CN106568456A - Non-stop toll collection method based on GPS/Beidou positioning and cloud computing platform - Google Patents
Non-stop toll collection method based on GPS/Beidou positioning and cloud computing platform Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
Abstract
The invention discloses a non-stop toll collection method based on GPS/Beidou positioning and a cloud computing platform, and belongs to the field of electronic information. According to the method, a GPS tracing point is taken as the center of a circle to choose section collection belonged to the circle, and the section collection is taken as the chosen route. Direction constraint conditions are added to carry out common constraint, and a method is provided for judging the direction. A up-going/down-going judgmental algorithm based on route turning points is provided for judging the direction. The selection of final matched route is based on a trajectory coefficient similarity algorithm of Euclidean distance. The vehicle monitoring becomes automatic and is simplified based on the optimization of running track, alternative routes, and final matched route.
Description
Technical field
The invention belongs to electronic information field, be it is a kind of based on GPS/ Big Dippeves positioning and cloud computing platform, be applied to highway,
The autoelectrinic charging method of tunnel and large bridge.
Background technology
ETC (Electronic Toll Collection, E-payment system) technology depends on the Internet as shown in Figure 1
Information of vehicles is uploaded to into application database by work station in the way of image or mobile key in real time.Traditional ETC technologies are deposited
Recognition speed is slow, high installation cost and the problems such as difficult operation maintenance, and some charge station's remote locations, ETC hardware set
It is standby to be difficult to install and safeguard.Occur in recent years based on GPS, BEI-DOU position system E-payment system of new generation progressively
Development, route and distance that it is travelled by satellite fix registration of vehicle calculate automatically and deduct road expense, effectively solve
The drawbacks of above-mentioned traditional ETC technologies of having determined are present.Meanwhile, the development of the technology such as mobile interchange Network Communication, car networking and GIS,
To provide corresponding technology place mat based on the no-stop charging system of the GPS/ Big Dippeves and cloud computing platform.
The content of the invention
The shortcoming that the present invention is present for tradition ETC, devises the not parking receipts based on the GPS/ Big Dippeves and cloud computing platform
Charge system.System is constituted by on-vehicle positioning terminal, based on GIS and cloud platform non-parking charge software.Wherein on-vehicle positioning terminal
The vehicle GPS data of Real-time Collection are returned to by 3G/4G wireless networks by Cloud Server system by gps satellite/Big Dipper positioning
System.Not parking receipt and payment software includes that path determination strategy, vehicle positioning business and expense clearing operation that system is related to are carried out
Description, groundwork involved in the present invention are as follows：
(1) as shown in Fig. 2 devising the ETC system frame of integrated mobile Internet, GPS/ Big Dippeves positioning, GIS and cloud platform
Structure.
(2) in order that the vehicle GPS data with certain error can accurately be corrected to correct travel road in GIS
Lu Zhong, designs and Path Matching Algorithm of the application based on GPS/ Big Dippeves track.
(3) devise the vehicle positioning operation flow based on GIS.
(4) devise high in the clouds and flow process is cleared based on GIS no-stop charging systems expense.
Core algorithm based on the GPS/ Big Dippeves and the no-stop charging system of cloud computing platform is as follows：
Typical GPS/ Big Dipper motion car datas are a series of orderly GPS track points comprising vehicle latitude and longitude information, main
It is used to determine current vehicle position in real time.Rely solely on GPS/ big-dipper satellites positioning
, its precision easily receives external environment to be affected and produces error.In the crossing section shown in Fig. 3, A, B, C, D point
Not Wei section node, the solid line line segment that they are formed by connecting represents path locus；GPS1～GPS4Vehicle GPS collection point is followed successively by,
The dashed line segment that they are formed by connecting is vehicle driving trace.Assume GPS track point GPS1～GPS3Road can be uniquely matched
On section AB, but when B points, candidate match section is caused to increase due to the appearance of fork in the road, and GPS4To section BC and road
The distance of section BD is almost equal, and at this moment general matching algorithm is difficult to the follow-up running section for correctly judging vehicle, and this problem claims
For Y-junction problems.
If occurring above road misjudgment in the present system, the normal operation of Fare Collection System can be had a strong impact on.So
The present invention on the basis of former achievements improves and combines the alternative path set algorithm based on traffic limitation condition and be based on
The broken line similarity algorithm of editor's cost, realizes a kind of Path Matching Algorithm based on GPS track, by the GPS that will be gathered
Tracing point is screened and is matched with the path locus around which, is finally accurately judged to vehicle actual travel road, to guarantee
The normal operation of system.
Inventive algorithm using vehicle GPS sampling point set and path locus point set as master data, through three step realities
The accurate judgement of existing real vehicles travel, comprises the following steps that shown：
(1) search for alternative path collection
Vehicle driving trace is depicted according to continuous vehicle GPS collection point, with GPSiFor the center of circle, its pre-set radius is searched for
Interior all possible travel, constitutes alternative path collection RCi；
(2) screen alternative path collection
Limited with based on road network geometry connectedness by actual driving, calculate RCiWith each stage overall path PiIt is follow-up can
Walking along the street section collection PNiCommon factor Rinsect(i).And by RinsectI () updates and recombinates alternative overall path collection Pi+1。
(3) choose final matching path
All tracing points are traveled through successively, calculate path and GPS track path in P respectively using the thought of relative editor's cost
Similarity r, r values the maximum be then considered as it is closest with real road track, and as final matching path.
Although the geometry of wheelpath and its travel track is closely, as sampling site method is different, lead
The two is caused to distinguish with obvious characteristic.
First, the two sampling site dense degree is different.Tracks are to be drawn to form by artificial sampling site, institute's collection road circuit node
Among being evenly distributed on track；Wheelpath is obtained by on-vehicle positioning terminal Real-time Collection, if vehicle low running speed or quiet
Only, then the GPS track point in this time occurs the situation that aggregation even overlaps.
Secondly, the two sampled point meaning is different.The sampled point of tracks is road key node, mostly changes track
The key node in direction, although rare, but can simply draw out whole piece tracks；And track of vehicle is in intensive shape,
Multiple GPS gathers points are usually contained in one section of driving trace for tending to straight line, wherein most of sampled points do not change traveling rail
Mark direction, such point is for the selection of path set and path locus similarity comparison have no effect hereinafter.
So, this algorithm needs vehicle GPS driving trace is carried out simplifying process, removes invalid sampled point, only retains energy
Substantially change course bearing and equally distributed sampled point, as shown in Figure 4.
Hypothesis defines minimum steering angle λ for 30 °, and the weights of minimum sampled distance interval η are 3, before and after certain node
Section corner is more than λ and away from when nodal distance interval is more than η before and after which, then be referred to as key point.For track TR=in figure
p1p2p3p4p5p6p7p8, only p3、p4And p5Corner be more than λ, and the weights of sampled point distance are more than η before and after which, then by p3、
p4And p5Add key node collection.Further, since p1And p7Respectively track initial point and end point, so being also required to be added
Enter crucial set of node.Finally, set of node is pressed into node ID sequence, in obtaining figure, vehicle is simplified by what key node was formed by connecting
Driving trace TRkey=p1p3p4p5p7。
The value principle of λ and η should be consistent with road flex point sampling site practical situation, so could make driving rail to greatest extent
Mark is approximate with tracks.And shown in the computational methods such as formula (1-1) of the direction of motion changing value θ of tracing point p：
WhereinFor pi-1With piVector between point, andWherein pI, x、
pI, yWith pI-1, x、pi-1,yIt is tracing point p respectivelyiAnd pi-1Coordinate.
The determination of alternative path collection
Vehicle GPS positioning there is error in the case of, GIS describe wheelpath it is possible that skew, such as Fig. 5 institutes
Show.In figure, real segment is section track, and phantom line segments are the driving trace that each vehicle GPS tracing point is connected in sequence.
Each tracing point can cover different sections, such as GPS in certain limit radius1Point is in search_scop
The section covered in radius is a, d, f, and GPS2The covered section of point is a, b, c.Then it can be said that scanning in system
GPS1During point, section a, d, f are GPS1The alternative path collection of point.In the same manner, section a, b, c is GPS2Alternative path collection, section
B, e, g are GPS3The alternative path collection of point.For each GPS track point pi, all geometry connections in position error area by which
Section collection is designated as R (pi)。
Wherein, the value of radius Search_scop becomes according to each section load conditions, but should follow following principle：One
It is maximum error value that search radius Search_scop should be greater than GPS device positioning precision, in case actual travel road is divided
To outside search radius；Two is that search radius should cover current GPS point and close on track, in case search radius are too small to cause basic number
According to very few.
The screening of alternative path collection
In the Expressway Road net of reality, also include that direction of traffic limits, exceeds the speed limit except the geometry of road is connective
The driving restrictive conditions such as restriction, vehicle restriction.
As GPS track point piAlternative path collection R (pi) after determination, it is necessary to driven a vehicle restrictive condition according to the above
From the path of all geometry connections of vehicle periphery, current generation possible alternative path is filtered out.And each GPS is traveled through successively
Positioning track point pi, respectively the selection result of last time is screened and is updated, finally given all alternative path collection.
For example in the road conditions shown in Fig. 4, for being in GPS1The vehicle of point, its alternative path integrate as R (pi), and now
The geometry communication path for this road network recorded in data base includes a, d and f, and is limited according to the travel direction in each section,
The actual travel direction of vehicle is only limited with the direction in a sections and is consistent, i.e. the subsequent path collection in the path only has a, and by R (pi)
The subsequent path collection obtained after driving limits screening is designated as NR (pi)。
Use Ti(topo) R (p are representedi) (topological constraints condition is the definition node and road of specification for the topological constraints condition in section
Road path), use Ti(dirc) R (p are representedi) section direction constraints, then R (pi) direct later section collection NR
(pi) computational methods such as formula (1-2) shown in：
NR(pi)={ Rj∈R(pi)|Ti(topo)∩Ti(dirc)} (1-2)
If i=0, current point is initial track point, if R is (p0) element number be k, initialize k bar geometry access
Footpath collection, overall alternative path collection R (pathi)；If i ≠ 0, current point is intermediate trace points, calculates R (pi) with R on last stage
(pi-1) direct later section collection R (pi-1) common factor Rinsect(i)；If RinsectI () is sky, current path R (i) is nothing
Effect path, which is concentrated from current generation geometry communication path and is deleted；If RinsectI () has and only one section, then update and work as
Last stage subsequent path collection R (pi) and R (pathi)；If RinsectI () includes m bars section, then by R (pathi) replicate split into m
Bar totality alternative path, RinsectJ () (j ∈ [1, m]) is used as RinsectThe last item section of (j), at the same update its it is direct after
Continuous feasible path collection.
Finally, after the completion of the judgement of all GPS track points, you can obtain final entirety alternative path collection R (path).
Direction of traffic judges
It is noted that in all drivings are limited, the restrictive condition such as geometry connectedness, rate limitation, vehicle restriction
Can be judged according to the nodal community stored in data base, and the judgement of direction of traffic restrictive condition is Comparatively speaking complex.
The present invention proposes a kind of up-downgoing evaluation algorithm based on circuit flex point.Description road shape is stored in data base
Section node, can wherein be determined that the point in road driving direction becomes road flex point.Can be accurately using road flex point
Judge travel direction of the vehicle between two flex points, and what the travel direction of road flex point was to determine, such that it is able to judge vehicle
Relative to the travel direction in whole piece section.
Because it be all a little circuit flex point that algorithm takes, i.e., between two flex points, line segment is straight-line segment, so can be considered that algorithm makes
Straight line situation is with scene.All possible four kinds of circuit models as shown in Figure 6 are listed, and vehicle are represented respectively in t1、t2Moment
The relative position situation of four kinds of vehicles and flex point on two flex point circuits.Wherein, S1、S2For circuit flex point, P1、P2For vehicle
In t1And t2GPS track point before and after in time, and with the direction of arrow as up direction.
It is seen that situation one be vehicle front and back position in S1Before point；Situation two, vehicle front and back position are located at
Between two flex points；Situation three, vehicle front and back position is in S2After point；Situation four, although vehicle front and back position is between two points,
Direction is contrary with situation two.
After it is determined that vehicle belongs to above-mentioned four kinds of situations, can according to vehicle front and back position respectively two flex point of distance away from
Travel direction is judged from change.By taking situation one as an example, as shown in fig. 7, working as P cars from t1Moment drives to t2Moment, for S1Stand
Point distance change amount be：△ L=p1s1-p2s1, P cars are for S2Website distance change amount is：△ L '=p1s2-p2s2。
If △ is L<0 and △ L '>0, then may determine that P cars are away from S1Stand and close S2Stand, travel direction is S1Extremely
S2；Otherwise then it is proximate to S1Stand and away from S2Stand, travel direction is S2To S1.Thus, just understand vehicle relative to this section of section
Travel direction, if direction of traffic is consistent with the direction in section in data base, illustrates that the car meets section direction of traffic and limits bar
Part, and this section is added into follow-up planning driving path collection NR (pi) in；Otherwise then illustrate that direction of traffic is violated section direction and limits bar
Part, this section should be from alternative path collection R (pi) middle deletion.
The selection in final matching path
Final alternative path collection NR (p are obtained after all GPS track points have been traveled throughn), NR (pi) may include one or
Mulitpath, and they are consistent with the traffic limitation condition of wheelpath, but wherein only have a paths to be vehicle reality
Driving path.Now need to be contrasted with each bar alternative path track according to traffic route track, so as to obtain similarity most
High path is used as final matching path.
For track similarity contrast method, a kind of existing similarity of paths determination methods based on curve similarity,
But the method requires coordinate system unification, and the change of the distance between curve can affect that final Similarity value ScoreSim's is big
It is little.But real road mostly is the sparse track is formed by connecting by short straight line section, rather than the curve of curvature even variation, so document
The method for being adopted is not particularly suited for the path locus in the actual road conditions studied by this problem and compares.
Another kind of existing algorithm take into account the sparse features of wheelpath, it is proposed that a kind of based on Euclidean distance
Sparse track Similarity measures, by editing distance (minimum editor's number of times needed for being changed into another kind of track from a kind of track), thought should
Among using track Similarity measures, that is, calculate from track P and be edited into editor's cost that track Q is spent, cost value is less, then
The similarity of two sparse tracks is higher.But the method only accounts for the absolute Euclidean distance between two tracks, not by two tracks
The coordinate system of corresponding point is mutually unified, and have ignored the relative editor's cost between two track corresponding point.If such as between two tracks
There is another interference track, its editor's cost is less than the cost of desired trajectory forever, so as to cause misjudgment.
So this algorithm is improved to existing algorithm, it is proposed that the relative Euclidean distance computational methods of unified coordinate system,
By the coordinate offset amount of tracing point before and after calculating track Q, track P is carried out into corresponding trajectory displacement, to realize track line segment
Coordinate unification, the Euclidean distance for so calculating is exactly relative, it is to avoid the error in existing computational methods.
And the computational methods of Euclidean distance are to represent the coordinate vector of the track identical dimensional of mobile object, then calculate
Each when engrave correspondence two tracing points between Euclidean distance, synthesis is carried out to these distances then, you can obtain track
Between Euclidean distance.For example, in two-dimensional space, the Euclidean distance computational methods between two tracks of R, S are shown in formula (1-3)：
In formula,Sampling numbers of the k for track R, S, E (R, S) is
Euclidean distance between them；ri、siI-th locus of points point, r are represented respectivelyi,x、ri,yWith si,x、si,yRepresent respectively respective x,
Y-coordinate, distance represent tracing point riAnd siEuclidean distance.
For the track of vehicle of process is simplified in track, first by its each key point coordinate sequence, sequence P is constituted；Will row
The trajectory coordinates serializing of circuit is sailed, sequence Q is constituted.If m, n are respectively the length of P, Q, piFor i-th element of P, qiFor sequence
I-th element of row Q, qi' for i-th element being transformed in sequence Q under P coordinate systems.Sequence Q is converted in sequence of calculation P
Relative Euclidean distance during, on the basis of sequence Q, make P to Q operational transformations.P, Q track schematic diagram is as shown in Figure 8.
Calculation procedure in detail is as follows：
(1) calculate transition deviation amount
Want to calculate relative editor's cost of B to E, it is necessary to which E points are updated in the coordinate system of track P.Firstly the need of
X, the Y-coordinate side-play amount of starting point D to E are calculated respectively, and wherein O is origin system, as shown in formula (1-4), (1-5)：
(2) coordinate is replaced
A is moved to into E ' according to the side-play amount that the first step is calculated, as positions of the track Q under the P coordinate systems of track, E ' coordinates
Computational methods are shown in formula (1-6), (1-7)：
substitute(pi,x,qi,x)=pi-1,x+der(qi,x) (1-6)
substitute(pi,y,qi,y)=pi-1,y+der(qi,y) (1-7)
(3) calculate Euclidean distance
Now the E points in the Q of track be regarded as by having been converted into the coordinate system of track P, the geometric distance of B to E ' and edit B
To relative editor's cost of E ', formula (1-8) is seen：
Wherein, | pi-qi' | for the Euclidean distance between two coordinate points, (Euclidean distance in two and three dimensions space is exactly
Actual range between 2 points).And the editor's cost between two tracks is then each point editor's cost sum, formula (1-9) is seen：
When the editor's cost between two sparse tracks is bigger, then representing needs more edit operations realize two
Conversion between track, also just illustrates that the similarity between two tracks is less；Otherwise then illustrate that the similarity between two tracks is bigger.
Successively by vehicle driving trace A, and final alternative path collection NR (pn) in track point coordinates corresponding to the B of path substitute into formula
(1-9) and obtain the Similarity value Similartiy (A, B) of each path locusi, its intermediate value the maximum is finally selected as final
Matching path.
(4) devise the vehicle positioning operation flow based on GIS：
Gps data collection towards on-vehicle positioning terminal as shown in Figure 9 is mainly watched by on-vehicle positioning terminal with storing process
Take module to complete, gps data is transmitted to gps data module and GIS servos respectively as the terminal of gps data transmission for it
Module.Cloud server system can send control message to on-vehicle positioning terminal by servo module according to user's request first.When
On-vehicle positioning terminal carries out corresponding control operation after receiving control message.Secondly, the vehicle GPS data of Real-time Collection are passed through
3G/4G wireless networks return to cloud server system.In this transmit process, server is constantly in listening state, waits car
Carry the data-message of positioning terminal.After data-message is received, GPS message can be sent to gps data by Cloud Server simultaneously
Module and GIS servo modules.Real-time GPS data is serialized by the matching process towards GIS, and is supplied to GIS loadings and is emulated.
GIS servo modules wait the gps data through parsing of on-vehicle positioning terminal servo module transmission.Server is according to vehicle coordinate
Vehicle periphery road net data is searched in Traffic network database, which is serialized together with vehicle driving trace gps data, is then subsequently loaded into
In GIS, and through the screening and editor's cost calculating of the Path Matching Algorithm based on GPS track described above, obtain road
Footpath matching result.Last GIS servo modules also need to for matching result to be forwarded to clearance module, and last charging knot is carried out for which
Calculate work.
(5) clear block process：
Matching result is read by clearance module first as shown in Figure 10, and is inquired about in road net data table according to road section ID
" whether charging " attribute, if toll road, illustrates that vehicle does not also sail out of charging section, continues to subsequent match result.Such as
Fruit is non-charging section, and clearing module needs to pay button log according to vehicle ID enquiring vehicles, and at this moment vehicle is likely to be at two kinds
Among situation：If last time is silent on vehicle in recording and sails record into, represent vehicle and be also introduced into the toll road, this
When should by vehicle ID, road section ID and sail into the time record；If last time has been recorded the car in recording and sailed record into, car is represented
Pass through toll road and sail out of, at this moment clear module should will be vehicle time of departure information record on record, and according to car
Type and corresponding section expenses standard carry out corresponding charging to driver personal account and pay button work.Realized with this
System is for the account settlement business of driving vehicle.
Invention effect
Building based on the GPS/ Big Dippeves and cloud computing platform is supported by mobile Internet mechanics of communication, the system is achievable
The automatization of road vehicle supervision, simplification under the optimization of wheelpath, alternative path and final matching path.Institute of the present invention
The no-stop charging system based on the GPS/ Big Dippeves and cloud computing platform of research provides one for the information system management of public transport
Set total solution, improves the intelligent level and work efficiency of road supervision, the method for designing of the system and
The development that the technology employed in process is realized also for intelligent transportation system provides certain new thinking.
1. the determination of selected path set：Prior art：Directly describe wheelpath with GPS location and then GIS
Innovatory algorithm：The section collection that choosing belongs to this circle is enclosed by the center of circle of GPS track point, as selected path.
2. the screening of selected path set：Prior art：Selected path set is reduced according only to topological constraints condition.
Innovatory algorithm：Add direction constraints to constrain jointly, and propose how to judge direction.
3. direction of traffic judges：A kind of up-downgoing evaluation algorithm based on circuit flex point is proposed, to judge direction.
4. the selection in final matching path：Prior art：(1) the similarity of paths determination methods based on curve similarity.
(2) the coefficient locus Similarity Algorithm based on Euclidean distance.
Innovatory algorithm：Rear improvement is combined based on existing two technologies：The relative Euclidean distance algorithm of unified coordinate system.
Description of the drawings
Fig. 1 tradition ETC technological frame figures.
The system architecture diagram of Fig. 2 present invention.
Fig. 3 Y-junction crossings schematic diagrams of the present invention.
Fig. 4 simplifies schematic diagram in track of the present invention.
Fig. 5 route matching schematic diagrams of the present invention.
Several relative position situations of Fig. 6 present invention.
Fig. 7 linear road travel directions of the present invention judge schematic diagram.
Fig. 8 P, Q track schematic diagrams of the present invention.
Vehicle positioning business process map of Fig. 9 present invention based on GIS.
Figure 10 clearing operation flow charts of the present invention.
Specific embodiment
The present invention adopts and scheme is implemented as follows：
As shown in Fig. 2 system architecture diagrams, system realize process mainly comprising collection, transmission, matching and settle accounts four ranks
Section, corresponds respectively to GPS/ Big Dipper data acquisitions, data transfer and parsing, route matching and the driver of on-vehicle positioning terminal
The charge clearing of account.
(1) gather：The on-vehicle positioning terminal being deployed on actual travel vehicle, is the data acquisition platform of system, mainly
Responsible collection vehicle real time GPS/Big Dipper data.
(2) transmit：The transmission of data relies primarily on the 3G/4G modules of on-vehicle positioning terminal and completes, the module by gather
Data are packaged into the message with certain format with vehicle identification information, and are passed through 3G/4G network transmissions to cloud platform clothes
Business device system.
(3) match：When server system receive on-vehicle positioning terminal collection vehicle GPS data after, need by its with
The pre-loaded road net data in GIS is matched, and corrects track of vehicle by Path Matching Algorithm, so as to find vehicle reality
Border driving path.
(4) settle accounts：According to the matching result of GIS, server system starts to call settlement module, with reference to information of vehicles and road
Section expenses standard carries out corresponding charge accounting work to vehicle driver's personal account.
Claims (5)
1. based on GPS/ Big Dippeves positioning and the non-stop charging method of cloud computing platform, it is characterised in that：
System includes the ETC of integrated mobile Internet, GPS/ Big Dippeves positioning, GIS and cloud platform；
Shown in comprising the following steps that：
(1) search for alternative path collection
Vehicle driving trace is depicted according to continuous vehicle GPS collection point, with GPSiFor the center of circle, search in its pre-set radius
All possible travel, constitutes alternative path collection RCi；
(2) screen alternative path collection
Limited with based on road network geometry connectedness by actual driving, calculate RCiWith each stage overall path PiLater road
Section collection PNiCommon factor Rinsect(i)；And by RinsectI () updates and recombinates alternative overall path collection Pi+1；
(3) choose final matching path
All tracing points are traveled through successively, calculate the phase in path and GPS track path in P respectively using the thought of relative editor's cost
Like degree r, r values the maximum be then considered as it is closest with real road track, and as final matching path.
2. method according to claim 1, it is characterised in that：
Hypothesis defines minimum steering angle λ for 30 °, and before and after certain node, section corner is more than λ, by p3、p4And p5Add crucial
Set of node；Track initial point and end point are also required to be added into key node collection；Finally, set of node is pressed into node ID row
Sequence, obtains simplifying vehicle driving trace by what key node was formed by connecting.
3. method according to claim 1, it is characterised in that：
For each GPS track point pi, the section collection of its all geometry connection in position error area is designated as into R (pi)；
The value of the search radius Search_scop of alternative path should follow following principle：One is that search radius Search_scop should
More than the maximum error value of GPS device positioning precision；Two is that search radius should cover current GPS point and close on track；
As GPS track point piAlternative path collection R (pi) after determination, it is necessary to according to driving restrictive condition from vehicle periphery institute
In having the path of geometry connection, the alternative path of current generation is filtered out；And each GPS location tracing point p is traveled through successivelyi, point
The other the selection result to last time is screened and is updated, and finally gives all alternative path collection.
4. method according to claim 1, it is characterised in that：
The section node of description road shape is stored in data base, can wherein be determined that the point in road driving direction becomes road
Flex point；Travel direction of the vehicle between two flex points is judged using road flex point, so as to judge vehicle relative to whole piece section
Travel direction.
5. method according to claim 1, it is characterised in that：
By the coordinate offset amount of tracing point before and after calculating track Q, track P is carried out into corresponding trajectory displacement, to realize track
The coordinate unification of line segment；And the computational methods of Euclidean distance are by the coordinate vector table of the track identical dimensional of mobile object
The Euclidean distance between two tracing points of correspondence is engraved when showing, then calculating each, synthesis is carried out to these distances then, is obtained
Euclidean distance between track；
For the track of vehicle of process is simplified in track, first by its each key point coordinate sequence, sequence P is constituted；By driving line
The trajectory coordinates serializing on road, constitutes sequence Q；piFor i-th element of P, qiFor i-th element of sequence Q, qi' for sequence Q
In be transformed into i-th element under P coordinate systems；During the relative Euclidean distance that sequence of calculation P is converted to sequence Q, with
On the basis of sequence Q, P is made to Q operational transformations；
Calculation procedure in detail is as follows：
(1) calculate transition deviation amount
Want to calculate relative editor's cost of B to E, it is necessary to which E points are updated in the coordinate system of track P；Firstly the need of respectively
X, the Y-coordinate side-play amount of starting point D to E are calculated, wherein O is origin system, as shown in formula (1-4), (1-5)：
(2) coordinate is replaced
A is moved to into E ' according to the side-play amount that the first step is calculated, used as positions of the track Q under the P coordinate systems of track, E ' coordinates are calculated
Method is shown in formula (1-6), (1-7)：
substitute(pi,x,qi,x)=pi-1,x+der(qi,x) (1-6)
substitute(pi,y,qi,y)=pi-1,y+der(qi,y)
(1-7)
(3) calculate Euclidean distance
Now the E points in the Q of track have been converted into the coordinate system of track P, and the geometric distance of B to E ' regards the phase edited B to E ' as
To editing cost, formula (1-8) is seen：
Wherein, | pi-qi' | for the Euclidean distance between two coordinate points；And the editor's cost between two tracks is then each point editor
Cost sum, is shown in formula (1-9)：
By vehicle driving trace A, and final alternative path collection NR (pn) in track point coordinates corresponding to the B of path substitute into formula (1-
9) and obtain the Similarity value Similartiy (A, B) of each path locusi, its intermediate value the maximum is finally selected as final matching
Path.
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