CN108253974B - Floating Car location data automatic adaptation cushion route matching system and method - Google Patents
Floating Car location data automatic adaptation cushion route matching system and method Download PDFInfo
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Abstract
The present invention discloses Floating Car location data automatic adaptation cushion route matching system, comprising: location data acquiring unit；Electronic map；Traffic network database；Timesharing variable weight heavy-route link library, according to history Floating Car motion track and current current anchor point degree of rarefication dynamic setting link field range, road network is cut according to link field range, and goes out the path that every section reaches another indirectly connected road network in link field according to timesharing category of roads weighted calculation；And route matching unit.Route matching unit includes: historical location data collection acquiring unit, extracts the matched section road net data of multiple buffering ranges with the location data by location data acquiring unit real-time reception from Traffic network database, obtains historical location data collection；First matching unit samples the frequency according to current position determination data and is matched for the first time to historical location data collection；Fitting unit is based on timesharing variable weight heavy-route link library, is fitted correction to obtain final route matching result.
Description
Technical field
The invention belongs to intelligent transportation fields, in particular to are suitble to floating when sample frequency is lower and range of drift is larger
Vehicle location data automatic adaptation cushion route matching system and its Floating Car location data automatic adaptation cushion route matching method.
Background technique
Taxi (Floating Car) installation positioning system (for example, GPS positioning system or BEI-DOU position system etc., below
In be illustrated by taking GPS positioning system as an example) etc. after mobile units, it can be achieved that the traveling floating data of vehicle is passed through channel radio
Letter mode is transmitted to Floating Car information centre in real time, which includes the letter such as vehicle location, time, direction and speed
Breath, is handled using the relevant computation model such as map match, path culculating and algorithm, makes Floating Car position data and city
Road associates over time and space, finally obtains the Vehicle Speed of the passed through road of Floating Car and the row of road
The traffic congestion informations such as vehicle hourage, can wide range of services in each traffic department, such as can be used as traffic police department grasp road it is real-time
Traffic conditions formulate the voucher for alleviating congestion measure, can also provide data basis branch for Urban Traffic Planning, town road construction
Support.
For a long time in outdoor operation, the acquisition and transmission of data are easy by the factors shadow such as region, road conditions, weather taxi
It rings, some such as loss of data, redundancy, mistake and other issues can be generated, in addition each urban taxi is by equipment, operation ring
Border, operational regime etc. influence, and the GPS data upload frequency, position deviation rate are different, how to solve in low frequency time sampling condition
Under, and carrying out map match in the biggish situation of position excursion range is a core problem.
Map match is essentially a kind of correction technique, and core content is with the electronics with network topology structure
Subject to map road network information, the GPS data received is modified by map-matching algorithm[2], the mistake of map match
In terms of poor source is broadly divided into following four: external mutation Error, GPS system internal error, electronic map error and coordinate turn
Change error[3], due to the influence of the above various factors, the precision of map match can be damaged, therefore just need to find a kind of conjunction
Suitable map-matching method fights this trueness error, realizes precisely matching.
Map-matching algorithm can be simply divided into following several at present: simple projected map matching algorithm is based on weight
Topological theory matching algorithm, the map-matching algorithm based on probability statistics principle and dummy differential algorithm.
1) directly sciagraphy only considers the shape in section, distance, by GPS position information, projects to distance in electronic map
Nearest section, if it is in more complicated and dense city road network, the matching efficiency of direct sciagraphy is low, stability and
Self-recision ability is poor.
2) the topology matching algorithm based on weight mainly passes through the position with reference to previous moment vehicle and driving direction, base
In electronic map road network topology structure, candidate road section weight is determined, calculate according to weight coefficient and with reference to history GPS track
This moment final match point out, weight coefficient is determined mainly by experience, and weight coefficient will have a direct impact on map match
Precision.
3) principle and method of the map-matching algorithm based on probability statistics based on probability statistics principle, which constantly recycle, to be compared
The position and candidate roads section position of GPS point, calculate the confidence region of current data point, by comparing, judge in error region
Candidate roads in domain select final matching section and match point, and this algorithm cannot efficiently use vehicle driving history letter
Breath, can not also solve GPS point drifting problem.
4) dummy differential algorithm can carry out the estimation of correction amount under current time state using the correction amount of previous moment
And calculating, the position at current time can obtain pre-matching estimation point with reference to the correction amount of last moment, recycle simple geometry
Pre-matching point is projected on matching road and obtains final true match point by matching principle, and dummy differential algorithm can be certain
Wrong identification ratio is reduced in degree, but operation time can be significantly greatly increased, and to map matching real-time and reliability have centainly
It influences.
Summary of the invention
In view of above-mentioned problems of the prior art, emphasis of the present invention solves multiple in the city with network topology structure
In miscellaneous road network, Floating Car location data sample the frequency it is lower, loss of data, redundancy and error rate are higher, position excursion range compared with
Under big physical condition, traditional map matching process there are matching efficiencies lower, precision is not high and real-time and reliability
The problems such as not strong.
In order to solve the above-mentioned technical problem, Floating Car location data automatic adaptation cushion route matching disclosed by the invention system
System characterized by comprising location data acquiring unit, the location data for the transmission of real-time reception Floating Car client；Electricity
Sub- map, the section road net data including topological structure, and for the matching result that shows paths；Traffic network database will float
The historical location data of vehicle and the matching of the section road net data of the topological structure save；Timesharing variable weight heavy-route link library, root
According to history Floating Car motion track and current anchor point degree of rarefication dynamic setting link field range, according to link field range by road network
It is cut, and goes out every section according to timesharing category of roads weighted calculation and reach another indirectly connected road network in link field
Path；And route matching unit, including historical location data collection acquiring unit, first matching unit and fitting unit, it is described
Historical location data collection acquiring unit is extracted from the Traffic network database and by the location data acquiring unit real-time reception
The matched section road net data of multiple buffering ranges of location data, and then obtain in the extracted section road net data
Historical location data collection, the first matching unit according to current position determination data sample the frequency to the historical location data collection into
The first matching of row, the fitting unit are based on timesharing variable weight heavy-route link library, are fitted correction to first matched result
To obtain final route matching result.
In addition, the Floating Car location data automatic adaptation cushion route matching system, which is characterized in that the positioning number
According to the location data for being certain standard, which includes positioning system latitude and longitude coordinates, time, direction, speed, carrying shape
State attribute；The location data acquiring unit carries out dissection process to the received location data of institute, according to the standard, and to different
Regular data is cleaned.
In addition, the Floating Car location data automatic adaptation cushion route matching system, which is characterized in that in the road network
Each section data are the directive road sections of tool, which is to be defined by two endpoints and have space coordinate
The point set and broken line set of attribute, and each road section includes an intersection or an entrance；The history is fixed
Position data set acquiring unit is extracted and the positioning number by the location data acquiring unit real-time reception from the Traffic network database
According to multiple buffering ranges matched section road net data when, in the positioning number by the location data acquiring unit real-time reception
According to multiple buffering ranges in, the section of intersection is found out from the Traffic network database, positive, reversed and two-way the three of section
Kind situation carries out angle changing rate respectively, and filters out the section not in angular deviation allowed band according to due north angle, thus
Obtain the matched section road network number of multiple buffering ranges with the location data by the location data acquiring unit real-time reception
According to, and then obtain the historical location data collection in the extracted section road net data.
In addition, the Floating Car location data automatic adaptation cushion route matching system, which is characterized in that described first
When sampling the frequency according to current position determination data with unit and being matched for the first time to the historical location data collection, according to working as prelocalization
The time threshold of each calculating cycle is arranged in the data sampling frequency automatically, when reaching time threshold trigger condition, according to buffering
Range is grouped the historical location data collection, and concentrates each history to position number the historical location data of each grouping
According to section data be compared with the section data of preceding several cycle match, remove and the sections of preceding several cycle match do not have
There is the section of topological relation, and ensures that each historical location data only corresponds to a section, it is final to retain and preceding several periods
One group of most historical location data collection of the section quantity that matched section matches, obtains initial matching result.
In addition, the Floating Car location data automatic adaptation cushion route matching system, which is characterized in that the fitting is rectified
Just including: fitting correction for the first time, solving that range of drift is big, turns around to travel matching problem, and by the road under the conditions of simple road network
Duan Jinhang is effectively connected；Second of fitting correction, using positive sequence method, path is connected under the conditions of completing complicated road network, is corrected simultaneously
The error that fitting generates for the first time；Third time fitting correction, is corrected in reparation second of front fit procedure using inverted order method and is produced
Raw error completes route matching.
In order to solve the above-mentioned technical problem, Floating Car location data automatic adaptation cushion route matching side disclosed by the invention
Method characterized by comprising location data obtaining step, the location data for the transmission of real-time reception Floating Car client；Point
Time-varying weight path link library construction step connects according to history Floating Car motion track and current anchor point degree of rarefication dynamic setting
Domain range is connect, is cut road network in Traffic network database according to link field range, and according to timesharing category of roads weighted calculation
Every section reaches the path of another indirectly connected road network in link field out, and the Traffic network database determines the history of Floating Car
Position data and the section road net data of topological structure, which match, to be saved；Route matching step, including historical location data collection obtain step
Suddenly, matching step and fit procedure for the first time, the historical location data collection obtaining step from the Traffic network database extract with by
The matched section road net data of multiple buffering ranges of the location data of the location data obtaining step real-time reception, and then
Historical location data collection onto the extracted section road net data, the first matching step is according to current position determination data
The sampling frequency matches the historical location data collection for the first time, and the fit procedure is connected based on timesharing variable weight heavy-route
Library carries out cubic fit correction to first matched result to obtain final route matching result；And path shows step,
Show paths matching result on electronic map.
In addition, the Floating Car location data automatic adaptation cushion route matching method, which is characterized in that the positioning number
According to the location data for being certain standard, which includes positioning system latitude and longitude coordinates, time, direction, speed, carrying shape
State attribute；The location data obtaining step carries out dissection process to the received location data of institute, according to the standard, and to different
Regular data is cleaned.
In addition, the Floating Car location data automatic adaptation cushion route matching method, which is characterized in that in the road network
Each section data are the directive road sections of tool, which is to be defined by two endpoints and have space coordinate
The point set and broken line set of attribute, and each road section includes an intersection or an entrance；The history is fixed
Position data set obtaining step extracts and the positioning number by the location data obtaining step real-time reception from the Traffic network database
According to multiple buffering ranges matched section road net data when, in the positioning number by the location data obtaining step real-time reception
According to multiple buffering ranges in, the section of intersection is found out from the Traffic network database, positive, reversed and two-way the three of section
Kind situation carries out angle changing rate respectively, and filters out the section not in angular deviation allowed band according to due north angle, thus
Obtain the matched section road network number of multiple buffering ranges with the location data by the location data obtaining step real-time reception
According to, and then obtain the historical location data collection in the extracted section road net data.
In addition, the Floating Car location data automatic adaptation cushion route matching method, which is characterized in that described first
When sampling the frequency according to current position determination data with step and being matched for the first time to the historical location data collection, according to working as prelocalization
The time threshold of each calculating cycle is arranged in the data sampling frequency automatically, when reaching time threshold trigger condition, according to buffering
Range is grouped the historical location data collection, and concentrates each history to position number the historical location data of each grouping
According to section data be compared with the section data of preceding several cycle match, remove and the sections of preceding several cycle match do not have
There is the section of topological relation, and ensures that each historical location data only corresponds to a section, it is final to retain and preceding several periods
One group of most historical location data collection of the section quantity that matched section matches, obtains initial matching result.
In addition, the Floating Car location data automatic adaptation cushion route matching method, which is characterized in that the fitting is rectified
Just including: fitting correction for the first time, solving that range of drift is big, turns around to travel matching problem, and by the road under the conditions of simple road network
Duan Jinhang is effectively connected；Second of fitting correction, using positive sequence method, path is connected under the conditions of completing complicated road network, is corrected simultaneously
The error that fitting generates for the first time；Third time fitting correction, is corrected in reparation second of front fit procedure using inverted order method and is produced
Raw error completes route matching.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below to required in specific embodiment part
The attached drawing used does simple introduction, it is therefore apparent that drawings in the following description are only some embodiments of the invention, for this
For the those of ordinary skill of field, without creative efforts, it can also be obtained according to these attached drawings others
Attached drawing.
Fig. 1 is the Floating Car location data automatic adaptation cushion route matching system for indicating embodiment according to the present invention
Block diagram.
Fig. 2 is route matching in the Floating Car location data automatic adaptation cushion route matching system for indicate above embodiment
The block diagram of unit.
Fig. 3 indicates the stream of the Floating Car location data automatic adaptation cushion route matching method of embodiment according to the present invention
Cheng Tu.
Fig. 4 is route matching in the Floating Car location data automatic adaptation cushion route matching method for indicate above embodiment
The flow chart of step.
Fig. 5 is to indicate to obtain the exemplary diagram with the matched section road net data of multiple buffering ranges.
Fig. 6 is GPS point set electron map distribution map in low frequency time 40 minutes of embodiment.
Fig. 7 indicates situations such as GPS point drift value is larger in above-described embodiment, taxi turns around to travel.
Fig. 8 shows viaducts complicated in Fig. 6 in above-described embodiment.
Fig. 9 indicates first matching result in above-described embodiment.
Figure 10 indicates the partial enlarged view of first matching result in above-described embodiment, and left and right side, which respectively indicates, does not go the same way
The partial enlarged view of section.
Figure 11 indicates first time fitting result in above-described embodiment.
Figure 12 indicates to be fitted the error that insurmountable first matching generates in above-described embodiment for the first time.
Figure 13 indicates to be fitted untreated section for the first time.
Figure 14 indicates second of fitting result in above-described embodiment.
Figure 15 indicates that complicated road network connection is completed in second of fitting in above-described embodiment, but can generate new error.
Figure 16 is to indicate third time fitting result in above-described embodiment.
Figure 17 is that final matching results are added to the effect picture of road network.
Specific embodiment
In the following, illustrating the embodiment of the present invention in greater detail with reference to the attached drawings.The embodiment of the present invention can be deformed into various
Mode, the scope of the present invention should not be construed as limited to examples set forth below.
(embodiment)
Fig. 1 is the Floating Car location data automatic adaptation cushion route matching system indicated according to the preferred embodiment of the present invention
The block diagram of system 100.
As shown in Figure 1, the Floating Car location data automatic adaptation cushion route matching system 100 of first embodiment includes fixed
Position data capture unit 110, electronically Figure 150, Traffic network database 120, timesharing variable weight heavy-route link library 130 and path
With unit 140.
Wherein, location data acquiring unit 110 is used for the location data of real-time reception Floating Car client transmission.This implementation
The location data lattice of the input of 100 pairs of system of Floating Car location data automatic adaptation cushion route matching progress route matchings of mode
Formula has carried out standard definition, which provides foundation for initial data cleaning.Location data standard includes positioning system longitude and latitude
Spend the attributes such as coordinate, time, direction, speed, passenger carrying status.Location data acquiring unit 110 is preferably also to the received positioning of institute
Data carry out dissection process according to the standard, and clean to abnormal data, and valid data are transferred to next processing
Unit.
Electronically Figure 150 includes the section road net data of topological structure, and for show paths matching result and floating
Vehicle motion track.
Traffic network database 120 protects the historical location data of Floating Car and the matching of the section road net data of the topological structure
The dictionary data as spatial match is deposited, can be and convert the section road net data in electronically Figure 150.The road network
Middle each section data are the directive road sections of tool, which is to be defined by two endpoints and there is space to sit
The point set and broken line set of attribute (for example, latitude and longitude coordinates) are marked, and each road section includes an intersection or one
A entrance.Each broken line can calculate a part of due north azimuth as basic attribute data according to coordinate, and foundation is led
Chart draws characteristic, a part that each section has positive, reversed and two-way three kinds of characteristics to be also used as basic data.
Timesharing variable weight heavy-route link library 130 is the base library of route matching fitting, according to history Floating Car motion track
With current anchor point degree of rarefication dynamic setting link field range, road network is cut according to link field range, and according to timesharing
Category of roads weighted calculation goes out the path that every section reaches another indirectly connected road network in link field.
Fig. 2 is route matching in the Floating Car location data automatic adaptation cushion route matching system for indicate above embodiment
The block diagram of unit 140.
Route matching unit 140 includes that historical location data collection acquiring unit 141, first matching unit 142 and fitting are single
Member 143.
Historical location data collection acquiring unit 141 is extracted from the Traffic network database 120 and is obtained with by the location data
The matched section road net data of multiple buffering ranges of the location data of 110 real-time reception of unit, and then obtain extracted institute
State the historical location data collection in the road net data of section.Wherein, the buffering range refers to is with the location data of real-time reception
The range of center certain distance radius, the multiple buffering range refer to multiple and different centered on the location data of real-time reception
The range of distance radius.At this point, historical location data collection acquiring unit 141 is preferably real-time by location data acquiring unit 110
In multiple buffering ranges of received location data, the section of intersection is found out from Traffic network database 120, section forward direction,
Reversed and two-way three kinds of situations carry out angle changing rate respectively, and are filtered out not in angular deviation allowed band according to due north angle
Section, thus as shown in figure 5, obtaining and location data (such as the GPS number by 110 real-time reception of location data acquiring unit
According to) the matched section road net data of multiple buffering ranges, and then obtain the history in extracted section road net data positioning
Data set.
The first matching unit 142 samples the frequency according to current position determination data and carries out just to the historical location data collection
Secondary matching.At this point, the first matching unit 142 preferably samples the frequency according to current position determination data is arranged each calculating week automatically
The time threshold of phase, when reaching time threshold trigger condition, (point set of each calculating cycle cannot be very little, otherwise will affect
With accuracy, such as table 1), starting is by closely depositing filtering to far slowing down.That is, it is preferred that according to the distance centered on current position determination data
The sequence of the ascending buffering range of radius is grouped the historical location data collection, and by the history of each grouping
Location data concentrates the section data of each historical location data and the section data of preceding several cycle match to be compared, remove with
The section of preceding several cycle match does not have the section of topological relation, and ensures that each historical location data only corresponds to a road
Section, it is final to retain one group of most historical location data collection of the section quantity to match with the section of preceding several cycle match, it obtains
To initial matching result.Wherein, the historical location data collection is grouped can not be and is according to current position determination data
The sequence of the ascending buffering range of the distance radius at center can be the descending sequence of the distance radius, or
It is to be carried out according to other rules or random sequence.
1 location data of table samples the frequency and route matching calculating cycle threshold value table
The fitting unit 143 is based on timesharing variable weight heavy-route link library, is fitted correction to first matched result
To obtain final route matching result.The fitting correction preferably includes: fitting correction for the first time, solution range of drift is big, falls
The matching problems such as head traveling, and the redundancy that the section under the conditions of simple road network is effectively connected, but is generated when first matching
Section will not be eliminated, while the interchange overpass under the conditions of complicated road network such as comprising main and side road, ring road can have error of fitting；The
Quadratic fit correction, using positive sequence method, path is connected under the conditions of completing complicated road network, while correcting the mistake that fitting generates for the first time
Difference, second of fitting can equally generate new error；Third time fitting is corrected, and is intended for second using inverted order method correction reparation front
The error generated during closing completes route matching.
Fig. 3 indicates the stream of the Floating Car location data automatic adaptation cushion route matching method of embodiment according to the present invention
Cheng Tu.Fig. 4 indicates path matching step in the Floating Car location data automatic adaptation cushion route matching method of above embodiment
Flow chart.
In the following, illustrating the Floating Car location data automatic adaptation cushion route matching side of present embodiment in conjunction with Fig. 3 and Fig. 4
Method, this method include location data obtaining step S110, timesharing variable weight heavy-route link library construction step S120, route matching step
Rapid S130 and path show step S140.
In location data obtaining step S110, the location data of real-time reception Floating Car client transmission.Furthermore it is preferred that also
To the received location data of institute, dissection process is carried out according to the standard, and clean to abnormal data, and by valid data
It is transferred to next processing unit.
In timesharing variable weight heavy-route link library construction step S120, according to history Floating Car motion track and current anchor point
Degree of rarefication dynamic setting link field range, cuts road network in Traffic network database according to link field range, and according to timesharing
Category of roads weighted calculation goes out the path that every section reaches another indirectly connected road network in link field.Wherein, the road network
In database, the historical location data of Floating Car and the matching of the section road net data of topological structure are saved.
As shown in figure 4, route matching step S130 includes historical location data collection obtaining step S131, first matching step
S132 and fit procedure S133.
The historical location data collection obtaining step S131 is extracted from the Traffic network database and is obtained with by the location data
The matched section road net data of multiple buffering ranges of the location data of unit real-time reception is taken, and then is obtained extracted described
Historical location data collection in the road net data of section.At this point, it is preferred that being extracted from the Traffic network database and by the location data
When the matched section road net data of multiple buffering ranges of the location data of obtaining step real-time reception, by the location data
In multiple buffering ranges of the location data of obtaining step real-time reception, the section of intersection is found out from the Traffic network database,
Positive, reversed and two-way three kinds of situations in section carry out angle changing rate respectively, and are filtered out not according to due north angle in angle
Section in deviation allowed band, thus as shown in figure 5, obtaining and the positioning by the location data obtaining step real-time reception
The matched section road net data of multiple buffering ranges of data, and then obtain the history in the extracted section road net data
Location data collection.
The first matching step S132 samples the frequency according to current position determination data and carries out to the historical location data collection
First matching.At this point, it is preferred that according to current position determination data sample the frequency historical location data collection is matched for the first time when,
The time threshold that each calculating cycle is arranged in the frequency automatically is sampled according to current position determination data, is reaching time threshold trigger condition
When, the historical location data collection is grouped according to the buffering range, and by the historical location data of each grouping
It concentrates the section data of each historical location data and the section data of preceding several cycle match to be compared, removes and preceding several weeks
Phase matched section does not have the section of topological relation, and ensures that each historical location data only corresponds to a section, finally
Retain one group of most historical location data collection of the section quantity to match with the section of preceding several cycle match, obtains initial
With result.
The fit procedure S133 is based on timesharing variable weight heavy-route link library, carries out cubic fit to first matched result
Correction is to obtain final route matching result.The fitting correction preferably includes: fitting correction for the first time solves range of drift
Greatly, turn around the matching problems such as traveling, and the section under the conditions of simple road network is effectively connected；Second of fitting correction, is adopted
With positive sequence method, path is connected under the conditions of completing complicated road network, while correcting the error that fitting generates for the first time；Third time, which is fitted, to be rectified
Just, the error repaired and generated in the fit procedure of second of front is corrected using inverted order method, completes route matching.
Finally, showing step S140 in path, show paths matching result on the electronic map.
Through the above steps, the Floating Car location data automatic adaptation cushion route matching system of present embodiment completes floating
Motor-car travels on Various Complex road network road, such as includes main and side road, overpass, the tubaeform of ring road, diamond shape, alfalfa leaf type
Interchange viaduct, and the exact path under the physical conditions such as GPS point (anchor point) the sampling frequency is low, range of drift is big
Match, can accomplish real-time perception sampling, sample the frequency automatically according to GPS point (anchor point) and degree of rarefication adjustment calculating cycle, do
Taxi run trace is restored to low latency response computation and in electronic map.
<embodiment>
Below with about 40 minutes duration of one group of taxi or so sample frequency lower (40~60 seconds/point) and drift
The calculating process of above embodiment, this sample point are described for the GPS data of shifting range (peak excursion is close to 20 meters) bigger than normal
Distribution such as Fig. 6, including range of drift big data point such as Fig. 7, complicated interchange viaduct such as Fig. 8 in navigation picture.
Firstly, the location data acquiring unit real-time reception of Floating Car location data automatic adaptation cushion route matching system arrives
The laggard rower quasi- neutralizing analysis of GPS point, then carries out road network, in the buffering range of the GPS point, according to the sky improved above
Between object intersection method calculate the section of intersection, and be filtered using forward and reverse and due north angle deviation, obtain the GPS point
After the section set in different buffering ranges, the GPS point gathered into the section is concentrated.
Later, according to the sampling frequency of current GPS adjustment calculating cycle time threshold, (it is 40 that this sample samples the frequency to system
~60 seconds/point, time threshold was automatically regulated to be 5 minutes), starting to remote change by being closely cached after meeting time threshold trigger condition
Filter is grouped GPS point set (each GPS point only corresponds to a section) according to buffering range, and will be described in each grouping
History GPS point concentrates the section data of each history GPS point and the section data of preceding several cycle match to be compared, and removes with before
The section of several cycle match does not have the section of topological relation, and ensures that each history GPS point only corresponds to a section, most
Retain one group of most history GPS point collection of the section quantity to match with the section of preceding several cycle match eventually, obtains initial
With as a result, such as Fig. 9, partial enlargement can see a large amount of parallel section, non-intersecting section, such as Figure 10.
On the basis of first matching result, it is based on timesharing variable weight heavy-route link library, carries out cubic fit correction.First
Secondary fitting can solve the matching problems such as range of drift is big, turns around and be attached simpied method network section, such as Figure 11, but first
The error section that timing generates is still remained such as Figure 12, at the same complicated road network such as main and side road, overhead route and interchange viaduct without
Method connection, such as Figure 13.Complicated road network connection such as Figure 14 is completed in second of fitting, and corrects the error that fitting generates for the first time, together
When can generate new error section such as Figure 15.Error is generated in third time fitting emphasis correction front fit procedure, as a result such as Figure 16,
It is superimposed road network bandwagon effect such as Figure 17, this sample is completed since then from GPS point and collects route matching and track displaying overall process.
Industrial applicibility
Technology disclosed in the present application is suitble to the technical issues of institute's positioning map in need matching of intelligent transportation field, in turn
It is suitably applied various positioning systems, navigation system, in traffic administration monitoring system.
Claims (10)
1. a kind of Floating Car location data automatic adaptation cushion route matching system, which is characterized in that
Include:
Location data acquiring unit, the location data for the transmission of real-time reception Floating Car client；
Electronic map, the section road net data including topological structure, and for the matching result that shows paths；
Traffic network database saves the historical location data of Floating Car and the matching of the section road net data of the topological structure；
Timesharing variable weight heavy-route link library is connected according to history Floating Car motion track and current anchor point degree of rarefication dynamic setting
Domain range cuts road network according to link field range, and goes out every section even according to timesharing category of roads weighted calculation
Connect the path that another indirectly connected road network is reached in domain；And
Route matching unit, including historical location data collection acquiring unit, first matching unit and fitting unit, the history are fixed
Position data set acquiring unit is extracted and the positioning number by the location data acquiring unit real-time reception from the Traffic network database
According to the matched section road net data of multiple buffering ranges, and then it is fixed to obtain the history in the extracted section road net data
Position data set, the first matching unit sample the frequency according to current position determination data and carry out for the first time to the historical location data collection
Matching, the fitting unit are based on the timesharing variable weight heavy-route link library, are fitted to the first matched result strong
Just obtaining final route matching result.
2. Floating Car location data automatic adaptation cushion route matching system according to claim 1, which is characterized in that
The location data is the location data of certain standard, which includes positioning system latitude and longitude coordinates, time, side
To, speed, passenger carrying status attribute；
The location data acquiring unit carries out dissection process to the received location data of institute, according to the standard, and to exception
Data are cleaned.
3. Floating Car location data automatic adaptation cushion route matching system according to claim 1, which is characterized in that
Each section data are the directive road sections of tool in the road network, which defined by two endpoints
And point set and broken line set with space coordinate attribute, and each road section includes an intersection or a discrepancy
Mouthful；
The historical location data collection acquiring unit is extracted from the Traffic network database and by the location data acquiring unit reality
When received location data multiple buffering ranges matched section road net data when, real by the location data acquiring unit
When received location data multiple buffering ranges in, the section of intersection is found out from the Traffic network database, section just
Angle changing rate is carried out respectively to, reversed and two-way three kinds of situations, and is filtered out according to due north angle and do not allowed model in angular deviation
Interior section is enclosed, multiple buffering ranges with the location data by the location data acquiring unit real-time reception are thus obtained
The section road net data matched, and then obtain the historical location data collection in the extracted section road net data.
4. Floating Car location data automatic adaptation cushion route matching system according to claim 1, which is characterized in that
The first matching unit samples the frequency according to current position determination data and is matched for the first time to the historical location data collection
When, the time threshold that each calculating cycle is arranged in the frequency automatically is sampled according to current position determination data, is reaching time threshold triggering
When condition, the historical location data collection is grouped according to the buffering range, and the history of each grouping is positioned
The section data of each historical location data are compared with the section data of preceding several cycle match in data set, remove with it is former
The section of a cycle match does not have the section of topological relation, and ensures that each historical location data only corresponds to a section,
It is final to retain one group of most historical location data collection of the section quantity to match with the section of preceding several cycle match, it obtains just
Beginning matching result.
5. Floating Car location data automatic adaptation cushion route matching system according to claim 1, which is characterized in that
The fitting is corrected
Fitting correction for the first time, solves that range of drift is big, turns around to travel matching problem, and by the section under the conditions of simple road network into
Row effectively connection；
Second of fitting correction, using positive sequence method, path is connected under the conditions of completing complicated road network, while being corrected fitting for the first time and being produced
Raw error；
Third time fitting correction, the error repaired and generated in the fit procedure of second of front is corrected using inverted order method, completes path
Matching.
6. a kind of Floating Car location data automatic adaptation cushion route matching method, which is characterized in that
Include:
Location data obtaining step, the location data for the transmission of real-time reception Floating Car client；
Timesharing variable weight heavy-route link library construction step, according to history Floating Car motion track and current anchor point degree of rarefication dynamic
Link field range is set, is cut road network in Traffic network database according to link field range, and add according to timesharing category of roads
Power calculates the path that every section reaches another indirectly connected road network in link field, and the Traffic network database is by Floating Car
Historical location data and the matching of the section road net data of topological structure save；
Route matching step, including historical location data collection obtaining step, first matching step and fit procedure, the history are fixed
Position data set obtaining step extracts and the positioning number by the location data obtaining step real-time reception from the Traffic network database
According to the matched section road net data of multiple buffering ranges, and then it is fixed to obtain the history in the extracted section road net data
Position data set, the first matching step sample the frequency according to current position determination data and carry out for the first time to the historical location data collection
Matching, the fit procedure are based on timesharing variable weight heavy-route link library, carry out cubic fit correction to first matched result and come
Obtain final route matching result；And
Path shows step, and show paths matching result on the electronic map.
7. Floating Car location data automatic adaptation cushion route matching method according to claim 6, which is characterized in that
The location data is the location data of certain standard, which includes positioning system latitude and longitude coordinates, time, side
To, speed, passenger carrying status attribute；
The location data obtaining step carries out dissection process to the received location data of institute, according to the standard, and to exception
Data are cleaned.
8. Floating Car location data automatic adaptation cushion route matching method according to claim 6, which is characterized in that
Each section data are the directive road sections of tool in the road network, which defined by two endpoints
And point set and broken line set with space coordinate attribute, and each road section includes an intersection or a discrepancy
Mouthful；
The historical location data collection obtaining step extracts from the Traffic network database and by the location data obtaining step reality
When received location data multiple buffering ranges matched section road net data when, real by the location data obtaining step
When received location data multiple buffering ranges in, the section of intersection is found out from the Traffic network database, section just
Angle changing rate is carried out respectively to, reversed and two-way three kinds of situations, and is filtered out according to due north angle and do not allowed model in angular deviation
Interior section is enclosed, multiple buffering ranges with the location data by the location data obtaining step real-time reception are thus obtained
The section road net data matched, and then obtain the historical location data collection in the extracted section road net data.
9. Floating Car location data automatic adaptation cushion route matching method according to claim 6, which is characterized in that
The first matching step samples the frequency according to current position determination data and is matched for the first time to the historical location data collection
When, the time threshold that each calculating cycle is arranged in the frequency automatically is sampled according to current position determination data, is reaching time threshold triggering
When condition, the historical location data collection is grouped according to buffering range, and by the historical location data of each grouping
It concentrates the section data of each historical location data and the section data of preceding several cycle match to be compared, removes and preceding several weeks
Phase matched section does not have the section of topological relation, and ensures that each historical location data only corresponds to a section, finally
Retain one group of most historical location data collection of the section quantity to match with the section of preceding several cycle match, obtains initial
With result.
10. Floating Car location data automatic adaptation cushion route matching method according to claim 6, which is characterized in that
The fitting is corrected
Fitting correction for the first time, removal range of drift is big, turn around running section, and the section under the conditions of simple road network is had
Effect connection；
Second of fitting correction, using positive sequence method, path is connected under the conditions of completing complicated road network, while being corrected fitting for the first time and being produced
Raw error；
Third time fitting correction, the error repaired and generated in the fit procedure of second of front is corrected using inverted order method, completes path
Matching.
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| CN109657713A (en) * | 2018-12-11 | 2019-04-19 | 武汉大学 | A kind of multiple-factor road network method and system based on crowd-sourced road net data |
| CN111311675B (en) * | 2020-02-11 | 2022-09-16 | 腾讯科技（深圳）有限公司 | Vehicle positioning method, device, equipment and storage medium |
| CN112033418B (en) * | 2020-09-15 | 2023-05-12 | 四川大学 | Offline map matching method |
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