=6, determine that automobile is interval at each gear, the average acceleration in each rotating speed interval according to the acceleration a that step one collects
then the average acceleration in each gear interval is got
maximal value, obtain peak acceleration a
max;
Step 3, Data Comparison, gather the real-time rotate speed Ω of automobile
h, real time acceleration a
h, real-time speed of a motor vehicle v
h, according to ratio of gear
calculate real-time ratio of gear δ
h, by real-time ratio of gear δ
hbe matched to gear corresponding in step 2 interval, the real-time rotate speed Ω gathered
h, real time acceleration a
h, real-time speed of a motor vehicle v
hthe correlation data obtained with step 2 contrasts, and determines whether the driving behavior of automobile is suddenly accelerate driving behavior, anxious driving behavior of slowing down, collision driving behavior.
Adaptive driving behavior analysis method of the present invention, in vehicle traveling process, continuous collection running car data, the rotating speed Ω etc. of such as acceleration a, speed of a motor vehicle v and engine, comprise various transport condition, can set up the benchmark that driver driving behavior judges fully, the data of collection are more, this benchmark more can react the normal driving behavior of driver, also just can contrast the bad steering behavior of driver;
In step, each automobile all can Resurvey data after becoming mobile status from halted state, automobile is from stopping to mobile status, very likely there is the change of dead weight capacity, as empty wagon stops, starting after load-carrying, the different load condition of automobile also can be different for the judgement of driving behavior, therefore, after becoming mobile status from stopping, Resurvey data, make this method can adapt to the different load condition of automobile.
Data gathered in addition are the data of state of giving it the gun on level road, and under level road gives it the gun state, the complete connection status of whole kinematic train process, can show the most real ratio of gear, can calculate ratio of gear the most accurately.Under level road, also the most real acceleration can be shown.Therefore can collect very accurately rational car steering information under level road, be convenient to step 2 calculating and obtain correlation data accurately.
Gear is divided by ratio of gear interval in step 2, also delimit rotating speed interval simultaneously, form the judgment matrix of correlation data, correspondence goes out the value of the interval acceleration a in different rotating speeds interval of each gear, good compatibility stepless speed-change automobile and step speed change automobile, make that acceleration a is interval at each gear, rotating speed interval in have different values, the reference value of stepless speed-change automobile under free position can be reacted, the well compatible judgment standard of stepless speed-change automobile and step speed change automobile.
Step 3 gathers real time acceleration real-time rotate speed Ω
h, real time acceleration a
h, real-time speed of a motor vehicle v
h, by real-time ratio of gear δ
hbefore matching in judgment matrix, contrast, effectively improve judgement precision.Adaptive driving behavior analysis method of the present invention, in vehicle traveling process, continuous collection running car data, the rotating speed Ω etc. of such as acceleration a, speed of a motor vehicle v and engine, comprise various transport condition, can set up the benchmark that driver driving behavior judges fully, the data of collection are more, this benchmark more can react the normal driving behavior of driver, also just can contrast the bad steering behavior of driver.
Hand gear is compared with automatic stepless speed change, and because the connection for transmission of hand gear is than stepped distribution, the data by gathering calculate the ratio of gear of each gear, therefore in gear interval division, follow gear and arrange division.Hand gear and step speed change automobile very conveniently can find out the ratio of gear of each gear, are convenient to separate suitable gear interval.
Collision judgment:
Judge module contrast real time acceleration, as the real time acceleration a of Real-time Collection
hwhen being greater than 1 g, be judged to be collision, g is gravity acceleration value.
Rotating speed judges:
In step 3, when the real-time rotate speed Ω h collected is more than or equal to rotary speed threshold value Ω m, judge module determination automobile is current accelerates driving behavior for anxious, and rotary speed threshold value Ω m is 3000 ~ 4000 revolutions per seconds.
Suddenly accelerate to judge:
In step 3, real time acceleration a
hwith the acceleration a in gear interval same in table 2
max, acceleration factor λ
1contrast, when real time acceleration ah is greater than acceleration factor λ
1with acceleration a
maxlong-pending, determine that automobile is current and accelerate driving behavior for anxious; Described acceleration factor λ
1be 0.5≤λ
1< 1, in the present embodiment, preferentially selects λ
1=0.7.
Suddenly to slow down judgement
In step 3, real time acceleration a
hwith the peak acceleration a in same gear interval
max, acceleration factor λ
2contrast, as real time acceleration a
hbe greater than acceleration factor λ
1with acceleration a
maxlong-pending, determine automobile current be anxious driving behavior of slowing down, described acceleration system λ
2be 1≤λ
2< 4.In the present embodiment, preferentially select λ
2=0.7.
The gas pedal degree of depth judges:
Correlation data also comprises the gas pedal degree of depth, and set for judging the anxious gas pedal degree of depth L accelerated, step 3 also gathers real-time gas pedal degree of depth L
h, work as L
hduring > L, determine that automobile is current and accelerate driving behavior for anxious.
The brake pedal degree of depth judges:
Correlation data also comprises the brake pedal degree of depth, and set for judging the anxious brake pedal degree of depth K slowed down, described step 3 also gathers real-time brake pedal degree of depth K
h, work as K
hduring > K, determine automobile current be anxious driving behavior of slowing down.
Zig zag judges:
Step 2 comprises the acceleration a calculating and obtain along vehicle traveling direction
m, described acceleration a
mfor adjacent two differences of speed and the ratio of interval time,
V
1, v
2for the adjacent real-time speed of a motor vehicle gathered, Δ t is the acquisition time interval of the adjacent speed of a motor vehicle.
During turning, the acceleration a measured by sensor equals centripetal acceleration a
towith along vehicle traveling direction acceleration a
mvector, calculate centripetal acceleration
substitution formula 1 can try to achieve a
to.
In step 3, centripetal acceleration a
towith the peak acceleration a in same gear interval
max, acceleration factor λ
3contrast, works as a
to> λ
3a
maxtime, 1 < λ
3< 4, determine automobile current for zig zag driving behavior, in the present embodiment, preferentially select λ
3=2.
In addition, step one also gathers rotating of steering wheel angular velocity, when the speed of a motor vehicle is greater than 50km/h, and when bearing circle angle per second is greater than 30 °, is judged to be zig zag.
Road conditions of jolting transport condition judges:
As the real-time speed of a motor vehicle v that step 3 collects
hduring for low speed, and real time acceleration a
hchange frequency be greater than change frequency threshold value, acceleration a
hchange peak value be greater than change peak threshold time, determine automobile current be road conditions driving behavior of jolting.
Duty ratio calculates:
Described correlation data is recorded as at least 3 correlation datas, and the present embodiment preferentially records 10 groups
Choose the average acceleration in same gear interval and same rotating speed interval in each correlation data successively
contrast, the correlation data of numerical approximation is judged as the correlation data of identical transport condition, then the quantity of the correlation data of identical transport condition is contrasted, the correlation data of what the correlation data quantity of identical transport condition was maximum is automobile transport condition in the unloaded state, i.e. light condition correlation data;
Extract the average acceleration of unloaded state vs's data in same gear interval and same rotating speed interval
with the average acceleration in load condition correlation data
In the unloaded state
In the loaded state
With gear district with the interval F of rotating speed
2=F
1
Duty ratio can be obtained
In the present embodiment, Surveillance center receives and the delivery module transmission the adding up driving behavior judgment means data of returning, and for driver, by the statistical study to driving behavior, clearly can know the driving habits of driver.
Hand gear sets up the partitioned matrix of 5 × 7 the data in each gear interval and rotating speed interval,
wherein
δ
zxyfor the mode ratio of gear in an xth rotating speed interval and y gear interval, a
xyfor the accekeration in an xth rotating speed interval and y gear interval, 1≤x≤5,1≤y≤7.
Can set up a data model being convenient to compare by matrix model, accelerate to compare speed, hand gear is identical at driving behavior decision method with stepless automatic transmission.
Above-mentioned matrix model is as follows:
For stepless speed-change automobile, the ratio of gear δ of collection is divided into five gear intervals, such as δ ≈ 20 ~ 100, and namely obtaining gear interval is the interval δ of the first gear
1the interval δ of=100 ~ 84, second gear
2=84 ~ 68, the interval δ of third gear
3=68 ~ 52, the interval δ in fourth speed position
4=52 ~ 36, the interval δ in fifth speed position
5=36 ~ 20,
For manual transmission cars or automatic transmission transmission cars, ratio of gear is in approximate stepped change, and the ratio of gear of each ladder approximates fixed value;
For 5 grades of Audi A6 automatic gearshift automobiles, ratio of gear δ is divided into the interval δ of the first gear by gear
1the interval δ of ≈ 100, second gear
2≈ 60, the interval δ of third gear
3≈ 40, the interval δ in fourth speed position
4≈ 30, the interval δ in fifth speed position
5≈ 20,
Rotating speed Ω is divided into n rotating speed interval, n=6, rotating speed length of an interval degree is 500, transfers first interval to 1000 ~ 1500, and next interval is 1500 ~ 2000 turns, Ω
1to Ω
6represent the first rotating speed respectively successively interval interval to the 6th rotating speed.
Determine that automobile is interval at each gear, the average acceleration in each rotating speed interval according to the acceleration a that step one collects
obtain following data:
Table 1
Get the average acceleration in each gear interval
maximal value, obtain peak acceleration a
max;
Peak acceleration a
maxas follows:
| a max | |
| δ 1 | 90 |
| δ 2 | 76 |
| δ 3 | 65 |
| δ 4 | 56 |
| δ 5 | 49 |
Table 2
Embodiment 2
Compared with embodiment 1, the step 2 of the present embodiment also comprises the angle theta calculating domatic and surface level.
When automobile 1 stops or travelling on surface level 3, the mounting plane of acceleration transducer on automobile 1 is parallel to surface level 3 on request, therefore the mounting plane of acceleration transducer is parallel to the traveling plane 2 of described automobile 1 on domatic arbitrarily, the actual sensor actual measureed value of acceleration recorded of such acceleration transducer
be vehicle actual measureed value of acceleration
equal, namely
The domatic mechanical analysis to automobile 1 as shown in Figure 1, it is in the traveling plane 2 of θ that automobile 1 travels on the domatic angle of surface level 3.Set up automobile three-dimensional cartesian coordinate system, its x, y-axis place plane is parallel to domatic, and z-axis is perpendicular to the traveling plane 2 of automobile 1.Because the mounting plane of acceleration transducer is parallel to the traveling plane 2 of described automobile 1 on domatic arbitrarily, therefore the three-dimensional vehicle coordinate system of automobile 1 and the three-dimensional cartesian coordinate system of acceleration transducer are the same coordinate system.In the present embodiment, acceleration transducer use gamut, namely x, y, z tri-axle all use.
The sensor actual measureed value of acceleration of acceleration transducer
can observe and obtaining, and this vehicle actual measureed value of acceleration
for acceleration of gravity
with the actual output acceleration of automobile 1
vector, namely
It is π-θ that gravity accelerates with domatic normal angle, vehicle actual measureed value of acceleration
corresponding triangle angle is π+θ.
And cos π+θ=-sin θ.
Wherein can be obtained by leg-of-mutton cosine formula by the force analysis of automobile 1:
In addition, no matter be that motor vehicle engine exports acceleration, brake acceleration and side-friction when turning round, the output acceleration of motor vehicle all derives from (comprising traction acceleration and braking acceleration etc.) friction force of wheel after all, and this friction force is always present in the plane at automobile 1 place, therefore can draw, vehicle actual measureed value of acceleration
component in z-axis and acceleration of gravity
component in z-axis is equal, therefore has:
if vehicle actual measureed value of acceleration
projection value in z-axis is z
1, it measures the sensor actual measureed value of acceleration acceleration obtained
the z-axis value that Observable obtains, and acceleration of gravity
projection value in z-axis is
therefore
thus domatic angle θ and vehicle actual measureed value of acceleration gravity acceleration value can be obtained
with z-axis projection value z
1pass be:
Obtain θ,
θ is the angle of automobile 1 track and surface level, is plane road conditions when θ=0.
θ ≠ 0, automobile 1 travels in upward slope or descending road conditions.
The actual output accekeration of automobile 1 simply and accurately can be obtained by above-mentioned formula 1 and formula 2
namely a asked
m.
Work as a
mduring > a, automobile 1 accelerates descending or slows down to go up a slope, a
m< a then goes up a slope or deceleration descending for accelerating.
Work as a
mduring > a, collect the gas pedal degree of depth, and a
h> 0.7a
max, be judged to suddenly to accelerate descending; a
mduring > a, collect the brake pedal degree of depth, a
h> 0.7a
max, be judged to be anxious deceleration descending; a
mduring < a, collect the gas pedal degree of depth, and a
h> 0.5a
max, be judged to be that anxious acceleration is gone up a slope; a
mduring < a, collect the gas pedal degree of depth, and a
h> 0.5a
max, be judged to be anxious deceleration descending.
Ascents and descents is road conditions important and dangerous in vehicle traveling process, and the urgency for ascents and descents is accelerated, anxious judgement of slowing down is particularly important.The present embodiment can be understood according to car steering information the urgency that climb and fall is fast and accelerate and anxious deceleration behavior.
Claims (10)
1. a drive automatically behavior analysis method, is characterized in that, comprises the steps:
Step one, image data, after automobile becomes mobile status from halted state, gather acceleration alpha, speed of a motor vehicle ν and the engine speed Ω of automobile under level road, state of giving it the gun;
Step 2, acquisition correlation data, first collect according to step one and often organize speed of a motor vehicle ν, engine speed Ω, δ is compared in the transmission that acquisition automobile is often organized, then ratio of gear δ is divided into m gear interval, rotating speed Ω is divided into n rotating speed interval, determines that automobile is interval at each gear, the average acceleration in each rotating speed interval according to the acceleration a that step one collects
then the average acceleration in each gear interval is got
maximal value, obtain peak acceleration a
max;
Step 3, Data Comparison, gather the real-time rotate speed Ω of automobile
h, real time acceleration a
h, real-time speed of a motor vehicle v
h, obtain real-time ratio of gear δ
h, by real-time ratio of gear δ
hbe matched to gear corresponding in step 2 interval, the real-time rotate speed Ω gathered
h, real time acceleration a
h, real-time speed of a motor vehicle v
hthe correlation data obtained with step 2 contrasts, and determines the driving behavior of automobile.
2. a kind of drive automatically behavior analysis method as claimed in claim 1, is characterized in that, in step 3, as the real-time rotate speed Ω collected
hbe more than or equal to rotary speed threshold value Ω
mtime, determine that automobile is current and accelerate driving behavior, rotary speed threshold value Ω for anxious
mit is 3000 ~ 4000 revolutions per seconds.
3. a kind of adaptive driving behavior analysis method as claimed in claim 1 or 2, is characterized in that, in described step 3, and real time acceleration a
hwith the acceleration a in same gear interval
max, acceleration factor λ
1contrast, as real time acceleration a
hbe greater than acceleration factor λ
1with acceleration a
maxlong-pending, determine that automobile is current and accelerate driving behavior for anxious; Described acceleration factor λ
1be 0.5≤λ
1< 1.
4. a kind of drive automatically behavior analysis method as claimed in claim 1 or 2, is characterized in that, in described step 3, and real time acceleration a
hwith the peak acceleration a in same gear interval
max, acceleration factor λ
2contrast, as real time acceleration a
hbe greater than acceleration factor λ
2with acceleration a
maxlong-pending, determine automobile current be anxious driving behavior of slowing down, described acceleration system λ
2be 1≤λ
2< 4.
5. a kind of drive automatically behavior analysis method as claimed in claim 1 or 2, is characterized in that, in step 3, gathers real-time centripetal acceleration a
towith the peak acceleration a in same gear interval
max, acceleration factor λ
3contrast, as real-time centripetal acceleration a
tobe greater than acceleration factor λ
3with acceleration a
maxlong-pending, determine automobile current be zig zag driving behavior, described acceleration system λ
3be 1 < λ
3< 4.
6. a kind of drive automatically behavior analysis method as claimed in claim 1, is characterized in that, as the real-time speed of a motor vehicle v that step 3 collects
hduring for low speed, and real time acceleration a
hchange frequency be greater than change frequency threshold value, acceleration a
hchange peak value be greater than change peak threshold time, determine automobile current be road conditions driving behavior of jolting.
7. a kind of drive automatically behavior analysis method as claimed in claim 2, is characterized in that, as the real time acceleration a that step 3 collects
hwhen being greater than 1 acceleration of gravity, determine that automobile is collision driving behavior.
8. a kind of drive automatically behavior analysis method as claimed in claim 1, it is characterized in that, in step 3, described correlation data is recorded as at least 3 correlation datas, chooses the average acceleration in same gear interval and same rotating speed interval in each correlation data successively
contrast, the correlation data of numerical approximation is judged as the correlation data of identical transport condition, then the quantity of the correlation data of identical transport condition is contrasted, the correlation data of what the correlation data quantity of identical transport condition was maximum is automobile transport condition in the unloaded state, i.e. light condition correlation data;
Extract the average acceleration of unloaded state vs's data in same gear interval and same rotating speed interval
with the average acceleration in load condition correlation data
obtain duty ratio r.
9. a drive automatically behavior judgment means, is characterized in that, described driving behavior judgment means comprises:
Acquisition module, for being connected with automobile OBD interface, gathering running car data, namely gathering the running car data of automobile under level road, state of giving it the gun;
Computing module, accepts the data gathered of acquisition module, and calculates according to the data gathered, and obtains correlation data, sets up contrast matrix;
Judge module, is connected with acquisition module and computing module respectively, for receiving the automobile real time status information that acquisition module collects, contrasting, judge driving behavior with the contrast matrix in computing module.
10. a kind of drive automatically behavior judgment means as claimed in claim 9, its feature exists, and described driving behavior judgment means also comprises:
Signal transmission module, is connected with judge module, for receiving the bad steering behavioural information that judge module sends, and bad steering information is sent to Surveillance center;
Surveillance center, for the bad steering behavior of Received signal strength transport module, line item of going forward side by side;
GPS locating module, for locating and detect the driving trace of automobile.
Priority Applications (1)
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| CN112014593A (en) * | 2019-05-28 | 2020-12-01 | 浙江德盛铁路器材股份有限公司 | Device and method for monitoring and evaluating quality condition of railway track basic equipment |
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