CN108036794A - A kind of high accuracy map generation system and generation method - Google Patents
A kind of high accuracy map generation system and generation method 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
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
- G01C21/32—Structuring or formatting of map data
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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
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/40—Correcting position, velocity or attitude
- G01S19/41—Differential correction, e.g. DGPS [differential GPS]
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
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Abstract
The present invention relates to a kind of high-precision map generation system and method, wherein, system includes：One data acquisition module, the view data for the vehicle front road scene that its vehicle DGPS data provided according to DGPS systems and camera provide, obtains the running data of each tracing point and the plane xy coordinates for the tracing point being distributed on road axis on vehicle driving trace；One data processing module being connected with the data acquisition module, it is according to the running data of each tracing point and the plane xy Coordinate generation road axis of the tracing point being distributed on road axis, and road topology relation is generated according to the road axis, to obtain the structural information of whole map；And the map display module being connected with the data processing module.The present invention is by the way that the image information obtained above by camera and DGPS information are merged, it is achieved thereby that generating the purpose of high-precision map with lower cost solution.
Description
Technical field
The present invention relates to a kind of high-precision map generation system and generation method for garden pilotless automobile.
Background technology
It is well known that, it is necessary to which map making is automobile navigation in the R＆D process of automatic driving vehicle.It is existing at present
In technology, the method for map is generated mainly including following several：
1st, the method disclosed in patent document CN105579811A, utilizes external image, Inertial Measurement Unit and wireless
E measurement technology GNSS (Global Navigation Satellite System, Global Satellite Navigation System) and other not wireless
The data fusion of measurement sensor measurement is as a result, determine circuit track of the user in global coordinates, and combine this track and answer
With vSLAM (Visual simultaneous localization and mapping, vision positioning immediately and map structure
Build) image characteristic point of technology, obtain planar structure and (or) stereochemical structure map.
2nd, the method disclosed in patent document CN104573733A, using image taking module, horizontal laser light radar,
GPS processing modules, inertial navigation module, rotary encoder and image pre-processing module and geographic information processing module next life
Into map.
3rd, the method disclosed in patent document CN106441319A, utilizes satellite photo, onboard sensor (laser radar
And camera), integrated positioning system (global position system and inertial navigation system) obtain original road data fusion generation ground
Figure.
In the above method, the precision of map all is improved with relatively more sensors, but multisensor is brought
The problem of be raising in cost, the especially cost of laser radar is differed from tens thousand of to hundreds thousand of.
The content of the invention
In order to solve the above-mentioned problems of the prior art, the present invention is intended to provide it is a kind of high accuracy map generation system and
Generation method, while map generation precision is improved, effectively to reduce cost.
A kind of high-precision map generation system described in one of present invention, it includes：
Before the vehicle that one data acquisition module, its vehicle DGPS data provided according to DGPS systems and camera provide
The view data of square road scene, obtains the running data of each tracing point on vehicle driving trace, each tracing point
Running data includes：Plane xy coordinates, speed, course angle and tracing point of the tracing point to left and right sides lane line away from
From；
One data processing module being connected with the data acquisition module, it is according to the running data of each tracing point
Road axis is generated, and road topology relation is generated according to the road axis, to obtain the structural information of whole map；
And
One map display module being connected with the data processing module, it is according to the structural information wash with watercolours of the whole map
Dye roadway, and Real time displaying current vehicle position.
In above-mentioned high-precision map generation system, the data acquisition module includes：
The one DGPS information process units being connected with the DGPS systems, it parses the vehicle DGPS data,
To extract latitude and longitude coordinates, speed and the course angle of each tracing point, and by gauss projection by each track
The latitude and longitude coordinates of point are converted to the plane xy coordinates of each tracing point；And
The one camera information processing unit being connected with the camera, its image to the vehicle front road scene
Data carry out image preprocessing, lane detection and lane line tracking, and according to default image coordinate and world coordinates it
Between mapping relations, obtain each tracing point to the distance of left and right sides lane line.
In above-mentioned high-precision map generation system, the data processing module includes：
The one map vector generation unit being connected with the data acquisition module, it is according to the traveling of each tracing point
Data, filter out bad point and shift point in the tracing point, and are fitted and are generated in the road after remaining tracing point is clustered
Heart line；And
The one topological map generation unit being connected with the map vector generation unit, it is carried according to the road axis
By way of crossing and dead end street information, to define road data, the road topology relation is generated.
In above-mentioned high-precision map generation system, the data processing module further includes one and is given birth to the topological map
Into the characteristics map generation unit of unit connection, it is used to add map location mark and roadway characteristic mark on whole map
Note.
In above-mentioned high-precision map generation system, further include one and be connected to the camera and the data acquisition module
Camera information receiving module between block, and a DGPS being connected between the DPGS and the data acquisition module believe
Cease receiving module.
In above-mentioned high-precision map generation system, further include one be connected with the data acquisition module be used for provide
The camera calibration module of mapping relations between described image coordinate and world coordinates.
A kind of accurately drawing generating method described in the two of the present invention, it comprises the following steps：
The vehicle front road scene that step S1, the vehicle DGPS data provided according to DGPS systems and camera provide
View data, obtain the running data of each tracing point on vehicle driving trace, the running data bag of each tracing point
Include：Distance of plane xy coordinates, speed, course angle and the tracing point of the tracing point to left and right sides lane line；
Step S2, road axis is generated according to the running data of each tracing point, and according to the road-center
Line generates road topology relation, to obtain the structural information of whole map；And
Step S3, roadway, and Real time displaying vehicle present bit are rendered to according to the structural information of the whole map
Put.
In above-mentioned accurately drawing generating method, the step S1 includes：
Step S11, parses the vehicle DGPS data, extract each tracing point latitude and longitude coordinates,
Speed and course angle, and the latitude and longitude coordinates of each tracing point are converted to by each tracing point by gauss projection
Plane xy coordinates；And
Step S12, the view data of the vehicle front road scene is carried out image preprocessing, lane detection and
Lane line tracks, and according to the mapping relations between default image coordinate and world coordinates, obtains each tracing point and arrive
The distance of left and right sides lane line.
In above-mentioned accurately drawing generating method, the step S2 includes：
Step S21, according to the running data of each tracing point, filters out the bad point and shift point in the tracing point,
And fitting generates the road axis after remaining tracing point is clustered；And
Step S22 is raw to define road data according to the road-center line drawing road mouth and dead end street information
Into the road topology relation.
In above-mentioned accurately drawing generating method, the step S2 is further included：
Step S23, adds map location mark and roadway characteristic mark on whole map.
As a result of above-mentioned technical solution, the present invention (is used for FCW only with camera (or camera) with vehicle
(Forward Collision Warning) forward direction collision warning, LDW (Lane departure warning) deviation report
The forward sight camera multiplexing of the function such as alert) view data of road scene is obtained, cost is thus greatlyd save, and employ
The double GPSs (that is, DGPS) different with existing GPS technology obtain vehicle DGPS data (absolute location information for including vehicle),
Since DGPS contains master and slave two gps signals, the problems such as can be used for overcoming signal drift that single GPS may be brought from gps signal,
Which thereby enhance signal accuracy.The present invention is by the way that the image information obtained above by camera and DGPS information are melted
Close, it is achieved thereby that generating the purpose of high-precision map with lower cost solution.
Brief description of the drawings
Fig. 1 is a kind of structure diagram of high-precision map generation system of the present invention；
Fig. 2 is the structure diagram of data processing module in a kind of high-precision map generation system of the present invention；
Fig. 3 is the schematic diagram that the view data provided in the present invention according to camera corrects tracing point plane xy coordinates；
Fig. 4 is the schematic diagram that shift point is removed in the present invention；
Fig. 5 is the schematic diagram that vehicle is defined with road direction angle in the present invention.
Embodiment
Below in conjunction with the accompanying drawings, presently preferred embodiments of the present invention is provided, and is described in detail.
Please refer to Fig.1,2, one of present invention, i.e. it is a kind of high accuracy map generation system, including：Camera calibration module
1st, camera information receiving module 2, DGPS information receiving modules 3, data acquisition module 4, data processing module 5, data storage
Module 6, map display module 7, central processing module 8 and driver module 9, wherein,
Camera calibration module 1 is connected with data acquisition module 4, camera 10 by camera information receiving module 2 with
Data acquisition module 4 connects, and DGPS systems 20 are connected by DGPS information receiving modules 3 with data acquisition module 4, data acquisition
Module 4 is connected by central processing module 8 with data processing module 5, and data processing module 5 passes through data memory module 6 and ground
Figure display module 7 connects, and central processing module 8 is connected with map display module 7 and driver module 9 respectively, and display is driven
Dynamic model block 9 is also connected with map display module 7.
Specifically, camera calibration module 1 is used to provide the mapping relations between image coordinate and world coordinates.
Data acquisition module 4 includes：The camera information processing unit 41 that is connected with camera information receiving module 2 and
The DGPS information process units 42 being connected with DGPS information receiving modules 3, wherein,
The view data for the vehicle front road scene that camera information processing unit 41 provides camera 10 carries out figure
As pretreatment, lane detection and lane line tracking etc. processing, and according to camera calibration module 1 provide image coordinate and
Mapping relations between world coordinates, obtain on vehicle driving trace each tracing point to left and right sides lane line and road edge
Distance；
DGPS information process units 42 parse the vehicle DGPS data that DGPS systems 20 provide, each to extract
Latitude and longitude coordinates, speed and the course angle of tracing point, and be converted to the latitude and longitude coordinates of each tracing point by gauss projection
The plane xy coordinates of each tracing point；
In addition, camera information processing unit 41 is also connected with DGPS information process units 42, so that according to each track
Point is modified the plane xy coordinates of each tracing point to the distance of left and right sides lane line and road edge, to be distributed
The plane xy coordinates of tracing point on heart line in the road.
Data processing module 5 includes：The map vector generation unit 51 and map vector being connected with data acquisition module 4
The topological map generation unit 52 and the characteristics map generation being connected with topological map generation unit 52 that generation unit 51 connects
Unit 53, wherein,
Map vector generation unit 51 is according to the plane xy coordinates of the tracing point being distributed on road axis and each
The running data of tracing point, speed, course angle and the tracing point of the tracing point being especially distributed across on road axis
To the distance of left and right sides lane line and road edge etc., filter out the bad point in tracing point and shift point (in the present embodiment, may be used
Realized by data prediction subelement 511), and generation road axis is fitted after remaining tracing point is clustered, i.e. generation
The tracing point of orderly, equally distributed road-center (in the present embodiment, can be by connecting with data prediction subelement 511
The road axis generation subelement 512 connect is realized)；
Topological map generation unit 52 is according to road-center line drawing road mouth and dead end street information (in the present embodiment
In, can be realized by road Node extraction subelement 521), to define road data, the road topology relation is generated, that is, is carried
Take generation road relation net (in the present embodiment, can be by the road topology relation that is connected with road Node extraction subelement 521
Generation subelement 522 is realized), to obtain the structural information of whole map, (including how many road, every road include in map
Link relation of which tracing point, every road and other roads etc.)；
Characteristics map generation unit 53 is used to add map location on whole map and mark (in the present embodiment, to lead to
Map location mark subelement 531 is crossed to realize) and roadway characteristic mark (it is sub that roadway characteristic mark in the present embodiment, can be passed through
Unit 532 is realized), wherein, map location mark includes fixed character position mark (such as position of gas station) and interim spy
Sign mark (such as starting final position of navigation), the feature that roadway characteristic mark refers to add road according to traffic sign are believed
Breath, for example, whether road restricts driving, road whether allow lane change etc. (in the present embodiment, roadway characteristic mark subelement 532 can use
In definition road width and road).
Data memory module 6 is used for the cartographic information for storing the output of data processing module 5.
Map display module 7 is according to the structural information of the whole map stored in data memory module 6 (such as path locus
Tracing point plane xy coordinates) be rendered to roadway, and Real time displaying current vehicle position.
Central processing module 8 is respectively that data acquisition module 4, data processing module 5, map display module 7 and display are driven
Dynamic model block 9 provides command information, and (whether, for example, informing data acquisition module 4, whether its data format gathered is correct, stop
Or continue the instruction such as gathered data), and the data that data acquisition module 4 is exported are supplied to data processing module 5.
Driver module 9 is used to provide driver to map denotation unit 7.
The two of the operation principle of said system, the i.e. present invention, i.e., a kind of accurately drawing generating method, including following step
Suddenly：
The vehicle front road that step S1, the vehicle DGPS data provided according to DGPS systems 20 and camera 10 provide
The view data of scene, obtains the running data of each tracing point on vehicle driving trace, the running data bag of each tracing point
Include：Plane xy coordinates, speed, course angle and tracing point of the tracing point to left and right sides lane line and road edge away from
From, and according to each tracing point to the distance of left and right sides lane line and road edge to the plane xy coordinates of each tracing point into
Row is corrected, to obtain the plane xy coordinates for the tracing point being distributed on road axis；
Step S2, according to the running data of each tracing point and the plane xy for the tracing point being distributed on road axis
Coordinate, generates road axis, and generates road topology relation according to road axis, to obtain the structure of whole map letter
Breath；And
Step S3, roadway, and Real time displaying current vehicle position are rendered to according to the structural information of whole map.
In the present embodiment, above-mentioned steps S1 is specifically included：
Step S11, parses vehicle DGPS data, extracts the latitude and longitude coordinates, speed and boat of each tracing point
To angle, and the latitude and longitude coordinates of each tracing point are converted to by gauss projection the plane xy coordinates of each tracing point；And
Step S12, image preprocessing, lane detection and track are carried out to the view data of vehicle front road scene
Line tracks, and according to the mapping relations between default image coordinate and world coordinates, obtains each tracing point to the left and right sides
The distance of lane line and road edge, and according to each tracing point to the distance of left and right sides lane line and road edge to each
The plane xy coordinates of tracing point are modified, to obtain the plane xy coordinates for the tracing point being distributed on road axis.
Above-mentioned steps S2 is specifically included：
Step S21, according to the plane of the running data of each tracing point and the tracing point being distributed on road axis
Xy coordinates, filter out bad point and shift point in tracing point, and generation road axis is fitted after remaining tracing point is clustered；With
And
Step S22, according to road-center line drawing road mouth and dead end street information, to define road data, generates road
Road topological relation；And
Step S23, adds map location mark and roadway characteristic mark on whole map.
In the present embodiment, camera information processing unit 41 is mainly used for the picture number according to vehicle front road scene
Factually show lane detection and following function, which mainly includes image preprocessing, lane detection, lane line and track three
Point, wherein, image preprocessing section point includes：Area-of-interest selection, gray processing, filtering, edge extracting and binary conversion treatment；
Lane detection and tracking include：First it is detected that left and right two straight line nearest apart from selected tracing point, apart from this two
Straight line of the air line distance in scope D is set as left and right straight line cluster, and it is (specific to be fitted left and right lane line according to the point in straight line cluster
Reference can be made to the patent application of Application No. 201710568932.X《A kind of multilane detection method and tracking》, herein no longer
It is described in detail).Camera information processing unit 41 is according to obtained above-mentioned left and right track line model and realizes to camera into rower
Fixed result (mapping relations i.e. between image coordinate and world coordinates), you can obtain tracing point (i.e. vehicle body) and arrive the left and right sides
The distance of lane line.
In the present embodiment, DGPS systems 20 send vehicle DGPS data with 5-20hz (frequency can set and fix),
The valid data that DGPS information process units 42 therefrom extract include：(1) UTC time, hhmmss (Hour Minute Second)；(2) shape is positioned
State, A=are effectively positioned, the invalid positioning of V=；(3) latitude ddmm.mmmmm (degree point)；(4) latitude hemisphere N (Northern Hemisphere) or S (south
Hemisphere)；(5) longitude dddmm.mmmmm (degree point)；(6) longitude hemisphere E (east longitude) or W (west longitude)；(7) ground speed (000.0
~999.9 sections)；(8) ground course (000.0~359.9 degree, with the positive north for reference data)；(9) UTC dates, ddmmyy
(day month year)；(10) magnetic declination (000.0~180.0 degree, 0) then mend by leading digit deficiency；(11) magnetic biasing angular direction, E (east) or W
(west)；(12) pattern instruction (A=autonomous positionings, D=difference, E=estimations, N=data invalids).DGPS information process units 42
Above-mentioned latitude and longitude coordinates data are mainly converted to by the plane xy coordinate (meters on longitude and latitude in gauss projection by gauss projection
Calculation method is known in the art general knowledge, and details are not described herein again).
In addition, in the present embodiment, during due to carrying out vehicle DGPS data acquisitions, DGPS systems 20 relative to road position
Put (as shown in Figure 3) not being to determine.Therefore the view data according to camera is needed when generating road axis, to rail
The plane xy coordinates (x, y) of mark point are modified, i.e. according to each tracing point to left and right sides lane line and road edge away from
It is modified from the plane xy coordinates to each tracing point, is sat with obtaining the plane xy for the tracing point being distributed on road axis
Mark, the coordinate for the tracing point being distributed in after amendment on road axis is (X, Y).As shown in figure 3, due to (its coordinate of tracing point 1
For (x1, y1)) and tracing point 2 (its coordinate is (x2, y2)) acquisition interval it is shorter, therefore be believed that in acquisition interval DGPS transport
Dynamic rail mark is straight line, therefore the coordinate (X of tracing point on road axis can be obtained by equation below1, Y1)：
Wherein, s1And l1It is distance of the tracing point 1 to both sides of the road edge respectively, s2And l2It is that tracing point 2 arrives road respectively
The distance of both sides of the edge.
In the present embodiment, the data prediction subelement 511 in map vector generation unit 51 is mainly used for realizing bad
Point filtering and shift point remove, wherein：
Bad point filtering refers to：If the velocity information that continuous moment vehicle DGPS data obtain is (since vehicle DGPS data are adopted
Then divided by the sampling period collection is fixed frequency, therefore by calculating the distance between two tracing points, you can is obtained approximate
Velocity amplitude) differ by more than threshold value, then illustrate the tracing point collection the very big probability of vehicle DGPS data be wrong, therefore based on
Previous moment be valid data on the basis of, it is necessary to exclude the tracing point of later moment in time.
The principle that shift point removes can be such as Fig. 4：Pass through continuous three tracing points：1: 2: 3 is put to judge；Point 1 and point 3
The straight line being linked to be is denoted as L, if the length D of the projection of point 2 to straight line L have exceeded road and had a lot of social connections W, illustrates that a little 2 very big probabilities are to drift about
Point, it is therefore desirable to remove point 2.
In the present embodiment, in map vector generation unit 51 road axis generation subelement 512 be mainly used for by
Fitting generation road axis after remaining tracing point (being primarily referred to as being distributed in the tracing point on road axis) cluster, its
In：
Remaining tracing point cluster is referred to：By clustering algorithm (due to the algorithm general knowledge known in this field, therefore below only
Do simple introduction) carry out tracing point cluster along the storage order (i.e. the extending direction of road) of track.Specifically include with
Lower step：
(1) density threshold P and cluster radius d is set, tracing point is not exactly at due to data error
On traval trace, and it is distributed across on the position of twice of about road width and (regards shift point more than 2 times), d's
Value can determine that the value of P is different under different pieces of information collection, should be bigger than normal under density data collection, sparse number according to this regularity of distribution
According to collection under should be smaller；
(2) tracing point chain is stored in after all effectively vehicle DGPS data collected in road area being carried out Gaussian transformation
In table, the attribute data of each tracing point includes its plane xy coordinates and a mark for whether having completed cluster；
(3) first track point data in chained list is chosen, if the data represent that the tracing point had been participating in cluster,
Then continue to select next track point data in chained list, until finding the data not clustered；If tracing point did not participated in cluster,
Then jump procedure (4)；
(4) tracing point of cluster was not participated in using this as the center of circle, and distance d clusters for radius, judges the track in cluster circle
Count out, if number has exceeded density threshold P, it is node (that is a, method by taking average, by model to be clustered
Tracing point cluster in enclosing is a point), the plane xy coordinates of the node are respectively the equal of the plane xy coordinates of these tracing points
Value, which is stored in cluster node chained list, performs step (5)；
(5) it is all that these tracing points are poly- labeled as having participated in no matter track counts out whether exceed density threshold P in the circle
Class, performs step (6)；
(6) tracing point that is nearest and having neither part nor lot in cluster from the cluster node is found in tracing point chained list, if energy
Find, then continuing step (4), (centre point in step (4) refers to a cluster node found in this step and upper most at this time
Tracing point that is near and not participating in cluster), otherwise perform step (7)；
(7) all cluster node set are exported, these cluster nodes are linked up and are regarded as path locus, that is,
Say, a road can be indicated with limited cluster node in the form of a chained list, and adjacent cluster node exists
It is continuous in chained list, such as in digital map navigation, automobile passes through per stretch, it is believed that each cluster node of approach.
The advantages of above-mentioned clustering method, is that obtained cluster node is that order is distributed, even if car during acquisition trajectories point
There is repetition in the track opened or opens back and forth all without influence, and each cluster node distribution is than more uniform.
Road axis generates subelement 512 after above-mentioned tracing point cluster is completed, fitting generation road axis, wherein
Including：
(1) road direction is calibrated
In general, it is inaccurate to calculate road direction by simple gps coordinate point, it is therefore desirable to which intelligent vehicle is more
Real time calibration is carried out to road direction during secondary traveling, that is, judges whether current vehicle is in the state of smooth ride,
That is, whether vehicle travel direction in one section of operating range tends towards stability, if so, then it will be understood that vehicle heading with it is current
Road direction keeping parallelism, can make θ at this timeroad=θcar(θroadRepresent road direction, θcarRepresent vehicle heading).Specifically
Simply it can judge whether the current travel direction of intelligent vehicle tends towards stability using the vehicle data in 10 sampling periods；Pass through 10
Vehicle traveling angle in a sampling period, its mean square deviation SD is calculated by equation below：
Wherein, θiRepresent the vehicle traveling angle (direction) in ith sample cycle；N indicates that N number of sampling period take part in
Calculate；Represent the average of vehicle traveling angle (direction) in N number of sampling period；If SD ＜ τ, then it is assumed that vehicle heading
Tend towards stability, τ is the wealthy value of stability, is determined by actual conditions.
(2) lane line and path locus coordinate are calibrated
When running into camera or navigation equipment with the presence of side's invalid data, according to navigation GPS Status Flags and
Camera reliability mark is judged.Since road has continuity in practice, therefore utilize this feature can be to the section " risk
Road " carries out pre-generatmg.
If camera runs into invalid data, the road of road and last sampling period t tool residing for current vehicle are assumed
There is identical extending direction, i.e. the orientation angle of present road remains unchanged within a sampling period.According to Fig. 5, by
Vehicle sensors can read Vehicle Speed v, can be in the hope of：
L2=L1+vtsin (θ-α)
R2=R1-vtsin (θ-α)
Wherein, (x1, y1) is the coordinate of tracing point 1, and (x2, y2) is the coordinate of tracing point 2, and L1, R1 are respectively tracing point 1
To the distance at both sides of the road edge, L2, R2 are respectively distance of the tracing point 3 to both sides of the road edge, and α travels angle, θ for vehicle
For road direction angle.
If DGPS systems are not at Differential positioning state, as shown in figure 5, can be according to current trace points and a upper track
The information such as the distance of line, car speed, collection period calculate the GPS location of tracing point by equation below：
X2=x1+vtcos (α)
Y2=y1+vtsin (α)
Wherein, v is Vehicle Speed, and t is the sampling period, and (x1, y1) is the coordinate of tracing point 1, and (x2, y2) is track
The coordinate of point 2, L1, R1 are respectively distance of the tracing point 1 to both sides of the road edge, and L2, R2 are respectively tracing point 2 to both sides of the road
The distance at edge, α travel angle for vehicle, and θ is road direction angle.
Due to the uncertainty in risk section, therefore pass through minimum, it is necessary to taken multiple measurements to the road when generating map
Square law obtains optimal path locus (i.e. the set of the tracing point of road axis coordinate composition) and road track line coordinates, leads to
The road-center line coordinates obtained and the road width measured (the highway sideline distance obtained by camera obtains) are crossed,
Road can be defined in more detail, and the relation of vehicle and road can be more accurately shown when being navigated.
In the present embodiment, the road Node extraction subelement 521 of topological map generation unit 52 can be used for extracting road
Mouth and dead end street information, specifically：Since the cluster node order obtained in map vector generation unit 51 is distributed, and
And label is all imparted, therefore road crossing tracing point can be extracted by following steps and (it is poly- to have been subjected to map vector generation unit 51
The node of class)：
If the 1st, using cluster node as the center of circle, with 2 times of cluster radius for radius draw circle (this is because in cluster process,
All be to be clustered with one times of cluster radius r, if therefore collection point it is more than enough, the cluster node after cluster is approximate
In equally distributed, the distance of each node is in the range of r~2r), if the point in circle is more than 3, and the label put is not
Continuously, then crossing is likely to (this is because the node after cluster is approaches uniformity, therefore if a crossing of not following the Way
Road, within the cluster radius of 2r, points should no more than 3 for it；If more than 3, represent road and bifurcated road occur
Mouthful), which is added into list L；
2nd, it can be found that road is more chaotic or road crossing near have more erroneous judgement point (this is because road bifurcated
Two roads occur apart from closer situation in mouth, thus the point near real road interface port can be also included after clustering into
Come), using distance as diversity factor, classify to the node in above-mentioned list L, cluster 1, cluster 2 etc. are defined as per class.
3rd, each point in cluster is judged, using each point as the center of circle, cluster radius draws circle for radius, finds out and is comprised in number in circle
Most points, then it is crossing that the point, which has maximum probability,；And dead end street is associated because of other no roads, therefore it is cluster half
The point that round dot is minimum is included in footpath；
When the cluster node between the crossing point and end point that have found road, each road cross point and end point belongs to
This road, can thus generate the topological relation that subelement 522 defines road by road topology relation.It can finally lead to
The attribute information that characteristics map generation unit 53 adds some roads to the cluster node of road is crossed, thus generates characteristics map.
In conclusion the present invention can be generated available in a short time by the DGPS and camera data fusion of low cost
In the unmanned high-precision navigation map in garden.By the present invention, after only road in park information need to be collected by automobile, you can
Map is quickly generated, and available for the optimum path planning to garden unmanned vehicle.Meanwhile adopted during automatic driving vehicle traveling
The real time data of collection can be merged with historical data again, optimization, the precision for improving map, it is achieved thereby that sustainable low cost
The generation method of high-precision two-dimensional map.
It is above-described, it is only presently preferred embodiments of the present invention, is not limited to the scope of the present invention, of the invention is upper
Stating embodiment can also make a variety of changes.What i.e. every claims and description according to the present patent application were made
Simply, equivalent changes and modifications, falls within the claims of patent of the present invention.The not detailed description of the present invention is
Routine techniques content.
Claims (10)
1. a kind of high accuracy map generation system, it is characterised in that it includes：
The vehicle front road that one data acquisition module, its vehicle DGPS data provided according to DGPS systems and camera provide
The view data of road scene, obtains the running data of each tracing point on vehicle driving trace, the traveling of each tracing point
Data include：Plane xy coordinates, speed, course angle, tracing point to left and right sides lane line and road edge of the tracing point
Distance；The data acquisition module is always according to each tracing point to the distance of left and right sides lane line and road edge to each
The plane xy coordinates of tracing point are modified, to obtain the plane xy coordinates for the tracing point being distributed on road axis；
One data processing module being connected with the data acquisition module, its according to the running data of each tracing point and
The plane xy coordinates of the tracing point being distributed on road axis, generate road axis, and according to the road-center
Line generates road topology relation, to obtain the structural information of whole map；And
One map display module being connected with the data processing module, it is rendered to according to the structural information of the whole map
Roadway, and Real time displaying current vehicle position.
2. high accuracy map generation system according to claim 1, it is characterised in that the data acquisition module includes：
The one DGPS information process units being connected with the DGPS systems, it parses the vehicle DGPS data, to carry
Take out latitude and longitude coordinates, speed and the course angle of each tracing point, and by gauss projection by each tracing point
Latitude and longitude coordinates are converted to the plane xy coordinates of each tracing point；And
The one camera information processing unit being connected with the camera and DGPS information process units, before it is to the vehicle
The view data of square road scene carries out image preprocessing, lane detection and lane line tracking, and according to default image
Mapping relations between coordinate and world coordinates, obtain each tracing point to left and right sides lane line and road edge away from
From, and the plane according to each tracing point to the distance of left and right sides lane line and road edge to each tracing point
Xy coordinates are modified, with the plane xy coordinates for the tracing point being distributed in described in acquisition on road axis.
3. high accuracy map generation system according to claim 1, it is characterised in that the data processing module includes：
The one map vector generation unit being connected with the data acquisition module, it is according to the running data of each tracing point
And the plane xy coordinates of the tracing point being distributed on road axis, filter out the bad point in the tracing point and drift
Point, and be fitted after remaining tracing point is clustered and generate the road axis；And
The one topological map generation unit being connected with the map vector generation unit, it is according to the road-center line drawing road
Crossing and dead end street information, to define road data, generate the road topology relation.
4. high accuracy map generation system according to claim 3, it is characterised in that the data processing module further includes
The one characteristics map generation unit being connected with the topological map generation unit, it is used to add map location on whole map
Mark and roadway characteristic mark.
5. high accuracy map generation system according to claim 1, it is characterised in that the system also includes one to be connected to
Camera information receiving module between the camera and the data acquisition module, and one be connected to the DPGS and institute
State the DGPS information receiving modules between data acquisition module.
6. it is according to claim 1 high accuracy map generation system, it is characterised in that the system also includes one with it is described
The camera calibration mould for being used to provide the mapping relations between described image coordinate and world coordinates of data acquisition module connection
Block.
7. a kind of accurately drawing generating method, it is characterised in that the described method comprises the following steps：
The figure for the vehicle front road scene that step S1, the vehicle DGPS data provided according to DGPS systems and camera provide
Picture data, obtain the running data of each tracing point on vehicle driving trace, and the running data of each tracing point includes：Should
Plane xy coordinates, speed, course angle and tracing point of tracing point to left and right sides lane line and road edge distance, and
The plane xy coordinates of each tracing point are repaiied according to each tracing point to the distance of left and right sides lane line and road edge
Just, the plane xy coordinates for the tracing point being distributed in acquisition on road axis；
Step S2, according to the flat of the running data of each tracing point and the tracing point being distributed on road axis
Face xy coordinates, generate road axis, and generate road topology relation according to the road axis, to obtain whole map
Structural information；And
Step S3, roadway, and Real time displaying current vehicle position are rendered to according to the structural information of the whole map.
8. accurately drawing generating method according to claim 7, it is characterised in that the step S1 includes：
Step S11, parses the vehicle DGPS data, extracts latitude and longitude coordinates, the speed of each tracing point
And course angle, and the latitude and longitude coordinates of each tracing point are converted to by gauss projection the plane of each tracing point
Xy coordinates；And
Step S12, image preprocessing, lane detection and track are carried out to the view data of the vehicle front road scene
Line tracks, and according to the mapping relations between default image coordinate and world coordinates, obtains each tracing point to left and right
The distance of both sides lane line and road edge, and according to each tracing point to left and right sides lane line and road edge away from
It is modified from the plane xy coordinates to each tracing point, with the tracing point that is distributed in described in acquisition on road axis
Plane xy coordinates.
9. accurately drawing generating method according to claim 7, it is characterised in that the step S2 includes：
Step S21, according to the running data of each tracing point and the tracing point being distributed on road axis
Plane xy coordinates, filter out bad point and shift point in the tracing point, and are fitted after remaining tracing point is clustered described in generation
Road axis；And
Step S22, according to the road-center line drawing road mouth and dead end street information, to define road data, generates institute
State road topology relation.
10. accurately drawing generating method according to claim 9, it is characterised in that the step S2 is further included：
Step S23, adds map location mark and roadway characteristic mark on whole map.
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