CN103761430B - A kind of road network peak period recognition methods based on Floating Car - Google Patents

A kind of road network peak period recognition methods based on Floating Car Download PDF

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CN103761430B
CN103761430B CN201410012796.2A CN201410012796A CN103761430B CN 103761430 B CN103761430 B CN 103761430B CN 201410012796 A CN201410012796 A CN 201410012796A CN 103761430 B CN103761430 B CN 103761430B
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tci
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CN103761430A (en
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邹娇
陶刚
刘俊
高万宝
方林
李立超
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Anhui Keli Information Industry Co Ltd
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Abstract

The present invention relates to a kind of road network peak period recognition methods based on Floating Car, the defect of the road network peak period recognition methods for being not based on floating car technology is solved compared with prior art.The present invention is comprised the following steps:Section bicycle sample speed is calculated using Floating Car gps data;Extract road-section average travel speed;Calculating cycle traffic congestion index TCI;Extract beginning and ending time peak hour morning and evening point.The present invention can analyze system by existing floating car technology and urban road congestion, therefrom analyze road grid traffic temporal behavior, extract road network peak period.

Description

A kind of road network peak period recognition methods based on Floating Car
Technical field
The present invention relates to traffic planninng technical field, a kind of specifically road network peak period based on Floating Car Recognition methods.
Background technology
Floating car technology is to run a kind of skill that vehicle dynamic location information obtains road situation according to pavement of road Art, using the Floating Car with GPS information(Taxi or bus)Can be with the displacement information of Real-time Collection vehicle, by time sequence The vehicle location coordinate of row is matched with map, can obtain the speed data of floating vehicle.Floating car technology will can be adopted In the collection data Cun Chudao databases of a year, cycle link flow information is obtained using cycle link speed information.
AADT(The annual day magnitude of traffic flow of road, annual average daily traffic)Be traffic model and Administrative decision very important parameter, grinds in traffic programme, highway layout, traffic safety, transport need analysis, traffic control etc. Study carefully the effect that field suffers from key.Existing AADT is calculated and is not recycled traditional manual counts, also by floating The Road average-speed of car technical limit spacing, the accurate estimation of intellectuality for realizing road AADT is calculated by a series of models.Meet Traffic programme, traffic design, the demand data of traffic administration, improve operating efficiency.
Peak period(peak hours)Refer to due to the rush hour road traffic morning and evening section that commuting traffic is caused.It is early high The peak period is usually:7:00-9:00, evening peak is usually 17:00-19:00, discontinuous point is with region, category of roads, road when specific Section difference and have differences.Peak period algorithm for estimating can realize that city road network and the peak period in region calculate, and be Road conditions issuing service provides basic data source, is played an important role in traffic administration and traffic-information service.Utilizing During floating car technology calculates AADT, when the hour magnitude of traffic flow is calculated, the judgement of its peak period then foundation《City road Road traffic congestion assessment indicator system》(Exposure draft)Middle illustrated road traffic morning and evening peak period standard.But each The peak period in city differs, if the actual peak period using unified standard obviously with each city is variant, from And influence the intelligent estimation precision of AADT.How developing one kind can enter walking along the street based on floating car technology for different cities The recognition methods for netting peak period has become the technical problem for being badly in need of solving.
The content of the invention
Road network peak period the invention aims to solve to be not based in the prior art floating car technology recognizes The defect of method, there is provided a kind of road network peak period recognition methods based on Floating Car solves the above problems.
To achieve these goals, technical scheme is as follows:
A kind of road network peak period recognition methods based on Floating Car, comprises the following steps:
Section bicycle sample speed is calculated using Floating Car gps data;
Extract road-section average travel speed;
Calculating cycle traffic congestion index TCI;
Extract beginning and ending time peak hour morning and evening point.
Described utilization Floating Car gps data calculates section bicycle sample speed and comprises the following steps:
Adjacent 2 points before and after sample vehicle j is passed through of routing information { P is obtained by Floating Car gps datai, i=1, 2, L, n };
By path length Δ djWith time difference Δ tjObtain this section of Average Travel Speed in path
If approach section number only one of which orKilometer/hour when, willIt is assigned to section P1;Otherwise, by four kinds of traffic The instantaneous velocity v of state principle combination starting point1With the instantaneous velocity v of terminal2, to each section speed difference assignment of approach.
The determination methods of four kinds of described traffic behavior principles are as follows:
Deceleration regime, meetsWhen, initial section velocity amplitude is assigned toOther section velocity amplitudes are total Travel time Δ tjThe travel time in initial section is subtracted, speed is then obtained divided by the time by distance;
Acceleration mode, meetsWhen, terminate section velocity amplitude and be assigned toOther section velocity amplitudes are total Travel time Δ tjThe travel time in initial section is subtracted, speed is then obtained divided by the time by distance;
First slow down and accelerate afterwards, initial section velocity amplitude is assigned to v1, terminate section velocity amplitude and be assigned to v2, middle section velocity amplitude It is total travel time Δ tjThe travel time in initial section is subtracted, speed is then obtained divided by the time by distance;
First accelerate to slow down afterwards, approach section velocity amplitude is assigned to
Described extraction road-section average travel speed computing formula is
Wherein, ViIt is segmental arc PiAverage speed, liIt is segmental arc PiLength, tijIt is jth car segmental arc P in the pathsiOn Travel time, niIt is segmental arc PiThe upper number of vehicles for participating in calculating.
Described calculating cycle traffic congestion index TCI is comprised the following steps:
Based on road-section average travel speed ViCongestion status identification is carried out, congested link is judged;
Section congestion mileage ratio RCR is calculated, through street congestion mileage ratio RCRf, trunk roads congestion mileage are calculated respectively Ratio RCRa, secondary distributor road congestion mileage ratio RCRm and branch road congestion mileage ratio RCRl, computing formula are as follows:
RCR=RCRf*ω1+RCRa*ω2+RCRm*ω3+RCRl*ω4
Wherein,
L (i) is the length of section i, and Lc (i) is the length of the section i for getting congestion,
nf:Through street section total number,
na:Trunk roads section total number,
nm:Secondary distributor road section total number,
nl:Branch road section total number,
W1, w2, w3, w4 represent the weight of each grade road respectively,
Road grid traffic congestion index TCI is calculated, computing formula is as follows:
Wherein:a=RCR*100.
Described beginning and ending time peak hour extraction morning and evening point is comprised the following steps:
Judge in 24 hours one day TCI curves whether Normal Distribution, if Normal Distribution enters next step meter Calculate, if disobeying normal distribution, then it represents that same day traffic abnormity, reject data and reselect data;
Setting confidence value c, c are the error range that estimate is allowed with population parameter;
According to 24 hours TCI changing values, the maxima and minima of TCI is taken,
With 0 point to 12 points to divide, TCI maximums are max_a, and wherein a is the number of cycles of 1-288, and the cycle is 5 points Clock;TCI front portions minimum value is min_t1, and wherein t1 is the corresponding periodicity of minimum value;TCI rear portions minimum value min_t2, wherein T2 is the corresponding periodicity of minimum value;
With 12 points to 24 points to divide, TCI maximum max_p, wherein p are the number of cycles of 1-288, and the cycle is 5 minutes; Minimum value min_t3, wherein t3 are the corresponding periodicities of minimum value for TCI front portions;TCI rear portions minimum value min_t4, wherein t4 are most It is small to be worth corresponding periodicity;
The zoning gross area S1, S2, S3, S4,
Calculate variance area S1'、S2'、S3'、S4',
By S1, S2, S3, S4 and S1'、S2'、S3'、S4' the corresponding substitution formula c=S of differencei'/SiSolve, divided by solving J1, j2, j3, j4 are not obtained, wherein, i=1,2,3,4, Si' it is variance area, SiIt is intervening areas;
The morning peak period is determined for T1 to T2, the evening peak period is determined for T3 to T4, and wherein T1, T2, T3, T4 distinguish successively The Period Start Time of correspondence j1, j2, j3, j4.
Whether the formula of Normal Distribution is the described TCI curves that judge:
And
Wherein:It is arithmetic mean of instantaneous value, M is median, and s is standard deviation.
Beneficial effect
A kind of road network peak period recognition methods based on Floating Car of the invention, compared with prior art can be by existing Some floating car technologies and urban road congestion analysis system, therefrom analyze road grid traffic temporal behavior, when extracting road network peak Section.The period of road grid traffic load most serious is obtained, is supported for traffic administration person and traffic planners provide data, improve AADT Intelligent estimation precision.
Brief description of the drawings
Fig. 1 is flow chart of the method for the present invention
Fig. 2 is TCI24 hours curvilinear motion figure and relevant parameter mark figure
Specific embodiment
To make have a better understanding and awareness to architectural feature of the invention and the effect reached, to preferably Embodiment and accompanying drawing coordinate detailed description, are described as follows:
As shown in figure 1, a kind of road network peak period recognition methods based on Floating Car of the present invention, including following step Suddenly:
The first step, section bicycle sample speed is calculated using Floating Car gps data.
Bicycle sample mean travelling speed in a measurement period in section is calculated using Floating Car gps data, first, is led to Cross the routing information { P that Floating Car gps data obtains at front and rear adjacent 2 points that sample vehicle j is passed throughi, i=1,2, L, n }.Its It is secondary, can be by path length Δ d based on gps datajWith time difference Δ tjObtain this section of Average Travel Speed in pathAgain, when approach section number only one of which be represent not across crossing orKilometer/hour i.e. unimpeded shape During state, willIt is assigned to section P1;Otherwise, by the instantaneous velocity v for combining starting point1With the instantaneous velocity v of terminal2, point four kinds of traffic shapes Each the section speed difference assignment of state to approach.
When Floating Car is in deceleration regime, that is, meetWhen, initial section velocity amplitude is assigned toOther Section velocity amplitude is total travel time Δ tjThe travel time in initial section is subtracted, is then obtained divided by the time by distance Speed, then speed is assigned to section P1
When Floating Car is in acceleration mode, meetWhen, terminate section velocity amplitude and be assigned toOther Section velocity amplitude is total travel time Δ tjThe travel time in initial section is subtracted, is then obtained divided by the time by distance Speed, then speed is assigned to section P1
Accelerate afterwards when Floating Car is in first to slow down, initial section velocity amplitude is assigned to v1, terminate section velocity amplitude and be assigned to v2, in Between section velocity amplitude be total travel time Δ tjThe travel time in initial section is subtracted, is then obtained divided by the time by distance To speed, then speed is assigned to section P1
First accelerate to slow down afterwards when Floating Car is in, approach section velocity amplitude is assigned toAgain willIt is assigned to section P1
Second step, extracts road-section average travel speed.
Extracting road-section average travel speed computing formula is
Wherein, ViIt is segmental arc PiAverage speed, liIt is segmental arc PiLength, tijIt is jth car segmental arc P in the pathsiOn Travel time, niIt is segmental arc PiThe upper number of vehicles for participating in calculating.Here, n is worked asiEqual to 0, i.e., there is no data to cover on the section Gai Shi, we are supplemented with one week historical average speeds of different time sections of historical accumulation;Work as niWhen being not equal to 0, section Average travel speed is then the harmonic average speed of multiple samples.
3rd step, calculating cycle traffic congestion index TCI.
Cycle traffic congestion index refers in a measurement period(Typically 5 minutes), retouched with the numerical value of one 0~10 The congestion level of current region road network is stated, is the quantizating index for describing congestion level.Calculation procedure is as follows:
First, based on road-section average travel speed ViCongestion status identification is carried out, congested link is judged.
Speed interval table in table 1, judges whether current road segment belongs to congestion status, will be the road of congestion status Segment data puts forward for next step treatment.Threshold value table data source in table 1 was announced according to 2010《Urban road is handed over Siphunculus manages assessment indicator system》Middle regulation, the corresponding threshold value of motor vehicle average travel speed in city thoroughfare, and according to conjunction Fertile city's actual traffic characteristic has carried out what fine setting was obtained.When different cities use, can be according to local actual traffic characteristic Carry out adapting to fine setting.
The road condition that table 1 is based on road-section average travelling speed divides speed interval table
Classification 1 grade:Free flow 2 grades:It is unimpeded 3 grades:Jogging 4 grades:It is crowded 5 grades:Congestion
Through street More than 65km/h 65-40km/h 40-30km/h 30-15km/h Below 15km/h
Major trunk roads More than 50km/h 50-30km/h 30-22km/h 22-12km/h Below 12km/h
Subsidiary road More than 40km/h 40-25km/h 25-18km/h 18-10km/h Below 10km/h
Branch road More than 35km/h 35-23km/h 23-16km/h 16-8km/h Below 8km/h
Secondly, section congestion mileage ratio RCR is calculated.
Through street congestion mileage ratio RCRf, trunk roads congestion mileage ratio RCRa, secondary distributor road congestion mileage are calculated respectively Ratio RCRm and branch road congestion mileage ratio RCRl, computing formula is as follows:
RCR=RCRf*ω1+RCRa*ω2+RCRm*ω3+RCRl*ω4
Wherein,
L (i) is the length of section i, and Lc (i) is the length of the section i for getting congestion,
nf:Through street section total number,
na:Trunk roads section total number,
nm:Secondary distributor road section total number,
nl:Branch road section total number,
W1, w2, w3, w4 represent the weight of each grade road respectively,
W1, w2, w3, w4 represent the weight of each grade road respectively, from total the passing through of each grade road of road network vehicle Mileage historical data statistical analysis draws.In table 2, there are working day weights recommendation tables and festivals or holidays weights recommendation tables respectively, In practice, it is also possible to the specified calculating of w1, w2, w3, w4 is carried out with reference to provincial standard.
Table 2《Urban road traffic congestion assessment indicator system》Beijing provincial standard
Working day Through street Trunk roads Secondary distributor road Branch road It is total
Peak period 0.19 0.43 0.15 0.23 1.00
It is full-time average 0.20 0.41 0.16 0.23 1.00
Festivals or holidays Through street Trunk roads Secondary distributor road Branch road It is total
It is full-time average 0.20 0.41 0.16 0.23 1.00
Finally, road grid traffic congestion index TCI is calculated.
Computing formula is as follows:
Wherein:A=RCR*100, the value according to a is different, selects corresponding computing formula.
4th step, extracts beginning and ending time peak hour morning and evening point.
Comprise the following steps:
(1)As shown in Fig. 2 first judge in 24 hours one day TCI curves whether Normal Distribution, if obeying normal state point Cloth is calculated into next step, if disobeying normal distribution, then it represents that same day traffic abnormity, there is emergency situations.Data are not Data easily are calculated as reference, therefore is rejected data and is reselected data.Differentiate whether Normal Distribution is used TCI curves Method, be one of existing statistics the inside normal distribution-test method, be the ratio with sample median M with arithmetic mean of instantaneous value Judged with the relation of standard deviation with arithmetic mean of instantaneous value, reflect peak shape and kurtosis, formula is as follows:
And
Wherein:It is arithmetic mean of instantaneous value, M is median, and s is standard deviation.
(2)Setting confidence value c, c are the error range that estimate is allowed with population parameter.Confidence value is estimating for judgement Calculation value, can be actually needed to be specified, in general in order to ensure larger confidence level, one according to city and policymaker As take confidence value more than 90.
(3)According to 24 hours TCI changing values, the maxima and minima of TCI is taken.
With 0 point to 12 points to divide, TCI maximums are max_a, and wherein a is the number of cycles of 1-288, and the cycle is 5 points Clock, 288 were divided and got for a cycle with 5 minutes according to 24 hours.TCI front portions minimum value is min_t1, and wherein t1 is The corresponding periodicity of minimum value.TCI rear portions minimum value min_t2, wherein t2 are the corresponding periodicities of minimum value.
With 12 points to 24 points to divide, TCI maximum max_p, wherein p are the number of cycles of 1-288, and the cycle is 5 minutes. Minimum value min_t3, wherein t3 are the corresponding periodicities of minimum value for TCI front portions.TCI rear portions minimum value min_t4, wherein t4 are most It is small to be worth corresponding periodicity.
(4)The zoning gross area S1, S2, S3, S4, its computing formula are as follows:
(5)Calculate variance area S1'、S2'、S3'、S4', its computing formula is as follows:
(6)By S1, S2, S3, S4 and S1'、S2'、S3'、S4' the corresponding substitution formula c=S of differencei'/SiSolve, by asking Solution respectively obtains j1, j2, j3, j4, wherein, i=1,2,3,4, Si' it is variance area, SiIt is intervening areas.
(7)The morning peak period is determined for T1 to T2, the evening peak period is determined for T3 to T4, wherein T1, T2, T3, T4 difference It is corresponding in turn to the Period Start Time of j1, j2, j3, j4.Because j1, j2, j3, j4 are represented herein, by 24 hours with 5 points Clock is 288 periodicities in cycle, by specific time point T1, T2, T3, T4 representated by j1, j2, j3, j4, so as to can just sentence Break and the morning peak period for T1-T2, evening peak period are T3-T4.
General principle of the invention, principal character and advantages of the present invention has been shown and described above.The technology of the industry Personnel it should be appreciated that the present invention is not limited to the above embodiments, the simply present invention described in above-described embodiment and specification Principle, various changes and modifications of the present invention are possible without departing from the spirit and scope of the present invention, these change and Improvement is both fallen within the range of claimed invention.The protection domain of application claims by appending claims and its Equivalent is defined.

Claims (5)

1. a kind of road network peak period recognition methods based on Floating Car, it is characterised in that comprise the following steps:
1) section bicycle sample speed is calculated using Floating Car gps data;
2) road-section average travel speed is extracted;
3) calculating cycle traffic congestion index TCI;
4) beginning and ending time peak hour morning and evening point is extracted;Described beginning and ending time peak hour extraction morning and evening point includes following step Suddenly:
141) judge in 24 hours one day TCI curves whether Normal Distribution, if Normal Distribution enters next step meter Calculate, if disobeying normal distribution, then it represents that same day traffic abnormity, reject data and reselect data;
142) setting confidence value c, c are the error range that estimate is allowed with population parameter;
143) according to 24 hours TCI changing values, the maxima and minima of TCI is taken,
With 0 point to 12 points to divide, TCI maximums are max_a, and wherein a is the number of cycles of 1-288, and the cycle is 5 minutes;TCI Anterior minimum value is min_t1, and wherein t1 is the corresponding periodicity of minimum value;TCI rear portions minimum value min_t2, wherein t2 are most It is small to be worth corresponding periodicity;
With 12 points to 24 points to divide, TCI maximum max_p, wherein p are the number of cycles of 1-288, and the cycle is 5 minutes;TCI Anterior minimum value min_t3, wherein t3 are the corresponding periodicities of minimum value;TCI rear portions minimum value min_t4, wherein t4 are minimum It is worth corresponding periodicity;
144) the zoning gross area S1, S2, S3, S4,
S 1 = Σ t 1 a ( T C I _ i - min _ t 1 ) , i ∈ [ t 1 , a ] ,
S 2 = Σ a t 2 ( T C I _ i - min _ t 2 ) , i ∈ [ a , t 2 ] ,
S 3 = Σ t 3 p ( T C I _ i - min _ t 3 ) , i ∈ [ t 3 , p ] ,
S 4 = Σ p t 4 ( T C I _ i - min _ t 4 ) , i ∈ [ p , t 4 ] ;
145) variance area S is calculated1′、S2′、S3′、S4',
S ′ 1 = Σ j 1 a ( T C I _ j 1 - min _ t 1 ) , j ∈ [ t 1 , a ] ,
S 2 ′ = Σ a j 2 ( T C I _ j 2 - min _ t 2 ) , j ∈ [ a , t 2 ] ,
S 3 ′ = Σ j 3 p ( T C I _ j 3 - min _ t 3 ) , j ∈ [ t 3 , p ] ,
S 4 ′ = Σ p j 4 ( T C I _ j 4 - min _ t 4 ) , j ∈ [ p , t 4 ] ;
146) by S1, S2, S3, S4 and S1′、S2′、S3′、S4The corresponding substitution formula c=S of ' differencei'/SiSolve, by solving J1, j2, j3, j4 are respectively obtained, wherein, i=1,2,3,4, Si' it is variance area, SiIt is intervening areas;
147) the morning peak period is determined for T1 to T2, the evening peak period is determined for T3 to T4, and wherein T1, T2, T3, T4 distinguish successively The Period Start Time of correspondence j1, j2, j3, j4.
2. a kind of road network peak period recognition methods based on Floating Car according to claim 1, it is characterised in that:It is described Utilization Floating Car gps data calculate section bicycle sample speed comprise the following steps:
21) adjacent 2 points before and after sample vehicle j is passed through of routing information { P is obtained by Floating Car gps datai, i=1, 2 ..., n }, wherein n be vehicle traveling path in the section number that includes;
22) by path length Δ djWith total travel time Δ tjObtain this section of Average Travel Speed in path
If 23) approach section number only one of which orKilometer/hour when, willIt is assigned to section P1;Otherwise, by four kinds of traffic shapes The instantaneous velocity v of state principle combination starting point1With the instantaneous velocity v of terminal2, to each section speed difference assignment of approach;
The determination methods of four kinds of described traffic behavior principles are as follows:
231) deceleration regime, meetsWhen, initial section velocity amplitude is assigned toOther section velocity amplitudes are total Travel time Δ tjThe travel time in initial section is subtracted, speed is then obtained divided by the time by distance;
232) acceleration mode, meetsWhen, terminate section velocity amplitude and be assigned toOther section velocity amplitudes are total Travel time Δ tjThe travel time in initial section is subtracted, speed is then obtained divided by the time by distance;
233) first slow down and accelerate afterwards, initial section velocity amplitude is assigned to v1, terminate section velocity amplitude and be assigned to v2, middle section velocity amplitude It is total travel time Δ tjThe travel time in initial section is subtracted, speed is then obtained divided by the time by distance;
234) first accelerate to slow down afterwards, approach section velocity amplitude is assigned to
3. a kind of road network peak period recognition methods based on Floating Car according to claim 1, it is characterised in that:It is described Extraction road-section average travel speed computing formula be
V i = l i t i = l i ( Σ j = 1 n l i v j ) / n = n Σ j = 1 n 1 v j , i f n i ≠ 0 V i ‾ , i f n i = 0 .
4. a kind of road network peak period recognition methods based on Floating Car according to claim 1, it is characterised in that described Calculating cycle traffic congestion index TCI comprise the following steps:
41) based on road-section average travel speed ViCongestion status identification is carried out, congested link is judged;
42) section congestion mileage ratio RCR is calculated, through street congestion mileage ratio RCRf, trunk roads congestion mileage is calculated respectively Ratio RCRa, secondary distributor road congestion mileage ratio RCRm and branch road congestion mileage ratio RCRl, computing formula are as follows:
If during through street,
If during trunk roads,
If during secondary distributor road,
If during branch road,
RCR=RCRf* ω1+RCRa*ω2+RCRm*ω3+RCRl*ω4
Wherein,
L (i) is the length of section i, and Lc (i) is the length of the section i for getting congestion,
nf:Through street section total number,
na:Trunk roads section total number,
nm:Secondary distributor road section total number,
nl:Branch road section total number,
W1, w2, w3, w4 represent the weight of each grade road respectively,
43) road grid traffic congestion index TCI is calculated, computing formula is as follows:
T C I = a 2 , ( 0 &le; a &le; 4 ) 2 + a - 4 2 , ( 4 < a &le; 8 ) 4 + ( a - 8 ) &times; 2 3 , ( 8 < a &le; 11 ) 6 + ( a - 11 ) &times; 2 3 , ( 11 < a &le; 14 ) 8 + a - 14 5 , ( 14 < a &le; 24 ) 10 , ( a &GreaterEqual; 24 )
Wherein:A=RCR*100.
5. a kind of road network peak period recognition methods based on Floating Car according to claim 1, it is characterised in that described The TCI curves that judge whether the formula of Normal Distribution is:And
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