CN108171993A - A kind of vehicle on highway speed calculation method based on mobile phone signaling big data - Google Patents
A kind of vehicle on highway speed calculation method based on mobile phone signaling big data Download PDFInfo
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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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- 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
- G08G1/012—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/20—Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
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Abstract
The present invention relates to the present invention provides a kind of vehicle on highway speed calculation method based on mobile phone signaling big data, belong to intelligent transportation field.This method is specially：The geographical grid system of grid division structure is carried out according to highway circuit, obtains the base station information table of highway, and build base station and the matched information table of road grid；Mobile network mobile phone signaling data stream is obtained in real time, and effectively trip section is carried out after line number Data preprocess and is divided；Carry out highway user identification；Finally extraction highway user track sets information concentrates each user per tracing point two-by-two away from discrete time, and passes through a kind of distance weighted speed calculation method and calculate car speed.The development of the road network monitoring system of vehicle supervision department is greatly facilitated in the present invention, obtains the traffic behavior of road network in real time, is conducive to circuit of making rational planning for, while have great significance to improving resident trip service.
Description
Technical field
The invention belongs to intelligent transportation fields, are related to a kind of vehicle on highway speedometer based on mobile phone signaling big data
Calculation method.
Background technology
In recent years, the emergence of economic growth and technological progress results in intelligent transportation system (ITS) to transport services
Demand is higher and higher, and the Real-time Traffic Information system for how building ITS is more and more important.The traffic flow data master of expressway at present
It to need to install on road by induction coil, earth magnetism, video, radar detedtor and detectors, these modes such as infrared
Detector device needs to expend a large amount of manpower and materials.Or collecting vehicle information is carried out by GPS, but this mode needs
GPS relevant devices are loaded on operation vehicle, initial investment is of high cost, and collects that data are imperfect, has certain limitation
Property.Therefore the prison to highway network is carried out there is an urgent need to a kind of method at low cost, wide, the round-the-clock real time monitoring of covering at present
Control.
At present, with comprehensive covering of mobile network, popularizing comprehensively for mobile phone carries out acquisition road using mobile phone signaling data
Net traffic flow parameter and the method for carrying out highway running state monitoring have become current intelligent transportation system (ITS)
New paragon, can be very good the various demands for meeting current system.
Majority patent is carried out based on mobile phone signaling data in the technical research of vehicle on highway speed calculating at present, big
General step includes：(1) Collecting and dealing of data, the institute for obtaining the highw ay m onitoring region of T to T+t periods in real time are useful
Family mobile phone signaling track data after carrying out data prediction to signaling data, obtains the user mobile phone signaling number of monitoring time section
Gather according to track；(2) map match establishes geographical grid system according to highway actual path and the base station position information on periphery
Then system carries out base station and the matching of expressway road grid according to Euclidean distance formula；(3) highway user identifies, root
Judge whether user is highway user according to the similarity of subscriber signaling track sets and pathway station sequence, obtain at a high speed
Highway user signaling data track set H_D；(4) traffic parameter estimation etc. is basis merely wherein in average speed calculating
The mode of the ratio of distance and time carrys out calculating speed value, and this scheme calculating is single, and computational accuracy is not high enough, and due to mesh
The influence of the factors such as the positioning accuracy of preceding base station is high, complicated traffic, it is simple by the ratio of distance and time
Mode carrys out calculating speed value and is not enough to accurately judge road traffic state.
Invention content
In view of this, the purpose of the present invention is to provide a kind of vehicle on highway speed based on mobile phone signaling big data
Computational methods are higher by the shorter calculating speed precision of distance apart from road grid to improve the precision of car speed estimation
The characteristics of, setting one is with apart from relevant best weight value function, being fused in traditional speed calculation formula, greatly improving
Computational accuracy.
In order to achieve the above objectives, the present invention provides following technical solution：
A kind of vehicle on highway speed calculation method based on mobile phone signaling big data, this method step are：
S1：The step of vehicle on highway speed calculates is carried out according to based on mobile phone signaling data, carries out mobile phone signaling number
According to Collecting and dealing；Then map match is carried out, establishes geographical grid system；Then highway user identification is carried out, is obtained
To for calculating the highway user signaling data track set H_D of expressway road grid average speed；
S2：After the highway user signaling data track set H_D for obtaining T to the T+t periods, order traversal highway
Subscriber signaling data track set H_D extracts the track sets of each user；
S3：Traversed the tracing point in the track sets of each user two-by-two to each user's sequence, tracing point is
Base sites include timestamp and geographical location information in the signaling data of base station, in user trajectory sequence per track two-by-two
Computing unit of the point as a calculating user velocity；
S4：According to the road grid that geographical grid system divides, corresponding speed container is set for each road grid, is used
In the weighting velocity amplitude that each computing unit of preservation obtains；
S5：According to the computing unit that traversal obtains, it is defined as tracing point TracenWith tracing point Tracem, calculate each single
The path distance of member and distance time；
S6：According to the thought of physical motion, by obtaining feature in the angle of statistical significance：Comprising road grid
The path distance of two tracing point computing units is shorter, then bigger to the contribution margin of the road grid average speed；According to this feature,
Set a Gauss weight function with path distance inverse correlation
S7：The weighting velocity amplitude of two tracing point computing units is calculated, by the path distance between two tracing points that are calculated
Dn,mWith distance time Tn,mRatio multiplied by with Gauss weight functionObtain the weighting velocity amplitude of the computing unitIt and will
The velocity amplitudeIt is put into the corresponding road grid velocity container between two tracing points,
S8：Step S2~S7 is repeated, until in the highway user signaling data track set H_D of T to T+t periods
User trajectory sequence all traverses completion；
S9：The weighting sets of speeds in each road grid velocity container is finally traversed, to adding in each road grid
Power sets of speeds carries out and operation obtains the average speed value V of the road gridk, 1≤k≤N,
Wherein l is expressed as l-th of subscriber signaling in k-th of section, NkRepresent the number of users in k-th of section,Represent the
N section is to the distance in m-th of section, 1≤k≤Nk,Represent n-th of section to the time in m-th of section, 1≤l≤Nk；
Further, the step S5 is specially：
S501：The tracing point of sequence traverse user track sets two-by-two, with per tracing point Trace two-by-twonAnd TracemAs
One computing unit then according to the matched geographical grid system in base station in step S1 and road grid, obtains two tracks
Point TracenAnd TracemBetween road grid subsequence { gn[an,bn],…,gm[am,bm], wherein [an,bn] represent grid position
Serial number is put, then two tracing point TracenAnd TracemDistance Dn,mIt is calculated by equation below：
The number of road grids of the wherein M between two tracing points, L are the length of road grid；
S502：Calculate tracing point TracenAnd TracemBetween journey time, if tracing point TracenTimestamp be
TimeStampn, tracing point TracemTimestamp be TimeStampm, then the journey time between two tracing points is Tn,m；
Tn,m=TimeStampn-TimeStampm。
The beneficial effects of the present invention are：The present invention is higher by the shorter calculating speed precision of distance apart from road grid
The characteristics of, setting one is with apart from relevant best weight value function, being fused in traditional speed calculation formula, greatly improving
Computational accuracy, to better meet the demand of ITS systems.
Description of the drawings
In order to make the purpose of the present invention, technical solution and advantageous effect clearer, the present invention provides drawings described below and carries out
Explanation：
Fig. 1 is the flow chart of the vehicle on highway speed calculation method based on mobile phone signaling big data；
Fig. 2 is the circuit mapping graph of highway geography grid system；
Fig. 3 is the user trajectory figure for the different path lengths that expressway includes a section grid.
Specific embodiment
Below in conjunction with attached drawing, the preferred embodiment of the present invention is described in detail.
As shown in Figure 1, the present invention provides a kind of vehicle on highway side speed calculations based on mobile phone signaling big data
Method, step are：
Step 1, the rectangular grid for being defined to L according to length and width according to highway route carry out dividing the processing of grid section,
And a direction of setting high-speed highway is its positive direction, it can thus be appreciated that the grid route sequence of highway is G={ g1,g2,
g3,…,gn, g thereiniFor a road grid, whole raster combineds is a highway route.
Step 2 obtains the base station information data that expressway nearby monitors region, then establishes base station and super expressway grid
Match information table B_G, the match information table of base station and road includes base station location area number LAI, base station cell number CI, base
The longitude LNG to stand, the latitude LAC of base station, place grid number GD, matched road grid number GS.Wherein base station and road
The matching step of grid is as follows：
Step 2.1, according to the base station information table near expressway, can obtain base station grid sequence according to the grid processing of step 1
It is classified as B={ b1,b2,b3,…,bn}。
Step 2.2 obtains base station b according to the coverage area of base stationiRoad grid { the g of coveringn,…,gm, then basis
Euclidean distance formula DbigiCalculation base station biThe each road grid g included to itiDistance, be expressed as Dbg={ dn,…,
dm}。
Step 2.3 takes DbgThe minimum grid of middle distance is set to matched road grid G Si, step 2.1~2.3 are repeated, most
The match information table B_G of base station road is understood afterwards.
Step 3, all user mobile phone signaling track datas in the highw ay m onitoring region of acquisition T to T+t times, user
Mobile phone signaling data mainly includes unique ID, signaling data position area number LAI, base station cell number CI and timestamp
TimeStamp fields.Then the data predictions such as dirty data filtering, ping-pong are carried out to signaling data；Finally according to signaling
The timestamp sequencing of data is combined arrangement to the signaling track data of each user, obtains the user of monitoring time section
Mobile phone signaling data track set U_D.
Step 4 carries out height according to the match information table B_G of user mobile phone signaling data track set U_D and base station road
The matching judgement of fast highway user according to longest one of user mobile phone signaling data track section of effectively going on a journey, judges user
Whether be running on expressway user, and generate for calculate highway each road grid velocity highway
Subscriber signaling data track set H_D.Specific steps are as follows：
Step 4.1, the user trajectory of extraction mobile phone signaling data track set U_D carry out the segmentation of effectively trip section, take
The longest sequence of trip section sequence, which is used as, judges sequence.
Step 4.2 obtains longest effective trip section track sets Trace={ bn,…,bm(wherein, biRepresent base station
Grid serial number, sequencing arrangement temporally), according to N number of base station of Trace track sets, count b in Trace sequencesi
The base station number N being present in the match information table B_G of base station road1, calculate Trace tracks and the match information of base station road
Similarity λ=N of table B_G1/ N sets a threshold value M, as λ >=M, is then determined as height to determine whether for highway user
Fast highway user simultaneously jumps to step 4.3；Otherwise it is determined as non-freeway user.
Step 4.3, according to the grid serial number of track sets in Trace { n ..., m } be incremented by and successively decrease determine public affairs at a high speed
The forward travel and backward going of road user is then forward travel if it is being incremented by, otherwise backward going.By judging, finally
Obtain highway user signaling data track set H_D.
Step 5, the average speed that highway grid section is carried out according to highway user signaling data track set H_D
Degree calculates.The track sets of each user are extracted from the set H_D of highway user signaling data track, are then traversed two-by-two
Tracing point in the track sets of each user, tracing point is base sites, include in the signaling data of base station timestamp and
Geographical location information, as the computing unit of a calculating speed, is then calculated using in user trajectory sequence per tracing point two-by-two
Each path distance of unit and distance time, with the ratio of path distance and distance time multiplied by anti-with path distance with one
Relevant Gauss weight function obtains the velocity amplitude of a Weighted distance, and is put into corresponding road grid velocity container,
Finally the velocity amplitude in road grid velocity container is carried out and operation obtains the average speed value of the road grid.It is specific
Step is as follows：
Step 5.1 sets corresponding speed container for each road grid, for preserve it is that each computing unit obtains plus
Weigh velocity amplitude.
User trajectory sequence in step 5.2, order traversal extraction highway user signaling data track set H_D, so
The tracing point of sequence traverse user track sets two-by-two afterwards, with per tracing point Trace two-by-twonAnd TracemIt is calculated as one single
Member then according to the matched geographical grid system in base station in step 1 and road grid, obtains two tracing point TracenWith
TracemBetween road grid subsequence { gn[an,bn],…,gm[am,bm], wherein [an,bn] represent grid positions serial number, then
Two tracing point TracenAnd TracemDistance Dn,mIt can be calculated by equation below：
The number of road grids of the wherein M between two tracing points, L are the length of road grid.
Step 5.3 calculates tracing point TracenAnd TracemBetween journey time, if tracing point TracenTimestamp
For TimeStampn, tracing point TracemTimestamp be TimeStampm, then the journey time between two tracing points is Tn,m。
Tn,m=TimeStampn-TimeStampm
Step 5.4, the thought according to physical motion, by being understood in the angle of statistical significance comprising road grid
The path distance of two tracing point computing units is shorter, then bigger to the contribution margin of the road grid average speed.According to this feature,
Set a Gauss weight function with path distance inverse correlation
Step 5.5, the weighting velocity amplitude for calculating two tracing point computing units, by the distance between two tracing points that are calculated
Distance Dn,mWith distance time Tn,mRatio multiplied by with Gauss weight functionObtain the weighting velocity amplitude of the computing unit
And by the velocity amplitudeIt is put into the corresponding road grid velocity container between two tracing points.
Step 5.6 repeats step 5.2~5.5, until the highway user signaling data track collection of T to T+t periods
It closes user trajectory sequence in H_D and all traverses completion.
Step 5.7 finally traverses weighting sets of speeds in each road grid velocity container, in each road grid
Speed collection carry out and operation obtain the average speed value V of the road gridk(1≤k≤N)。
Wherein l is expressed as l-th of subscriber signaling in k-th of section, NkRepresent the number of users in k-th of section,Represent the
N section is to the distance (1≤k≤N in m-th of sectionk),Represent n-th of section to m-th of section time (1≤l≤
Nk)。
Fig. 2 is the circuit mapping graph of highway geography grid system；Fig. 3 includes a section grid not for expressway
With the user trajectory figure of path length.
Finally illustrate, preferred embodiment above is merely illustrative of the technical solution of the present invention and unrestricted, although logical
It crosses above preferred embodiment the present invention is described in detail, however, those skilled in the art should understand that, can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (2)
1. a kind of vehicle on highway speed calculation method based on mobile phone signaling big data, it is characterised in that：This method step
For：
S1：The step of vehicle on highway speed calculates is carried out according to based on mobile phone signaling data, carries out mobile phone signaling data
Collecting and dealing；Then map match is carried out, establishes geographical grid system；Then highway user identification is carried out, is used
In the highway user signaling data track set H_D for calculating expressway road grid average speed；
S2：After the highway user signaling data track set H_D for obtaining T to the T+t periods, order traversal highway user
Signaling data track set H_D extracts the track sets of each user；
S3：Traversed the tracing point in the track sets of each user two-by-two to each user's sequence, tracing point is base station
Point includes timestamp and geographical location information in the signaling data of base station, to make in user trajectory sequence per tracing point two-by-two
Computing unit for a calculating user velocity；
S4：According to the road grid that geographical grid system divides, corresponding speed container is set for each road grid, for protecting
Deposit the weighting velocity amplitude that each computing unit obtains；
S5：According to the computing unit that traversal obtains, it is defined as tracing point TracenWith tracing point Tracem, calculate each unit
Path distance and distance time；
S6：According to the thought of physical motion, by obtaining feature in the angle of statistical significance：Include two rails of a road grid
The path distance of mark point computing unit is shorter, then bigger to the contribution margin of the road grid average speed；According to this feature, setting
One with the Gauss weight function of path distance inverse correlation
S7：The weighting velocity amplitude of two tracing point computing units is calculated, by the path distance D between two tracing points that are calculatedn,mWith
Distance time Tn,mRatio multiplied by with Gauss weight functionObtain the weighting velocity amplitude of the computing unitAnd by the speed
Angle valueIt is put into the corresponding road grid velocity container between two tracing points,
S8：Step S2~S7 is repeated, until user in the highway user signaling data track set H_D of T to T+t periods
Track sets all traverse completion；
S9：The weighting sets of speeds in each road grid velocity container is finally traversed, to the weighting speed in each road grid
Degree set carries out and operation obtains the average speed value V of the road gridk, 1≤k≤N,
Wherein l is expressed as l-th of subscriber signaling in k-th of section, NkRepresent the number of users in k-th of section,Represent n-th of tunnel
Section to m-th of section distance, 1≤k≤Nk,Represent n-th of section to the time in m-th of section, 1≤l≤Nk。
2. a kind of vehicle on highway speed calculation method based on mobile phone signaling big data according to claim 1,
It is characterized in that：The step S5 is specially：
S501：The tracing point of sequence traverse user track sets two-by-two, with per tracing point Trace two-by-twonAnd TracemAs one
Computing unit then according to the matched geographical grid system in base station in step S1 and road grid, obtains two tracing points
TracenAnd TracemBetween road grid subsequence { gn[an,bn],…,gm[am,bm], wherein [an,bn] represent grid positions
Serial number, then two tracing point TracenAnd TracemDistance Dn,mIt is calculated by equation below：
The number of road grids of the wherein M between two tracing points, L are the length of road grid；
S502：Calculate tracing point TracenAnd TracemBetween journey time, if tracing point TracenTimestamp be
TimeStampn, tracing point TracemTimestamp be TimeStampm, then the journey time between two tracing points is Tn,m；
Tn,m=TimeStampn-TimeStampm。
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| CN110708664A (en) * | 2019-10-11 | 2020-01-17 | 同帅科技（天津）有限公司 | Traffic flow sensing method and device, computer storage medium and electronic equipment |
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| CN113205700A (en) * | 2021-03-26 | 2021-08-03 | 福建新大陆软件工程有限公司 | High-speed vehicle position identification method based on mobile phone signaling road network matching |
| CN113487865A (en) * | 2021-07-02 | 2021-10-08 | 江西锦路科技开发有限公司 | System and method for acquiring information of vehicles running on highway |
| CN113487865B (en) * | 2021-07-02 | 2022-07-22 | 江西锦路科技开发有限公司 | System and method for acquiring information of vehicles running on highway |
| CN114333323A (en) * | 2022-01-05 | 2022-04-12 | 北京航空航天大学合肥创新研究院(北京航空航天大学合肥研究生院) | Highway travel speed prediction method based on pressure characteristics |
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