CN102368354A - Road security evaluation method based on floating vehicle data acquisition - Google Patents
Road security evaluation method based on floating vehicle data acquisition Download PDFInfo
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- CN102368354A CN102368354A CN2011103191488A CN201110319148A CN102368354A CN 102368354 A CN102368354 A CN 102368354A CN 2011103191488 A CN2011103191488 A CN 2011103191488A CN 201110319148 A CN201110319148 A CN 201110319148A CN 102368354 A CN102368354 A CN 102368354A
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Abstract
The invention provides a road security evaluation method based on floating vehicle data acquisition. The method is characterized in that: considering that unsafety of a road can be reflected on an operation of a driver which drives a vehicle, the unsafety is reflected on parameters of floating vehicle speed, acceleration and the like. Thus, through installing a data acquisition apparatus on the floating vehicle, data is acquired and processed, an evaluation index reflecting road unsafety is obtained and is subjected to a gray cluster analysis, security of the road is divided into four levels of excellent, good, fair and poor, and traffic accident data in previous years is utilized to examine a road safety threshold. By utilizing floating vehicle acquisition data, security of the road is subjected to evaluation, an evaluation result is more visual and accurate, simultaneously timely discovering an unsafe road is facilitated, the unsafe rode is improved, drivers on the road are prompted to pay attention to driving safety, and generation of traffic accidents are reduced.
Description
Technical field
The present invention relates to a kind of road safety evaluation method of gathering based on floating car data.Because the insecurity of road can be reflected in driver's the operation; Installation data harvester on Floating Car; Image data is also handled, and obtains reflecting the evaluation index of road insecurity, like percentage speed variation, add/the deceleration frequency, bearing circle rotary speed etc.Through on highway section to be evaluated, going, utilize grey clustering analysis with the security of road be divided into excellent, good, in, differ from four grades, and safety threshold is tested.
Background technology
Along with expanding economy, newly-built road and motor vehicle quantity are on the increase, and the road safety problem also increases gradually.The security of road is estimated and analyzed, important meaning is arranged, road safety evaluation and Floating Car image data aspect have all been launched correlative study both at home and abroad for minimizing traffic hazard number, raising road safety.
Further investigate the road safety evaluation since nineteen ninety abroad, Australia, Britain, New Zealand, Norway etc. implement road safety evaluation country early, and the U.S. has introduced the road safety evaluation in the nineties.Nineteen ninety, Britain proposed the method that road safety is estimated, and rose in England and Scotland in April, 1991 and carried out the safety evaluation of arterial road and highway projects, again road safety was estimated instruction and had carried out revising in 1996.Australia approximately in the past 15 in the period of; Stress that always the road safety engineering is to reduce the road accident rate; The action investigation accident prone location that many Highway Administration Bureaus all take the initiative; And worked out the road safety evaluation guide, each state of Australia all in various degree begin to adopt Road Safety Audit.In Canada, in order to eliminate the traffic safety hidden danger of road itself, the effective measures that Canadian government is taked in the road traffic construction are carried out the road safety evaluation system exactly.In the 21 world's road meeting in 1999; Marc GAUDRY and Karine VERNIER are on the research basis of original path management system; Use the mathematical statistics scheduling theory,, set up the relation of accident rate and accident (Crash) severity and road traffic environment etc. respectively through a large amount of investigation; Relational model between the speed of a motor vehicle and the road traffic environment, and done preliminary identification.On this basis, the speed of a motor vehicle and accident risk relational model some Primary Study have been done.Foreign study shows that the road safety evaluation can effectively prevent traffic hazard, reduces the road accident rate and the order of severity, reduces road and opens the back reconstruction, improves and the operation management expense, promotes the traffic safety culture.According to the national statistics of carrying out safety evaluation, the return rate of safety evaluation is 15～40 times of investment.
Contrast foreign study present situation, domestic research still is in the starting stage.The Guo Zhongyin of Tongji University professor research direction mainly is the relation of road alignment and traffic safety; Nineteen ninety-five takes the lead in road safety is carried out systematic research at home; What at first carry out is that road safety evaluation and road stain are differentiated and improved Study on Technology; Further disclosed the relation of road traffic environment and road safety afterwards, for design provides foundation to road safety, card is in the research of carrying out in a deep going way to concern between road traffic environment, road travelling speed, the road safety three.Xiong Jian teach in 2006 on the basis of " people's---car---environment " road traffic drive simulation experiment porch, the correlation technique of Urban Road Traffic Design virtual reality system has been accomplished in research, has realized the digitizing of urban highway traffic and visual.Traffic Institutes Of Chongqing has accomplished the linear safety evaluatio research of mountainous area highway in 2005.This research has proposed to set up theory and the method based on the linear security model of mountainous area highway of artificial neural network first; And set up the linear security relationship model of mountainous area highway operating speed forecast model, operating speed and mountainous area highway on this basis, disclosed that mountainous area highway is linear, concerned between operating speed and the operation security property.
At present, the Floating Car technology is also carried out correlative study both at home and abroad, set up the Floating Car system that is fit to own characteristic of city.The ADVANCE plan in Chicago,U.S area, through merging data and the historical accident examining report research Floating Car technology that annular detector is gathered, wherein the Floating Car report can be estimated journey time more accurately than toroid winding.Korea S has begun in 1996 that " Korea S's Traffic Information " center " (KORTIC) systematic research main is just carried out traffic data collection through moving detection vehicle annular detector and closed loop circuit TV monitoring and controlling.The Oregon of Poland adopts motorbus to estimate that as Floating Car the average overall travel speed of road section has had actual result; Engineering staff's research has drawn under certain highway section motorbus goes top speed and can be used as the theory of this highway section vehicle average overall travel speed, and extends to other roads in this city.At home; Utilize Floating Car to analyze traffic and be still a newer field; Guangzhou, Hangzhou, Beijing and Chongqing have begun at traffic and transportation system GPS to be installed on a large scale, and existing unit utilizes Floating Car to hire a car in Hangzhou, utilizes the analysis of public transport Floating Car research road traffic condition in Guangzhou.
At present; More existing patent Applying Floating car data image data carry out that the road is clear Journal of Sex Research and traffic evaluation; Like number of patent application: 201010601798.7 " based on the traffic jam point recognition methods of Floating Car technology "; Utilization utilizes the regular in the process of moving collection vehicle numbering of Floating Car, Position, Velocity and Time information, obtains traffic jam point position after the processing; Number of patent application: 201110030820.1 " the traffic flow crossing based on floating car data turns to time-delay to obtain system and method " can provide a kind of new traffic flow crossing to turn to delay data; " based on the method for evaluating macroscopic road network traffic state of floating car data " of number of patent application: CN200910088917.0 utilizes Floating Car to obtain each item traffic behavior evaluation index, and road network is estimated; " traffic evaluation method and the system " of number of patent application: CN201010520218.1 utilizes floating car data to obtain transport information and it estimated.
Analyze domestic and international research present situation and patent situation; Floating Car mainly is used for image data; Aspect traffic, mainly use Floating Car to carry out road management and traffic evaluation; Therefore the correlative study that does not at present also utilize floating car data that road safety is estimated, utilizes floating car data that road safety is estimated and analysis has crucial meaning.
Summary of the invention
The present invention realizes through following technology:
1, utilizes the security of floating car data evaluation path
On unsafe highway section, the driver need take corresponding operation to avoid the generation of accident, and these operations are different with operation under normal circumstances.As when traffic conflict took place, the driver was for fear of bumping against with opposed vehicle, can suddenly slow down, suddenly beat bearing circle, get over line etc.Therefore, the insecurity of road can be reflected in the specific operation of driver, and driver's operation can be with the changes in vehicle speed rate, add/and deceleration frequency etc. representes.Utilize the corresponding data of Floating Car collection reflection driver's operation, promptly can utilize these data that road safety is estimated.
The data that need to gather are seen table 1 with the employed equipment of collection.
Data and equipment that table 1 is gathered
| The data of gathering | The equipment that uses |
| The speed of Floating Car, position, road curvature | GPS |
| The acceleration, deceleration degree of Floating Car | Gyroscope |
| Floating Car steering wheel angle, braking number of times | The backguy displacement transducer |
| Driver's sighting distance, Floating Car are got over the line situation | Camera |
| Road grade | Slope Transducer |
2, evaluation index rationally chooses
Rationally choose evaluation index, help accurately to judge the security of road.Evaluation index needs to reflect road conditions comprehensively, from people, car, three aspects, road road is estimated.Data to Floating Car collects are handled, and can extract evaluation index.The evaluation index of choosing is seen table 2.
Table 2 evaluation index
3, the standardization of evaluation index
For increasing the science and the accuracy of evaluation result, need carry out standardization to index.Can know that by table 2 evaluation index of choosing all is a quantitative target, and the implication of each index is different, computing method are different, causes the dimension of each index also different, can not measure each other between the index, brought inconvenience to evaluation.
The general profitable type of the type of quantitative target, cost type, fixed, interval type etc.Benefit type attribute is meant the attribute that property value is the bigger the better, like driver's sighting distance value; Cost type attribute is meant the more little good more attribute of property value, like the rotary speed of bearing circle; The fixed attribute is meant that property value is more near the good more attribute of certain fixed value; Depart from the type attribute and be meant that property value departs from the good more attribute of certain fixed value; Interval type attribute is meant that property value is more near the good more attribute in certain interval, like Floating Car speed.In order to reflect actual conditions as much as possible, get rid of the influence that brings owing to the difference of unit difference and numerical value magnitude between each index, each index unification is changed in [0,1] scope.According to dissimilar indexs, normalization function has following several types:
The normalization function of cost type index:
The normalization function of benefit type index:
The normalization function of fixed index:
The normalization function of interval type index:
In the formula: M
iBe the maximal value of evaluation index i, m
iBe the minimum value of evaluation index i, d
i=[m
i, M
i] be the threshold value of evaluation index i, x
iBe the property value of evaluation index i, m
*Be fixed value,
Be fixed interval.
4, grey clustering analysis
After index carried out standardization, can carry out safety evaluatio to road.Grey cluster is that the albefaction weight function according to grey correlation matrix or grey number is gathered into several definable class method for distinguishing with some observation indexs and object of observation.Floating Car is gone on many highway sections, and the evaluation index when obtaining on these highway sections, going adopts GRAY CLUSTER that the security in highway section to be evaluated is classified, with road safety be divided into excellent, good, in, differ from four grades.
The highway section that n is to be evaluated is as cluster object { x
i(i=1,2 ..., n); M evaluation index is as cluster index { u
j(j=1,2 ... m); S evaluation criterion (promptly excellent, good, in, differ from four grades) is as cluster ash type { z
k(k=1,2 ..., s).Then according to the sample value x of i cluster object for j cluster index
Ij, confirm that the cluster sample matrix is X:
Adopt probabilistic method to confirm evaluation index; Real data with evaluation index; Handle through nondimensionalization, analyze the cumulative percentage frequency of data, draw the cumulative percentage frequency curve; On curve, confirm the pairing numerical value of different specific cumulative percentage frequencies, in the road safety excellent, good, in, differ from the pairing values of respectively corresponding 15%, 40%, 60%, the 85% cumulative percentage frequency curve of four grades.
Adopt Fuzzy consistent matrix and root method to confirm the weight of each index, structure cluster vector can carry out cluster to certain object, and safety evaluatio is carried out in highway section to be evaluated.
5, the accuracy of check threshold value
The grey clustering analysis method road safety is divided into " in " and the value of the overall target of " poor ", be the threshold value of dividing road safety.According to cluster result, the gps data that will be divided into the highway section of " poor " extracts, and these highway sections are shown on map.Extract traffic hazard in the former years data in all highway sections, and the branch highway section compares.If the traffic hazard number in " poor " highway section is apparently higher than other highway sections, then threshold value is correct, otherwise just need reselect threshold value.
Performing step:
(1) relevant device is installed on Floating Car,, and is debugged successfully, on highway section to be evaluated, go like GPS, gyroscope etc., and measurement data;
(2) data that obtain are handled, obtained the value of evaluation index on each highway section;
(3) evaluation index is carried out standardization;
(4) utilize the grey clustering analysis method, treat evaluation path and carry out safety evaluatio;
(5) extract all highway section traffic hazard in former years data, the correctness of check threshold value and evaluation result.
The present invention has following characteristics: driver's operation is the main cause that causes traffic hazard; The present invention with driver's maloperation with percentage speed variation, add/the deceleration frequency, the bearing circle velocity of rotation waits and quantizes; With grey clustering method road safety is estimated; And test with traffic hazard in former years number, make evaluation result more accurately with directly perceived.
Embodiment
(1) GPS, gyroscope, backguy displacement transducer, camera and Slope Transducer are installed on Floating Car, and debug successfully.On highway section to be evaluated, go, read Floating Car speed on these highway sections, acceleration-deceleration, position, steering wheel angle, braking number of times, line situation, road grade, road curvature, driver's sighting distance information more.
(2) the data branch highway section that obtains is handled, obtain the value of each evaluation index: difference, the acceleration-deceleration of Floating Car, bearing circle rotary speed, the Floating Car of difference, Floating Car speed, highway section fixing speed and the Floating Car speed of real-time driver's sighting distance value, driver's sighting distance and regulation driving sighting distance are got over linear distance, road grade, curvature on the highway section; This highway section come-up motor-car acceleration-deceleration frequency, braking frequency and line frequency more.
(3) evaluation index is carried out standardization: wherein, driver's sighting distance value belongs to benefit type index, is the bigger the better; The difference of difference, highway section fixing speed and the Floating Car speed of driver's sighting distance and regulation driving sighting distance, bearing circle rotary speed, braking frequency, Floating Car more line frequency, Floating Car more linear distance, road grade belong to cost type index, more little good more; Floating Car speed, Floating Car acceleration-deceleration, Floating Car acceleration-deceleration frequency, road curvature belong to interval type index, and be good more near certain interval more.Dissimilar indexs is carried out standardization according to different standardization formula, unified changing in [0,1] scope.
(4) with each evaluation index as evaluation criterion, adopt the grey clustering analysis method, with the security in different highway sections be divided into excellent, good, in, differ from four grades.
(5) road safety is divided into " in " and the value of the overall target of " poor ", be the road safety threshold value.All highway section traffic hazard in former years numbers are extracted, if the traffic hazard number in highway section that is cited as " poor " obviously more than other highway sections, then selection of threshold is correct, evaluation result is accurate.And the highway section that will be cited as " poor " is presented on the map.
Claims (6)
1. road safety evaluation analysis method of gathering based on floating car data is characterized in that:
Comprise the steps:
(1) relevant device is installed on Floating Car,, and is debugged successfully, on highway section to be evaluated, go like GPs, gyroscope etc., and measurement data;
(2) data that obtain are handled, obtained the value of evaluation index on each highway section;
(3) evaluation index is carried out standardization;
(4) utilize the grey clustering analysis method, treat evaluation path and carry out safety evaluatio;
(5) extract all highway section traffic hazard in former years data, the correctness of check threshold value and evaluation result.
2. road safety evaluation analysis method of gathering according to claim 1 based on floating car data; It is characterized in that; Described step (1) specifically is meant: GPs, gyroscope, backguy displacement transducer, camera and Slope Transducer are installed on Floating Car, and debug successfully.On highway section to be evaluated, go, read Floating Car speed on these highway sections, acceleration-deceleration, position, steering wheel angle, braking number of times, line situation, road grade, road curvature, driver's sighting distance information more.
3. road safety evaluation analysis method of gathering according to claim 1 based on floating car data; It is characterized in that; Described step (2); Specifically be meant: handle in the data branch highway section to obtaining, and obtains the value of each evaluation index: difference, the acceleration-deceleration of Floating Car, bearing circle rotary speed, the Floating Car of difference, Floating Car speed, highway section fixing speed and the Floating Car speed of real-time driver's sighting distance value, driver's sighting distance and regulation driving sighting distance are got over linear distance, road grade, curvature on the highway section; This highway section come-up motor-car acceleration-deceleration frequency, braking frequency and line frequency more.
4. road safety evaluation analysis method of gathering according to claim 1 based on floating car data; It is characterized in that described step (3) specifically is meant: evaluation index is carried out standardization: wherein; Driver's sighting distance value belongs to benefit type index, is the bigger the better; The difference of difference, highway section fixing speed and the Floating Car speed of driver's sighting distance and regulation driving sighting distance, bearing circle rotary speed, braking frequency, Floating Car more line frequency, Floating Car more linear distance, road grade belong to cost type index, more little good more; Floating Car speed, Floating Car acceleration-deceleration, Floating Car acceleration-deceleration frequency, road curvature belong to interval type index, and be good more near certain interval more.Dissimilar indexs is carried out standardization according to different standardization formula, unified changing in [0,1] scope.
5. road safety evaluation analysis method of gathering according to claim 1 based on floating car data; It is characterized in that; Described step (4); Specifically be meant: each evaluation index as evaluation criterion, is adopted the grey clustering analysis method, with the security in different highway sections be divided into excellent, good, in, differ from four grades.
6. road safety evaluation analysis method of gathering according to claim 1 based on floating car data; It is characterized in that; Described step (5) specifically is meant: road safety is divided into " in " and the value of the overall target of " poor ", be the road safety threshold value.All highway section traffic hazard in former years numbers are extracted, if the traffic hazard number in highway section that is cited as " poor " obviously more than other highway sections, then selection of threshold is correct, evaluation result is accurate.And the highway section that will be cited as " poor " is presented on the map.
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| CN103226666A (en) * | 2013-05-10 | 2013-07-31 | 天津市市政工程设计研究院 | Method for evaluating effect of complex function interflow vertical crossing system |
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| CN108182802A (en) * | 2017-12-26 | 2018-06-19 | 夏莹杰 | A kind of Traffic Safety Analysis method driven based on information attenuation model and by car plate data mining |
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| CN108711281A (en) * | 2018-03-23 | 2018-10-26 | 武汉理工大学 | A method of with section actual driving speed data evaluation Highway Safety |
| CN108765956A (en) * | 2018-06-14 | 2018-11-06 | 广东工业大学 | A kind of traffic status of express way comprehensive estimation method |
| CN110264825A (en) * | 2019-07-31 | 2019-09-20 | 交通运输部公路科学研究所 | A kind of drive simulation safe evaluation method, apparatus and system |
| CN111179590A (en) * | 2019-12-24 | 2020-05-19 | 山东国惠安创智能物联发展有限公司 | Remote control method and server for driving speed of electric vehicle |
| CN114037268A (en) * | 2021-11-08 | 2022-02-11 | 哈尔滨工业大学 | Highway prior safety evaluation system suitable for design phase |
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Application publication date: 20120307 |