CN108304774A - A method of evaluation main line greenbelt characteristic influences driver's vision - Google Patents
A method of evaluation main line greenbelt characteristic influences driver's vision Download PDFInfo
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Abstract
The present invention is a kind of method that evaluation main line greenbelt characteristic influences driver's vision, step：Eye tracker is worn with driver and drives vehicle traveling, is recorded a video with eye tracker and records driver's eye movement situation；Video guide is entered into eye tracker analysis software, carry out the divisions such as trunk visibility region of interest, hat width region of interest, the high region of interest of tree, tree-like region of interest, sky ratio region of interest, each region of interest blinkpunkt number is analyzed and exports, the value characterized by the corresponding region of interest blinkpunkt number of a certain specific greenbelt index accounts for the ratio of all index blinkpunkt numbers；Build the relationship between greenbelt Index Influence angle value y and each index value of greenbeltx1For height value, x2For tree-like index value, x3For hat width and the ratio between have a lot of social connections, x4For sky ratio, x5For trunk visibility index value, x6For spacing in the rows value；Independent variable, that is, greenbelt index value x is inputted in SPSS softwaresiWith corresponding characteristic value yi, solve undetermined constant a, b, c, d, e, f, g.
Description
Technical field
The present invention relates to a kind of methods that evaluation main line greenbelt influences driver's vision, belong to traffic safety skill
Art field.
Background technology
Show that urban traffic accident quantity was in rising trend in recent years through investigation, statistics shows by driving human and environment
Composite factor cause traffic accident rate and account for about 1/3,90% driving information is obtained by vision in driver's driving conditions
, and very big proportion is accounted in the first field of view pergola on the city road area of driving a vehicle, urban arterial road greenbelt is as city road
A kind of recessive effect factor of road traffic safety is often ignored.For a long time, green for being related to the city of traffic safety
Change band research, is concentrated mainly on and color, monotonicity etc. are analyzed, lack commenting in terms of driver's vision effect
Valence.Therefore, need to develop a kind of function more comprehensively, the relevant technologies and side that greenbelt influences driver's vision can be evaluated
Method improves the safety of vehicle traveling to reduce negative effect of the road landscape environment to driver.
Invention content
The object of the present invention is to provide a kind of method that the evaluation multiple index values of greenbelt influence driver's vision, the party
Method is objective, accurate, and intuitively reflects greenbelt to the influence to driver's vision with quantification manner, can be to build, repair
Whole greenbelt provides the quantization reference standard of more science.
The method that evaluation main line greenbelt characteristic of the present invention influences driver's vision, it includes the following steps：
1) with driver wear eye tracker drive vehicle on road with constant speed drive, with eye tracker to driver before
The square visual field is recorded a video, while recording driver's eye movement situation；
2) video guide that eye tracker records is entered into eye tracker analysis software, and carries out following interest Division：Trunk is visual
Degree region of interest is that driver is clearly discernible tree body trunk, the region that leaf does not block in the first visual angle；The region of interest of hat width
Trunk visibility region of interest is divided into extend diameter outermost region up to tree body；It sets high region of interest and is divided into hat width interest
Area is with up to tree body highest point region；Tree-like region of interest is divided into tree body outer profile and extends to section region；Sky ratio interest
Zoning is divided into above the first visual angle of driver sky without vegetation occlusion area；Each region of interest is non-overlapping and need to completely cover
All viewable portions of road green belt；
3) it utilizes eye tracker analysis software and exports the blinkpunkt number of each region of interest；It is a certain specific green with the road
The ratio that change accounts for all index blinkpunkt numbers with the corresponding region of interest blinkpunkt number of index is characterized value.All indexs are watched attentively
Point number, that is, all region of interest blinkpunkt number and.If the corresponding region of interest one of a certain specific greenbelt index, this
The blinkpunkt number of one region of interest is exactly the corresponding region of interest blinkpunkt number of the specific greenbelt index.A certain specific greening
If the corresponding region of interest two of band index, the blinkpunkt number of the two region of interest be exactly that the specific greenbelt index is corresponding
Region of interest blinkpunkt number.
4) relationship between greenbelt Index Influence angle value y and each index value of greenbelt is built：
In formula, a, b, c, d, e, f, g are undetermined constant；x1For height value, i.e., trees from ground upwardly to treetop away from
From unit m；x2For tree-like index value, the space structure of tree-like i.e. trees is divided into steeple shape, spherical shape, umbrella shape, with driver
The product determination of sighting distance and the above tangible part area of trunk at driver visual angle, unit m3；x3For hat width and the ratio between have a lot of social connections,
Trees hat width is the average value in trees north and south and east-west direction width；x4For sky ratio, i.e., have at the first visual angle of driver
Effect sky area accounts for the ratio of the driver visual field gross area, dimensionless；x5For trunk visibility index value, with driver's sighting distance with
The product of visual trunk area determines at driver visual angle, unit m3；x6For spacing in the rows value, i.e., the spacing distance of adjacent two trees,
Unit is m；
5) independent variable, that is, greenbelt index value x is inputted in SPSS softwaresi, dependent variable is corresponding with greenbelt index value
Characteristic value yi, solve undetermined constant.
Program in relation to solving undetermined constant：
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA COLLIN TOL
/ CRITERIA=PIN (.05) POUT (.10)
/NOORIGIN
/ DEPENDENT influence values
/ METHOD=ENTER x1x2x3x4(...)
/ SCATTERPLOT=(* ZRESID, * ZPRED)
/RESIDUALS DURBIN HISTOGRAM(ZRESID)NORMPROB(ZRESID).
Evaluation model under friction speed：
It is described as the further improvements in methods influenced on driver's vision on the evaluation main line greenbelt characteristic
Step 4) is：Build the relationship between greenbelt Index Influence angle value y and each index value of greenbelt：
In formula, i, h are constant to be defined, vSpeedFor highway layout speed.
As the further improvements in methods influenced on driver's vision on the evaluation main line greenbelt characteristic, step
3) in, using eye tracker analysis software and when exporting the blinkpunkt number of each region of interest, the video intercepting time is 20s left
The right side need to select vehicle without the section of primary cross mouth when carrying out video intercepting.
As the further improvements in methods influenced on driver's vision on the evaluation main line greenbelt characteristic, step
1) in, vehicle is surveyed under the constant speed of 40km/h, 45km/h, 50km/h, 55km/h, 60km/h respectively in same a road section
Examination.
It is described as the further improvements in methods influenced on driver's vision on the evaluation main line greenbelt characteristic
Eye tracker is Sweden's Tobii Glasses eye trackers, which is ErogLAB.
As the further improvements in methods influenced on driver's vision on the evaluation main line greenbelt characteristic, divide
Influence the grade of angle value y；According to driver's point system and expert graded, the specific section of the grade classification of disturbance degree y is formulated；
Grade interval is divided into that visual effect is suitable, visual effect is general, bad 3 part of visual effect；Greenbelt is judged on this basis
Whether build reasonable.
Beneficial effects of the present invention：
This appraisement system carries out road experiment on real vehicle using eye tracker experimental method, and driver's blinkpunkt is captured by eye tracker
It falls in the position and track of greenbelt, to scientifically analyze the fixation distribution of driver in the process of moving, rejects subjective
Influence of the factor to experimental result.It can be judged with this method and have whether greenbelt can generate driver's vision effect
The influence of degree gives relevant departments' a certain amount reference standard when building, modifying greenbelt, is allowed to Rational choice greenbelt
The specific level of each index ensures the stability of driving to give the comfortable aesthetic method of driver and vigilance appropriate and excitement.
Description of the drawings
Fig. 1 is the tree-like schematic diagram of steeple shape；
Fig. 2 is spherical tree-like schematic diagram；
Fig. 3 is the tree-like schematic diagram of umbrella shape；
The interest Division schematic diagram of Fig. 4；
Fig. 5 returns the normal state P-P figures of standardized residual.
Specific implementation mode
1. appraisement system forms
1.1 evaluation object
This method be suitable for it is visual in the first visual angle of driver to typical dry strip ARC band, can survey (including directly or
The method that connects measures or estimation), comparable, quantifiable index evaluated, and the index need to generate driver certain regard
Feel stimulation.Such as height, hat width, trunk visibility, sky ratio, the spacing in the rows etc. of greenbelt.
Instrument and personnel needed for 1.2
1) hardware device：Camera；Laser range finder；Reflector；Meter ruler；Colorimetric card；(Tobii can be used in eye tracker
Glasses) etc..
2) analysis software：SPSS；ErogLAB (is indicated：The product is that Sweden's Tobii Glasses eye trackers are mating soft
Part)；EXCEL etc..
3) personnel needed for：Experienced driver is several, it is desirable that comprehensive from many-sided progress such as its driving age, age, gender
It closes and considers.
2. evaluation procedure
2.1 Delphi method are to greenbelt index screening
Since greenbelt index covering scope is larger, if all carrying out quantitative analysis to each index, experiment is increased
Workload and complexity.Greenbelt vegetation for different plantation forms, type is not to the visual impact degree of driver
With, therefore specified link can pointedly be analyzed.This appraisement system carries out greenbelt index using Delphi method
Screening, this method mainly drafts application form by investigator, according to blas, respectively to panel member in a manner of letters
It is consulted；And panel member's (letters) in a manner of anonymous submits opinion.By consulting and feeding back, expert repeatedly several times
The opinion of group membership gradually tends to concentrate, and finally obtains collective's judging result with very high-accuracy.The system of expert estimation table
Fixed must include the specific explanations to evaluation metrics, and template is as shown in table 1, invite the expert for having related work, research experience to choosing
Greenbelt indices by way of road are evaluated, and in conjunction with the obvious index feature difference of different tree species, drive visual angle and season
The index that the influence factors such as section alternating provide each greenbelt carries out the scoring of concrete numerical value.Standards of grading are：It influences very
Greatly 100 points, be affected for 75 points, influence generally 50 points, influence smaller to be 25 points, almost without influencing to be 0 point.
Visual impact Delphi method expert estimation table of the 1 greenbelt index of table to driver
After waiting for grade form receipt, expert opinion is subjected to comprehensive analysis, the intensity and variation lines of parameter
Number.Finally, it is larger to choose intensity, the smaller index of the coefficient of variation.
1) intensity
In formula, MjFor the intensity of i-th of index expert opinion, its size determines the significance level of index；mjTable
Show the score value for participating in j-th of index；CijIndicate the score value of i-th of expert couple, j-th of index.
2) coefficient of variation
In formula, σiTo indicate standard deviation of the expert to jth；VjIndicate the coefficient of variation, that the coefficient of variation mainly reflects is expert
The coordination degree (i.e. the convergent of expert opinion) of opinion is the important indicator for representing evaluation relative fluctuation size.Variation lines
Number is smaller, then represents expertise and more concentrate.
The quantitative analysis of 2.2 greenbelt indexs
After index screening, data on the spot need to be carried out to the index for testing road and acquired, with related tool, instrument
Quantitative analysis is carried out to it.
Greenbelt height marker can be carried out by laser range finder, using triangle hook stock principle (bow, the elevation angle and it is horizontal away from
From) measuring tree body height, measurement result is as unit of rice.
The hat width index of greenbelt can be by crown mapping measurement method, it is assumed that tree crown on the ground be projected as ellipse,
Elliptical long axis and short axle are measured, takes mean value, measurement result is as unit of rice.
Greenbelt spacing in the rows index can be measured by laser range finder and mating reflector, between two adjacent tree bodies away from
From as spacing in the rows, measurement result is as unit of rice.
Greenbelt sky ratio index can be recorded a video at the first visual angle of driver by camera, shielded after video recording
The measurement for carrying out sky area and entire picture area ratio when being played on curtain to each frame picture using square method, takes mean value.
Greenbelt trunk visibility index determining, since driver is different at a distance from tree body, trunk visibility is in driving
The visual perception of people is also different.Distance is closer, then tree body can seem relatively large, conversely, then relatively small.Therefore, it sets
Dry visibility is determined with the product of visual trunk area at the sighting distance of driver and driver visual angle.
The measurement of the tree-like index of greenbelt, is determined according to the outer contour shape of tree body, and conventional arterial highway shade tree is tree-like
It is broadly divided into steeple shape (Fig. 1), spherical (Fig. 2), umbrella shape (Fig. 3).It is identical with trunk visibility measuring principle, it is regarded with driver
Away from the determination of the product of the above tangible part area of trunk at driver visual angle.
2.3 eye tracker real train tests determine index feature value
On real vehicle road experiment should with driving safety under the premise of carry out, experimental subjects wear eye tracker carry out viewpoint to medium
A series of preparations drive vehicle to road driving to be evaluated, and Observation personnel is sitting in copilot station and is responsible for carrying out experiment software
Unlatching, when reaching target road open software recorded a video and record driver's vision changing condition；It is driven out to target road
When, check whether software data record completely carries out Saving and Closing eye tracker.For analyze at various speeds greenbelt to driving
The visual impact of people is sailed, driver need to change speed after same road driving and continue to test.According to《Urban road is set
Count specification》(CJJ37-2016) arterial street designed driving speed be 40-60km/h, driver become running speed, respectively with
40km/h, 45km/h, 50km/h, 55km/h, 60km/h are tested.
After experiment, the video that eye tracker is recorded imports ErogLAB softwares, carries out interest Division, and video is cut
It takes the time to be advisable with 20s or so, vehicle need to be selected without primary cross mouth and road traffic state when carrying out video intercepting
Change little section, give up the road sections part for having traffic abnormity, in primary cross mouth, crossing, large-scale public is provided
The positions such as entrance need to individually intercept video.Interest Division (Fig. 4) is introduced for one main line of the cities Xian Yimou：
Set high region of interest 1,7；Hat width region of interest 2,8；Trunk visibility region of interest 3,9；Tree-like region of interest 4,6；Sky ratio
Example region of interest 5.The region of interest 3,9 of trunk visibility is divided into figure is clearly discernible tree body trunk in the first visual angle of driver,
The region that leaf does not block.The region of interest 2,8 of hat width is divided into trunk visibility region of interest to extend diameter most up to tree body
The regions Wai Chu.It sets high region of interest 1,7 and is divided into hat width region of interest with up to tree body highest point region.4,6 strokes of tree-like region of interest
It is divided into tree body outer profile and extends to section region.Sky ratio region of interest 5 be divided into above the first visual angle of driver sky without
Vegetation occlusion area.Other indexs can concrete foundation real road situation, greenbelt feature divided, but require region of interest not
It can be overlapped and need completely all viewable portions of covering path greenbelt.For example, the region of interest of greenbelt spacing in the rows index is two-phase
Gap portion between adjacent trees, but gap portion can not expand to non-motorized lane or pavement region.
After interest Division, driver's fixation distribution figure and hotspot graph can be automatically generated.Utilize software itself
Statistic tools can export the blinkpunkt number of each region of interest.In all after watching point analysis attentively of road of experiment, with this
The corresponding region of interest blinkpunkt number of a certain specific greenbelt index of road accounts for all index blinkpunkt number (i.e. all region of interest
Blinkpunkt number and) ratio be characterized value.
The foundation of 2.4 evaluation models
Model establishes process and can be divided into following three steps：
1) experimental data, rejecting abnormalities data are analyzed
This evaluation model be using phytometer value as independent variable, characteristic value be dependent variable on the basis of establish.It is commented for enhancing
The usability of valence result and accuracy reject abnormal data with Grubbs methods of inspection.It calculates in different drivers'
The average value of the characteristic value of identical indexAnd standard deviation S.G values are calculated, according to number and confidence level requirement is measured, are looked into
Grubbs check tables (table 2).Compare GIt calculatesWith GTableIf GIt calculates＞ GTable, reject, on the contrary retain.
In formula, S is standard deviation value；N driver's sums.
In formula, XnFor n-th driver's characteristic value.
2 Grubbbs check tables of table
2) it proposes rational it is assumed that the inherent quantitative relationship of analysis
The height of different greenbelts has more apparent difference, driver when driving, with the increase of speed,
Range of vision can be reduced.Thus work as tree body height within the scope of driver's dynamic visual field, with the increase of height, driver is regarded
Feeling influences therewith to increase, but should tend towards stability with the increase of height more than the field range.Thus highly refer to
Mark and the fixation characteristics value of driver should show certain logarithmic relationship.
The different tree-like degree that will have a direct impact on driver and hat width is watched attentively, by research, when it is tree-like be spherical when,
It can give driver's equably associative perception, and then tree body radius is constantly changing steeple shape from top to bottom when being, thus to driving
The attraction degree of watching attentively for sailing people can more spherical height.Therefore the tree-like feature of deducibility is in certain linear relationship with influence value
The hat width index of greenbelt should be taken into consideration with having a lot of social connections, and influence of the width for hat width is then presented as that blocking the way is had a lot of social connections
When spending larger, the size of hat width is to appear in driver within sweep of the eye with small scale feature, when road width is smaller, hat width
Size be then that driver is appeared within sweep of the eye with large scale feature.
Since driver is different at a distance from tree body, trunk visibility is also different in the visual perception of driver.Away from
From closer, then tree body can seem relatively large, conversely, then relatively small.The index of trunk visibility can first be assumed to be linear pass
System judges whether degree of fitting and conspicuousness meet regulation using SPSS outputs result.
For the sky ratio index of greenbelt generally between 1%-50%, indices quantification fluctuation is little, can directly use
Simple unary linear relation describes the relationship that the index is influenced with driver's vision.
When greenbelt spacing in the rows is relatively small, it can give driver slight dizzy sense, can then seem again when spacing in the rows is relatively large
Excessively spacious, driver can excessively watch the scenery between two plants attentively.Thus spacing in the rows index and the relationship of visual impact can be used
Second-degree parabola form.Best spacing in the rows is found, both driver will not will not be given with spacious vision with the dizzy sense of a driver
Impression.
Assume in summary be about the relationship between greenbelt Index Influence angle value and its index value
In formula, a, b, c, d, e, f, g are undetermined constant；x1For height value, i.e., trees from ground upwardly to treetop away from
From unit m；x2For tree-like index value, the space structure of tree-like i.e. trees is divided into steeple shape, spherical shape, umbrella shape, with driver
The product determination of sighting distance and the above tangible part area of trunk at driver visual angle, unit m3；x3For hat width and the ratio between have a lot of social connections,
Trees hat width is the average value in trees north and south and east-west direction width；x4For sky ratio, i.e., have at the first visual angle of driver
Effect sky area accounts for the ratio of the driver visual field gross area, dimensionless；x5For trunk visibility index value, with driver's sighting distance with
The product of visual trunk area determines at driver visual angle, unit m3；x6For spacing in the rows value, i.e., the spacing distance of adjacent two trees,
Unit is m.
Environmentally change travel speed in same link by driver, the driver's blinkpunkt analyzed under friction speed is special
Property, the disturbance degree under friction speed can be obtained.With the increase of speed, the dynamic range of vision of driver is reduced therewith, and with
The increase of speed, driver, which can more focus mostly on, watches road traffic environment rather than road landscape environment attentively, may therefore conclude that vehicle
It is negatively correlated that speed influences angle value with greenbelt.Obtain the greenbelt disturbance degree model under different designs speed.
In formula, i, h are constant to be defined, vSpeedFor highway layout speed.
3) undetermined constant is solved
Utilize input phytometer value independent variable x in SPSS softwaresi, characteristic value dependent variable yi, solve undetermined constant.
It is compiled for the height of specific a few arterial highways, hat width, trunk visibility, sky ratio, tree-like five kinds of index language
Code is following (then need to input its dependent variable after encoding Article 6/METHOD=ENTER if you need to other target variables)：
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA COLLIN TOL
/ CRITERIA=PIN (.05) POUT (.10)
/NOORIGIN
/ DEPENDENT influence values
/ METHOD=ENTER height hat widths are had a lot of social connections than tree-like sky ratio trunk visibility
/ SCATTERPLOT=(* ZRESID, * ZPRED)
/RESIDUALS DURBIN HISTOGRAM(ZRESID)NORMPROB(ZRESID).
After running program, input results can show following content (table 3,4,5, Fig. 5)：
The variable of 3 inputs of table/removinga
A. dependent variable：Influence value
B. requested all variables have been inputted.
4 model of table is made a summaryb
A. predictive variable：(constant), trunk visibility, height, hat width, which is had a lot of social connections, to be compared, and sky ratio is tree-like
B. dependent variable：Influence value
5 coefficient of tablea
A. dependent variable：Influence value
Wherein：The side R represents degree of fitting in table 4, and the side R >=0.7 illustrates that degree of fitting is good.De Bin-Watson value is close near 2
It is related to indicate that there is no sequences, which is not shadowing property.Be in table 5 each non-normalisation coefft correspond to each variable be
Number.And conspicuousness≤0.05 shows that independent variable has a significant impact to dependent variable.VIF≤5 show to be not present between each independent variable
Synteny.
According to requirements above, result is verified, discovery is satisfied by above-mentioned requirements.Greenbelt height is obtained to establish
The function of many variables modeling of degree, hat width, trunk visibility, sky ratio, tree-like five kinds of indexs
Y=1.4lnx1+3.1x2+1.8x3-0.83x4+x5+3.2 (8)
Similarly, speed variables being introduced after SPSS can obtain based on evaluation path greenbelt height, hat under friction speed
The function of many variables model of width, trunk visibility, sky ratio, tree-like five kinds of indexs：
Y=1.4lnx1+3.1x2+1.8x3-0.83x4+x5-0.17vSpeed+h (9)
In formula, vSpeedFor the design speed of road；H values see the table below 3.
6 h values of table suggest table
| vSpeed(km/h) | h |
| 40 | 10.00 |
| 45 | 10.85 |
| 50 | 11.70 |
| 55 | 12.55 |
| 60 | 13.40 |
If still needing to other road indexs, carried out according to above-mentioned steps, you can obtain the evaluation of specified link greenbelt index
Model.
2.5 evaluations influence the grade classification of angle value y
It in above process, can be by the way that each index value of greenbelt be substituted into evaluation model, to obtain greening to be evaluated
The influence angle value of band.But judge whether the greenbelt is built rationally, it also needs to establish certain opinion rating, i.e., in different shadows
In loudness value section, greenbelt is different the visual impact of driver, opinion rating can be divided into influence is very big, influence compared with
Greatly, influence is general, it is smaller to influence, almost without influence.
Opinion rating is established on the basis of above-mentioned expert graded and driver's point system, to make the evaluation criterion have
Stronger versatility and accuracy, need to collect a large amount of road landscape data, and different driving ages, gender, height, eyesight are covered in invitation
Etc. features driver carry out real train test scoring.If due to fund, the limitation of time, equipment, a large amount of real vehicle examinations can not be carried out
Test, then can certain amount, quality real train test on the basis of, using drive simulation cabin experimental method, effectively to test scene
It is emulated, completes experiment indoors.
Driver's point system is the scoring that driver carries out indices during real train test influence degree.Scoring
Standard is using 5 points of systems：Influence very greatly 5 points；It is affected to divide；Influence generally 3 points；It influences smaller to be 2 points；Almost without shadow
It is 1 point to ring (it is suitable to lay).After scoring, the index of all experiment roads is subjected to subclassification.Such as：For height
Subclassification can be 0-5m, 5-10m, 10-15m, 15-20m etc..Tree-like subclassification is steeple shape, umbrella shape, spherical shape etc..It will be different
Score value conclude into corresponding subclassification, take mean value after conclusion.Step analysis tree is established with step analysis software YAAHP
Shape figure inputs the mean value of calculating, you can obtains the weighted value of female class index.
Expert estimation rule be invite have related work, research experience expert to choose road greenbelt indices
It is made whether to lay suitable evaluation, using ten point system：The index is suitable to driver's vision influence degree, lays relatively reasonable
(1-3 points)；The index is excessive to driver's vision influence degree, it is proposed that finishing (4-6 points)；The index influences driver's vision
Degree is very big, there are security risk, needs to modify (7 points or more).
After above-mentioned steps, index weights and expert graded are performed mathematical calculations (formula 10), determine the road
The comprehensive evaluation index of index.
In formula：B is comprehensive evaluation index；X is each index weights；FiFor effective expert estimation value；N is expert's sum.
The comprehensive evaluation index of road index is subjected to value arrangements, choose visual effect suitable for (comprehensive evaluation index compared with
Low, typically constitute from the 15%-20% of total experiment road way), general (comprehensive evaluation index is medium, and it is total to typically constitute from experiment for visual effect
The 30%-40% of road way), (comprehensive evaluation index is higher, typically constitutes from the total road way of experiment for the bad road of visual effect
15%-20%).
After the visual effect of road is demarcated, the index parameter value of these roads is substituted into evaluation model, is obtained not
With the evaluation interval that the opinion rating of disturbance degree divides, these sections can be used as evaluation criterion to weigh greenbelt to be evaluated
Whether reasonable, if excessive visual stimulus is generated to driver if building.It ought to for the general or bad road of visual effect
When according to the suitable scoring section of visual effect, the specific level of each factor of Rational choice, combining assessment model makes greenbelt comment
Divide and fall into the section, to driver with comfortable aesthetic method and vigilance appropriate and excitement, ensures the stability of driving.
By carrying out the experiment of above-mentioned steps to certain city dry strip ARC band, tentatively obtained about greenbelt height, it is tree-like,
The best scoring section of trunk visibility, sky ratio and hat width five indices is [15,20], section of generally scoring [12,15)
And (20,24], remaining influence angle value not in above-mentioned section is the bad road of visual effect, need to rationally adjust each factor
It is specific horizontal, so that greenbelt scoring is fallen into [15,20].Due to the limitation of time and experimental facilities, and there are seasons to road
The influence of road vegetation, the scoring section still need to further accurate, optimization.
Claims (7)
1. a kind of method that evaluation main line greenbelt characteristic influences driver's vision, it is characterized in that：It includes the following steps：
1) eye tracker is worn with driver and drives vehicle with constant speed drive on road, with eye tracker to being regarded in front of driver
Open country is recorded a video, while recording driver's eye movement situation；
2) video guide that eye tracker records is entered into eye tracker analysis software, and carries out following interest Division：Trunk visibility
Region of interest is that driver is clearly discernible tree body trunk, the region that leaf does not block in the first visual angle；The interest zoning of hat width
It is divided into trunk visibility region of interest to extend diameter outermost region up to tree body；It sets high region of interest and is divided into hat width region of interest
With up to tree body highest point region；Tree-like region of interest is divided into tree body outer profile and extends to section region；Sky ratio region of interest
Sky is divided into above the first visual angle of driver without vegetation occlusion area；Each region of interest is non-overlapping and need to completely cover
All viewable portions of road greening band；
3) it utilizes eye tracker analysis software and exports the blinkpunkt number of each region of interest；With a certain specific greenbelt of the road
The ratio that the corresponding region of interest blinkpunkt number of index accounts for all index blinkpunkt numbers is characterized value；
4) relationship between greenbelt Index Influence angle value y and each index value of greenbelt is built：
In formula, a, b, c, d, e, f, g are undetermined constant；x1For height value, i.e. trees face upward from ground to the distance of treetop, single
Position is m；x2For tree-like index value, the space structure of tree-like i.e. trees is divided into steeple shape, spherical shape, umbrella shape, with driver's sighting distance with
The product of the above tangible part area of trunk determines at driver visual angle, unit m3；x3For hat width and the ratio between have a lot of social connections, trees hat
Width is the average value in trees north and south and east-west direction width；x4For sky ratio, i.e., effective sky at the first visual angle of driver
Area accounts for the ratio of the driver visual field gross area, dimensionless；x5For trunk visibility index value, with driver's sighting distance and driver
The product of visual trunk area determines at visual angle, unit m3；x6For spacing in the rows value, i.e., the spacing distance of adjacent two trees, unit is
m；
5) independent variable, that is, greenbelt index value x is inputted in SPSS softwaresiWith corresponding characteristic value yi, solve undetermined constant.
2. the method that evaluation main line greenbelt characteristic influences driver's vision as described in claim 1, it is characterized in that：It is described
Step 4) is the relationship built between greenbelt Index Influence angle value y and each index value of greenbelt：
Wherein, i, h are undetermined constant, vSpeedFor highway layout speed.
3. the method that evaluation main line greenbelt characteristic influences driver's vision as described in claim 1, it is characterized in that：Step
3) in, using eye tracker analysis software and when exporting the blinkpunkt number of each region of interest, the video intercepting time is 20s left
The right side need to select vehicle without the section of primary cross mouth when carrying out video intercepting.
4. the method that evaluation main line greenbelt characteristic influences driver's vision as described in claim 1, it is characterized in that：Step
1) in, vehicle is surveyed under the constant speed of 40km/h, 45km/h, 50km/h, 55km/h, 60km/h respectively in same a road section
Examination.
5. the method that evaluation main line greenbelt characteristic influences driver's vision as described in claim 1, it is characterized in that：It is described
Eye tracker is Sweden's Tobii Glasses eye trackers, which is ErogLAB.
6. the method that evaluation main line greenbelt characteristic influences driver's vision as described in claim 1, it is characterized in that：It divides
Influence the grade of angle value y；According to driver's point system and expert graded, the specific section of the grade classification of disturbance degree y is formulated；
Grade interval is divided into that visual effect is suitable, visual effect is general, bad 3 part of visual effect；Greenbelt is judged on this basis
Whether build reasonable.
7. fly the method that evaluation main line greenbelt characteristic influences driver's vision as described in claim 1, it is characterized in that：It utilizes
SPSS softwares carry out the regression analysis of Multivariate Linear function and the regression analysis of unit nonlinear function.
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