CN106875680A - Crossing average latency computational methods based on big data analysis - Google Patents
Crossing average latency computational methods based on big data analysis Download PDFInfo
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- CN106875680A CN106875680A CN201710168746.7A CN201710168746A CN106875680A CN 106875680 A CN106875680 A CN 106875680A CN 201710168746 A CN201710168746 A CN 201710168746A CN 106875680 A CN106875680 A CN 106875680A
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- crossing
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- average latency
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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]
Abstract
The invention discloses a kind of crossing average latency computational methods based on big data analysis.The present invention counts outlet and crossing section by map datum, then the track chain across crossing is found out according to magnanimity floating car data, by the running time and the running distance that count all track chains across crossing, estimate the average latency at each crossing, here average latency includes all direction of traffics at crossing, statistical average is carried out to all directions when the visualization of crossing average latency is carried out, is easy to displaying.Invention utilizes real floating car data and map datum, and data have the characteristics of data volume is big, data accuracy is high, and the crossing transit time for thus estimating is more accurate.
Description
Technical field
The invention belongs to data mining technical field, and in particular to a kind of crossing average waiting based on big data analysis
Time estimation method.
Background technology
With the great-leap-forward development at full speed of China's economy, living standards of the people are improved constantly, to urban transportation supply, service
Propose requirement higher, such as unobstructed traffic, efficient traffic circulation etc..Traditional traffic study, research mode exist
City size, Traffic Systems, today of Urban vehicles poputation explosive growth have increasingly seemed unable to do what one wishes,
In such as crossing average latency, i.e. certain time period, average value of a large amount of motor vehicles in the stand-by period at crossing.
The parameter is, by big data analysis means, to be obtained according to True Data analysis, by dividing for True Data
Analysis checking finds that the crossing average latency is different from traffic light time, is also not suitable for being substituted by the section speed between crossing.
At present, traditional traffic study, research meanses there is no method to obtain this parameter, be gathered around in road speeds calculating, traffic
The aspects such as stifled index is calculated, path planning calculating, the main section speed using between crossing is used as foundation, the current shape at crossing
State description is replaced by the section speed between crossing.Such as, certain unobstructed section, it is 40km/h that it characterizes speed, but on road
The crossing at section two ends is equally 40km/h, by the distance at crossing about in 100m or so, if with the speed of 40km/h
Calculate, it will be very of short duration, but in fact, on one section of relatively long section, section is likely to be unobstructed, but
Crossing is likely to require 2 traffic lights could be passed through, and, from stop, etc. until restarting, by crossing, will be much high
Time required for 100 meters of distances are crossed with the speed of 40km/h.This time error is calculated for road speeds, characterized,
Traffic congestion index based on road speeds is calculated can temporarily be ignored, but larger mistake will be produced in terms of path planning
Difference, finds, it is contemplated that when crossing waits by being contrasted with the conventional shortest path planning algorithm for not accounting for the crossing stand-by period
Between path planning algorithm, will significantly better than not accounting for the algorithm of crossing stand-by period in time most short this index.
The crossing stand-by period, in addition to it can greatly improve path planning service quality, in road speeds, traffic congestion
Index sign aspect can also play castering action, such as, existing road speeds, traffic congestion index only characterize section, such as
Shown in Fig. 4, the color and passage rate in section are exactly the color and passage rate at crossing.In fact, the current state quilt at crossing
Mask, be so both unfavorable for traffic programme, traffic scheduling, traffic guidance is also unfavorable for that the road is clear.
The content of the invention
Deficiency of the present invention for prior art, there is provided a kind of crossing average latency based on big data analysis
Computational methods.
The central scope of technical solution of the present invention：Outlet and crossing section are counted by map datum, then basis
Magnanimity floating car data finds out the track chain across crossing, by count all track chains across crossing running time and driving away from
From, the average latency at each crossing is estimated, the average latency here includes all direction of traffics at crossing, is entering
Statistical average is carried out to all directions during the visualization of walking along the street mouthful average latency, is easy to displaying.
The inventive method is comprised the following steps：
Step 1. reads in real floating car data and GIS map data；
Step 2. road section information according to the map in data, is calculated crossing, and crossing section is marked；
Step 3. counts the floating wheel paths across crossing；
Step 4. calculates the average crossing stand-by period, obtains a result.
The device have the advantages that：The present invention utilizes real floating car data and map datum, and data have
The characteristics of data volume is big, data accuracy is high, the crossing transit time for thus estimating is more accurate.
Brief description of the drawings
Fig. 1 is the flow chart for estimating the crossing average latency.
Fig. 2 crossings and coupled section schematic diagram.
Across the crossing track chain schematic diagrames of Fig. 3-1.
The unimpeded running time schematic diagrames of Fig. 3-2.
Fig. 4 Baidu maps Hangzhou part real-time road.
Fig. 5 China certain city's time period crossing average latency figure.
Specific embodiment
Below in conjunction with accompanying drawing, the invention will be further described.As shown in figure 1, the present invention comprises the following steps：
Step 1. data prepare
To importing floating car data, map datum in database, floating car data include the number-plate number, track point coordinates,
The record time；Map datum comprising field have road section ID, starting point longitude and latitude, midpoint longitude and latitude, terminal longitude and latitude, link length,
Road speed limit；
Step 2. counts crossing and the section passed through across crossing
2-1. counts outlet and crossing section
Crossing refers to the junction of three roads or crossroad, as shown in Fig. 2 being a crossroad in figure.
Read in map datum.Road section information table (as shown in table 2-1) is created, including road section ID, starting point coordinate, terminal are sat
Mark, link length, road speed limit, the road segment midpoints coordinate in GIS GIS-Geographic Information System are not used in the present invention, therefore this
This information is ignored in invention in statement.
Table 2-1 road section information tables
| Road section ID | Starting point coordinate | Terminal point coordinate | Link length | Road speed limit |
| (JD1,WD1) | (JD2,WD2) | length1 | freespeed1 | |
| (JD2,WD2) | (JD3,WD3) | length2 | freespeed2 | |
| (JD2,WD2) | (JD4,WD4) | length3 | freespeed3 | |
| (JD2,WD2) | (JD5,WD5) | length4 | freespeed4 | |
| (JD6,WD6) | (JD1,WD1) | length5 | freespeed5 | |
| …… | …… | …… | …… | …… |
End points refers to the beginning and end in section.The end points interconnection in all sections is constituted in GIS map data
Road network.Therefore, it can, by traveling through road section information table 2-1, the section that all end points are connected be counted, so as to draw table 2-
2 terminal point information tables.If the section quantity that end points is connected>When=3, then by end points, labeled as crossing, (crossing refers to road junction
Mouth or crossroad), i.e. crossing tag field is set to 1 in table 2-2, otherwise sets to 0.
Table 2-2 terminal point information tables
Crossing section refers to the section that crossing is connected, then in the road section ID list that crossing end points is connected in table 2-2
Every section be all crossing section.1 crossing (JD2, WD2), coupled section R are labeled as such as crossing1,R2,R3,R4
The as crossing section of crossing (JD2, WD2).
2-2. sets up across crossing road section information table
When vehicle across certain crossing when travelling, it will have different travel directions, it is necessary to different in calculating crossing
The crossing stand-by period of travel direction.As shown in Fig. 2 when vehicle from R5Through R1When driving towards crossing, it across the preceding section in crossing is
R1, it across section behind crossing be probably R2,R3,R4, it is therefore desirable to across intersection information table is created, as shown in table 2-3, will be crossed over
The direction that is possible at crossing is recorded, including across the preceding section in crossing, across section behind crossing, the crossing coordinate of process, and gives
Crossing numbering is IPi。
Across the intersection information tables of table 2-3
| Across the preceding section in crossing | Across section behind crossing | The crossing coordinate of process | Crossing point numbering |
| 1 | 2 | (JD3,WD3) | |
| 1 | 3 | (JD3,WD3) | |
| 1 | 4 | (JD3,WD3) | |
| 2 | 1 | (JD3,WD3) | |
| 2 | 3 | (JD3,WD3) | |
| 2 | 4 | (JD3,WD3) | |
| …… | …… | …… | …… |
Step 3. counts the track chain across crossing
Track chain across crossing refers to Floating Car across continuous two tracing points of crossing traveling, that is, two tracks
The matching section of point is all crossing section and is connected by crossing point.As shown in figure 3-1, the same track Tp of car2Cross section
R1, across crossing IP1Afterwards, section R is turned to4, leave track Tp3.Not only to excavate Tp2→Tp3Track chain, in addition it is also necessary to record across
Crossing IP more1, and the section R passed through before and after1And R4。
3-1. collects across crossing track chain
Floating car data is read, floating wheel paths table (as shown in table 3-1) are created, table includes track point coordinates, vehicle
Numbering, records the time, matches section.Wherein matching section needs to be drawn by subsequent calculations.
Table 3-1 Floating Car track data tables
| Track point coordinates | The number-plate number | The record time | Matching section |
Tracing point is expressed as Tpi, the record time of tracing point is expressed as Tpi.t, matching section is expressed as Ri。
1) utilizes map gridding algorithm, calculates each tracing point TpiMatching section Ri, table 3- is inserted into matching section
In 1.
2) includes various leap relations due to same crossing, when different leap relations also has different crossings to wait
Between, citing is as shown in Fig. 2 from R1To R2With from R2To R1And from R1To R3All it is different leap relations, the four crossway in Fig. 2
Mouth has 12 kinds and crosses over relation, will be from section RiCross section RjIt is designated as the relation of crossing over<Ri,Rj>.Create across crossing track chain
Set matrix (3.1) TrajSet, whereinRelation is crossed in expression<Ri,Rj>Comprising institute
There is track chain；
3) reads table 3-1 Floating Car track data tables according to car number and record time ascending order.Same car it is continuous
Two tracing point TpiAnd Tpi+1Referred to as track chain<Tpi,Tpi+1>.Table 3-1 is read, tracing point Tp is determinediAnd Tpi+1Matching road
Section is respectively RxAnd Ry.If RxAnd RyThe crossing section marked in table 2-3 is belonged to, is then claimed<Tpi,Tpi+1>It is the rail across crossing
Mark chain, is written into the set in matrix (3.1)In.
Citing such as Fig. 3-1, is the 4 of car continuous path points in figure, is sequentially Tp1→Tp2→Tp3→Tp4, wherein
Tp1And Tp2Matching section be R1, Tp3And Tp4Matching section be R4, track chain<Tp2,Tp3>Across crossing point IP1, then will
Track chain<Tp2,Tp3>Write-in matrix (3.1)In.
3-2. calculates across crossing track chain<Tpi,Tpi+1>Running time and running distance.
Across crossing track chain<Tpi,Tpi+1>Running time be：
t(Tpi,Tpi+1)=Tpi+1.t-Tpi.t (3.2)
Table across the intersection information tables of 2-3 are read, according to tracing point TpiAnd Tpi+1Matching section RxAnd Ry, draw the track chain
The crossing of leap is IPn, then the running distance of the track chain：
dist(Tpi,Tpi+1)=dist (Tpi,IPn)+dist(IPn,Tpi+1) (3.3)
Formula (3.3) can be construed to across crossing point IPnTrack chain<Tpi,Tpi+1>Running distance be tracing point
TpiTo crossing point IPnEuclidean distance plus crossing point IPnTo tracing point Tpi+1Euclidean distance.
3-3. calculates across crossing track chain<Tpi,Tpi+1>The crossing stand-by period
If across the crossing track chain of vehicle<Tpi,Tpi+1>Shi Changtong is travelled, then travel speed of the vehicle at crossing can be higher.
As shown in figure 3-2, it is assumed that vehicle is with road speed limit freespeedRxAnd freespeedRyTravel respectively across crossing
IPiFront and rear section RxAnd RyOn, by track chain<Tpi,Tpi+1>It is divided into<Tpi,IPi>With<IPi,Tpi+1>Two parts, Ze Kua roads
Mouth track chain<Tpi,Tpi+1>Running time t in the case of unblockedfree(Tpi,Tpi+1) be<Tpi,IPi>With<IPi,
Tpi+1>Shown in unimpeded running time sum, such as formula (3.4).
Track chain<Tpi,Tpi+1>Crossing stand-by period twait(Tpi,Tpi+1) unimpeded traveling is subtracted for actual transit time
Time, the as car pass through IP at the momentiCrossing Rx→RyThe stand-by period in direction.As shown in formula (3.5),
twait(Tpi,Tpi+1)=t (Tpi,Tpi+1)-tfree(Tpi,Tpi+1) (3.5)
Step 4. estimates the average crossing stand-by period
4-1. sets up crossing stand-by period sample set matrix
Matrix TList (as shown in (4.1)) is created, whereinRxRepresent across before crossing
Section, RyRepresent across section behind crossing,It is to include to belong to the relation of leap<Rx,Ry>All crossing stand-by period
Set (as shown in (4.2)), i.e., matrix (3.1) is correspondingIn all of track chain
The crossing stand-by period (calculates) according to formula (3.5).
4-2. calculates crossing average latency matrix
Each single item in matrix 4.1In value all meet normal distribution N (μ (twait(Tpi,Tpi+1)),σ2
(twait(Tpi,Tpi+1))), it is rightUsing Grubbs test method rejecting abnormalities value, mean μ (t is then tried to achievewait(Tpi,
Tpi+1)) just it is across relation<Rx,Ry>The crossing average latency be：
Twait(Rx,Ry)=μ (twait(Tpi,Tpi+1)) (4.3)
To all of leap relation in matrix 4.1 all as formula (4.3) is calculated, outlet average latency matrix is obtained：
Formula (4.4) has been calculated the crossing institute directive average latency, for the ease of display, can be by crossing
The directive average latency be averagely displayed in figure as shown in Figure 5, although perfect way is with different face
Color shows each direction, but this partial content still not comprising in the present invention.Therefrom it can be found that the road of present invention offer
The mouth stand-by period, the degree of accuracy of path planning can be not only substantially improved, existing traffic system congestion, road network can more be led to
Row ability carries out beneficial complement sign, can also be that traffic programme and administrative department provide reference.
In addition, the content of the formula (4.4) that the present invention is obtained can also be path planning and road situation characterize, such as
Congestion index design is improved and provides reference.
Claims (5)
1. the crossing average latency computational methods analyzed based on big data, it is characterised in that：
Step 1. counts outlet and crossing section by map datum, sets up across crossing road section information table, described crossing
Refer to the junction of three roads or crossroad, described crossing section refers to the section that crossing is connected；
Step 2. finds out the track chain across crossing according to magnanimity floating car data；The described track chain across crossing refers to Floating Car
Across continuous two tracing points of crossing traveling；
Step 3. estimates the average of each crossing by counting running time and the running distance of all track chains across crossing
Stand-by period；The described average latency includes all direction of traffics at crossing.
2. it is according to claim 1 based on big data analysis crossing average latency computational methods, it is characterised in that
Step 2 is specifically：
Step 2-1. collects across crossing track chain；
Step 2-2. calculates running time and the running distance of across crossing track chain；
Step 2-3. calculates the crossing stand-by period of across crossing track chain.
3. it is according to claim 2 based on big data analysis crossing average latency computational methods, it is characterised in that：
Step 2-1 is specifically：
1) read floating car data, create floating wheel paths table, the table include track point coordinates, car number, record the time and
Matching section；
2) utilizes map gridding algorithm, calculates the matching section of each tracing point, and matching section is inserted into floating wheel paths table
In；
3) creates across crossing track chain set matrix；
4) reads floating wheel paths table according to car number and record time ascending order；Continuous two tracing points of same car claim
It is track chain；Determine the section of the two track Point matchings；If the two sections belong to be marked in across crossing road section information table
The crossing section of note, then the track chain is the track chain across crossing, is written into across crossing track chain set matrix.
4. it is according to claim 1 based on big data analysis crossing average latency computational methods, it is characterised in that
Step 3 is specifically：
3-1. sets up crossing stand-by period sample set matrix, and it includes, across the preceding section in crossing, across section behind crossing, belonging to leap
The set of all crossing stand-by period of relation；
3-2. calculates crossing average latency matrix：
To belonging to the set across all crossing stand-by period of relation using Grubbs test method rejecting abnormalities value, try to achieve
Value, as across the crossing average latency of relation；
Average is asked for all of leap relation in crossing stand-by period sample set matrix, crossing average latency square is obtained
Battle array.
5. it is according to any one of claim 1 to 4 based on big data analysis crossing average latency computational methods,
It is characterized in that：Statistical average is carried out to all directions when the visualization of crossing average latency is carried out, is easy to displaying.
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| CN108776345A (en) * | 2018-03-30 | 2018-11-09 | 喻爱平 | A kind of real-time graph big data acquisition method, device and its system |
| CN113271546A (en) * | 2021-04-26 | 2021-08-17 | 重庆凯瑞特种车有限公司 | Garbage collection and transportation intelligent management platform |
| CN113888872A (en) * | 2021-10-20 | 2022-01-04 | 沈阳世纪高通科技有限公司 | Method for calculating traffic light duration based on floating car data |
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Application publication date: 20170620 |