CN108109378A - A kind of method that Evaluation of Traffic Safety is carried out to road net planning - Google Patents

A kind of method that Evaluation of Traffic Safety is carried out to road net planning Download PDF

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Publication number
CN108109378A
CN108109378A CN201810069917.5A CN201810069917A CN108109378A CN 108109378 A CN108109378 A CN 108109378A CN 201810069917 A CN201810069917 A CN 201810069917A CN 108109378 A CN108109378 A CN 108109378A
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section
traffic
intersection
road
accident
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孟祥海
柳昕汝
梁心雨
吴佩洁
刘振博
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Harbin Institute of Technology
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Harbin Institute of Technology
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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
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • G06Q50/265—Personal security, identity or safety

Abstract

A kind of method that Evaluation of Traffic Safety is carried out to road net planning, the present invention relates to the methods that Evaluation of Traffic Safety is carried out to road net planning.It the purpose of the present invention is to solve existing traffic safety management mostly based on the evaluation after accident, does not combine with Planning and design, causes the accident frequency height, follow-up road safety improves the problem of investment is high.Detailed process is：First, the section to target road network and intersection carry out Type division；2nd, the traffic accident number of each type of section and intersection is predicted respectively；3rd, based on two, latent defect Multiple trauma is differentiated；4th, inducement analysis is carried out to the latent defect Multiple trauma identified；5th, based on two, road network unit traffic safety grading evaluation criteria is established, traffic safety status classification is carried out to road network.The present invention is used to carry out Evaluation of Traffic Safety field to road net planning.

Description

A kind of method that Evaluation of Traffic Safety is carried out to road net planning
Technical field
The present invention relates to the methods that Evaluation of Traffic Safety is carried out to road net planning.
Background technology
In various factors in the influence of traffic accident, the factor related with road occupies sizable ratio, road network Planning and designing rationally whether to traffic safety have material impact.Many traffic accidents to a certain extent with road Network planning draws the defects of inconsiderate related or even some accidents the direct origin cause of formation is exactly in highway layout.Although road network now Traffic safety problem is considered in design planning, but is limited only to geometry linear and road network pattern aspect more, has ignored friendship The comprehensive function of other aspect factors such as logical operating status, traffic environment, this traffic insurance system risk are still larger. At present, urban traffic safety management is also focused in subsequent processing and analysis, but the generation of lot of accident already cause it is huge Big casualties and property loss, therefore it is very necessary to establish the safety management mode aimed at prevention.
Only by traffic safety theory and the theoretical combination of railway network planning, highway layout is checked with traffic safety technology Achievement could fundamentally ensure the long-term stability of road traffic system.
The research of external Planning and design and traffic safety mainly has：Anaatasior Zervas have studied Influence of the road geometry linear to traffic safety.Rechel Goldstine have studied influence of the road width to traffic safety. Rune Elvik focus has been transferred to the periphery block of central business district, studies the relation of its improvement plan and traffic safety. Manne Millot combine resident trip mode with traffic safety, have studied urban development, trip mode pacifies traffic Full influence.Robert B. analyze the accident occurrence quantity under different cities land-use style, different employment distributions.Jake Kononov thinks that early construction need to take into full account safety factor, it is proposed that a kind of security consideration side for transport system program Method.Dominique Lord establish a kind of frame knot that traffic safety problem is considered in the urban road transportation network planning stage Structure realizes traffic safety and the combination of railway network planning theory.
Domestic Evaluation of Traffic Safety is assessed after being mainly, and has not been entered into the safety evaluation in railway network planning stage.Intersect Research in terms of mouth and road safety design mainly has：Han Fengchun, Cao Jinxuan have studied the accident impact factor of level-crossing, And the security design principle of level-crossing is proposed, it is excellent including reducing conflict point quantity, reduction battleground area, major flow First and control relative velocity etc..Jiang Heng analyzes the setting of intersection design element and the relation of accident rate, and proposes safety Design objective value or value suggestion.Tian Luquan has studied the traffic accident rate of each standard highway and the relation of road conditions.Liang Xia, Guo Zhong Print, Fang Shouen have studied highway route index and the relation of traffic safety using front/rear analytic approach.Pei Yulong, horse Thoroughbred horse has studied the influence of plane in road alignment condition, vertical section, cross section and intersection parameters to traffic accident, and carries Corresponding preventive measure is gone out.
The content of the invention
The purpose of the present invention is to solve existing traffic safety management mostly based on the evaluation after accident, no and road network Planning and designing combine, and cause the accident frequency height, follow-up road safety improves the problem of investment is high, and proposes one The method that kind carries out road net planning Evaluation of Traffic Safety.
It is a kind of to road net planning carry out Evaluation of Traffic Safety method detailed process be：
Step 1: the section and intersection to target road network carry out Type division；
Step 2: the traffic accident number of each type of section and intersection is predicted respectively；
Step 3: the traffic accident number in each type of section and intersection based on prediction, differentiates that latent defect is more Hair point；
Step 4: inducement analysis is carried out to the latent defect Multiple trauma identified；
Step 5: the traffic accident number in each type of section and intersection based on prediction, establishes the friendship of road network unit Logical safety grade assessment standard carries out traffic safety status classification to road network.
Beneficial effects of the present invention are：
The present invention establishes different types of urban road accident prediction model, is carried for the accident forecast in railway network planning stage Theoretical foundation is supplied；The present invention proposes that the latent defect Multiple trauma based on BP networks differentiates model for the road network of planning stage And accident inducement differentiates model, organically combines railway network planning with traffic safety；The present invention establishes section, hands over The traffic safety grade scale of prong and road network contributes to planning stage road network safe mass to evaluate；The present invention proposes road network rule Scheme Evaluation of Traffic Safety and road network improved method are drawn, programme is made to take into full account safety factor, has ensured road network significantly Security performance.A kind of road net planning Traffic safety evaluation method of the present invention reduces accident occurrence frequency, in the planning stage Road is improved, saving follow-up road safety improves investment, solves existing traffic safety management mostly based on after accident Evaluation, do not combine with Planning and design, cause the accident frequency height, follow-up road safety improves investment The problem of high.With reference to table 9 illustrate existing road road network prediction accident number be 1055.9 times, using the present invention to upgrading of a road after Road network prediction accident number be 684.7 times, road network prediction accident number be substantially reduced.
Description of the drawings
Fig. 1 is the flow chart of the present invention；
Fig. 2 is accident index and volume of traffic scatter diagram, EnFor the average of accident forecast number, σnFor accident forecast number Variance；
Fig. 3 is road grid traffic safety evaluation and ameliorative way flow chart；
Fig. 4 analyzes road network figure for the embodiment of the present invention.
Specific embodiment
Specific embodiment one：The present embodiment will be described with reference to Fig. 1, present embodiment it is a kind of to road net planning into The method detailed process of row Evaluation of Traffic Safety is：
Step 1: the section and intersection to target road network carry out Type division；
Step 2: the traffic accident number of each type of section and intersection is predicted respectively；
Step 3: the traffic accident number in each type of section and intersection based on prediction, differentiates that latent defect is more Hair point；
Step 4: the inducement that railway network planning level is carried out to the latent defect Multiple trauma identified is analyzed；
Step 5: the traffic accident number in each type of section and intersection based on prediction, establishes the friendship of road network unit Logical safety grade assessment standard carries out traffic safety status classification to road network.
According to accident forecast result, the discriminating of latent defect Multiple trauma and inducement and the evaluation of road network security performance, Evaluation of Traffic Safety is carried out to road net planning, and proposes Improving advice.
Specific embodiment two：The present embodiment is different from the first embodiment in that：To target in the step 1 The section of road network and intersection carry out Type division；Detailed process is：
Application system clustering procedure carries out category division to the section of target road network and intersection, and section is divided into four classes Not, it is respectively the section first kind, the second class of section, the 4th class of section three classes and section；Intersection is divided into two classifications, point It Wei not the second class of the intersection first kind and intersection；
The section first kind is comprising road segment classification：One piece of 2 track of plate, one piece of 4 track of plate, two pieces of 4 tracks of plate and three blocks of plates 4 Track；
The second class of section is comprising road segment classification：One piece of 6 track of plate, two pieces of 6 tracks of plate, three pieces of 6 tracks of plate and four blocks of plates 8 Track；
Section three classes are comprising road segment classification：One piece of 8 track of plate and two pieces of 8 tracks of plate；
The 4th class of section is comprising road segment classification：Four pieces of 6 tracks of plate and 10 track of viaduct；
The intersection first kind is comprising road segment classification：It is main with time intersect three-way intersection, it is secondary with secondary intersecting three-way intersection, It is main to intersect simple intersection and secondary and time intersecting simple intersection with secondary；
The second class of intersection is comprising road segment classification：Main and main intersecting three-way intersection and master and main intersecting four-legs intersection Mouthful.
As shown in table 1, table 2.
1 section category division result of table
2 intersection category division result of table
Other steps and parameter are same as the specific embodiment one.
Specific embodiment three：The present embodiment is different from the first and the second embodiment in that：Divide in the step 2 The traffic accident number of each type of section and intersection is not predicted；Detailed process is：
According to prediction accident number modelEstablish each type of section and intersection pair The accident prediction model answered：
The traffic Accident Forecast Model of the section first kind is YO=0.0334AADT0.245e0.0293V-0.0624W+0.0757N
The traffic Accident Forecast Model of the second class of section is YT=4.5585AADT0.094e0.256L+0.0419N
The traffic Accident Forecast Model of section three classes is YTH=232.2931AADT0.2500e-0.1610W+0.0952N
The traffic Accident Forecast Model of the 4th class of section is YF=26.7625 × e-0.9020L+0.0987N
The traffic Accident Forecast Model of the intersection first kind is
The traffic Accident Forecast Model of the second class of intersection isFormula In, Y is prediction accident number；AADT is annual average daily traffic；xiFor i-th of independent variable；M is independent variable number；α、P、βiPoint Coefficient that Wei be not to be calibrated；
YOFor the traffic accident prediction number of the section first kind；YTFor the traffic accident prediction number of the second class of section；YTH For the traffic accident prediction number of section three classes；YFFor the traffic accident prediction number of the 4th class of section；YO jFor intersection A kind of traffic accident prediction number；YT jFor the traffic accident prediction number of the second class of intersection；AADT is the traffic of annual day Amount；V is speed, unit km/h；W is width of roadway, unit m；N is crossing number；L is road section length, unit km； AADTDTFor straight-going traffic annual average daily traffic；AADTRTFor right-hand rotation traffic annual average daily traffic；NjFor intersection entrance vehicle Road sum.
The all types of section of table 3 and crossing accident prediction model
Other steps and parameter are the same as one or two specific embodiments.
Specific embodiment four：Unlike one of present embodiment and specific embodiment one to three：The step 3 In the traffic accident number of each type of section based on prediction and intersection, differentiate latent defect Multiple trauma；Detailed process For：
Section in road network and intersection are divided into three kinds of dangerous spot, normal point and point of safes security types, utilize three Layer BP neural network model differentiates latent defect multi-happening section and intersection.
BP neural network model is established, 3 BP neural network input layer, interlayer, output layer transfer functions take respectively Logsigmoid functions, tansigmoid functions and satline functions；
BP neural network model differentiates model for section hazardous location identification model or crossing accident Multiple trauma；
Differentiating model for section latent defect Multiple trauma, logsigmoid function neural members number is 10, Tansigmoid function neural members number is that 10, satline function neural members number is 3；
Differentiating model for intersection latent defect Multiple trauma, logsigmoid function neural members number is 5, Tansigmoid function neural members number is that 5, satline function neural members number is 3；
The input variable of BP neural network model is link counting, category of roads, the speed of service, cross-sectional form (example Such as one block of plate, two blocks of plates, three blocks of plates, four blocks of plates), number of track-lines, width of roadway and entrance quantity accident relation factor (road network Planning stage data), the output of BP neural network model is three kinds of security types, is respectively dangerous spot, normal point or point of safes；
Dangerous spot is latent defect Multiple trauma.
Other steps and parameter are identical with one of specific embodiment one to three.
Specific embodiment five：Unlike one of present embodiment and specific embodiment one to four：The BP nerves Network model establishes process：
The 50% of the place of accident number prediction will be carried out in step 2 as training sample, residue 50% is as test specimens This；The place that accident number prediction is carried out in step 2 is divided into two groups；Place is broad sense, is exactly that it includes its all attribute Data, attribute data include link counting, category of roads, the speed of service, cross-sectional form, number of track-lines, width of roadway and go out Entry number etc.；
The place (section or intersection) that accident number prediction is carried out in step 2 is divided into two groups, one group as training Sample, another group is used as test sample；Place is broad sense, is exactly that it includes all attribute datas in the place, attribute data bag Include link counting, category of roads, the speed of service, cross-sectional form, number of track-lines, width of roadway and entrance quantity etc.；
First, training sample is input to BP neural network model to be trained, has obtained input layer, interlayer, output layer The weight matrix and bias vector of each layer, training precision 0.03 are completed the parameter calibration of BP neural network model, are trained Good BP neural network model；
2nd, trained BP neural network prototype network is tested using test sample, if BP neural network mould Type exports result and is differed with the result of test sample calibration originally within [10%, 30%], then shows that BP neural network model is built It has been stood that, Generalization Capability is stronger, can be perfectly suitable for the discriminating of latent defect multi-happening section.
If BP neural network model exports result and is differed not at [10%, 30%] with the result of test sample calibration originally Within (or the less phase difference dangerous spot number of sample size differs 3 or more), then one, two are re-executed until BP neural network mould Type exports result and is differed with the result of test sample calibration originally within [10%, 30%].
Other steps and parameter are identical with one of specific embodiment one to four.
Specific embodiment six：Unlike one of present embodiment and specific embodiment one to five：The trained sample Originally obtained with the security type of test sample by accident number probability distribution method, matrix method and quality discrimination control methods, process For：
When a kind of method in accident number probability distribution method, matrix method and quality discrimination control methods identifies a certain place For Accident Area, then the point is dangerous spot sample；
When all methods in accident number probability distribution method, matrix method and quality discrimination control methods all think a certain place For point of safes when, then the point is point of safes sample；
Normal point sample is used as in addition to dangerous spot sample and point of safes sample.
Other steps and parameter are identical with one of specific embodiment one to five.
Specific embodiment seven：Unlike one of present embodiment and specific embodiment one to six：The step 4 In the inducement of railway network planning level carried out to the latent defect Multiple trauma that identifies analyze；Detailed process is：
Inducement analysis is carried out to latent defect Multiple trauma using the accident inducement discrimination method of probability distribution；
The inducement of latent defect Multiple trauma has link counting, category of roads, cross-sectional form, number of track-lines, road surface Width and entrance quantity etc.；
Wherein (cross-sectional form, category of roads, number of track-lines are for scale variable for cross-sectional form, category of roads, number of track-lines It is known), scale variable is used to be grouped；Such as cross-sectional form, category of roads, the number of track-lines in table 8；Cross-sectional form, road Grade and any combination of number of track-lines 3 are used to be grouped；
Width of roadway, entrance quantity, link counting are the real value variable (sample data of every group of corresponding real value variable It is known)；
Discrimination standard row vector is established to real value variable by probability distribution method, process is：
Latent defect Multiple trauma is grouped according to scale variable, the sample data for calculating every group of correspondence real value variable is equal Value and variance, according to ril=Eil+kσilFix limit desired value；Significance takes 95%, and coefficient k value is 1.5；
In formula, rilFor the boundary desired value of i-th of scale variable of l groups, EilFor the sample of i-th of scale variable of l groups Data mean value, σilFor the sample data variance of i-th of scale variable of l groups；L values are positive integer；I values are 1,2 or 3；
For l groups discrimination standard row vector:
Rl=(r1l,r2l,r3l)
In formula, r1lFor the boundary desired value of first scale variable cross-sectional form of l groups, r2lFor second ruler of l groups Spend the boundary desired value of variable category of roads, r3lFor the boundary desired value of the 3rd scale variable number of track-lines of l groups；
The real value variable of latent defect Multiple trauma and discrimination standard row vector are compared, if a certain element is big in real value variable In the corresponding element of discrimination standard row vector, then the element is one of accident inducement；
A certain element is some in width of roadway, entrance quantity, link counting in real value variable；
If a certain element is less than or equal to the corresponding element of discrimination standard row vector in real value variable, which is not accident One of inducement.
Other steps and parameter are identical with one of specific embodiment one to six.
Specific embodiment eight：Unlike one of present embodiment and specific embodiment one to seven：The step 5 In establish road network unit traffic safety grading evaluation criteria, to road network carry out traffic safety status classification；Detailed process is：
In step 5, traffic safety status classification is carried out to all units of road network first, is divided into level Four.Level representative is pacified Entirely in order, every accident index is substantially less than average value under defined significance.Level Four safe condition is poor, Middle part level Four level of security section and node are exactly the Accident Area under traditional sense.
The net unit (1 section or 1 intersection) that satisfies the need carries out traffic safety classification；Process is：
Now illustrate the definite method of evaluation index value range by taking Fig. 2 as an example.
Annual average daily traffic AADT is divided into discrete section, to n-th of section, the starting volume of traffic is AADTn, terminate The volume of traffic is AADTn+1；It determines the section for being under the jurisdiction of the section or intersection number, and calculates the average E of accident forecast numbern And variances sigman；N values are positive integer；
When obtaining the E in n-th of sectionn、En+σn、En-σnAfterwards, got back for all sections three groups of new sample numbers According to：{En}、{En+σn}、{En-σn}；{ E is determined respectivelyn}、{En+σn}、{En-σnThree groups of sample datas regression curve y1=f1 (x)、y2=f2(x)、y3=f3(x),
Wherein x is AADT, y1、y2、y3Respectively the average of accident forecast number, average double variance and average subtracts one Times variance；
By three groups of regression curves using AADT as abscissa, accident forecast number is drawn for ordinate, and three groups of regression curves will Fig. 2 marks off four regions, and four regions correspond to the traffic safety first order in section or intersection, section respectively from bottom to up Or the traffic safety second level of intersection, the traffic safety of the traffic safety third level in section or intersection, section or intersection The fourth stage；
Accident forecast number boundary value of each section per level-one is obtained according to three curves to get road network unit traffic has been arrived Safety grade assessment standard；
First kind road section traffic volume safety classification standard based on accident number is shown in Table 4 (other summaries).
First kind road section traffic volume safety classification standard of the table 4 based on accident number
According to road network unit traffic safety grading evaluation criteria, traffic safety classification is carried out to entire road network；Process is：
Road grid traffic safety classification standard scale is established, road grid traffic safety classification standard scale includes road grid traffic security level With degree of safety index, degree of safety index is divided into H section from small to large, the corresponding road network security level of every part of correspondence, H Road grid traffic security level is divided into H grades by the degree of safety interval index arranged from small to large from small to large；
The weighted average that road grid traffic degree of safety index is road network unit safe class is defined, i.e.,：
Wherein, DnetFor road network degree of safety index, the real number between 1~4 is taken；LaFor the traffic safety grade in a-th of section Not, the integer between [Isosorbide-5-Nitrae] is taken；IjFor the traffic safety rank of j-th of level-crossing, the integer between [Isosorbide-5-Nitrae] is taken (to be exactly The section or traffic safety first order of intersection, section or the traffic safety of the intersection second level, road in traffic safety classification The traffic safety fourth stage of the traffic safety third level of section or intersection, section or intersection, is exactly table 4)；C, d are respectively road Section and the number of intersection, value is positive integer；Integer of the H values between [1,6]；
By DnetIt is compared with the degree of safety index in road network safety classification standard scale, finds identical DnetCorresponding safety Rank.
According to the size of road network degree of safety index, the traffic safety degree of road network is divided into six grades, specific grade scale It is shown in Table 5.
5 road network safety classification standard of table
Road grid traffic safety evaluation is differentiated with ameliorative way by accident forecast, dangerous spot and its inducement, road network safety Four function modules compositions such as performance evaluation, road network improvement, flow chart are shown in Fig. 3.
Accident forecast module
The major function of accident forecast module is to provide traffic accident prediction data.Module input is exactly planned road network scheme Road information and traffic flow data etc., module bodies be exactly accident prediction model storehouse, module output is exactly road network unit Prediction accident number.
Dangerous spot and inducement identification module
The major function of the module is to find out potential Accident Area in planned road network scheme, and determines that it induces accident The factor of generation.Core technology is that the latent defect Multiple trauma based on BP neural network is differentiated model and counted based on variance analysis The accident inducement of distribution differentiates model.
Road network security performance evaluation module
The major function of the module is the overall traffic safety performance of program evaluation road network scheme.Traffic assignation provides road The data on flows of net unit, and accident prediction model then gives accident forecast index, thus can determine the peace of road network unit It is complete horizontal.Road network degree of safety index is calculated on this basis, and determines that the overall of road network is pacified according to road network safety classification standard Full performance.
Road network improves module
The function of the module has following two aspects：1. improve initial plan road network scheme；2. optimize final planned road network Scheme.With reference to the latent defect Multiple trauma and its corresponding accident inducement identified, alternative can be proposed to improve and built View, also can further optimize final planned road network scheme.
Other steps and parameter are identical with one of specific embodiment one to seven.
Beneficial effects of the present invention are verified using following embodiment：
Step 1: statistical basis road network and attribute, and all roads are divided into respective classes；
Step 2: establish accident prediction model；
Accident impact factor generally comprises annual average daily traffic, road section length, speed, width of roadway and branch on section Crossing number etc., intersection then depend primarily upon annual average daily traffic and the entrance lane number in point direction etc..These variables are just It is the independent variable for establishing accident prediction model.Between accident number and influence factor, generally there are following curved line relations：
Wherein, Y is prediction accident number；AADT is annual average daily traffic；xiFor i-th of independent variable；M is independent variable Number；α、P、βiCoefficient respectively to be calibrated.
Certainly, whether AADT is necessarily present in prediction model, and variable when additionally depending on successive Regression chooses result.Root Data according to statistics, calibrate all types of sections and crossing accident prediction model is shown in Table 6.
The all types of section of table 6 and crossing accident prediction model
Step 3: traffic safety status is evaluated；
According to the prognosis traffic volume of railway network planning and the prediction accident number of calculating, definite safety classification standard is compared, So that it is determined that the traffic safety degree of road network unit, obtains level-one, two level, three-level, the road scope of level Four level of security and number Amount.
It is classified according to the traffic safety of all road network units, calculates road network degree of safety index, evaluate the totality of entire road network Safety level of service.Road network degree of safety formula of index is as follows：
Step 4: latent defect Multiple trauma differentiates；
By the variable letter of the annual average daily traffic of all sections and intersection, category of roads, speed of service etc. in road network Breath input BP neural network hazardous location identification model, identifies the latent defect Multiple trauma in road network.
Step 5: prominent accident inducement differentiates；
Differentiate that model carries out accident inducement discriminating to latent defect Multiple trauma using accident inducement.Wherein, lure Inducement element is following 6 variables：Cross-sectional form, category of roads, number of track-lines, AADT, width of roadway and entrance quantity.First three A variable is scale variable, for being grouped.Then, for each group, the average of three real value variables and side after calculating respectively Difference, and determine criterion.Attribute variable's value of Accident Area with criterion is compared, finally defines prominent thing Therefore inducement.
Step 6: road network improves；
It is not strictly limited in road network land for roads for the latent defect Multiple trauma and its accident inducement identified Supposed premise under the conditions of, initial road network is improved.Main contents include：Increase width of roadway and adjust the traffic capacity, It adjusts cross-sectional form, branch entry number etc. is reduced by isolation facility.
Step 7: security performance comparative analysis before and after road network improvement.
Assignment of traffic is carried out to the road network scheme after adjustment, then prediction has drawn the accident number improved in road network scheme And define corresponding safe class.Accident index before and after road network improves is compared, if security performance greatly improves, proves road Net corrective measure is rationally effective.
Embodiment one：
The present embodiment road net planning Evaluation of Traffic Safety is specifically to be prepared according to following steps with road network improved method 's：
This example according to object of this investigation and is combined based on the data of certain big city inner city planned road network scheme The relevant information of road network is tested, the safety evaluation and road network for carrying out planned road network scheme improve.The road network scope of research is shown in Fig. 4. For the road network scope of research, applied forecasting model calculates accident frequency, and compares safe class standard, obtains each road network list The traffic safety of member is horizontal, the results are shown in Table 7.
As shown in Table 7：
(1) level of security is that the section of level-one, two level, three-level and level Four is respectively 17,86,22 and 44, accounts for sum Percentage is respectively 10%, 51%, 13% and 26%, though level of security is little for the section accounting of level Four, accident number is about Overall half is accounted for, need to be paid close attention to；
(2) according to the safe class of all road network units, the degree of safety index for calculating whole road network is 2.55, corresponding peace Congruent grade is level Four, it is known that the whole road network security performance before planning is poor.
7 accident forecast result of table and road network unit safe condition
Using BP neural network hazardous location identification model, potential 7 Accident Areas in road network are identified, and should Differentiate that model carries out inducement discriminating to latent defect Multiple trauma with accident inducement, obtain accident-prone road section and its protrusion Accident inducement is shown in Table 8.
As shown in Table 8：
(1) it is 108.8 times to add up prediction accident number on Accident Area, accounts for survey region and always predicts accident number 10.3%, and its section quantity only accounts for the 4.1% of whole section quantity, traffic safety problem protrudes；
(2) factor for causing accident is mainly width of roadway deficiency, the volume of traffic is larger or entrance quantity is more；
(3) 7 road network safe condition of the table of comparisons, Accident Area section are level Four level of security, and risk is larger.
8 Accident Area of table and its inducement identification result
Note：" ☆ " represents prominent unit, that is, the accident inducement identified.
For the latent defect Multiple trauma identified, especially induce Multiple trauma that the key factor of traffic accident occurs, Under the conditions of road network land for roads is not strictly limited supposed premise, initial road network is improved as follows：
(1) western 16 streets, field street width of roadway are increased, and accordingly adjusts its traffic capacity；
(2) An Sheng streets width of roadway is increased, and reduces branch intersection quantity；
(3) it is three pieces of plate six-lane sections by Anguo street road adjustment of cross-section, and reduces branch by quarantine measures and enter Mouth quantity；
(4) Straight Street East and Straight Street West width of roadway are increased, and is three pieces of plate six-lane roads by adjustment of cross-section Form of fracture.
Assignment of traffic, accident forecast are re-started to improved road network, and then determines that its safe class is shown in Table 9.
Security performance comparative analysis before and after 9 road network of table improves
As shown in Table 9, the poor section of the safe conditions such as three-level and level Four significantly reduces in road network after improvement, and safety etc. Grade increases considerably for the section of level-one, and it is good that road network overall safety grade also becomes safe condition from the poor level Four of safe condition Good two level illustrates that improvement road network scheme is rationally effective.
The present invention can also have other various embodiments, without deviating from the spirit and substance of the present invention, this field Technical staff makes various corresponding changes and deformation in accordance with the present invention, but these corresponding changes and deformation should all belong to The protection domain of appended claims of the invention.

Claims (8)

  1. A kind of 1. method that Evaluation of Traffic Safety is carried out to road net planning, it is characterised in that：The method detailed process is：
    Step 1: the section and intersection to target road network carry out Type division；
    Step 2: the traffic accident number of each type of section and intersection is predicted respectively；
    Step 3: the traffic accident number in each type of section and intersection based on prediction, differentiates latent defect Multiple trauma；
    Step 4: inducement analysis is carried out to the latent defect Multiple trauma identified；
    Step 5: the traffic accident number in each type of section and intersection based on prediction, establishes road network unit traffic peace Full grading evaluation criteria carries out traffic safety status classification to road network.
  2. 2. a kind of method that Evaluation of Traffic Safety is carried out to road net planning according to claim 1, it is characterised in that：Institute It states in step 1 and Type division is carried out to the section of target road network and intersection；Detailed process is：
    Application system clustering procedure carries out category division to the section of target road network and intersection, and section is divided into four classifications, point It Wei not the section first kind, the second class of section, the 4th class of section three classes and section；Intersection is divided into two classifications, is respectively The second class of the intersection first kind and intersection；
    The section first kind is comprising road segment classification：One piece of 2 track of plate, one piece of 4 track of plate, two pieces of 4 tracks of plate and three pieces of 4 vehicles of plate Road；
    The second class of section is comprising road segment classification：One piece of 6 track of plate, two pieces of 6 tracks of plate, three pieces of 6 tracks of plate and four pieces of 8 vehicles of plate Road；
    Section three classes are comprising road segment classification：One piece of 8 track of plate and two pieces of 8 tracks of plate；
    The 4th class of section is comprising road segment classification：Four pieces of 6 tracks of plate and 10 track of viaduct；
    The intersection first kind is comprising road segment classification：It is main with time intersect three-way intersection, it is secondary with time intersecting three-way intersection, master and Secondary intersecting simple intersection and time intersect simple intersection with secondary；
    The second class of intersection is comprising road segment classification：Main and main intersecting three-way intersection and master and main intersecting simple intersection.
  3. 3. a kind of method that Evaluation of Traffic Safety is carried out to road net planning according to claim 2, it is characterised in that：Institute State the traffic accident number for predicting each type of section and intersection in step 2 respectively；Detailed process is：
    The traffic Accident Forecast Model of the section first kind is YO=0.0334AADT0.245e0.0293V-0.0624W+0.0757N
    The traffic Accident Forecast Model of the second class of section is YT=4.5585AADT0.094e0.256L+0.0419N
    The traffic Accident Forecast Model of section three classes is YTH=232.2931AADT0.2500e-0.1610W+0.0952N
    The traffic Accident Forecast Model of the 4th class of section is YF=26.7625 × e-0.9020L+0.0987N
    The traffic Accident Forecast Model of the intersection first kind is
    The traffic Accident Forecast Model of the second class of intersection is
    In formula, YOFor the traffic accident prediction number of the section first kind；YTFor the traffic accident prediction number of the second class of section；YTH For the traffic accident prediction number of section three classes；YFFor the traffic accident prediction number of the 4th class of section；YO jFor intersection A kind of traffic accident prediction number；YT jFor the traffic accident prediction number of the second class of intersection；AADT is the traffic of annual day Amount；V is speed, unit km/h；W is width of roadway, unit m；N is crossing number；L is road section length, unit km； AADTDTFor straight-going traffic annual average daily traffic；AADTRTFor right-hand rotation traffic annual average daily traffic；NjFor intersection entrance vehicle Road sum.
  4. 4. a kind of method that Evaluation of Traffic Safety is carried out to road net planning according to claim 3, it is characterised in that：Institute The traffic accident number in each type of section and intersection in step 3 based on prediction is stated, differentiates latent defect Multiple trauma； Detailed process is：
    BP neural network model is established, 3 BP neural network input layer, interlayer, output layer transfer functions take respectively Logsigmoid functions, tansigmoid functions and satline functions；
    BP neural network model differentiates model for section hazardous location identification model or crossing accident Multiple trauma；
    Differentiate model for section latent defect Multiple trauma, logsigmoid function neural members number is 10, tansigmoid letters Number neuron number is that 10, satline function neural members number is 3；
    Differentiate model for intersection latent defect Multiple trauma, logsigmoid function neural members number is 5, tansigmoid letters Number neuron number is that 5, satline function neural members number is 3；
    The input variable of BP neural network model for link counting, category of roads, the speed of service, cross-sectional form, number of track-lines, Width of roadway and entrance quantity, the output of BP neural network model are three kinds of security types, be respectively dangerous spot, normal point or Point of safes；
    Dangerous spot is latent defect Multiple trauma.
  5. 5. a kind of method that Evaluation of Traffic Safety is carried out to road net planning according to claim 4, it is characterised in that：Institute Stating BP neural network model foundation process is：
    The 50% of the place of accident number prediction will be carried out in step 2 as training sample, residue 50% is as test sample；
    Place is section and intersection；
    First, training sample is input to BP neural network model to be trained, has obtained input layer, interlayer, each layer of output layer Weight matrix and bias vector, training precision 0.03, complete BP neural network model parameter calibration, obtain trained BP neural network model；
    2nd, trained BP neural network prototype network is tested using test sample, if BP neural network model is defeated The result for going out result with test sample calibration originally is differed within [10%, 30%], then shows that BP neural network model foundation is complete；
    If BP neural network model export the result that result and test sample are demarcated originally differ not [10%, 30%] with It is interior, then one, two are re-executed until BP neural network model output result is differed with the result of test sample calibration originally Within [10%, 30%].
  6. 6. a kind of method that Evaluation of Traffic Safety is carried out to road net planning according to claim 5, it is characterised in that：Institute The security type for stating training sample and test sample is obtained by accident number probability distribution method, matrix method and quality discrimination control methods It arrives, process is：
    When a kind of method in accident number probability distribution method, matrix method and quality discrimination control methods identifies a certain place as thing Therefore Multiple trauma, then the point is dangerous spot sample；
    When all methods in accident number probability distribution method, matrix method and quality discrimination control methods all think a certain place for peace During full point, then the point is point of safes sample；
    Normal point sample is used as in addition to dangerous spot sample and point of safes sample.
  7. 7. a kind of method that Evaluation of Traffic Safety is carried out to road net planning according to claim 6, it is characterised in that：Institute State the latent defect Multiple trauma progress inducement analysis to identifying in step 4；Detailed process is：
    The inducement of latent defect Multiple trauma has link counting, category of roads, cross-sectional form, number of track-lines, width of roadway With entrance quantity；
    Wherein cross-sectional form, category of roads, number of track-lines are scale variable, and scale variable is used to be grouped；
    Width of roadway, entrance quantity, link counting are real value variable；
    Discrimination standard row vector is established to real value variable by probability distribution method, process is：
    Latent defect Multiple trauma is grouped according to scale variable, calculate every group of correspondence real value variable sample data average and Variance, according to ril=Eil+kσilFix limit desired value；Significance takes 95%, and coefficient k value is 1.5；
    In formula, rilFor the boundary desired value of i-th of scale variable of l groups, EilFor the sample data of i-th of scale variable of l groups Average, σilFor the sample data variance of i-th of scale variable of l groups；L values are positive integer；I values are 1,2 or 3；
    For l groups discrimination standard row vector:
    Rl=(r1l,r2l,r3l)
    In formula, r1lFor the boundary desired value of first scale variable cross-sectional form of l groups, r2lBecome for second scale of l groups Measure the boundary desired value of category of roads, r3lFor the boundary desired value of the 3rd scale variable number of track-lines of l groups；
    The real value variable of latent defect Multiple trauma and discrimination standard row vector are compared, if a certain element is more than and sentences in real value variable The corresponding element of other standard row vector, then the element is one of accident inducement；
    A certain element is some in width of roadway, entrance quantity, link counting in real value variable；
    If a certain element is less than or equal to the corresponding element of discrimination standard row vector in real value variable, which does not induce for accident One of factor.
  8. 8. a kind of method that Evaluation of Traffic Safety is carried out to road net planning according to claim 7, it is characterised in that：Institute It states and road network unit traffic safety grading evaluation criteria is established in step 5, traffic safety status classification is carried out to road network；Specific mistake Cheng Wei：
    The net unit that satisfies the need carries out traffic safety classification；Process is：
    Annual average daily traffic AADT is divided into discrete section, to n-th of section, the starting volume of traffic is AADTn, terminate traffic It measures as AADTn+1；It determines the section for being under the jurisdiction of the section or intersection number, and calculates the average E of accident forecast numbernAnd side Poor σn；N values are positive integer；
    When obtaining the E in n-th of sectionn、En+σn、En-σnAfterwards, got back for all sections three groups of new sample datas： {En}、{En+σn}、{En-σn}；{ E is determined respectivelyn}、{En+σn}、{En-σnThree groups of sample datas regression curve y1=f1(x)、 y2=f2(x)、y3=f3(x),
    Wherein x is AADT, y1、y2、y3The respectively average of accident forecast number, average doubles variance and the average times side that subtracts one Difference；
    By three groups of regression curves using AADT as abscissa, accident forecast number is drawn for ordinate, and three groups of regression curves will scheme to draw Four regions are separated, four regions correspond to the traffic safety first order, section or the friendship of section or intersection respectively from bottom to up The traffic safety second level of prong, the traffic safety the 4th of the traffic safety third level in section or intersection, section or intersection Grade；
    Accident forecast number boundary value of each section per level-one is obtained according to three curves to get road network unit traffic safety has been arrived Grading evaluation criteria；
    According to road network unit traffic safety grading evaluation criteria, traffic safety classification is carried out to entire road network；Process is：
    Road grid traffic safety classification standard scale is established, road grid traffic safety classification standard scale includes road grid traffic security level and peace Degree of safety index is divided into H section by whole step index from small to large, and the H degree of safety interval indexs arranged from small to large will Road grid traffic security level is divided into H grades from small to large；
    The weighted average that road grid traffic degree of safety index is road network unit safe class is defined, i.e.,：
    <mrow> <msub> <mi>D</mi> <mrow> <mi>n</mi> <mi>e</mi> <mi>t</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>a</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>c</mi> </munderover> <msub> <mi>L</mi> <mi>a</mi> </msub> <mo>+</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>d</mi> </munderover> <msub> <mi>I</mi> <mi>j</mi> </msub> </mrow> <mrow> <mi>c</mi> <mo>+</mo> <mi>d</mi> </mrow> </mfrac> </mrow>
    Wherein, DnetFor road network degree of safety index, the real number between 1~4 is taken；LaFor the traffic safety rank in a-th of section, take Integer between [Isosorbide-5-Nitrae]；IjFor the traffic safety rank of j-th of intersection, the integer between [Isosorbide-5-Nitrae] is taken；C, d are respectively section With the number of intersection；
    By DnetIt is compared with the degree of safety index in road network safety classification standard scale, finds identical DnetCorresponding safe level Not.
CN201810069917.5A 2018-01-24 2018-01-24 A kind of method that Evaluation of Traffic Safety is carried out to road net planning Pending CN108109378A (en)

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CN110379161A (en) * 2019-07-18 2019-10-25 中南大学 A kind of city road network traffic flow amount distribution method
CN111005274A (en) * 2019-12-25 2020-04-14 广州方纬智慧大脑研究开发有限公司 Automatic generation method, system and storage medium for traffic organization of road plane intersection
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CN108922170B (en) * 2018-06-13 2020-11-27 同济大学 Intersection safety evaluation method based on electronic police snapshot data
CN108986542A (en) * 2018-07-26 2018-12-11 华南理工大学 A kind of automatic distinguishing method of city intersection accident potential stain
CN108986542B (en) * 2018-07-26 2021-03-30 华南理工大学 Automatic distinguishing method for urban intersection accident potential black points
CN109671274A (en) * 2019-01-24 2019-04-23 交通运输部公路科学研究所 A kind of highway risk automatic evaluation method based on latent structure and fusion
CN109671274B (en) * 2019-01-24 2020-09-25 交通运输部公路科学研究所 Highway risk automatic evaluation method based on feature construction and fusion
CN110379161B (en) * 2019-07-18 2021-02-02 中南大学 Urban road network traffic flow distribution method
CN110379161A (en) * 2019-07-18 2019-10-25 中南大学 A kind of city road network traffic flow amount distribution method
CN111005274A (en) * 2019-12-25 2020-04-14 广州方纬智慧大脑研究开发有限公司 Automatic generation method, system and storage medium for traffic organization of road plane intersection
CN111005274B (en) * 2019-12-25 2021-09-14 广州方纬智慧大脑研究开发有限公司 Automatic generation method, system and storage medium for traffic organization of road plane intersection
CN111639837A (en) * 2020-04-30 2020-09-08 同济大学 Road network service performance evaluation method and device, storage medium and terminal
CN111639837B (en) * 2020-04-30 2023-02-10 同济大学 Road network service performance evaluation method and device, storage medium and terminal
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CN112766567B (en) * 2021-01-15 2024-01-09 南通市规划设计院有限公司 Evaluation method, system and storage medium for urban road network planning implementation effect
CN112767697A (en) * 2021-01-19 2021-05-07 东南大学 Traffic safety evaluation method, system and device based on traffic conflict prediction
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