CN101587644B - Automatic detection method for traffic accident on urban expressway based on non-continuous sliding sequence - Google Patents

Automatic detection method for traffic accident on urban expressway based on non-continuous sliding sequence Download PDF

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CN101587644B
CN101587644B CN2009100523520A CN200910052352A CN101587644B CN 101587644 B CN101587644 B CN 101587644B CN 2009100523520 A CN2009100523520 A CN 2009100523520A CN 200910052352 A CN200910052352 A CN 200910052352A CN 101587644 B CN101587644 B CN 101587644B
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occupation rate
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minute
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traffic
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杜豫川
孙立军
蔡晓禹
汤震
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Shanghai Jiafeng Chelu Digital Technology Co.,Ltd.
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Tongji University
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Abstract

The invention provides an automatic detection method for traffic accident on urban expressway based on non-continuous sliding sequence, which collects real time traffic flow information through a detection system and an earth coil; whether a traffic accident happens is judged according to the obtained average time occupancy data with process using a non-continuous sliding one-minute occupancy sequence. If an accident happens, the alarm sends out for announcing the traffic management department to take corresponding measures for the accident, otherwise the data is continued to be collected for detection. The method provided by the invention has the advantages of high detection rate for detection, low false alarm rate, short testing time, selected index with clear meaning, and is suitable for realizing engineering.

Description

City expressway automatic detection method for traffic accident based on non-continuous sliding sequence
Technical field
The present invention relates to a kind of city expressway automatic detection method for traffic accident; Particularly be based on the city expressway automatic detection method for traffic accident of 1 minute occupation rate sequence of discontinuous slip; Can be used for whether existing traffic hazard to carry out real time automatic detection, relate to traffic intelligent management and control technology city expressway.
Background technology
Traffic hazard is meant: continue a period of time, cause road passage capability to reduce, and background traffic flow situation is produced the accident of appreciable impact.City expressway is being brought into play enormous function as the skeleton of urban road traffic network.The burst traffic hazard not only is embodied in safety of person vehicle is formed threat the influence of city expressway, and more important is the traffic congestion bottleneck that generation is comparatively serious, and causes the Urban Expressway System operational efficiency to reduce.Reduce the negative effect of burst accident to Urban Expressway System, one of key link is a discovery accident fast and accurately.
Traffic hazard detects the element that (Automatic Incident Detection) is advanced person's traffic control and management system automatically, its objective is through finding traffic hazard as early as possible, carries out the scene cleaning as early as possible, and the minimizing accident is to the influence of traffic flow.Along with the appearance of (often claiming vehicle checker) of traffic data real-time automatic collecting equipment, various automatic accident detection method ultimate principles based on vehicle checker are identical: through the variation of identification accident generation back road traffic condition, reach the purpose of the accident of detecting.Automatic accident detection method; Owing to do not need people's participation, and the variation of traffic is had automatic identification capability, discovery accident is quick and precisely gone forward side by side and is acted so report to the police; Therefore take the emergency processing measure as early as possible after more helping accident to take place; Reduce duration of fault, the loss that the reduction accident is caused becomes the focus that various countries are studied.
Automatically the development of accident detection algorithm mainly comprises state recognition, traffic and theoretical model, statistics, artificial intelligence and image recognition etc. so far at present.But have its limitation separately: the state recognition method requires rule of thumb calibration index threshold value, but is using the later stage to be difficult to revise; Catastrophe theory is difficult enforcement on the city expressway of traffic stream characteristics complicacy; Mathematical statistics and artificial intelligence all need a large amount of detailed accident samples to learn; Image recognition algorithm receives weather effect bigger.In the above algorithm, have only the state recognition algorithm to obtain the application verification on the engineering, other algorithms only stay in theory or simulation study stage mostly.
Summary of the invention
The objective of the invention is to overcome the deficiency that existing automatic accident detection algorithm exists; Propose a kind of city expressway automatic detection method for traffic accident based on 1 minute occupation rate sequence of discontinuous slip, its verification and measurement ratio, detection time and rate of false alarm all are superior to existing algorithm.
For reaching above purpose, the solution that the present invention adopted is:
A kind of city expressway automatic detection method for traffic accident based on non-continuous sliding sequence, it may further comprise the steps:
1) detection system is gathered the telecommunication flow information of a fixed step size in real time through earth coil;
2) judge according to the real-time traffic stream information of gathering whether have traffic hazard take place, if judgement has an accident then give the alarm, notice vehicle supervision department takes corresponding measure if detecting the highway section; Otherwise continue to read real time data, judge next time;
The collection of described real-time traffic stream information generates 1 minute occupation rate data sequence of discontinuous slip as the basic data of differentiating algorithm.
Structure serves as the 1 minute occupation rate sequence of discontinuous slip at interval of sliding with minimum period 20s, and its construction method is:
if o i 20 s > 1.5 * o i - 1 mov 5 m or o i 20 s < 0.5 * o i - 1 mov 5 m o i + 1 20 s > 1.5 * o i - 1 mov 5 m or o i + 1 20 s < 0.5 * o i - 1 mov 5 m o i + 2 20 s > 1.5 * o i - 1 mov 5 m or o i + 2 20 s < 0.5 * o i - 1 mov 5 m , O i = o i + 2 1 m
else， O i = o i mov 1 m
Wherein: O i---i value of 1 minute occupation rate sequence of discontinuous slip;
---i value of average 1 minute occupation rate sequence;
Figure GSB00000628670200024
---with 20s is at interval, i value of the 1 minute occupation rate sequence of sliding;
I value of ---20s occupation rate sequence;
Figure GSB00000628670200026
---with 20s is at interval, i value of the 5 minutes occupation rate sequences of sliding.
Judge the method whether highway section has an accident that detects:
1) handles the detection road section traffic volume stream information of gathering in real time, generate 1 minute occupation rate data sequence of discontinuous slip;
2) confirm the threshold value of judge index;
Whether the correlated judgment index of 3) calculating 1 minute occupation rate data sequence of discontinuous slip is compared with decision threshold, judge to have an accident.
The correlated judgment index of 1 minute occupation rate data sequence of described discontinuous slip is respectively occupation rate O T, k, 1 minute occupation rate of k section t discontinuous slip constantly; The occupation rate time difference
Figure GSB00000628670200027
K section t constantly with the difference of 1 minute occupation rate of t-1 discontinuous slip constantly; Occupation rate space difference
Figure GSB00000628670200028
The difference of t moment upper reaches k section and 1 minute occupation rate of the discontinuous slip of adjacent downstream k+1 section; Occupation rate space time difference
Figure GSB00000628670200029
T is occupation rate space difference and t-1 moment occupation rate space difference poor constantly.
Threshold value determination method is: based on the off-line calibration of historical casualty data or based on predetermined threshold value and in one day accident and non-casualty data online review one's lessons by oneself just definite.
Described occupation rate O T, k, the occupation rate time difference
Figure GSB000006286702000210
Occupation rate space difference
Figure GSB000006286702000211
With occupation rate space time difference
Figure GSB000006286702000212
When all being not less than threshold value, the judgement accident takes place.
According to the needs that accident detects automatically, the basic data that is used for the judgement accident should satisfy following two basic demands: under accident situation, have good mutability, be convenient to carry out accident identification; Under non-accident situation, have good stationarity, reduce the false alarm under the normal traffic situation.Adopt 1 minute occupation rate sequence of discontinuous slip to carry out data processing, can realize this two targets effectively.
Owing to adopted such scheme, the present invention to have following characteristics: accident verification and measurement ratio of the present invention is high, and false alarm rate is low, and detection time is short, and index for selection has clear and definite meaning, is fit to Project Realization.
Description of drawings
Fig. 1 is 1 minute occupation rate sequence of discontinuous slip (O i) algorithm flow that makes up;
Fig. 2 is the signal of many indexs serial accident determination methods;
Fig. 4 is the off-line calibration method based on historical casualty data;
Fig. 5 is the online from modification method of threshold value;
Fig. 6 is that threshold value is from the correction algorithm flow process.
Embodiment
Below in conjunction with the accompanying drawing illustrated embodiment the present invention is further described.
Research shows, as far as with 20 seconds be the time average occupation rate data of step-length, its undulatory property is bigger, is difficult to directly apply to automatic accident detection algorithm.If employing was the time average occupation rate data sequence of step-length with 1 minute, have mutability under the best accident, but sense cycle was extended for 1 minute from 20 seconds; And 20 seconds serving as that the 1 minute occupation rate sequence of slip at interval of sliding has stationarity under the best non-accident, but the sudden change under the accident is obvious inadequately.The minimum period 20s that 1 minute occupation rate sequence of discontinuous slip is obtained with data slides at interval, and in conjunction with the advantage of above two kinds of data sequences, its construction method is following:
if o i 20 s > 1.5 * o i - 1 mov 5 m or o i 20 s < 0.5 * o i - 1 mov 5 m o i + 1 20 s > 1.5 * o i - 1 mov 5 m or o i + 1 20 s < 0.5 * o i - 1 mov 5 m o i + 2 20 s > 1.5 * o i - 1 mov 5 m or o i + 2 20 s < 0.5 * o i - 1 mov 5 m , O i = o i + 2 1 m
else， O i = o i mov 1 m
In the formula: O i---i value of 1 minute occupation rate sequence of discontinuous slip;
---i value of average 1 minute occupation rate sequence;
Figure GSB00000628670200034
---with 20s is at interval, i value of the 1 minute occupation rate sequence of sliding;
I value of
Figure GSB00000628670200035
---20s occupation rate sequence.
Figure GSB00000628670200036
---with 20s is at interval, i value of the 5 minutes occupation rate sequences of sliding;
Before algorithm begins to make up 1 minute occupation rate sequence of Continuous Sliding, should at least have 5 minutes 20s at interval raw data exist.Be exemplified below:
20s original occupation rate data sequence at interval:
18?19?17?18?19?20?21?19?19?20?21?19?21?17?22?24?21?28?35?42?43?45?48?41?36?20?17?19?18?20
1 minute occupation rate sequence (since the 5th minute end) of the corresponding discontinuous slip that makes up:
20.0?20.0?20.0?24.3?24.3?40.0?40.0?40.0?44.7?44.7?44.7?44.7?44.7?24.3?24.3
With 1 minute occupation rate data sequence of discontinuous slip algorithm that is fundamental construction, sense cycle can reach that 20s is consistent with raw data the shortest at interval, has guaranteed the higher detection frequency, helps the timely discovery of accident.
As the basic data that the judgement accident takes place, confirm four indexs of the automatic accident detection of this algorithm use with 1 minute occupation rate data sequence of discontinuous slip, adopt " serial judgement " to carry out accident and judge as many indexs accident associating determination methods:
(1) occupation rate (O T, k), 1 minute occupation rate of k section t discontinuous slip constantly.
(2) occupation rate time difference k section t constantly with the difference of 1 minute occupation rate of (t-1) discontinuous slip constantly. d t , k l = O l , k - O t - 1 , k
(3) difference of occupation rate space difference
Figure GSB00000628670200043
t moment upper reaches k section and 1 minute occupation rate of the discontinuous slip of adjacent downstream k+1 section.
Figure GSB00000628670200044
(4) occupation rate space time difference
Figure GSB00000628670200045
t moment occupation rate space difference and t-1 moment occupation rate space difference is poor. d t , k s &RightArrow; t = d t , k s - d t - 1 , k s
Order is judged above-mentioned 4 indexs, when satisfying condition simultaneously, is judged as accident condition, and wherein any index is ineligible then jumps out judgement, thinks that accident free takes place.
Implementation method of the present invention is following, with reference to shown in Figure 3:
1. arrange checkout equipment (earth coil) in city expressway surveyed area upstream and downstream, gather occupation rate parameter averaging time with certain sample unit (as 20 seconds), as the basic data of algorithm.
2. confirm the threshold value of judge index.To some sections, the elementary section in the identical track in same detection highway section, adopt the same threshold group, promptly same threshold vector.To confirming of metrics-thresholds, the present invention proposes the off-line calibration method of two kinds of method: A. based on historical casualty data, and B. is based on predetermined threshold value and accident and non-casualty data online from modification method in a day.
A. based on the off-line calibration method of historical casualty data
At first, delimit highway section and track to be calibrated,, transfer the data in respective stretch track in the historical data base according to the accident record of confirming with manual work supervision, telephone call or other modes;
Subsequently, calculate the maximal value that obtains each key parameter.Adopt limited exhaustive thought, avoid doing too much unnecessary computing.Promptly earlier confirm the scope that it is exhaustive, needn't carry out computing surpassing its peaked scope according to each key parameter maximal value; According to its situation of change each key parameter is confirmed corresponding step-size in search respectively again, thereby obtain the threshold vector of some various combinations.
At last, these threshold vectors are moved detection algorithm one by one, obtain each threshold value and divide into groups, choose and detect one group of best threshold value of effect as recommending threshold value to the detection effect of historical accident.
Be exemplified below table:
Table 1 is based on historical data off-line calibration key parameter
Figure GSB00000628670200047
B. based on predetermined threshold value and accident and non-casualty data online in a day, judge relatively by three grades mainly to constitute that the algorithm detailed process is with reference to figure 6 from modification method.
At first, according to historical data analysis,, obtain predetermined threshold value vector T=[T for the preset one group of threshold value in each track, highway section 1, T 2, T 3, T 4], T wherein iIt is the predetermined threshold value of i index; Carry out one-day operation according to T,, acquire the set of bare maximum separately of following four indexs of normal traffic situation in a day 24 hours through confirming to detecting actual the having an accident in highway section And the set of the relative minimum of following four indexs of accident situation, promptly can distinguish the minimum value set of accident condition and normal condition Wherein
Figure GSB00000628670200053
Max j(t i) represent that j plays accident i key parameter t takes place in back 3 minutes iThe maximal value that is obtained.
Subsequently, with T and t Max, t MinCarry out vector respectively relatively.Wherein i, j, m, n, k, l ∈ 1,2,3,4}:
(1) when the predetermined threshold value of all indexs, show that then preset threshold value might be judged as accident with normal condition:
1. if
Figure GSB00000628670200055
is empty, then accident free takes place in 24 hours same day.
Figure GSB00000628670200056
ε＝1；
2. if T then iBe provided with still higherly, can not detect whole accidents, need turn down to T '=t Min
3. if
Figure GSB00000628670200058
T then iCan detect whole accidents, at this moment:
If
Figure GSB00000628670200059
Show that then the i index occurs all having under each accident greater than the situation of mxm. under the normal condition, can heighten T iExtremely T i &prime; = t i Max + &epsiv; , ε=1;
If
Figure GSB000006286702000511
Show that then the i index just equals the maximal value under the normal condition at the relative minimum under each accident, get this moment T i &prime; = t i Max ;
If
Figure GSB000006286702000513
shows that then relative minimum under this emergency conditions less than the maximal value under the normal condition, will cause the appearance of false alarm.Get
Figure GSB000006286702000514
and can detect to guarantee whole accidents this moment;
If t MaxIn the k index
Figure GSB000006286702000515
The 1st index Then get respectively
Figure GSB000006286702000517
Promptly get T '=t Min
4. if t MinIn the m index
Figure GSB000006286702000518
And the n index
Figure GSB000006286702000519
Then order respectively
Figure GSB000006286702000520
Promptly get T '=t Min
(2) when the predetermined threshold value
Figure GSB000006286702000521
of all indexs, show that predetermined threshold value can not be judged as accident with normal condition:
1. if
Figure GSB000006286702000522
is empty, then accident free takes place in 24 hours same day.Get T ' i=T i, i.e. T '=T;
2. if
Figure GSB000006286702000523
Then all accidents can both be detected, and get T ' i=T i, i.e. T '=T;
3. if t MinIn the m index
Figure GSB000006286702000524
And the n index Then order respectively
Figure GSB000006286702000526
Promptly get T '=t Min
4. if
Figure GSB00000628670200061
then has accident to be failed to report.At this moment:
If
Figure GSB00000628670200062
Show that then the i index occurs all having under each accident greater than the situation of mxm. under the normal condition, can heighten T iExtremely ε=1;
If
Figure GSB00000628670200064
Show that then the i index just equals the maximal value under the normal condition at the relative minimum under each accident, get this moment T i &prime; = t i Max ;
If
Figure GSB00000628670200066
shows that then relative minimum under this emergency conditions less than the maximal value under the normal condition, will cause the appearance of false alarm.Reduce T this moment iValue, order
Figure GSB00000628670200067
To guarantee that whole accidents can detect;
If t MaxIn the k index
Figure GSB00000628670200068
The 1st index
Figure GSB00000628670200069
Then get respectively
Figure GSB000006286702000610
Promptly get T '=t Min
(3) when then showing part predetermined threshold value (Ti),
Figure GSB000006286702000611
might normal condition be judged as accident:
1. if t MinBe sky, then accident free takes place in 24 hours same day.Get T ' k=T k, i.e. T '=T;
2. if
Figure GSB000006286702000612
Then all accidents can both be detected, and get T ' this moment k=T k, i.e. T '=T;
3. if
Figure GSB000006286702000613
then has accident to be failed to report.This season,
Figure GSB000006286702000614
can detect to guarantee whole accidents;
4. if t MinIn the m index
Figure GSB000006286702000615
And the n index
Figure GSB000006286702000616
Then the m index can detect all accidents, and the n index has accident and fails to report.At this moment:
If t k Max < t k Min , Then can improve T k &prime; = t k Max + &epsiv; , ε=1;
If t k Max < t k Min , Then T k &prime; = t k Max , Be T '=t Max
If
Figure GSB000006286702000621
Then have normal condition to be reported by mistake the possibility for accident, get for guaranteeing that whole accidents are detected this moment
Figure GSB000006286702000622
Be T '=t Min
If t MaxIn the k index
Figure GSB000006286702000623
The 1st index
Figure GSB000006286702000624
Then get respectively Promptly get T '=t Min
At last, with adjusted metrics-thresholds vector T '=[T ' 1, T ' 2, T ' 3, T ' 4] as new metrics-thresholds T, the accident that is used for next day is differentiated.
3. calculate four index O that the serial of 1 minute occupation rate data sequence of discontinuous slip is judged T, k,
Figure GSB00000628670200071
With
Figure GSB00000628670200072
4. order is judged successively, relatively O T, kWith T 1,
Figure GSB00000628670200073
With T 2, With T 3With
Figure GSB00000628670200075
With T 4If all indexs have all been passed through serial arithmetic, satisfy simultaneously: O T, k>=T 1,
Figure GSB00000628670200076
Figure GSB00000628670200077
With
Figure GSB00000628670200078
Then thinking has accident to take place, and sends warning.
Sample calculation analysis
The observation accident of Shanghai City city expressway is chosen in this experiment, and many indexs accident detection method that this research is set up and existing basic California algorithm and California 7# algorithm carry out parallel testing.Data are the Shanghai Urban through street that derives from through street, Shanghai supervisory system, are the coil section occupation rate averaging time data of step-length with 20 seconds.1 minute occupation rate data sequence of discontinuous slip algorithm adopts preceding 1 heavenly calendar historical event in advance so data are carried out the threshold value demarcation.
Test result is as shown in table 2.
Discontinuous slip 1 minute occupation rate data sequence algorithm of table 2 and the contrast of California test of heuristics
(detection zone 1 day data comprises 3 accidents)
Testing result shows:
(1) in 13477 times are detected, do not report by mistake, rate of false alarm is 0; 2 wrong reports have taken place in basic California algorithm in 7200 times are detected, rate of false alarm is 0.03%; 9 wrong reports have taken place in California 7# algorithm in 7200 times are detected, rate of false alarm is 0.12%.The many indexs detection method that shows this method is superior to basic California algorithm and California 7# algorithm on the performance of avoiding reporting by mistake;
(2) this algorithm all can effectively detect 3 test accidents with basic California algorithm, and California 7# algorithm can only detect 2 test accidents;
(3) this algorithm detection time and two kinds of California algorithms are basic identical, all find constantly early than artificial accident.
The above-mentioned description to embodiment is can understand and use the present invention for ease of the those of ordinary skill of this technical field.The personnel of skilled obviously can easily make various modifications to these embodiment, and needn't pass through performing creative labour being applied in the General Principle of this explanation among other embodiment.Therefore, the invention is not restricted to the embodiment here, those skilled in the art should be within protection scope of the present invention for improvement and modification that the present invention makes according to announcement of the present invention.

Claims (4)

1. city expressway automatic detection method for traffic accident based on non-continuous sliding sequence, it is characterized in that: it may further comprise the steps:
1) detection system is gathered the telecommunication flow information of a fixed step size in real time through earth coil;
2) judge according to the real-time traffic stream information of gathering whether have traffic hazard take place, if judgement has an accident then give the alarm, notice vehicle supervision department takes corresponding measure if detecting the highway section; Otherwise continue to read real time data, judge next time;
The collection of described real-time traffic stream information generates 1 minute occupation rate data sequence of discontinuous slip as the basic data of differentiating algorithm, specifically: making up with minimum period 20s is the 1 minute occupation rate sequence of discontinuous slip at interval of sliding, and its construction method is:
if o i 20 s > 1.5 * o i - 1 mov 5 m or o i 20 s < 0.5 * o i - 1 mov 5 m o i + 1 20 s > 1.5 * o i - 1 mov 5 m or o i + 1 20 s < 0.5 * o i - 1 mov 5 m o i + 2 20 s > 1.5 * o i - 1 mov 5 m or o i + 2 20 s < 0.5 * o i - 1 mov 5 m , O i = o i + 2 1 m
else O i = o i mov 1 m
Wherein: O i---i value of 1 minute occupation rate sequence of discontinuous slip;
Figure FSB00000565199800014
---i value of average 1 minute occupation rate sequence;
Figure FSB00000565199800015
---with 20s is at interval, i value of the 1 minute occupation rate sequence of sliding;
I value of
Figure FSB00000565199800016
---20s occupation rate sequence;
Figure FSB00000565199800017
---with 20s is at interval; I value of the 5 minutes occupation rate sequences of sliding
The method whether said judgement detection highway section has an accident is:
1) handles the detection road section traffic volume stream information of gathering in real time, generate 1 minute occupation rate data sequence of discontinuous slip;
2) confirm the threshold value of judge index;
Whether the correlated judgment index of 3) calculating 1 minute occupation rate data sequence of discontinuous slip is compared with decision threshold, judge to have an accident.
2. the city expressway automatic detection method for traffic accident based on non-continuous sliding sequence as claimed in claim 1 is characterized in that: the correlated judgment index of 1 minute occupation rate data sequence of described discontinuous slip is respectively occupation rate O T, k, 1 minute occupation rate of k section t discontinuous slip constantly; The occupation rate time difference
Figure FSB00000565199800018
K section t constantly with the difference of 1 minute occupation rate of t-1 discontinuous slip constantly; Occupation rate space difference
Figure FSB00000565199800019
The difference of t moment upper reaches k section and 1 minute occupation rate of the discontinuous slip of adjacent downstream k+1 section; Occupation rate space time difference
Figure FSB000005651998000110
T is occupation rate space difference and t-1 moment occupation rate space difference poor constantly.
3. the city expressway automatic detection method for traffic accident based on non-continuous sliding sequence as claimed in claim 1, it is characterized in that: threshold value determination method is: based on the off-line calibration of historical casualty data or based on predetermined threshold value and in one day accident and non-casualty data online review one's lessons by oneself just definite.
4. the city expressway automatic detection method for traffic accident based on non-continuous sliding sequence as claimed in claim 2 is characterized in that: described occupation rate O T, k, the occupation rate time difference Occupation rate space difference With occupation rate space time difference
Figure FSB00000565199800023
When all being not less than threshold value, the judgement accident takes place.
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CN108198415A (en) * 2017-12-28 2018-06-22 同济大学 A kind of city expressway accident forecast method based on deep learning

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CN2800397Y (en) * 2005-06-17 2006-07-26 天津市长庆电子科技有限公司 Automatic alarm apparatus for road transport traffic accident
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