CN103646534A - A road real time traffic accident risk control method - Google Patents
A road real time traffic accident risk control method Download PDFInfo
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- CN103646534A CN103646534A CN201310596435.2A CN201310596435A CN103646534A CN 103646534 A CN103646534 A CN 103646534A CN 201310596435 A CN201310596435 A CN 201310596435A CN 103646534 A CN103646534 A CN 103646534A
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Abstract
The invention discloses a road real time traffic accident risk control method which is a road real time traffic accident risk prediction and control method based on a multi-category support vector machine, and is used for predicting the possibility of occurrence of traffic accidents in a road segment. An accident prediction model based on the multi-category support vector machine is established for the detected road segment, and collected real time traffic characteristic parameters are introduced into the accident prediction model to determine whether risks of the occurrence of the traffic accidents exist. According to the method, the collected real time traffic characteristic parameters are used to predict the traffic accidents which are possible to occur, and the method has relatively good prediction precision, so that defects and insufficiencies in the analysis of traffic safety through utilizing aggregation statistics in the prior art are overcome. The method has a practical engineering application value in determining the risks of occurrence of various kinds of traffic accidents.
Description
Technical field
The invention belongs to intelligent traffic administration system and control technology field, use support vector machine to existing traffic hazard learning classification model and then carry out accident risk discrimination and classification, proposing a kind of to the method for discrimination of certain section road traffic accident occurrence risk and control solution.
Background technology
The increase of automobile pollution and day by day frequently road traffic trip and logistics transportation, bring about a prosperous economy and life aspect in, traffic safety environment has been brought to day by day serious pressure, objectively also the research and development of the safe and smooth without hindrance correlation technique of road traffic environment have been proposed to active demand.
Along with the lifting of traffic safety management level and the development of vehicle active safety technology, transportation security environments has obtained very large improvement; Especially super expressway traffic environment, national freeway traffic environment according to statistics, national traffic accidents quantity is since two thousand three progressively downward trend according to statistics, and accumulative total fall reaches 70%.Yet downtrending is in recent years gradually steady, and the great traffic accidents number of casualties of highway maintains a high position always.At present traffic accidents form main manifestations is: rear-end impact, hit fixture and stationary vehicle, overturning, side impact, just brush up against scraping.
Summary of the invention
The problem to be solved in the present invention is: at transport information Real time data acquisition and storage, become under relatively easy this background, set up the relation between real time traffic data feature and street accidents risks, propose road real-time traffic accident risk prediction and control method based on multi-class support vector machine.
Technical scheme of the present invention is: based on multi-class support vector machine road real-time traffic accident risk prediction control method, surveyed area is set up road real-time traffic accident risk prediction and controlled model, by substitution Real-time Road accident risk identification and classification model after real time traffic data information proposition feature, according to Real-time Road accident risk identification and classification model Output rusults predicted detection region, whether have an accident and accident pattern, propose thus corresponding control measure.From two aspects below, launch: (1), street accidents risks affair character extract; (2), road traffic risk profile and control.
Technical scheme: for solving the problems of the technologies described above, the present invention adopts based on multi-class support vector machine road real-time traffic accident risk prediction and control method, comprises the following steps:
Steps A) gather under normal traffic states and have accident to occur before data sample N group { X under the state of t second (0.01≤t≤0.1)
1, X
2..., X
n.Each X
i(I=1,2,3 ..., N) comprise people, car, road, environmental information: according to the time of origin of traffic hazard and generation section, people from section sex x occurs in random acquisition traffic hazard
1, driving efficiency x
2; The spacing x of car
3, speed of a motor vehicle x
4, vehicle condition x
5; The type x of road
6, pavement behavior x
7, traffic x
8; And the weather x on the same day
9, pedestrian's situation x
10, visibility x
11.
Step B) gather and above-mentioned data sample { X
1, X
2..., X
ncorresponding traffic hazard classification sample { Y
1, Y
2..., Y
n, each Y
i(I=1,2,3 ..., N) corresponding to { w
1, w
2, w
3in a certain.W wherein
1represent rear-end impact accident, w
2represent to hit fixture and stationary vehicle, w
3represent normal condition.
Step C) traffic hazard data pre-service: training sample set is above-mentioned N group historical data sample { X
1, X
2..., X
n, wherein, each X
i={ x
1, x
2..., x
11(I=1,2,3 ..., N group casualty effect { Y N) and corresponding thereto
1, Y
2..., Y
n, each Y wherein
i(I=1,2 ..., N) corresponding to { w
1, w
2, w
3in a certain.
Step D) utilize above-mentioned sample data training multi-class support vector machine, draw accidents classification decision function
Parameter a
j, b
j.
Step e) to the classification of above-mentioned N group data sample, to sample X
i(I=1,2,3 ..., N), establish
x
iclassification be g (X
i)=w
j.
Step F) if sample X
iprediction classification g (X
i) be different from true classification Y
i, optimize multi-class support vector machine parameter, go to step D), until reach best result class precision.
Step G) every s second (0.01≤s≤0.1), gather real time traffic data X, i.e. people's sex x
1, driving efficiency x
2; The spacing x of car
3, speed of a motor vehicle x
4, vehicle condition x
5; The type x of road
6, pavement behavior x
7, traffic x
8, and the weather x on the same day
9, pedestrian's situation x
10, visibility x
11.According to criterion
x is assigned to w
jin class, i.e. the classification g of X (X)=w
j.
Step H) if g (X) equals w
1or w
2differentiate the current risk that has generation traffic hazard in this section, driver is carried out to early warning, as passed through variable information plate in this place ahead, section, and start opertaing device, by controlling the ring road of road or the Intersections of through street, reduce upstream vehicle flow, by variable speed-limit plate, to current limiting vehicle speed, reduce the travel speed of upstream vehicle.
Step I) if g (X) equals w
3, this section is current is safe condition, without the prompting that gives the alarm, goes to step G).
Compared with prior art, technical scheme of the present invention has following beneficial effect:
Accident judging nicety rate is high.Existing street accidents risks detection method is only utilized traffic flow data measuring and calculating traffic hazard probability, and the present invention has gathered simultaneously affects the several data of traffic hazard information, thereby can improve street accidents risks accuracy of detection.Bring the traffic information data in the section of Real-time Collection into traffic hazard discriminant classification function after study, in real time traffic hazard is occurred in section and detect.According to traffic hazard, whether occur, determine that current whether needs start early warning means, reduce street accidents risks, thereby improved the accuracy rate of vehicle regulation and control, reduced traffic hazard, effectively ensured the traffic safety of through street.Testing process is simple.In the present invention, obtain only need to gathering after classification function the real time traffic data information in section, just can real-time estimate setting-up time in future in, whether this section there is traffic hazard, easy to use, practical, has good application prospect.
Accompanying drawing explanation
Fig. 1 is accident identification and classification FB(flow block) of the present invention.
Fig. 2 is the real-time testing process schematic diagram of road in the present invention.
Embodiment
Below in conjunction with drawings and Examples, technical scheme of the present invention is described in further detail.
The invention discloses a kind of based on the real-time traffic accident risk differentiation of support vector machine analysis road and control method, according to the historical traffic accident information gathering, the discriminant classification function that utilizes multi-class support vector machine to set up, whether predicted detection section there is the risk that traffic hazard occurs, if occurred, take the corresponding opertaing device of Real-time Road, otherwise continue image data, judge next time; The advantage of the inventive method is to utilize the real-time traffic characteristic parameter that road traffic checkout equipment obtains to carry out real-time estimate to traffic hazard, and has good precision of prediction.Thereby this method is being differentiated the risk of through street traffic hazard, prediction traffic hazard generation aspect has actual engineering application and is worth.
The Real-time Traffic Information collecting, weather data, pedestrian's data, vehicle data information are brought in the traffic hazard identification and classification function that the present invention sets up, whether calculate current generation traffic hazard.If recorded, have an accident, show the current risk that has generation traffic hazard in this section, should give the alarm, and activate the control program reduction accident risk in dynamic traffic control system, then continue image data; If recorded, do not have an accident, continue image data, judge next time.
Vehicle regulate and control method of the present invention is according to the real time traffic data, weather data, pedestrian's data, the vehicle data that gather, and judgement detects the current risk that traffic hazard occurs that whether exists in section, is to adopt multi-class support vector machine analysis.
Practice process of the present invention is divided into be set up traffic hazard discriminant function relational expression and detects two processes of traffic hazard.
Set up accidents classification discriminant function relational expression: collect or casualty data, weather data and traffic data in a period of time of acquisition testing section.In order to guarantee that the accident forecast function of setting up can have good precision of prediction, the sample of collection is as far as possible large, and accident group data sample is greater than 200 conventionally, and normal group data sample is greater than 400.According to above-mentioned steps A) to step F) by training sample set, draw identification and classification function.
Claims (6)
1. a road real-time traffic accident risk control method, is characterized in that, concrete steps are:
Steps A) gather under normal traffic states and have accident to occur before data sample N group { X under the state of t second (0.01≤t≤0.1)
1, X
2..., X
n; Each X
i(I=1,2,3 ..., N) comprise people, car, road, environmental information: according to the time of origin of traffic hazard and generation section, people from section sex x occurs in random acquisition traffic hazard
1, driving efficiency x
2; The spacing x of car
3, speed of a motor vehicle x
4, vehicle condition x
5, road type x
6, pavement behavior x
7, traffic x
8; And the weather x on the same day
9, pedestrian's situation x
10, visibility x
11;
Step B) gather and above-mentioned data sample { X
1, X
2..., X
ncorresponding traffic hazard classification sample { Y
1, Y
2..., Y
n, each Y
i(I=1,2,3 ..., N) corresponding to { w
1, w
2, w
3in a certain.W wherein
1represent rear-end impact accident, w
2represent to hit fixture and stationary vehicle, w
3represent normal condition;
Step C) traffic hazard data pre-service: training sample set is above-mentioned N group historical data sample { X
1, X
2..., X
n, wherein, each X
i={ x
1, x
2..., x
11(I=1,2,3 ..., N group casualty effect { Y N) and corresponding thereto
1, Y
2..., Y
n, each Y wherein
i(I=1,2 ..., N) corresponding to { w
1, w
2, w
3in a certain;
Step D) utilize above-mentioned sample data training multi-class support vector machine, draw accidents classification decision function
Parameter a
j, b
j;
Step e) to the classification of above-mentioned N group data sample, to sample X
i(I=1,2,3 ..., N), establish
x
iclassification be g (X
i)=w
j;
Step F) if sample X
iprediction classification g (X
i) be different from true classification Y
i, optimize multi-class support vector machine parameter, go to step D), until reach best result class precision;
Step G) every s, gather real time traffic data X, i.e. people's sex x second
1, driving efficiency x
2; The spacing x of car
3, speed of a motor vehicle x
4, vehicle condition x
5; The type x of road
6, pavement behavior x
7, traffic x
8, and the weather x on the same day
9, pedestrian's situation x
10, visibility x
11.According to criterion
x is assigned to w
jin class, i.e. the classification g of X (X)=w
j;
Step H) if g (X) equals w
1or w
2, differentiate the current risk that has generation traffic hazard in this section, driver is carried out to early warning;
Step I) if g (X) equals w
3, this section is current is safe condition, without the prompting that gives the alarm, goes to step G);
2. according to road real-time traffic accident risk control method claimed in claim 1, it is characterized in that described steps A) in, t second before described traffic hazard occurs: 0.01≤t≤0.1.
3. according to road real-time traffic accident risk control method claimed in claim 1, it is characterized in that, on detection road, Vehicle License Plate Recognition System is installed, for each board, transfers the corresponding information data of driver in data bank, extract its sex and driving age and passing traffic hazard historical data.
4. according to road real-time traffic accident risk control method claimed in claim 1, it is characterized in that described step G) in, transport information sampling time interval s meets 0.01≤s≤0.1.
5. according to road real-time traffic accident risk control method claimed in claim 1, it is characterized in that, described step H) early warning in is: as passed through variable information plate in this place ahead, section, and start opertaing device, by controlling the ring road of road or the Intersections of through street, reduce upstream vehicle flow, by variable speed-limit plate, to current limiting vehicle speed, reduce the travel speed of upstream vehicle.
6. according to road real-time traffic accident risk control method claimed in claim 5, it is characterized in that, by variable speed-limit plate, to current limiting vehicle speed, each car speed amplitude of adjusting variation is in 5km/h.
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