CN110335468A - A kind of road safety state identification method - Google Patents
A kind of road safety state identification method Download PDFInfo
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- CN110335468A CN110335468A CN201910679711.9A CN201910679711A CN110335468A CN 110335468 A CN110335468 A CN 110335468A CN 201910679711 A CN201910679711 A CN 201910679711A CN 110335468 A CN110335468 A CN 110335468A
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- G—PHYSICS
- G08—SIGNALLING
- 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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- G—PHYSICS
- G08—SIGNALLING
- 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
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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Abstract
The present invention relates to a kind of road safety state identification methods, carry out interval division to entire road, the distribution function of accident black-spot in each section:Orthogonal curvilinear figure is done respectively to the distribution function of each accident black-spot in some section of chosen the road through road, the orthogonal curvilinear figure of each accident black-spot is superimposed, while the section section for meeting following three conditions can then be accredited as accident black-spot: curve is in x-axis institute envelope surface product >=3S after superposition；Length≤2L of the curve in x-axis after superposition；After superposition curve inside two-end-point with x-axis interface point quantity≤1.This recognition methods has the features such as scientific, comprehensive, objective, concise, accuracy is high.
Description
Technical field
The invention belongs to traffic accident assessment technology field, in particular to a kind of road safety state identification method.
Background technique
Conventional method is mostly considered using accident as individual discrete point, and accident occurs to be defined as on road
A bit, after all points are marked, the judge of security performance is carried out according to relationship between points to determine accident black-spot.Most
Common method is, if n or more accident occurs within the defined period for certain section L, defining the section is that accident is black
Point section.
This method has certain superiority, and the data needed are easy to get, and the determination process of accident black-spot is simply bright
, but there is also shortcomings, are embodied in:
(1) the reason of the occurring that cause the accident is many-sided comprehensive, such as road conditions factor, the volume of traffic, weather, driver
State, driving time etc..It only relies on accident number and defines stain, be on the one hand the severity for the accident that has ignored, on the other hand
Have ignored the multiplicity of cause of accident.
(2) when conventional method carries out accident black-spot investigation identification, screening process is usually recycle really with a fixed step size
Determine accident black-spot, when step-length is excessive, certain Dangerous Areas will be missed, and step-length is too small, will increase calculation amount, while by one
A little non-stain sections are included, and the stain accuracy identified is reduced.
Summary of the invention
The purpose of the present invention is to solve the above problem, provides a kind of road safety state identification method, this recognition methods
With the features such as scientific, comprehensive, objective, concise, accuracy is high.
To solve the above-mentioned problems, The technical solution adopted by the invention is as follows:
A kind of road safety state identification method, it is characterised in that:
(1) interval division is carried out to entire road, the distribution function of accident black-spot in each section:
Wherein: the specific value of COEFFICIENT K:
Minor accident: K=0.5；
Ordinary accident: K=1；
Major accident: K=2；
Serious accident: K=3；
μ, σ are two parameters of normal distyribution function；
(2) orthogonal curvilinear figure is done respectively to the distribution function of each accident black-spot in some section of chosen the road through road, by each thing
Therefore the orthogonal curvilinear figure of stain is superimposed；
(3) theoretically x ∈ [- ∞ ,+∞], the critical area S of enclosed curve:
Wherein L is demarcation interval length, unit km；
For ordinary accident: COEFFICIENT K=1,
(4) judging standard of accident black-spot are as follows:
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: step (2) superposition after curve inside two-end-point with x-axis interface point quantity≤1；
The section section for meeting three above condition simultaneously can then be accredited as accident black-spot；
(5) if some section is accredited as accident black-spot, identify that the road is dangerous；If all sections of entire road are not reflected
It is set to accident black-spot, then identifies the road safety.
Further, if one in the adjacent segments in selected section or Multiple Sections accident rate it is higher, in first identify
Be not identified as accident black-spot, can according to the distribution of traffic accident situation of the adjacent segments, the endpoint of mobile demarcation interval appropriate, if
Accident black-spot is accredited as after mobile endpoint, then it is assumed that the section is accident black-spot.
Further, it if accident rate is relatively low in the adjacent segments in selected section, or is moved for several times in the adjacent segments
Demarcation interval endpoint does not find accident black-spot, terminates the movement of demarcation interval endpoint in the adjacent segments, goes to other sections,
Until whole section is corrected.
The working principle of the invention:
(1) theoretically: the distribution of traffic accident approximate normal distribution in typical accident black-spot section, it can be assumed that it is danger that point, which occurs, for accident
It is dangerous, point occurs in accident, the risk highest of road also can be larger closing on the local risk that point occurs, with distance
Increase, the risk of road gradually weakens, i.e., road hazard linearity curve close to one by accident point occurs centered on just
State distribution curve.Using mileages of transport route, --- x is horizontal axis, road hazard --- f (x) is the longitudinal axis, corresponding normal distribution curve
As shown in Figure of description 1.
(2) to the research of accident black-spot: the form of the accident black-spot normal curve of point is occurred first for accident by the present invention
It showing, normal curve expression is accident hazard degree, it is overlapped by the lap of all accidental curves, finally
To a superimposed curve, that is, reflect the real hazard situation of road interval.
(3) present invention is comprehensive accident frequency and severity of injuries and determination to the identification of accident black-spot.Thing
Therefore frequency is more, represents this section and is more prone to accidents；Accident is more serious, then the risk for representing accident segment occurred is got over
It is high.Therefore the identification of accident black-spot is needed to comprehensively consider the two.
(4) present invention selects normal function to accidental curve, and reason is:
A. high both ends are low among normal curve, and stochastic variable reaches maximum value in accident point, then gradually excessive to two sides
Become smaller, it is on a declining curve.This is consistent with us previously for the analysis of accident.In nature and social phenomenon, great Liang Sui
Machine variable is all obeyed or approximate Normal Distribution.
B. the central-limit theorem in probability theory.The basic thought of central-limit theorem be in objective reality, it is many with
Machine variable is formed by a large amount of mutually independent enchancement factor combined influences, and this random variable is often approximate to obey normal state point
Cloth.
Its probability density are as follows:
There are two parameter, that is, μ and σ in general normal function, are illustrated respectively to μ and σ:
Parameter μ can be used for indicating the specific location that accidental curve is located on road, i.e., the accident which point occurs in road.
And judgment criteria of the parameter using σ as severity of injuries, accident are more serious, σ value is bigger.Corresponding to different σ values
Normal distribution curve is refering to shown in Figure of description 3, and on the outside of interface point, the big curve of σ value is higher than the small curve of σ value；It is handing over
On the inside of contact, the big curve of the σ value curve small lower than σ value, this does not meet convention.
So σ cannot be used as the parameter for measuring severity of injuries, since σ cannot carry out centainly the property of accident
Description, takes steady state value 1, i.e., to accident function selection standard normal function:
And 3 σ principles are selected in the influence section to single accident, i.e.,
P { μ-σ < X≤μ+σ }=0.683
P {+2 σ of μ -2 σ < X≤μ }=0.954
P {+3 σ of μ -3 σ < X≤μ }=0.997
But due to the probability in section [+2 σ of μ -2 σ, μ] upper curve be 0.954, i.e., not in curve ranges a possibility that be less than
5%, index has met the requirement of traffic engineering, and length of curve reduces nearly one third than [+3 σ of μ -3 σ, μ], makes general
Rate smaller portions obtain it is relatively reasonable ignore, therefore [+2 σ of μ -2 σ, μ] range is selected in influence section to single accident.
And after choosing the section between [+2 σ of μ -2 σ, μ], it can be seen that by Figure of description 4, on the side of accident impact range
The dangerous values of boundary's road are 0 by h direct mutagenesis, it is clear that do not meet social convention, therefore by curve entire lowering h, make curved side
Boundary's component values are 0, as shown in Figure of description 5:
Wherein h is the value that standard normal curve is located at 2 σ, numerical value are as follows:
One measurement index K is introduced to determining accident black-spot function, the variation of the index can embody the severity that accidents happened,
Thus the distribution function of accident black-spot is obtained:
For the specific value of K: minor accident: K=0.5, ordinary accident: K=1, major accident: K=2, serious accident: K=
3；
Theoretically x ∈ [- ∞ ,+∞], x ∈ (+2 σ of μ -2 σ, μ) in practical application.
Advantages of the present invention:
(1) the serious index COEFFICIENT K of accident is introduced, the road hazard that the accident of different severity is reflected can be embodied.
(2) road accident is expressed in the form of orthogonal curvilinear, image, intuitively, carry out black spot identification when can be straight
Observation accidental curve is connect, intuitive judgment is made according to curvilinear characteristic.
(3) in further scheme, it is determined that the coverage of accident is made by the reasonable extension to accident impact range
It obtains obtained Dangerous Area more to conform to the actual situation, can really reflect influence of the road conditions to traffic safety.
(4) the features such as this recognition methods has scientific, comprehensive, objective, concise, and accuracy is high.
Specific embodiment
The preferred embodiment of the present invention is described in detail below so that advantages and features of the invention can be easier to by
It will be appreciated by those skilled in the art that so as to make a clearer definition of the protection scope of the present invention.
Following specific examples will occur 3 generally in the section of the continuous 5km of road the preceding paragraph in measurement period (3 years)
Accident is as the critical value for judging accident black-spot.
A kind of road safety state identification method, it is characterised in that:
(1) interval division of 5km is carried out to entire road, the distribution function of accident black-spot in each section:
The specific value of COEFFICIENT K:
Minor accident: K=0.5；
Ordinary accident: K=1；
Major accident: K=2；
Serious accident: K=3；
μ, σ are two parameters of normal distyribution function；
Parameter μ indicates that accidental curve is located at the specific location on road, i.e., the accident which point occurs in road；
Parameter σ determines the dispersion degree of accident, and judgment criteria of the σ as severity of injuries, accident is more serious, and σ value is bigger；
(2) orthogonal curvilinear figure is done to the distribution function of each accident black-spot in some section of chosen the road through road respectively, utilizes stata
The orthogonal curvilinear figure of each accident black-spot is superimposed by software, and curve and X-axis surround region area after being superimposed at calculating, refering to saying
Shown in bright book attached drawing 2；
(3) theoretically x ∈ [- ∞ ,+∞], the critical area S of curve enclosed for normal distribution:
Wherein L is demarcation interval length, unit km；
For ordinary accident: COEFFICIENT K=1, L=5；
(4) judging standard of accident black-spot are as follows:
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: curve (except two-end-point) and x-axis interface point quantity≤1 inside two-end-point after step (2) superposition；
The section section for meeting three above condition simultaneously can then be accredited as accident black-spot.
If some section is accredited as accident black-spot, identify that the road is dangerous；If all sections of entire road not by
It is accredited as accident black-spot, then identifies the road safety.
For a specific embodiment described above, if one in the adjacent segments in selected section or Multiple Sections accident rate compared with
Height is not identified as accident black-spot in first identify, and can be drawn according to the distribution of traffic accident situation of the adjacent segments, movement appropriate
The endpoint of by stages, if being accredited as accident black-spot after mobile endpoint, then it is assumed that the section is accident black-spot.
For another specific embodiment described above, if accident rate is relatively low in the adjacent segments in selected section, or at this
Demarcation interval endpoint is moved in adjacent segments for several times and does not find accident black-spot, terminates demarcation interval endpoint in the adjacent segments
It is mobile, other sections are gone to, until whole section is corrected.
Specific embodiment one:
3 traffic accidents have occurred in the road interval of one 5km in 3 years, 1 minor accident occurs in section 2km respectively,
Coefficient is K=0.5；1 ordinary accident, coefficient K=1 occur for 3km；1 major accident, coefficient K=2 occur for 3.5km.
The distribution function of 3 traffic accident black-spots:Wherein
The orthogonal curvilinear figure that 3 traffic accident black-spots are done with distribution function respectively carries out Logistic by utilizing SPSS software
Model calibration is superimposed 3 traffic orthogonal curvilinear figures, and calculating after superposition that curve and X-axis surround region area is 3.782, is folded
Add length 5.44 of the rear curve in x-axis.
For ordinary accident: COEFFICIENT K=1, L=5, critical area are as follows:
Identification condition: after superposition curve in x-axis institute's envelope surface 3.782 >=3S of product, length 5.44 of the curve in x-axis after superposition≤
2L, two endpoints inside of curve and x-axis interface point quantity 0≤1 after superposition；
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: curve (except two-end-point) and x-axis interface point quantity≤1 inside two-end-point after step (2) superposition；
Meet three above condition simultaneously, therefore, it is determined that the road, there are accident black-spot, the road is dangerous.
Specific embodiment two:
2 traffic accidents have occurred in the road interval of one 5km in 3 years, 1 minor accident occurs in section 2km respectively,
Coefficient is K=0.5；1 minor accident, coefficient K=0.5 occur for 3km.
The distribution function of 3 traffic accident black-spots:Wherein
The orthogonal curvilinear figure that 2 traffic accident black-spots are done with distribution function respectively carries out Logistic by utilizing SPSS software
Model calibration is superimposed 2 traffic orthogonal curvilinear figures, and calculating after superposition that curve and X-axis surround region area is 1.221, is folded
Add length 4.23 of the rear curve in x-axis.
For ordinary accident: COEFFICIENT K=1, L=5, critical area are as follows:
Identification condition: curve accumulates 1.221 < 3S, length 4.23≤2L of the curve in x-axis after superposition in x-axis institute's envelope surface after superposition,
Two endpoints inside of curve and x-axis interface point quantity 0≤1 after superposition；
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: curve (except two-end-point) and x-axis interface point quantity≤1 inside two-end-point after step (2) superposition；
Do not meet three above condition simultaneously, therefore the road interval cannot be accredited as accident black-spot.
But in identification 3 years occur that ordinary accident together, COEFFICIENT K occur respectively at 0.5km behind the road interval
=1；1km, which is in identification 3 years, occurs that major accident together occurs respectively, COEFFICIENT K=2, therefore will be before original road interval
Aft terminal moves back 1km respectively.That is, 1 minor accident, coefficient K=0.5 occurs in 1km in taken road interval；
1 minor accident, coefficient K=0.5 occur for 2km；Ordinary accident together, COEFFICIENT K=1 occur for 4.5km；Occur respectively at 5km
Major accident together, COEFFICIENT K=2.
The distribution function of 4 traffic accident black-spots:Wherein
Again the orthogonal curvilinear figure that 4 traffic accident black-spots in the road interval are done with distribution function respectively, by utilizing SPSS
Software carries out Logistic model calibration, is superimposed to 4 traffic orthogonal curvilinear figures, and calculates curve and X-axis after superposition and surround area
Domain area is 3.219, length 7.94 of the curve in x-axis after superposition.
For ordinary accident: COEFFICIENT K=1, L=5, critical area are as follows:
Identification condition: after superposition curve in x-axis institute's envelope surface 3.219 >=3S of product, length 7.94 of the curve in x-axis after superposition≤
2L, two endpoints inside of curve and x-axis interface point quantity 0≤1 after superposition；
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: curve (except two-end-point) and x-axis interface point quantity≤1 inside two-end-point after step (2) superposition；
Meet three above condition simultaneously, therefore, it is determined that the road, there are accident black-spot, the road is dangerous.
Specific embodiment three:
In the road interval of one 5km in 3 years, in section, 1 minor accident, coefficient K=0.5 occur for 2km.
The distribution function of 1 traffic accident black-spots:Wherein
The orthogonal curvilinear figure that 1 traffic accident black-spots are done with distribution function respectively carries out Logistic by utilizing SPSS software
It is 0.612 that model calibration, this 1 traffic orthogonal curvilinear figure and X-axis, which surround region area, length 3.22 of the curve in x-axis.
For ordinary accident: COEFFICIENT K=1, L=5, critical area are as follows:
Identification condition: curve accumulates 0.612 < 3S, length 3.22 < 2L of the curve in x-axis after superposition in x-axis institute's envelope surface after superposition,
Two endpoints inside of curve and x-axis interface point quantity 0≤1 after superposition；
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: curve (except two-end-point) and x-axis interface point quantity≤1 inside two-end-point after step (2) superposition；
Do not meet three above condition simultaneously, therefore the road interval cannot be accredited as accident black-spot.
Occur ordinary accident together behind the road interval at 1km in identification 3 years, COEFFICIENT K=1, therefore will be original
Road interval before and after endpoint move back 1km respectively.That is, 1 minor accident occurs in 1km in taken road interval,
Coefficient is K=0.5；Ordinary accident together, COEFFICIENT K=1 occurs at 5km respectively.
The distribution function of 2 traffic accident black-spots:Wherein
Again the orthogonal curvilinear figure that 2 traffic accident black-spots in the road interval are done with distribution function respectively, by utilizing SPSS
Software carries out Logistic model calibration, is superimposed to 2 traffic orthogonal curvilinear figures, and calculates curve and X-axis after superposition and surround area
Domain area is 1.239, length 7.62 of the curve in x-axis after superposition.
For ordinary accident: COEFFICIENT K=1, L=5, critical area are as follows:
Identification condition: curve accumulates 1.239 < 3S, length 7.62 < 2L of the curve in x-axis after superposition in x-axis institute's envelope surface after superposition,
Two endpoints inside of curve and x-axis interface point quantity 0≤1 after superposition；
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: curve (except two-end-point) and x-axis interface point quantity≤1 inside two-end-point after step (2) superposition；
Do not meet three above condition simultaneously, therefore, it is determined that accident black-spot is not present in the road, the road interval is safe, and to it
He identifies road interval, finishes until this road interval is corrected.
The basic principles, main features and advantages of the present invention have been shown and described above.The technology of the industry
For personnel it should be appreciated that the present invention is not limited to the above embodiments, the description in above embodiments and description is only the present invention
Preference, the present invention do not limited by above-mentioned preference, without departing from the spirit and scope of the present invention, the present invention
Can also there are various changes and modifications, these changes and improvements are both fallen in the scope of protection of present invention.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (3)
1. a kind of road safety state identification method, it is characterised in that:
(1) interval division is carried out to entire road, the distribution function of accident black-spot in each section:
Wherein: the specific value of COEFFICIENT K:
Minor accident: K=0.5；
Ordinary accident: K=1；
Major accident: K=2；
Serious accident: K=3；
X ∈ (+2 σ of μ -2 σ, μ)；
μ, σ are two parameters of normal distyribution function；
(2) orthogonal curvilinear figure is done respectively to the distribution function of each accident black-spot in some section of chosen the road through road, by each thing
Therefore the orthogonal curvilinear figure of stain is superimposed；
(3) theoretically x ∈ [- ∞ ,+∞], the critical area S of enclosed curve:
Wherein L is demarcation interval length, unit km；
For ordinary accident: COEFFICIENT K=1,
(4) judging standard of accident black-spot are as follows:
Condition 1: curve is in x-axis institute envelope surface product >=3S after step (2) superposition；
Condition 2: length≤2L of the curve in x-axis after step (2) superposition；
Condition 3: step (2) superposition after curve inside two-end-point with x-axis interface point quantity≤1；
The section section for meeting three above condition simultaneously can then be accredited as accident black-spot；
(5) if some section is accredited as accident black-spot, identify that the road is dangerous；If all sections of entire road are not reflected
It is set to accident black-spot, then identifies the road safety.
2. a kind of road safety state identification method according to claim 1, which is characterized in that if the adjacent road in selected section
One in section or Multiple Sections accident rate it is higher, be not identified as accident black-spot in first identify, can be according to the adjacent segments
Distribution of traffic accident situation, the endpoint of mobile demarcation interval appropriate, if being accredited as accident black-spot after mobile endpoint, then it is assumed that the area
Between be accident black-spot.
3. a kind of road safety state identification method according to claim 1, which is characterized in that if the adjacent road in selected section
Accident rate is relatively low in section, or moves demarcation interval endpoint for several times in the adjacent segments and do not find accident black-spot, and terminating should
The movement of demarcation interval endpoint in adjacent segments, goes to other sections, until whole section is corrected.
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| CN105608902A (en) * | 2016-03-28 | 2016-05-25 | 辽宁省交通科学研究院 | Expressway black spot identification system and method |
| CN107784832A (en) * | 2016-08-25 | 2018-03-09 | 上海电科智能***股份有限公司 | A kind of method and apparatus for being used to identify the accident black-spot in traffic route |
| WO2018212444A1 (en) * | 2017-05-15 | 2018-11-22 | Quantumgate Inc. | System of traffic forecasting |
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