CN109147319A - A kind of road emergency event method of discrimination based on more traffic data indexs - Google Patents
A kind of road emergency event method of discrimination based on more traffic data indexs Download PDFInfo
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- CN109147319A CN109147319A CN201810883069.1A CN201810883069A CN109147319A CN 109147319 A CN109147319 A CN 109147319A CN 201810883069 A CN201810883069 A CN 201810883069A CN 109147319 A CN109147319 A CN 109147319A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- 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
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Abstract
This patent discloses a kind of road emergency event method of discrimination based on more traffic data indexs, which comprises step 1: obtaining historical data and calculates historical data index；Step 2: indexes suddenly changed method of discrimination is determined；Step 3: determine whether to have emergency event in road network and find the section that emergency event occurs.Road emergency event differentiation is carried out by using a variety of data targets in road network, detection accuracy reduces caused by solving the problems, such as single traffic data missing；It is able to use in a variety of road network detection systems, enriches the option of detector type in road network detection system.
Description
Technical field
The invention belongs to traffic state judging fields, more particularly to the road emergency event based on more traffic data indexs is sentenced
Other method.
Background technique
Along with the quickening of Urbanization Process In China, city automobile quantity is increased sharply, and urban transportation emergency event problem is more
Seriously.Traffic incident has become the common difficulty that each city in the whole nation is faced, while causing huge economic losses
Also bring along the indirect losses such as urban environment decay, the decline of residents ' health level, the reduction of Urban Traffic satisfaction.
In previous research, data used by urban highway traffic emergency event method of discrimination are relatively simple, mainly
It is the car speed and flow that Road Detection device obtains.Road incidents differentiation, discrimination precision are carried out according to single traffic data
It is often lower, and the problem of can usually face shortage of data.Shortage of data will cause detection accuracy reduction, prominent so as to cause traffic
The failure of hair event method of discrimination.Furthermore conventional traffic events method of discrimination can not adapt to all road detection systems.Often
The Road Detection device of rule has alert (video) detector of geomagnetic induction coil detector, microwave detector, electricity etc., corresponding detection data point
It Wei not loop data, microwave data, the alert data of electricity；These data have the characteristics that different.The characteristics of data diversity, makes often
The robustness of the traffic events method of discrimination of rule is poor.
The present invention proposes a kind of road emergency event method of discrimination based on more traffic data indexs, utilizes road traffic flow
The data such as amount, travel speed, occupation rate differentiate to whether urban road occurs emergency event.It on the one hand can be to the public
Traveler issues trip information service, improves the trip satisfaction of resident；On the other hand it is possible to notify that city traffic management department,
So that traffic events are intervened and are managed in time, the diffusion of traffic events is prevented and lower the loss of traffic events bring,
It has important practical significance.
Summary of the invention
It is an object of the invention to improve the method for discrimination of road emergency event in traffic system, road burst thing is being carried out
Part considers traffic parameter as much as possible when differentiating, to improve the science and practicability of method of discrimination.For this purpose, the present invention mentions
A kind of road emergency event method of discrimination based on more traffic data indexs is gone out.
In the present invention, the historical data of condition of road surface in road network is obtained first, then calculates historical data parameter；
Secondly the method for discrimination of indexes suddenly changed is determined；Finally determine in road network whether there is section according to the catastrophe of data target
Emergency event.
For achieving the above object, the specific technical solution of the present invention is as follows:
Step 1: it obtains historical data and calculates historical data index.Using road detection system existing in road network come
Obtain corresponding traffic data；Data carry out working day and nonworkdays is distinguished, data are picked within the scope of historical events time of origin
It is handled except equal；Treated, and data are stored as historical data.Obtain historical data after, calculate historical data mean value and
Variance, and calculate 3 σ ranges of historical data.
Step 2: indexes suddenly changed method of discrimination is determined.Each real-time traffic parameter in section in road network is obtained, traffic parameter is worked as
Value is except 3 σ ranges of historical data, then it is assumed that the traffic parameter index mutates.Some specific traffic is joined
Number index, when the index number of mutation is more than the threshold value of setting, then it is assumed that doubtful emergency event occurs for section.
Step 3: determine whether to have emergency event in road network and find the section that emergency event occurs.Obtain current road network
In each section data, calculate corresponding index value, and according to the obtained indexes suddenly changed method of discrimination of step 2, judgement is current
Data target whether mutate.The case where finally being mutated according to data target determines the thing that happens suddenly whether occurs in road network
Part simultaneously determines the section that emergency event occurs.
The technical advantages of the present invention are that:
The present invention carries out road emergency event differentiation using a variety of data targets in road network, solves single traffic data
Detection accuracy reduces problem caused by missing.
The present invention carries out road emergency event differentiation using a variety of data targets in road network, prominent relative to existing road
Hair event method of discrimination has higher robustness and discrimination precision.
The present invention, which is used, carries out road emergency event differentiation using a variety of data targets in road network, is able to use in a variety of
Road network detection system enriches the option of detector type in road network detection system.
Specific embodiment
Specific implementation of the patent mode is described in detail below.It should be pointed out that the specific embodiment is only
It is only the citing to this patent optimal technical scheme, the limitation to the scope of this patent can not be interpreted as.
Present embodiment provides the road emergency event method of discrimination based on more traffic data indexs, the method
Include the following steps:
Step 1: it obtains historical data and calculates historical data index.
1. obtaining historical data.The road network of selected research, takes continuous bimestrial number measured by the road network detection system
According to data separation working day and nonworkdays take the data conduct of each 10 minutes (configurable item) before and after present period in history
Preliminary historical data.
For example, current slot is 8:00-8:01, then historical data is this 20 minutes 7:51:00-8:11:00 in history
Data be historical data.To ensure that historical data is all normal data, historical events time of origin is proposed in historical data
Data in range.After proposing to preliminary historical data, the data of surrounding are screened as final historical data.
2. determining historical data index.
After obtaining historical data, the mean value of historical data is calculated
Wherein, x indicates that speed, flow, the equal occupation rate of vehicle, middle lane occupation rate, upstream vehicle pass through ratio.
Calculate the variance of historical data:
Wherein, n is the data volume of acquired historical data.
Calculate 3 σ ranges of historical data:
IfThen think beyond 3 σ ranges.
Step 2: indexes suddenly changed method of discrimination is determined.
In specific example of the invention, 5 traffic parameter indexs are chosen, respectively speed, flow, section vehicle occupies
Rate, upstream vehicle pass through ratio, crossing occupation rate.The determination method of this five indexes suddenly changeds is as follows:
1. velocity jump
Each time interval (default 1 minute), which calculates in 5 minutes windows (configurable), crosses vehicle average speed.I.e. 5 points
The average speed of each vehicle in clock time window.
Average speed (meter per second) of the section l in time period t；
L: section l length (rice)；
N: the vehicle number that section l upstream and downstream crossing is matched in time period t；
ti,t: after cancelling noise, pass through the journey time of the vehicle i of section l in time period t.
(1) if the speed that present period obtains exceeds 3 σ ranges of speed, then it is assumed that speed mutates.
(2) continuous 5 time intervals (configurable item) have the speed of 60% (configurable item) i.e. 3 time intervals
Mutation, then it is assumed that speed has mutation then to think that speed has mutation.
(3) when data source quantity is 3, data have data source quantity >=2 of mutation, then it is assumed that doubtful burst thing occurs
Part；When data source quantity≤2, there is 1 data source to generate mutation, then it is assumed that doubtful emergency event occurs.
2. flow is mutated
Each end cycle statistics calculates each entrance driveway flow:
Each phase i flow of the flow of the entrance driveway l=entrance driveway and.
(1) if the flow that present period obtains exceeds 3 σ ranges of flow, then it is assumed that flow mutates.
(2) continuous 5 time intervals have the flow of 60% i.e. 3 time interval to mutate, then it is assumed that flow has mutation
(3) when data source quantity is 3, data have data source quantity >=2 of mutation, then it is assumed that section where the data source
Doubtful emergency event occurs；When data source quantity≤2, there is 1 data source to generate mutation, then it is assumed that section where the data source
Doubtful emergency event occurs.
3. the equal occupation rate mutation of section vehicle
Each end cycle calculates the equal occupation rate of vehicle during each entrance driveway green light:
Average occupancy of the entrance driveway l in time period t；
N: number of track-lines；
oi,t: pass through the occupation rate of entrance driveway l phase i in time period t.
qi,t: pass through the flow of entrance driveway l phase i in time period t.
(1) if the equal occupation rate of vehicle that present period microwave equipment obtains exceeds 3 σ ranges of historical data, then it is assumed that should
Vehicle equal occupation rate in microwave equipment section mutates.
(2) continuous 5 time intervals of same microwave equipment have the equal occupation rate of the vehicle of 60% i.e. 3 time interval to occur prominent
Become, then it is assumed that the equal occupation rate of vehicle has mutation.
(3) any equal occupation rate of microwave equipment vehicle has mutation, then it is assumed that there is doubtful burst in the corresponding section of microwave equipment
Event.
4. upstream vehicle is mutated by ratio
(1) if current point in time, 3 σ ranges of the upstream vehicle by ratio more than historical data, then it is assumed that the entrance driveway
Upstream vehicle is mutated by ratio.
(2) continuous 5 time intervals have the entrance driveway upstream vehicle of 60% i.e. 3 time interval to occur by ratio prominent
Become, then it is assumed that the entrance driveway corresponding road section has doubtful emergency event.
5. crossing occupation rate is mutated
(1) if present period entrance driveway occupation rate exceeds 3 σ ranges of historical data, then it is assumed that entrance driveway occupation rate hair
Raw mutation.
(2) continuous 5 time intervals of same entrance driveway have the entrance driveway occupation rate of 60% i.e. 3 time interval to occur prominent
Become, then it is assumed that entrance driveway occupation rate has mutation, it is believed that there is doubtful emergency event in section corresponding to the entrance driveway.
Step 3: determine whether to have emergency event in road network and find the section that emergency event occurs.
(1) according to the calculation method of the historical data index determined in step 1, road average-speed, entrance driveway stream are calculated
Amount, the equal occupation rate of section vehicle, upstream vehicle by ratio, the historical data index value of 5 traffic parameters of entrance driveway occupation rate and
Its 3 σ range.
(2) data for obtaining each section in current time road network, calculate separately current time road average-speed, entrance driveway
The numerical value that flow, the equal occupation rate of section vehicle, upstream vehicle pass through 5 ratio, entrance driveway occupation rate traffic parameter indexs.
(3) according to the indexes suddenly changed method of discrimination determined in step 2, by the current time value and history of 5 data targets
Numerical value is compared, and judges each indexes suddenly changed situation.
(4) each time interval (defaulting each minute) is given a mark according to table 1 to each index.
If the index thinks that doubtful emergency event occurs, it is scored at 1；It, should if the index does not have data source
Index is scored at 0；If the index, in history normal range (NR), which is scored at -1 point.All index scores are cumulative, obtain
To total score, the section of total score > γ (being defaulted as 0) is that section occurs for emergency event.
Each index call table of table 1
Emergency event occurs for section, then records the Time To Event of system identification, section occurs, section mutation refers to
Mark and the corresponding history mean value of the index and standard deviation.
Continuous 5 time intervals, the section are scored at≤0, then system determines that event terminates, and record event end time.
Claims (2)
1. a kind of road emergency event method of discrimination based on more traffic data indexs, which is characterized in that the described method includes:
Step 1: it obtains historical data and calculates historical data index
Firstly, obtaining historical data；For selected road network, first consecutive time section measured by the road network detection system is taken
Historical data, data separation working day and nonworkdays；And it is taken in the historical data in history each first before and after present period
The data of predetermined instant are as preliminary historical data；After being proposed to preliminary historical data, the data of screening one month by a definite date
As final historical data；
Then, it is determined that historical data index；Calculate the mean value of historical data Wherein, x indicate speed, flow,
The equal occupation rate of vehicle, middle lane occupation rate, upstream vehicle pass through ratio；Calculate the variance of historical data:
Wherein, n is the data volume of acquired historical data；Calculate 3 σ ranges of historical data:When
Current data Xi meetsThen think beyond 3 σ ranges；
Step 2: indexes suddenly changed method of discrimination is determined
Access speed, flow, the equal occupation rate of section vehicle, upstream vehicle pass through ratio, crossing occupation rate, 5 traffic indicators parameters
Mutation as judgment basis；
For velocity jump, vehicle average speed is crossed in every one one time interval calculation first time window；That is first time window
The average speed of interior each vehicle,WhereinThe average speed, the L that are section l in time period t are road
Section l length (rice), n are vehicle number, the t that section l upstream and downstream crossing is matched in time period ti,tAfter cancelling noise, the time
Pass through the journey time of the vehicle i of section l in section t；When the speed that present period obtains exceeds 3 σ range of speed, speed is judged
First mutation occurs for degree；When continuous N number of time interval, there is the speed of the time interval of predetermined ratio to mutate, determine speed
Second mutation occurs for degree；When data source quantity is 3, there are data source quantity >=2 of mutation, then it is assumed that the first doubtful burst occurs
Event；When data source quantity≤2, there is 1 data source to generate mutation, then it is assumed that the second doubtful emergency event occurs；
Flow is mutated；The signal period of each intersection signal control device terminates statistics and calculates each entrance driveway flow: entrance driveway l
Each phase i flow of the flow=entrance driveway and；When the flow that present period obtains exceeds 3 σ range of flow, judge that flow is sent out
Raw first mutation.When continuous N number of time interval, there is the flow of the time interval of predetermined ratio to mutate, determines flow hair
Raw second mutation；When data source quantity is 3, there are data source quantity >=2 of mutation, then it is assumed that the first doubtful burst thing occurs
Part；When data source quantity≤2, there is 1 data source to generate mutation, then it is assumed that the second doubtful emergency event occurs；
Occupation rate mutation equal for section vehicle；The signal period of each intersection signal control device terminates to calculate each entrance driveway green light phase
Between the equal occupation rate of vehicle:WhereinThe average occupancy for being entrance driveway l in time period t, n are number of track-lines
oi,tFor occupation rate, the q for passing through entrance driveway l phase i in time period ti,tFor the flow for passing through entrance driveway l phase i in time period t；
When the equal occupation rate of vehicle that present period traffic monitoring equipment obtains exceeds 3 σ range of historical data, then it is assumed that the traffic monitoring is set
First mutation occurs for the standby equal occupation rate of section vehicle；Continuous 5 time intervals of same flow traffic monitoring device, there is 60% time interval
The equal occupation rate of vehicle mutates, then it is assumed that the second mutation occurs for the equal occupation rate of vehicle；Any equal occupation rate of traffic monitoring equipment vehicle has
Mutation, then it is assumed that there is doubtful emergency event in the corresponding section of traffic monitoring equipment
Upstream vehicle is mutated by ratio, if current point in time, 3 σs of the upstream vehicle by ratio more than historical data
Range, then it is assumed that by ratio the first mutation occurs for the entrance driveway upstream vehicle；Between the time that continuous 5 time intervals have 60%
Every entrance driveway upstream vehicle pass through ratio mutate, then it is assumed that the entrance driveway corresponding road section has doubtful emergency event；
Crossing occupation rate is mutated, if present period entrance driveway occupation rate exceeds 3 σ ranges of historical data, then it is assumed that into
First mutation occurs for mouth road occupation rate；Same continuous 5 time intervals of entrance driveway, have the entrance driveway of 60% time interval to occupy
Rate mutates, then it is assumed that entrance driveway occupation rate has mutation, it is believed that there is doubtful emergency event in section corresponding to the entrance driveway；
Step 3: determine whether to have emergency event in road network and find the section that emergency event occurs.
The data for obtaining each section in current time road network, calculate separately current time road average-speed, entrance driveway flow, road
The numerical value that the equal occupation rate of section vehicle, upstream vehicle pass through 5 ratio, entrance driveway occupation rate traffic parameter indexs；According in step 2
The current time value of 5 data targets and historical values are compared, judge each finger by determining indexes suddenly changed method of discrimination
Mark catastrophe；Each each index of time interval accumulates weighted value；If the index is according to the judgement of step 2, it is believed that hair
It is raw or it is doubtful doubtful emergency event occurs, then its weighted value+1；If the index does not have data source, the index weights number is not
Become；If the index is in history normal range (NR), the index weights numerical value -1.The weighted value of all indexs is added up, is obtained
To total weighted value, the section of total weighted value > γ is that section occurs for emergency event.
2. a kind of road emergency event method of discrimination based on more traffic data indexs of according to claim 1, feature
It is, in step 1, the first time period is one month, and first predetermined instant is 10 minutes.
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Cited By (6)
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| CN110264715A (en) * | 2019-06-20 | 2019-09-20 | 大连理工大学 | A kind of traffic incidents detection method based on section burst jamming analysis |
| CN111932899A (en) * | 2020-10-15 | 2020-11-13 | 江苏广宇协同科技发展研究院有限公司 | Traffic emergency control method and device based on traffic simulation |
| CN112991724A (en) * | 2021-02-09 | 2021-06-18 | 重庆大学 | Method and device for estimating occurrence position and occurrence time of highway abnormal event |
| CN114333324A (en) * | 2022-01-06 | 2022-04-12 | 厦门市美亚柏科信息股份有限公司 | Real-time traffic state acquisition method and terminal |
| CN114419887A (en) * | 2022-01-20 | 2022-04-29 | 青岛海信网络科技股份有限公司 | Road network index determining method and device |
| CN115620522A (en) * | 2022-10-21 | 2023-01-17 | 东南大学 | Urban road network dynamic traffic capacity calculation method based on real-time traffic data |
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