CN105489016B - A kind of urban road operating condition appraisal procedure - Google Patents
A kind of urban road operating condition appraisal procedure Download PDFInfo
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- CN105489016B CN105489016B CN201610069272.6A CN201610069272A CN105489016B CN 105489016 B CN105489016 B CN 105489016B CN 201610069272 A CN201610069272 A CN 201610069272A CN 105489016 B CN105489016 B CN 105489016B
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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
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
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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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- 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
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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Abstract
The present invention relates to a kind of urban road operating condition appraisal procedures, include the following steps：(1) GPS data from taxi is pre-processed；(2) path adaptation is carried out to the GPS data from taxi by pretreatment, obtains carrying data road type corresponding with non-carrying data；(3) to trunk roads, non-carrying data and the non-carrying data of secondary distributor road are handled, and judge whether to apply；(4) average travel speed in section is calculated；(5) road operating condition is assessed.A kind of urban road operating condition appraisal procedure disclosed by the invention has the advantages that：The number of applications of acquisition information can be improved, the information coverage of trunk roads and time branch can particularly be increased, the computational methods of proposition can directly apply to floating vehicle system real-time system, GPS data from taxi is handled and is calculated, the travel speed of different category of roads is obtained, so as to judge the congestion level in the section.
Description
Technical field
The invention belongs to technical field of data processing, and in particular to a kind of urban road operating condition appraisal procedure.
Background technology
Floating car traffic information acquisition technique is continuously applied to urban highway traffic postitallation evaluation, the master of Floating Car in recent years
Taxi is derived from, with tradition based on compared with fixed detector method, floating car data broad covered area, information is various in real time,
Data precision is high, small investment.Floating Car due to having " mobility ", broken the limitation of Points And lines and extended by space coverage
To face, the traffic information in each section in urban road network can be almost collected, is had excellent in apparent coverage area
Gesture.And GPS can ensure round-the-clock non-stop run in 24 hours, convenient for being loaded with the Floating Car of GPS receiver, collection is outer immediately
Go out the dynamic operation data of vehicle, data are various in real time.
In order to obtain the true operating status of Traffic Net, the Floating Car ability that must have sufficient amount in road network
Meet the required precision of telecommunication flow information acquisition.In general, Floating Car sample size is bigger, also bigger to the coverage rate of road network.
Accordingly, it is determined that meet the most suitable Floating Car sample size of Route coverage to ensure that the reliability for providing real time traffic data is ground
Study carefully with very important engineering application value.About determining Floating Car sample quantifier elimination, i.e., how many are needed on section
Floating Car, the true operation characteristic for reflecting the network of communication lines, forefathers have carried out numerous studies.
This problem, Srinivasan etc. are distributed for required Floating Car sample size the study found that in the 10min sampling periods
It is interior, for 80% section, it is ensured that at least 3 probe vehicles could accurately calculate road average-speed, it is therefore desirable to will
At least 5% vehicle is as probe vehicles in entire road network.Quiroga and Bullock are proposed based on link average speed estimation
The Floating Car sample size computation model of precision, the model are theoretical based on classical mathematical statistics standard deviation.Chen etc. is upper
On the basis of stating model, it is contemplated that the traffic characteristics of real road traffic introduce the relative error that average speed estimation allows,
Model is improved.The road being made of a highway and 5 signalized intersections is had estimated using simulation model of microscopic
Net Floating Car smallest sample amount.The simulation results show that 3% Floating Car is at least needed in traffic flow, it is ensured that error
Rate is less than 5%.12% Floating Car is at least needed in peak period, traffic flow can just ensure that data are reliable.The researchs such as Ferman
3% should be not less than by showing on highway or through street Floating Car ratio, and the Floating Car vehicle on other general urban roads
Ratio should be not less than 5%.The analysis based on road network traffic flow such as high tinkling of pieces of jades is fitted using the space-time curve of floating car data
Model considers the factors such as speed, category of roads, the non-passenger carrying status of taxi floating car weight and sending cycle, it is proposed that
For calculating the self-adapting float vehicle sample size computational methods of minimum GPS probe vehicles quantity needed for urban traffic flow state estimation.
And the validity of model is verified by taking Shanghai City as an example.Lin Si etc. is theoretical using the classical theory of probability, bound fraction traffic
The Floating Car sample size computational methods of properties of flow, it is proposed that the optimal sample capacity determining methods based on emulation experiment.And pass through
VISSIM carries out Floating Car emulation experiment, obtains when Floating Car ratio is 3%~5% in road network, traffic parameter estimated accuracy
Up to more than 95%.Hu little Wen etc. is established by taking urban taxi GPS data as an example in different characteristics of time interval and section sample size
Under demand, the functional relation between road network coverage rate and Floating Car quantity.The number that Zhu Liyun etc. is acquired according to Beijing's Floating Car
According to, it is proposed that the Construction procedures of a set of real-time road network speed calculation system of Floating Car for being suitable for complicated city road network, including GPS
The matching and section operating speed of data receiver, data prediction, data on electronics road network base map calculate.And largely to try
Test the feasibility of the data verification program and actual motion effect.Xiong Juan etc. demonstrates current sample using RTMS data as true value
The validity of floating car data under the conditions of this amount, and determine using the methods of sampling and similarity principle the smallest sample of Floating Car
Amount, and calculating ratio is less the same as the floating car data under sample size and the related coefficient of RTMS data.
Floating car data mainly includes the non-carrying data of effect and screening and the load of carrying data using rule research
This two parts of the application of objective data.For the screening of non-carrying data, most research both at home and abroad hires out car data in processing
When non-carrying data are considered as invalid data.Xin Feifei etc. thinks non-carrying taxi during traveller is found, often
There is roadside and wait the random larger driving behavior such as visitor, rest, irregular lane change and acceleration and deceleration, these all cannot really reflect
The actual traffic operation conditions of urban road, therefore delete empty wagons data during filter data is crossed.And Zhu carp is thought to delete
Except all empty wagons data can lead to the data deficiencies of system, therefore establish the model of empty wagons data processing, in model directly
Using through street and the empty wagons data of highway, for the empty wagons data of other category of roads, if no-load speed is more than speed limit
80%, then can directly use.After algorithm process, branch, subsidiary road and major trunk roads these three category of roads empty wagons
The average stroke speed estimated accuracy of data improves.
At present about the screening and processing of carrying data, a large amount of research is carried out both at home and abroad.It is old to refine red grade by error number
Three classes are summarized as according to Producing reason：With GPS satellite correlated error；The error related with signal propagation；It is related with receiving device
Error.The form of expression of the lower data of these error synthesis effect is summarized, with Threshold Test, based on traffic basic theories
And the methods of inspection such as micro-judgment judge wrong data and it are handled.Zhang Jingjing proposes statistical method and K-
The method that means classification is combined is filled the missing data of Floating Car, and it is preferable to demonstrate effect of filling a vacancy.To data
Noise reduction process is carried out to data to reduce error using wavelet transformation after being filled a vacancy.Zhaosheng Zhang etc. are proposed clearly
The method for washing and repairing floating car data --- multi-threshold control repairing method (Multithreshold Control Repair
Method, MTCRM), this method uses the rule process abnormal data of threshold value control and standardized transformation, with weighted mean method
Missing data is filled up with exponential smoothing.With this method, to Beijing, each grade road carries out data reparation, as a result shows number
Disclosure satisfy that the requirement of traffic status prediction according to the average deviation of reparation, demonstrate MCTRM effectively can clean and repair it is floating
Motor-car data.Qin Ling etc. exists data, location information of the location information there are large error during abnormal data is handled
The data that are remained unchanged in a period of time, data that location information remains unchanged whithin a period of time and speed is not zero and floating
Motor-car speed is significantly larger than or is considered as abnormal data with the data of the speed of the most of Floating Cars in section less than the same time.Edward
Chung etc. analyzes Floating Car and brings to a halt, parking for a long time, traffic lights, parking etc. of turning is waited for cause the Floating Car number of acquisition
According to discontinuous reason, and pass through the terminal that data processing determines to go on a journey every time.
Summarize above-mentioned domestic and international present Research, it can be seen that：Research for taxi data, in carrying data
The theoretical research in terms of these three of processing, the application of carrying data and Floating Car spatial-temporal distribution characteristic and practical application compared with into
It is ripe.For hiring out the research of Chefei's carrying data, processing mainly including non-carrying data and this two parts is used.Wherein for
Non- carrying data are considered as invalid data by the processing of non-carrying data, most research when car data is hired out in processing, and real
The non-carrying data in part can reflect practical traffic noise prediction on border, and the application aspect of non-carrying data is mainly collected at present
In in the research of the non-cabin factor of time non-cabin factor and space to taxi.Therefore, it is necessary to use existing data dependence
And the mathematical method of difference analysis is to the correlation metric of " carrying " with the travel speed of " non-carrying ", the progress of otherness index
Analysis, then analyze otherness index under different road types, period, speed interval, correlation metric changing rule, propose
Non- carrying data utilize rule.Processing and calculating to GPS data from taxi obtain link travel speed, carry out congestion and comment
Valency.
Invention content
Goal of the invention：The present invention has made improvements in view of the above-mentioned problems of the prior art, i.e., the invention discloses one kind
Urban road operating condition appraisal procedure.
Technical solution：A kind of urban road operating condition appraisal procedure, includes the following steps：
(1) GPS data from taxi is pre-processed；
(2) path adaptation is carried out to the GPS data from taxi by pretreatment, obtains carrying data and non-carrying data pair
Non- carrying data are divided into the non-carrying data in through street, the non-carrying data of trunk roads and the non-carrying of secondary distributor road by the road type answered
Data, the non-carrying data in through street are directly applied；
(3) to trunk roads, non-carrying data and the non-carrying data of secondary distributor road are handled, and judge whether to apply；
(4) average travel speed in section is calculated, calculation formula is as follows：
Wherein：
VlFor the average travel speed in section, L is the road section length, VIt is emptyIt is the average travel speed of non-carrying taxi, m
It is the quantity of non-carrying taxi, VIt carriesIt is the average travel speed of carrying taxi, n is the quantity of carrying taxi；
(5) road operating condition is assessed.
Further, step (1) includes the following steps：
(11) GPS data from taxi is divided into carrying data and non-carrying data；
(12) retain the non-carrying data continuously transmitted more than 2 minutes, remaining non-carrying data is deleted.
Further, step (3) includes：
(31) the arithmetic mean of instantaneous value v of the taxi speed of every 5 minutes is calculated according to carrying dataIt carriesWith carrying speed
Standard deviation sigmaIt carries；
(32) judge the non-carrying data v of same road segment identical periodIt is emptyWhether apply, if vIt is emptyIt is more thanThen should
With the non-carrying data vIt is empty, on the contrary then rejected, wherein k is constant, and the value range of k is 1.3~1.6.
Further, step (5) includes the following steps：
According to the average travel speed V in the section that step (4) obtainslBy section be divided into unimpeded section, substantially unimpeded section,
Slight congested link, moderate congested link and heavy congestion section,
When the section is through street,
If Vl＞ 65km/h, then the through street is unimpeded section；
If 50km/h ＜ Vl≤ 65km/h, then the through street is substantially unimpeded section；
If 35km/h ＜ Vl≤ 50km/h, then the through street is slight congested link；
If 20km/h ＜ Vl≤ 35km/h, then the through street is moderate congested link；
If Vl≤ 20km/h, then the through street is heavy congestion section；
When the section is trunk roads,
If Vl＞ 45km/h, then the trunk roads are unimpeded section；
If 35km/h ＜ Vl≤ 45km/h, then the trunk roads are substantially unimpeded section；
If 25km/h ＜ Vl≤ 35km/h, then the trunk roads are slight congested link；
If 15km/h ＜ Vl≤ 25km/h, then the trunk roads are moderate congested link；
If Vl≤ 15km/h, then the trunk roads are heavy congestion section；
When the section is secondary distributor road,
If Vl＞ 35km/h, then the secondary distributor road is unimpeded section；
If 25km/h ＜ Vl≤ 35km/h, then the secondary distributor road is substantially unimpeded section；
If 15km/h ＜ Vl≤ 25km/h, then the secondary distributor road is slight congested link；
If 10km/h ＜ Vl≤ 15km/h, then the secondary distributor road is moderate congested link；
If Vl≤ 10km/h, then the secondary distributor road is heavy congestion section.
Advantageous effect：A kind of urban road operating condition appraisal procedure disclosed by the invention has the advantages that：
The number of applications of acquisition information can be improved, can particularly increase the information coverage of trunk roads and time branch,
The computational methods of proposition can directly apply to floating vehicle system real-time system, and GPS data from taxi is handled and is calculated,
The travel speed of different category of roads is obtained, so as to judge the congestion level in the section.
Description of the drawings
Fig. 1 is a kind of flow chart of urban road operating condition appraisal procedure disclosed by the invention；
Fig. 2 a are shown based on the trunk roads travel speed for hiring out the calculating of Chefei's carrying data source with 1.6 times of trunk roads velocity contrasts
It is intended to；
Fig. 2 b are shown based on the secondary distributor road travel speed for hiring out the calculating of Chefei's carrying data source with 1.3 times of secondary distributor road velocity contrasts
It is intended to；
Fig. 3 is major trunk roads Guangdong and Guangxi Provinces street traffic index schematic diagram at times；
Fig. 4 is through street West 2nd Ring Road traffic index schematic diagram at times.
Specific embodiment：
The specific embodiment of the present invention is described in detail below.
As shown in Figure 1, a kind of urban road operating condition appraisal procedure, includes the following steps：
(1) GPS data from taxi is pre-processed；
(2) path adaptation is carried out to the GPS data from taxi by pretreatment, obtains carrying data and non-carrying data pair
Non- carrying data are divided into the non-carrying data in through street, the non-carrying data of trunk roads and the non-carrying of secondary distributor road by the road type answered
Data, the non-carrying data in through street are directly applied；
(3) to trunk roads, non-carrying data and the non-carrying data of secondary distributor road are handled, and judge whether to apply；
(4) average travel speed in section is calculated, calculation formula is as follows：
Wherein：
VlFor the average travel speed in section, L is the road section length, VIt is emptyIt is the average travel speed of non-carrying taxi, m
It is the quantity of non-carrying taxi, VIt carriesIt is the average travel speed of carrying taxi, n is the quantity of carrying taxi；
(5) road operating condition is assessed.
Further, step (1) includes the following steps：
(11) GPS data from taxi is divided into carrying data and non-carrying data；
(12) retain the non-carrying data continuously transmitted more than 2 minutes, remaining non-carrying data is deleted.
Further, step (3) includes：
(31) the arithmetic mean of instantaneous value v of the taxi speed of every 5 minutes is calculated according to carrying dataIt carriesWith carrying speed
Standard deviation sigmaIt carries；
(32) judge the non-carrying data v of same road segment identical periodIt is emptyWhether apply, if vIt is emptyIt is more thanThen should
With the non-carrying data vIt is empty, on the contrary then rejected, wherein k is constant, and the value range of k is 1.3~1.6.
Further, step (5) includes the following steps：
According to the average travel speed V in the section that step (4) obtainslBy section be divided into unimpeded section, substantially unimpeded section,
Slight congested link, moderate congested link and heavy congestion section,
When the section is through street,
If Vl＞ 65km/h, then the through street is unimpeded section；
If 50km/h ＜ Vl≤ 65km/h, then the through street is substantially unimpeded section；
If 35km/h ＜ Vl≤ 50km/h, then the through street is slight congested link；
If 20km/h ＜ Vl≤ 35km/h, then the through street is moderate congested link；
If Vl≤ 20km/h, then the through street is heavy congestion section；
When the section is trunk roads,
If Vl＞ 45km/h, then the trunk roads are unimpeded section；
If 35km/h ＜ Vl≤ 45km/h, then the trunk roads are substantially unimpeded section；
If 25km/h ＜ Vl≤ 35km/h, then the trunk roads are slight congested link；
If 15km/h ＜ Vl≤ 25km/h, then the trunk roads are moderate congested link；
If Vl≤ 15km/h, then the trunk roads are heavy congestion section；
When the section is secondary distributor road,
If Vl＞ 35km/h, then the secondary distributor road is unimpeded section；
If 25km/h ＜ Vl≤ 35km/h, then the secondary distributor road is substantially unimpeded section；
If 15km/h ＜ Vl≤ 25km/h, then the secondary distributor road is slight congested link；
If 10km/h ＜ Vl≤ 15km/h, then the secondary distributor road is moderate congested link；
If Vl≤ 10km/h, then the secondary distributor road is heavy congestion section.
Fig. 2 a are based on the trunk roads travel speed and 1.6 times of trunk roads velocity contrasts for hiring out the calculating of Chefei's carrying data source
Schematic diagram, Fig. 2 b are based on the secondary distributor road travel speed and 1.3 times of secondary distributor road velocity contrasts for hiring out the calculating of Chefei's carrying data source
Schematic diagram.As can be seen that non-carrying data filtering methods can make the speed of blended data and carrying speed in trunk roads and secondary
Branch keeps very high consistency.
Fig. 3 and Fig. 4 is the typical major trunk roads being calculated and the traffic index of through street, available for evaluation path congestion journey
Degree and congestion Annual distribution.
Embodiments of the present invention are elaborated above.But present invention is not limited to the embodiments described above,
In the knowledge that technical field those of ordinary skill has, it can also be done under the premise of present inventive concept is not departed from
Go out various change.
Claims (2)
1. a kind of urban road operating condition appraisal procedure, which is characterized in that include the following steps：
(1) GPS data from taxi is pre-processed；
(11) GPS data from taxi is divided into carrying data and non-carrying data；
(12) retain the non-carrying data continuously transmitted more than 2 minutes, remaining non-carrying data is deleted；
(2) path adaptation is carried out to the GPS data from taxi by pretreatment, it is corresponding with non-carrying data obtains carrying data
Non- carrying data are divided into the non-carrying data in through street, the non-carrying data of trunk roads and the non-carrying data of secondary distributor road by road type,
The non-carrying data in through street are directly applied；
(3) to trunk roads, non-carrying data and the non-carrying data of secondary distributor road are handled, and judge whether to apply；
(31) arithmetic mean of instantaneous value of the taxi speed of every 5 minutes is calculated according to carrying dataWith the standard of carrying speed
Poor σIt carries；
(32) judge the non-carrying data v of same road segment identical periodIt is emptyWhether apply, if vIt is emptyIt is more thanThen application should
Non- carrying data vIt is empty, on the contrary then rejected, wherein k is constant, and the value range of k is 1.3~1.6；
(4) average travel speed in section is calculated, calculation formula is as follows：
Wherein：
VlFor the average travel speed in section, L is the road section length, VIt is emptyIt is the average travel speed of non-carrying taxi, m right and wrong
The quantity of carrying taxi, VIt carriesIt is the average travel speed of carrying taxi, n is the quantity of carrying taxi；
(5) road operating condition is assessed.
2. a kind of urban road operating condition appraisal procedure according to claim 1, which is characterized in that step (5) includes
Following steps：
According to the average travel speed V in the section that step (4) obtainslSection is divided into unimpeded section, substantially unimpeded section, slight
Congested link, moderate congested link and heavy congestion section,
When the section is through street,
If Vl＞ 65km/h, then the through street is unimpeded section；
If 50km/h ＜ Vl≤ 65km/h, then the through street is substantially unimpeded section；
If 35km/h ＜ Vl≤ 50km/h, then the through street is slight congested link；
If 20km/h ＜ Vl≤ 35km/h, then the through street is moderate congested link；
If Vl≤ 20km/h, then the through street is heavy congestion section；
When the section is trunk roads,
If Vl＞ 45km/h, then the trunk roads are unimpeded section；
If 35km/h ＜ Vl≤ 45km/h, then the trunk roads are substantially unimpeded section；
If 25km/h ＜ Vl≤ 35km/h, then the trunk roads are slight congested link；
If 15km/h ＜ Vl≤ 25km/h, then the trunk roads are moderate congested link；
If Vl≤ 15km/h, then the trunk roads are heavy congestion section；
When the section is secondary distributor road,
If Vl＞ 35km/h, then the secondary distributor road is unimpeded section；
If 25km/h ＜ Vl≤ 35km/h, then the secondary distributor road is substantially unimpeded section；
If 15km/h ＜ Vl≤ 25km/h, then the secondary distributor road is slight congested link；
If 10km/h ＜ Vl≤ 15km/h, then the secondary distributor road is moderate congested link；
If Vl≤ 10km/h, then the secondary distributor road is heavy congestion section.
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| CN106251625B (en) * | 2016-08-18 | 2019-10-01 | 上海交通大学 | Three-dimensional urban road network global state prediction technique under big data environment |
| CN110609853B (en) * | 2019-09-18 | 2022-09-30 | 青岛海信网络科技股份有限公司 | Trunk line frequent congestion propagation rule mining method and device |
| CN113470347B (en) * | 2021-05-20 | 2022-07-26 | 上海天壤智能科技有限公司 | Congestion identification method and system combining bayonet vehicle passing record and floating vehicle GPS data |
| CN113808388A (en) * | 2021-08-03 | 2021-12-17 | 珠海市规划设计研究院 | Traffic jam analysis method comprehensively considering operation of cars and public traffic |
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