CN103600707B - A kind of parking position detection device and method of Intelligent parking system - Google Patents
A kind of parking position detection device and method of Intelligent parking system Download PDFInfo
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- CN103600707B CN103600707B CN201310545995.5A CN201310545995A CN103600707B CN 103600707 B CN103600707 B CN 103600707B CN 201310545995 A CN201310545995 A CN 201310545995A CN 103600707 B CN103600707 B CN 103600707B
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Abstract
The present invention discloses the level detecting apparatus of parking of a kind of Intelligent parking system, including sensor unit: four wide-angle cameras and ultrasonic distance-measuring sensor；Signal processing unit: panoramic view generation module, parking position detection module；Human-machine interface unit: output module is in order to show that panoramic view and the warehouse compartment detected, input module are in order to accept the various instructions of driver's input.Wherein, parking position detection module includes warehouse compartment line detection sub-module, obstacle car detection sub-module and parking position output sub-module.Invention additionally discloses the parking position detection method of a kind of Intelligent parking system.The present invention uses low cost sensor plan, the image information that the distance value obtained by merging ultrasonic distance-measuring sensor arrives with camera collection, improve parking position detection accuracy and precision, and ground exist warehouse compartment line and exist obstacle car multiple in the case of parking position can effectively be detected.
Description
Technical field
The invention belongs to automobile technical field, relate to drive assist system, refer more particularly to the parking position detection of Intelligent parking system
Device and method.
Background technology
Along with the increase of automobile pollution, parking stall growing tension, this problem of parking difficulty becomes more serious.For there is no warp
For the new hand tested, vehicle safety ground is stopped into parking position extremely difficult；From the point of view of experienced driver, vehicle
Stopping into narrow and small parking position is not an easy thing yet.Developing intellectual resource parking system, advantageously ensures that the peace of the process of parking
Quan Xing, improves comfortableness and the convenience of process of parking simultaneously.
Intelligent parking system generally comprises following module: parking position detection module, path planning module, tracking module, hold
Row module and human-machine interface module.Parking position detection module is the basis of Intelligent parking system, largely affects whole pool
The performance of car system.
At present, the parking position detection method of Intelligent parking system mainly includes following three kinds: 1. utilize ultrasonic distance-measuring sensor to enter
Row parking position detects.Owing to vehicle front or rear end exist fillet, limited to by ultrasonic distance-measuring sensor self character, front
There is the phenomenon not receiving echo at the fillet of rear end, it is bigger than normal than actual that this will result in the parking position detected；Additionally, this side
Method is not suitable for ground yet and there is warehouse compartment line but the situation that do not has front and back's obstacle car, such as parking lot etc..The auxiliary of parking of Volkswagen
System utilizes the sonac being arranged on bumper both sides, is scanned vehicle both sides when vehicle travels, and then detection is parked
Position.This system all has lift-launch in the vehicle such as sight, Magotan, CC of way under masses.2. utilize laser radar to carry out parking position inspection
Survey, have an advantage in that accuracy of detection is high, but laser radar is with high costs.The patent of Honda Motor Co.'s application
CN10187849 utilizes radar installations to send electromagnetic wave with predetermined time interval, detects electromagnetic wave according to the reception result of echo
The pip of reflection on object, and judge to park sky according to the arrangement of the body dimensions data from car prestored and pip
Between presence or absence.3. utilizing machine vision technique to carry out parking position detection, its difficult point is that image is vulnerable to the environment such as shade, illumination
The impact of condition.Wang Xudong proposes in " designing with system based on the automatic parking technique study looked around " and becomes based on Radon
The bright spot feature detection parking position changed and the method extracting empty parking position based on window of interest.Above scheme is respectively arranged with advantage, but
Yet suffer from deficiency.
Summary of the invention
It is an object of the invention to provide the parking position detection device and method of a kind of Intelligent parking system, there is warehouse compartment line on ground
With exist obstacle car multiple in the case of parking position can effectively be detected.
For reaching object above, solution of the present invention is:
A kind of level detecting apparatus of parking of Intelligent parking system, including sensor unit: the photographic head being positioned on automobile body and
Distance measuring sensor；Signal processing unit: panoramic view generation module, parking position detection module；Man-machine interface: output module in order to
Display panoramic view and the warehouse compartment detected, input module is in order to accept the various instructions of driver's input.
Described parking position detection module includes park bit line detection sub-module, obstacle car detection sub-module, parking position output sub-module；
Bit line detection sub-module of parking utilize ground park bit line detection parking position；Obstacle car detection sub-module Use barriers car test is surveyed and is parked
Position；Parking position output sub-module, according to bit line detection sub-module and the testing result of obstacle car detection sub-module of parking, finally determines
Go out parking position.
Described sensor unit includes being positioned at vehicle front side, rear side, left side, four wide-angle cameras on right side and being positioned at vehicle two
The ultrasonic distance-measuring sensor of side.
The installation site of described four photographic head should ensure that four camera collections to picture cover 360 degree of regions of vehicle's surroundings,
And adjacent two camera collections to picture have overlapping region.
Described man-machine interface output module by the parking position Overlapping display that detects on panoramic view, if be detected that parking position not
Correct or do not meet the wish of driver, driver can adjust position and (or) the direction of parking position by input module,
After driver changes position and (or) the direction of parking position, new four angular coordinates of parking position are exported intelligent parking system
The path planning module of system.
The method that the bit line detection sub-module of parking parked in level detecting apparatus of described Intelligent parking system determines parking position, bag
Include following steps: (1) Image semantic classification；(2) from panoramic view, straight line is extracted；(3) straight line is carried out post processing, to retain
Parking line segment corresponding to bit line in ground, deletes other mixed and disorderly line segments；(4) rectangle parking position is obtained.
The method that the obstacle car detection sub-module parked in level detecting apparatus of described Intelligent parking system determines parking position: according to
Hold the position of profile to determine parking position before and after obstacle car.
First obstacle Herba Plantaginis end profile position in global coordinate system uses following methods to determine: (1) utilizes ultrasonic ranging
Distance value that sensor obtains and vehicle posture information, simulate the straight line corresponding to obstacle car side profile；(2) when super
During the distance value generation positive transition of sound ranging sensor, store the panoramic view in this moment；(3) in panoramic view, sense is set emerging
Interest region (ROI), makes obstacle Herba Plantaginis end profile be positioned at area-of-interest；(4) to described area-of-interest image gray processing,
Do rim detection, obtain the coordinate of obstacle Herba Plantaginis end profile protruding point (First Point)；(5) by First Point to simulating
Straight line make vertical line, determine obstacle Herba Plantaginis end profile position in global coordinate system；
If there are two obstacle cars, then second obstacle car rear end profile position in global coordinate system uses following methods to determine:
(6) utilize distance value and vehicle posture information that ultrasonic distance-measuring sensor obtains, simulate corresponding to obstacle car side profile
Straight line；(2) when the distance value of ultrasonic distance-measuring sensor occurs negative saltus step, the panoramic view in this moment is stored；(3) exist
Panoramic view sets area-of-interest, makes obstacle car rear end profile be positioned at area-of-interest；(4) to described area-of-interest figure
As gray processing, do rim detection, obtain the obstacle Herba Plantaginis end profile protruding point i.e. coordinate of rearmost point；(5) by rearmost point
Make vertical line to the straight line simulated, determine obstacle car rear end profile position in global coordinate system.
Owing to have employed technique scheme, the method have the advantages that employing low cost sensor plan, by melting
The image information that the distance value that conjunction ultrasonic distance-measuring sensor obtains arrives with camera collection, improves the accuracy of parking position detection
And precision, and ground exist warehouse compartment line and exist obstacle car multiple in the case of parking position can effectively be detected.
Accompanying drawing explanation
Fig. 1 is the parking position detection apparatus function module diagram of Intelligent parking system of the present invention.
Fig. 2 is the flow chart of the parking position detection method of Intelligent parking system of the present invention.
Fig. 3 is sensor arrangement on vehicle in the embodiment of the present invention.
Fig. 4 is the panoramic view splicing generation in the embodiment of the present invention.
Fig. 5 is the algorithm flow chart of the bit line detection sub-module of parking of the present invention.
Fig. 6 is the flow chart of embodiment of the present invention cathetus post-processing approach.
Fig. 7 is the algorithm flow chart of obstacle car detection sub-module of the present invention.
Fig. 8 is global coordinate system and the schematic diagram of vehicle axis system in the present invention.
Fig. 9 is the flow chart that first obstacle Herba Plantaginis end profile of the present invention determines method.
Figure 10 is that in the embodiment of the present invention, first obstacle Herba Plantaginis end profile determines method schematic diagram.
Figure 11 is the parking position design sketch of Overlapping display in panoramic view that will detect in the embodiment of the present invention.
Detailed description of the invention
Below in conjunction with accompanying drawing illustrated embodiment, the present invention is further illustrated.
Refer to Fig. 1 and Fig. 2.
1, sensor unit:
Sensor unit includes: is positioned at vehicle front side, rear side, left side, four wide-angle cameras on right side and is positioned at vehicle both sides
Ultrasonic distance-measuring sensor.Wherein, the installation site of four photographic head should ensure that four camera collections to picture cover
360 degree of regions of vehicle's surroundings, and adjacent two camera collections to picture have overlapping region.Ultrasonic distance-measuring sensor is permissible
It is that left and right side respectively arranges one, it is also possible to it is multiple to be that left and right side is respectively arranged.In embodiment 1, front photographic head is arranged
At vehicle front grid, left and right photographic head is arranged at the rearview mirror of left and right, and rear photographic head is arranged on vehicle back door；On a left side
A ultrasonic distance-measuring sensor it is respectively mounted at right rear view mirror.Sensor arrangement on vehicle is as shown in Figure 3.
2, panoramic view generation module
(1) distortion is corrected
In order to obtain bigger field range, four photographic head being positioned at vehicle body surrounding in the present invention use flake wide-angle camera.
The image that fish-eye camera collects also exists bigger distortion, it is necessary first to it is corrected distortion.
In example 2, the radial distortion of a consideration video camera and tangential distortion, the distortion of camera parameter obtained according to demarcation,
Utilize following formula to four camera collections to image respectively be corrected distortion:
xcor=x+x(k1r2+k2r4+k3r6)+[2p1y+p2(r2+2x2)] formula (2-1)
ycor=y+y(k1r2+k2r4+k3r6)+[p1(r2+2y2)+2p2X] formula (2-2)
Wherein, (x y) is the original coordinates of a certain pixel；(xcor,ycor) be this pixel correcting distorted after coordinate；[k1,k2,k3] it is radial distortion parameter；[p1,p2] it is tangential distortion parameter.
(2) four width birds-eye views are generated
Four width images after correcting distortion are carried out Inverse projection respectively, is converted into the birds-eye view overlooking effect.
1) camera model
What camera imaging model described is that the imaging process of object, i.e. any point coordinate in three-dimensional world coordinate system are to being somebody's turn to do
Mathe-matical map relation between the coordinate of some imaging.
1. world coordinates is tied to the transformation relation of camera coordinate system
Wherein, R is the spin matrix of 3 × 3；T is the translation vector of 3 × 1； For joining matrix, (X outside video cameraw,Yw,Zw) it is
Certain some coordinate in world coordinate system in space；(Xc,Yc,Zc) it is this coordinate in camera coordinate system.
2. camera coordinates is tied to the transformation relation of image coordinate system
Wherein, For video camera internal reference matrix；(x y) is this coordinate in image coordinate system.
2) inverse perspective projection transformation
From formula (2-4), according to certain some coordinate (X in three-dimensional world coordinate systemw,Yw,Zw) this point can be calculated
Coordinate in image coordinate system (y), otherwise then can not by x.But it is if it is known that certain in certain some three-dimensional coordinate is one-dimensional, the most permissible
According to the coordinate in this dot image coordinate system, (x y), calculates the another bidimensional of this three-dimensional coordinate.Inverse perspective mapping refers to: build
Found the position corresponding relation of the point in image coordinate system and the point in known plane in three-dimensional world coordinate system.
Set up following coordinate system: choosing vehicle geometric center point and being projected in ground point straight down is zero Ow；YwAxle
Being oriented parallel to vehicle rear axle direction, pointing to vehicle left side is just；XwIt is perpendicular to YwAxle, pointing to vehicle front is just；It is perpendicular to
Ground is upwards ZwAxle positive direction.Using this coordinate system as world coordinate system.It is now assumed that Zw=0, i.e. suppose owning in image
Point is all located on ground in three-dimensional world coordinate system, utilizes the internal reference matrix of four video cameras and outer ginseng matrix, to four shootings
The image that machine collects carries out inverse perspective mapping respectively, obtains overlooking the birds-eye view of effect.
(3) splicing generates panoramic view
By inverse perspective mapping, obtaining four width and overlook the birds-eye view of effect, the birds-eye view that adjacent camera obtains has and partially overlaps
Four width birds-eye views, by alignment overlapping region, can be spliced into panoramic view by region.
First, the field range of panoramic view is set.This has also determined that the zoom factor of birds-eye view；
Then, it is determined that piece.Choose four straight lines in four width birds-eye views overlapping region between any two as piece.
Finally, four width birds-eye views are cut out along the position of piece, spliced.
Fig. 4 is the panoramic view splicing generation in embodiment 2.
3, parking position detection module
Parking position detection module includes park bit line detection sub-module, obstacle car detection sub-module, parking position output sub-module.Pool
Parking stall line detection sub-module utilize ground park bit line detection parking position；Parking position is surveyed in obstacle car detection sub-module Use barriers car test；
Parking position output sub-module, according to bit line detection sub-module and the testing result of obstacle car detection sub-module of parking, finally determines pool
Parking stall.
(1) park bit line detection sub-module
The algorithm flow chart of bit line detection sub-module of parking is as shown in Figure 5.
1) Image semantic classification
Panoramic view is carried out gray processing, cromogram is become gray-scale map.Gray-scale map is carried out medium filtering again, reduces in image
Noise.
2) straight line is extracted
1. rim detection
In embodiment 3, use canny operator that gray-scale map is carried out rim detection.Canny edge detection operator uses two thresholds
Value, if the gradient of a pixel is more than upper limit threshold, is then considered as edge pixel, if less than lower threshold, then thrown
Abandon, if therebetween, only just can be accepted with when being connected higher than the pixel of upper limit threshold when it.
Otsu algorithm is used to calculate the high-low threshold value of Canny operator in embodiment 3.Otsu algorithm basic ideas are chosen
Optimal threshold should make have best separation property between two classes obtained with this Threshold segmentation, and detailed process make use of the ash of image
Degree rectangular histogram, so that the gray value variance of target and background is target to the maximum to determine the threshold value that image is split.Canny operator
High threshold be:
T=ArgMax[w0(t)(u0(t)-u)2+w1(t)(u1(t)-u)2] formula (3-1)
Wherein, T is the high threshold of canny operator；T is the image segmentation threshold assumed；u0T () is the institute that brightness value is bigger than t
There is the average brightness value of pixel；w0T () is the ratio that brightness value is more than shared by the pixel of t；u1T () is that brightness value is less than t
The average brightness value of all pixels；w1T () is the ratio that brightness value is less than shared by the pixel of t；U is all pixels in image
The average brightness value of point.
After being calculated high threshold T, the more conventional empirical equation using high threshold to be equal to Low threshold twice obtains Low threshold.
2. Hough transformation
Straight line on two dimensional surface can describe by equation below:
ρ=xcos (θ)+ysin (θ) formula (3-2)
Wherein, ρ is the initial point distance to straight line, and θ is the inclination angle of this straight line.
ρ and θ constitutes two-dimensional space H (ρ, θ), and any point in H (ρ, θ) all correspond to the straight line on a certain plane domain.
Hough transform is exactly the point-line duality utilizing image space and Hough parameter space, the test problems in image space
It is transformed into parameter space.By carrying out simple cumulative statistics in parameter space, then find counting at Hough parameter space
The method detection of straight lines of device peak value.
3) straight line post processing
Owing to bit line of parking is with the presence of defect or ground shade etc., many mixed and disorderly line segments may be detected.It is thus desirable to utilize pool
The constraints that parking stall line meets, processes the straight line detected, the line segment corresponding to retain warehouse compartment line, deletes other miscellaneous
Random line segment.The constraints that bit line of parking meets includes: parking, bit line opposite side is parallel to each other, adjacent side is orthogonal, standard is parked
The size of position, the live width etc. of bit line of parking, can choose one or several constraintss therein and process straight line.?
In embodiment 3, the flow chart of straight line post-processing algorithm is as shown in Figure 6.Algorithm above provides a kind of method of straight line post processing,
Different constraints can also be chosen in other embodiments.
(2) obstacle car detection sub-module
The algorithm flow chart of obstacle car detection sub-module is as shown in Figure 7.
1) position of first obstacle Herba Plantaginis end profile is calculated
Global coordinate system is defined as with starting point vehicle rear axle midpoint of parking for initial point OG；YGDirection of principal axis is along vehicle
At the rear direction of principal axis of starting point of parking, pointing to vehicle left side is just；XGAxle is perpendicular to YGAxle, pointing to vehicle direction of advance is
Just.Vehicle axis system is defined as with vehicle rear axle midpoint for initial point O；Y direction along the rear direction of principal axis of vehicle,
Pointing to vehicle left side is just；X-axis is perpendicular to Y-axis, and pointing to vehicle direction of advance is just.Vehicle coordinate ties up to world coordinates
System follows vehicle motion.Fig. 8 is the schematic diagram of the global coordinate system defined in the present invention and vehicle axis system.
Calculate the algorithm flow chart of first obstacle Herba Plantaginis end outline position as shown in Figure 9.
1. obstacle car side profile straight line
I calculates the coordinate in global coordinate system of the point on obstacle car side profile
Ultrasonic distance-measuring sensor can be that left and right side respectively arranges one, it is also possible to it is multiple to be that left and right side is respectively arranged.In reality
Executing in example 4, vehicle left and right side respectively arranges a ultrasonic distance-measuring sensor.Forward travel, utilizes ultrasonic ranging to pass
Sensor, obtains distance value between vehicle and obstacle car.There is not positive transition in the distance value returned when ultrasonic distance-measuring sensor
Time, utilize the installation site parameter of distance value and ultrasonic distance-measuring sensor, obtain the point on side profile in vehicle axis system
Coordinate.
X=XultFormula (3-1)
Y=dis+YultFormula (3-2)
Wherein, (X, Y) is the coordinate in vehicle axis system of the point on side profile；(Xult,Yult) it is that ultrasonic sensor exists
The coordinate of installation site in vehicle axis system；The computational methods of dis are as follows: its value be left side ultrasonic distance-measuring sensor return away from
Distance values, or the opposite number of the distance value of right-side ultrasonic-wave distance measuring sensor return.
Wherein, positive transition refers to: the increase of the absolute value of the dis of the current time absolute value relative to the dis of previous moment more than to
Determine threshold value.
The vehicle posture information in recycling corresponding moment, the point being calculated on side profile coordinate in global coordinate system.
XG=(X+xv)cosθ-(Y+yv) sin θ formula (3-3)
YG=(X+xv)sinθ+(Y+yv) cos θ formula (3-4)
Wherein, (XG,YG) it is the coordinate in global coordinate system of the point on side profile；(xv,yv, θ) and it is the car in corresponding moment
Posture information (xvAnd yvIt is respectively corresponding moment vehicle axis system initial point (i.e. vehicle rear axle midpoint) in global coordinate system
X, y-coordinate；θ is the course angle of vehicle).
II simulates straight line with the point on side profile
In example 4, with method of least square, the point on side profile is done fitting a straight line.
Multiple ultrasonic distance-measuring sensor can also be respectively arranged in other embodiments at vehicle left and right side.Such as,
It is respectively arranged two ultrasonic distance-measuring sensors in arranged on left and right sides, then said method matching can be utilized to obtain two straight lines,
This two straight lines equation in global coordinate system is respectively as follows: YG=k1XG+b1、YG=k2XG+b2.Take k=0.5*
(k1+k2),b=0.5*(b1+b2), obtain straight line YG=kXG+ b, is the straight line that obstacle car side profile is corresponding.
2. obstacle car First Point
Adopting and define image coordinate system with the following method: initial point is defined on the left upper of image, level is to the right x-axis positive direction,
It is y-axis positive direction straight down.
I sets ROI
When the distance value generation positive transition of ultrasonic distance-measuring sensor, store the panoramic view in this moment.Panoramic view is set ROI,
Obstacle Herba Plantaginis end profile is made to be positioned at ROI region.
II gray processing, rim detection
First ROI image is converted to gray-scale map, and recycling canny edge detection operator carries out rim detection to gray-scale map.
III First Point coordinate in ROI image coordinate system
In ROI edge image, find the marginal point that y-coordinate value (in image coordinate system) is minimum, as obstacle Herba Plantaginis
End profile protruding point (First Point).
IV First Point coordinate in global coordinate system
First, First Point coordinate in the image coordinate system of panoramic view is calculated:
XH=XR+XXFormula (3-5)
YH=YR+YYFormula (3-6)
Wherein, (XH,YH) it is First Point coordinate in the image coordinate system of panoramic view；(XR,YR) it is that First Point is schemed at ROI
Coordinate in the image coordinate system of picture；(XX,YY) it is the upper left angle point of the ROI region coordinate in the image coordinate system of panoramic view.
Then, First Point coordinate in vehicle axis system is calculated:
XFV=(Ypix/2-YH)×(L/Ypix)+d formula (3-7)
YFV=(-XH+Xpix/2)×(L/Ypix) formula (3-8)
Wherein, (XFV,YFV) it is First Point coordinate in vehicle axis system, unit is centimetre；XpixSit at image for panoramic view
Pixel number on mark system x direction, in example 4 its value 320；YpixFor panoramic view pixel on image coordinate system y direction
Number, its value is 550 in the present embodiment；D is the geometric center distance to vehicle rear axle of vehicle, is 130(li in the present embodiment
Rice)；L is the actual distance value that scope that panoramic view can show in the longitudinal direction is corresponding, is 1550(centimetre in the present embodiment).
Finally, First Point coordinate in global coordinate system is calculated:
XF=(XFV+xv)cosθ-(YFV+yv) sin θ formula (3-9)
YF=(XFV+xv)sinθ+(YFV+yv) cos θ formula (3-10)
Wherein, (XF,YF) it is First Point coordinate in global coordinate system；(xv,yv, θ) and it is the distance value of ultrasonic sensor
There is vehicle posture information (x during positive transitionvAnd yvIt is respectively corresponding moment vehicle axis system initial point (i.e. vehicle rear axle midpoint)
X in global coordinate system, y-coordinate；θ is the course angle of vehicle).
3. vertical line is made to side profile straight line in First Point
Figure 10 is that in the present embodiment, first obstacle Herba Plantaginis end profile determines method schematic diagram.
2) second obstacle car is judged whether
After the distance value generation positive transition of ultrasonic distance-measuring sensor, vehicle continues to move forward, if moving forward to pre-spacing
From, all there is not negative saltus step in the distance value of ultrasonic distance-measuring sensor, then is judged to there is not second obstacle car；If it is the most capable
Sailing to preset distance, there is negative saltus step in the distance value of ultrasonic distance-measuring sensor, it is determined that for there is second obstacle car.Wherein,
Negative saltus step refers to: the reduction amount of the absolute value of the dis of the current time absolute value relative to the dis of previous moment is more than given threshold value.dis
Computational methods as follows: its value is the distance value that left side ultrasonic distance-measuring sensor returns, or right-side ultrasonic-wave distance measuring sensor returns
The opposite number of the distance value returned.
3) rectangle parking position
If there is second obstacle car, then according to first obstacle Herba Plantaginis end profile and the position of second obstacle car rear end profile, really
Make the rectangle parking position between two obstacle cars；If there is not second obstacle car, then according to first obstacle Herba Plantaginis end profile
Or rear end profile determines rectangle parking position.
(3) parking position output sub-module
The testing result of park bit line detection sub-module and obstacle car detection sub-module is inputed to parking position output sub-module.Park
The testing result of bit line detection sub-module and obstacle car detection sub-module includes following four situation, and parking position output sub-module is four
The available parking position obtained in the case of Zhong is as shown in the table:
Wherein, √ represents that detecting that warehouse compartment, X represent is not detected by warehouse compartment.
For situation 1, if the parking position region of obstacle car detection sub-module output comprises bit line detection sub-module output of parking
Parking position region, then export the parking position that bit line detection sub-module of parking detects；Otherwise, output obstacle car detection sub-module inspection
The parking position measured.
For situation 3, the parking position that output obstacle car detection sub-module detects.
4, man-machine interface
Man-machine interface includes output module and input module.Output module is in order to show panoramic view and the warehouse compartment detected, Ke Yitong
Cross touch screen, head up display (HUD) etc. to realize.Input module, in order to accept the various instructions of driver's input, can pass through
In touch screen, phonetic order, steering indicating light, car, button etc. realize.
If the parking position that Overlapping display is on panoramic view is incorrect or does not meets the wish of driver, driver can pass through people
The input module of machine interface adjusts position and (or) the direction of parking position.Position and (or) the side of parking position is changed driver
Backward, new four angular coordinates of parking position are exported the path planning module of Intelligent parking system.
Figure 11 is the parking position design sketch of Overlapping display in panoramic view that will detect.
The above-mentioned description to embodiment is to be understood that for ease of those skilled in the art and apply the present invention.It is familiar with
These embodiments obviously easily can be made various amendment by the personnel of art technology, and should General Principle described herein
Use in other embodiments without through performing creative labour.Therefore, the invention is not restricted to above-described embodiment, art technology
Personnel should be at the protection model of the present invention according to the announcement of the present invention, the improvement made without departing from scope of the invention and amendment
Within enclosing.
Claims (5)
1. the level detecting apparatus of parking of an Intelligent parking system, it is characterised in that: including: sensor unit: be positioned at car
Photographic head on vehicle body and distance measuring sensor；Signal processing unit: panoramic view generation module, parking position detect
Module；Man-machine interface: output module is in order to show panoramic view and the warehouse compartment detected, input module is in order to accept
The various instructions of driver's input；
Described parking position detection module includes park bit line detection sub-module, obstacle car detection sub-module, parking position output
Submodule；Bit line detection sub-module of parking utilize ground park bit line detection parking position；Obstacle car detection sub-module
Parking position is surveyed in Use barriers car test；Parking position output sub-module is according to bit line detection sub-module and the obstacle car test of parking
Survey the testing result of submodule, finally determine parking position；
The method that described obstacle car detection sub-module determines parking position: the position according to holding profile before and after obstacle car is come really
Determine parking position；
First obstacle Herba Plantaginis end profile position in global coordinate system uses following methods to determine: (1) utilizes ultrasonic
Distance value that ripple distance measuring sensor obtains and vehicle posture information, simulate corresponding to obstacle car side profile
Bar straight line；(2) when the distance value generation positive transition of ultrasonic distance-measuring sensor, looking around of this moment is stored
Figure；(3) in panoramic view, set area-of-interest, make obstacle Herba Plantaginis end profile be positioned at area-of-interest；
(4) to described area-of-interest image gray processing, do rim detection, obtain obstacle Herba Plantaginis end profile
The protruding point i.e. coordinate of First Point；(5) made vertical line by First Point to the straight line simulated, determine obstacle Herba Plantaginis
End profile position in global coordinate system；
If there are two obstacle cars, then second obstacle car rear end profile position in global coordinate system uses with lower section
Method determines: (6) utilize the distance value and vehicle posture information that ultrasonic distance-measuring sensor obtains, and simulate correspondence
Straight line in obstacle car side profile；(7) when the distance value of ultrasonic distance-measuring sensor occurs negative saltus step,
Store the panoramic view in this moment；(8) in panoramic view, set area-of-interest, make obstacle car rear end profile
It is positioned at area-of-interest；(9) to described area-of-interest image gray processing, do rim detection, obtain obstacle
The Herba Plantaginis end profile protruding point i.e. coordinate of rearmost point；(10) hung down to the straight line simulated by rearmost point
Line, determines obstacle car rear end profile position in global coordinate system.
The level detecting apparatus of parking of Intelligent parking system the most according to claim 1, it is characterised in that: described sensing
Device unit includes being positioned at vehicle front side, rear side, left side, four wide-angle cameras on right side and being positioned at vehicle both sides
Ultrasonic distance-measuring sensor.
The level detecting apparatus of parking of Intelligent parking system the most according to claim 2, it is characterised in that: described four
The installation site of photographic head should ensure that four camera collections to picture cover 360 degree of regions of vehicle's surroundings,
And adjacent two camera collections to picture have overlapping region.
The level detecting apparatus of parking of Intelligent parking system the most according to claim 1, it is characterised in that: described man-machine
Interface output module by the parking position Overlapping display that detects on panoramic view, if be detected that parking position the most just
Really or do not meet the wish of driver, driver can adjust position and or the side of parking position by input module
To, driver change parking position position and or direction after, new four angular coordinates of parking position are exported
The path planning module of Intelligent parking system.
The level detecting apparatus of parking of Intelligent parking system the most according to claim 1, it is characterised in that park described in:
Bit line detection sub-module determines that the method for parking position comprises the steps: (1) Image semantic classification；(2) from looking around
Figure extracts straight line；(3) straight line is carried out post processing, the line segment corresponding to retain ground parking position line, delete
Other mixed and disorderly line segments；(4) rectangle parking position is obtained.
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Families Citing this family (71)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104943686B (en) * | 2014-03-28 | 2018-11-06 | 北京奇虎科技有限公司 | Automatic parking implementation method and device based on wireless signal identification |
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| CN113085838A (en) * | 2021-04-02 | 2021-07-09 | 的卢技术有限公司 | Parking space detection method and system based on multi-sensor fusion |
| CN114494428B (en) * | 2021-12-23 | 2022-11-11 | 禾多科技（北京）有限公司 | Vehicle pose correction method and device, electronic equipment and computer readable medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1642808A1 (en) * | 2004-09-30 | 2006-04-05 | CLARION Co., Ltd. | Parking-assist system using image information from an imaging camera and distance information from an infrared laser camera |
| CN1987357A (en) * | 2006-12-26 | 2007-06-27 | 浙江工业大学 | Intelligent parking auxiliary device based on omnibearing computer sight |
| CN101218127A (en) * | 2005-07-08 | 2008-07-09 | 罗伯特·博世有限公司 | Parking device |
| CN101426669A (en) * | 2006-04-25 | 2009-05-06 | 丰田自动车株式会社 | Parking assistance device and parking assistance method |
| CN102449673A (en) * | 2009-06-03 | 2012-05-09 | 爱信精机株式会社 | Method of monitoring the surroundings of a vehicle, and device for monitoring the surroundings of a vehicle |
| CN102474597A (en) * | 2009-08-03 | 2012-05-23 | 爱信精机株式会社 | Vehicle peripheral image generation device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005343417A (en) * | 2004-06-07 | 2005-12-15 | Auto Network Gijutsu Kenkyusho:Kk | Parking assisting device |
-
2013
- 2013-11-06 CN CN201310545995.5A patent/CN103600707B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1642808A1 (en) * | 2004-09-30 | 2006-04-05 | CLARION Co., Ltd. | Parking-assist system using image information from an imaging camera and distance information from an infrared laser camera |
| CN101218127A (en) * | 2005-07-08 | 2008-07-09 | 罗伯特·博世有限公司 | Parking device |
| CN101426669A (en) * | 2006-04-25 | 2009-05-06 | 丰田自动车株式会社 | Parking assistance device and parking assistance method |
| CN1987357A (en) * | 2006-12-26 | 2007-06-27 | 浙江工业大学 | Intelligent parking auxiliary device based on omnibearing computer sight |
| CN102449673A (en) * | 2009-06-03 | 2012-05-09 | 爱信精机株式会社 | Method of monitoring the surroundings of a vehicle, and device for monitoring the surroundings of a vehicle |
| CN102474597A (en) * | 2009-08-03 | 2012-05-23 | 爱信精机株式会社 | Vehicle peripheral image generation device |
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