CN109931939A - Localization method, device, equipment and the computer readable storage medium of vehicle - Google Patents
Localization method, device, equipment and the computer readable storage medium of vehicle Download PDFInfo
- Publication number
- CN109931939A CN109931939A CN201910147235.6A CN201910147235A CN109931939A CN 109931939 A CN109931939 A CN 109931939A CN 201910147235 A CN201910147235 A CN 201910147235A CN 109931939 A CN109931939 A CN 109931939A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- correction amount
- lane line
- initial position
- determined
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Navigation (AREA)
- Traffic Control Systems (AREA)
Abstract
The disclosure provides localization method, device, equipment and the computer readable storage medium of a kind of vehicle, and method includes the initial position for obtaining inertial navigation system and determining vehicle;Carriageway image is obtained, the first correction amount is determined according to initial position, carriageway image;Laser radar scanning data are obtained, according to initial position, laser radar scanning data, determine position correction amount;According to initial position, the first correction amount, position correction amount, the real-time positioning information of vehicle is determined.Localization method, device, equipment and the computer readable storage medium for the vehicle that the disclosure provides, it is compared according to collected data with the positioning result that inertial navigation system obtains, and correction amount is determined based on comparison result, again on the basis of initial position, the correction amount is merged, to obtain current real time position.
Description
Technical field
This disclosure relates to which vehicle positioning technology more particularly to a kind of localization method of vehicle, device, equipment and computer can
Read storage medium.
Background technique
With the development of automatic Pilot technology, automatic driving vehicle is had been applied in real life.In order to guarantee vehicle
Form of security, automatic driving vehicle need in real time positioning, to determine driving direction according to current positioning.
In the prior art, by automatic driving vehicle carry high-precision RTK (Real-time kinematic, in real time
Dynamically) equipment realizes the demand positioned in real time.For RTK equipment using carrier phase difference technology, this technology is to locate in real time
The difference method of two measuring station carrier phase observed quantities is managed, then the carrier phase that base station acquires is issued into receiver user,
It carries out that difference is asked to resolve coordinate.
But carrier phase difference technology has very strong dependence for the accuracy of satellite-signal.And in automatic Pilot
In the driving process of vehicle, often there is dropout problem, such as in tunnel, just easily causes dropout.
Summary of the invention
The disclosure provides localization method, device, equipment and the computer readable storage medium of a kind of vehicle, existing to solve
Locating scheme in the technology technical problem too strong to satellite-signal dependence.
The first aspect of the disclosure is to provide a kind of localization method of vehicle, comprising:
Obtain the initial position that inertial navigation system determines vehicle;
Carriageway image is obtained, the first correction amount is determined according to the initial position, the carriageway image;
Laser radar scanning data are obtained, according to the initial position, the laser radar scanning data, determine that position is repaired
Positive quantity;
According to the initial position, first correction amount, the position correction amount, the real-time positioning of the vehicle is determined
Information.
Another aspect of the disclosure is to provide a kind of positioning device of vehicle, comprising:
Module is obtained, the initial position of vehicle is determined for obtaining inertial navigation system;
First determining module determines that first repairs according to the initial position, the carriageway image for obtaining carriageway image
Positive quantity;
Second determining module is swept for obtaining laser radar scanning data according to the initial position, the laser radar
It retouches data, determine position correction amount;
Locating module, described in determining according to the initial position, first correction amount, the position correction amount
The real-time positioning information of vehicle.
The another aspect of the disclosure is to provide a kind of positioning device of vehicle, comprising:
Memory;
Processor;And
Computer program;
Wherein, the computer program stores in the memory, and is configured to be executed by the processor to realize
The localization method of vehicle as described in above-mentioned first aspect.
The another aspect of the disclosure is to provide a kind of computer readable storage medium, is stored thereon with computer program,
The computer program is executed by processor the localization method to realize the vehicle as described in above-mentioned first aspect.
The localization method of vehicle, device, equipment and the computer readable storage medium that the disclosure provides have the technical effect that
Localization method, device, equipment and the computer readable storage medium for the vehicle that the disclosure provides, method include obtaining
Inertial navigation system determines the initial position of vehicle;Carriageway image is obtained, the first amendment is determined according to initial position, carriageway image
Amount;Laser radar scanning data are obtained, according to initial position, laser radar scanning data, determine position correction amount;According to initial
Position, the first correction amount, position correction amount, determine the real-time positioning information of vehicle.The localization method for the vehicle that the disclosure provides,
Device, equipment and computer readable storage medium, the positioning result obtained according to collected data and inertial navigation system into
Row compares, and determines correction amount based on comparison result, then on the basis of initial position, merge the correction amount, to be worked as
Preceding real time position.Method, apparatus, equipment and the computer readable storage medium that the disclosure provides, according to the practical row of vehicle
It sails situation to be adjusted on the basis of the initial position that inertial navigation obtains, to obtain accurately current vehicle location, energy
Enough realize the function of positioning in real time.
Detailed description of the invention
Fig. 1 is the flow chart of the localization method of the vehicle shown in an exemplary embodiment of the invention;
Fig. 2 is the flow chart of the localization method of the vehicle shown in another exemplary embodiment of the present invention;
Fig. 3 is the structure chart of the positioning device of the vehicle shown in an exemplary embodiment of the invention;
Fig. 4 is the structure chart of the positioning device of the vehicle shown in another exemplary embodiment of the present invention;
Fig. 5 is the structure chart of the positioning device of the vehicle shown in an exemplary embodiment of the invention.
Specific embodiment
In current automatic driving vehicle, need to install RTK equipment, for positioning in real time.But work as automatic driving vehicle
When by satellite-signal is poor or satellite-signal is lost region, the problem of will cause RTK equipment position inaccurate, for example,
In tunnel, vehicle can not receive satellite-signal.
Fig. 1 is the flow chart of the localization method of the vehicle shown in an exemplary embodiment of the invention.
As shown in Figure 1, the localization method of vehicle provided in this embodiment includes:
Step 101, the initial position of vehicle is determined according to inertial navigation system.
Wherein, method provided in this embodiment is by having the execution of the electronic equipment of computing capability, such as processor.The electronics
Equipment can be set in automatic driving vehicle, for being positioned in real time to vehicle.
Specifically, method provided in this embodiment, based on the location information obtained based on inertial navigation system, to its into
Row amendment, to obtain real-time vehicle location information.Inertial navigation system be one kind independent of external information, also not outward
The autonomic navigation system of portion's radiation energy.The basic functional principle of inertial navigation system be based on Newton mechanics law,
By measurement carrier in the acceleration of inertial reference system, it integrates the time, and it is transformed in navigational coordinate system,
It can obtain the information such as speed, yaw angle and the position in navigational coordinate system.
Further, inertial navigation system can be set in the electronic equipment for executing method provided in this embodiment,
It can be set in other electronic equipments, which can interact with electronic equipment, so that it is initial to send it to electronic equipment
Position.The request for obtaining location information can also be sent from electronic equipment to inertial navigation system, to make it to electronic equipment
Feed back initial position.
When practical application, since navigation information is generated by integral, position error increases at any time, long-term accuracy
Difference.Therefore, if directlying adopt the positioning result that inertial navigation system determines, there are problems that low precision.It is provided in this embodiment
In method, according to the ambient condition information that vehicle perceives, which is modified, to obtain accurate real time position
Information.
Further, it is also possible to which revised real time position is input in inertial navigation system, make it based on the current position
Set the initial position for determining lower a moment.
Step 102, carriageway image is obtained, the first correction amount is determined according to initial position, carriageway image.
Wherein, automatic driving vehicle is generally provided with context aware systems, especially by equipment such as camera, sensors
Environmental information around obtaining, to carry out environment sensing.In method provided in this embodiment, using in automatic driving vehicle
Environment sensing equipment determines vehicle-periphery, and is modified according to vehicle-periphery to initial position.
Specifically, the image capture module for shooting carriageway image can be set on automatic driving vehicle,
Such as camera.The quantity of camera can be configured according to demand.For example, in order to obtain the richer environment letter of information
Breath, then can be set multiple cameras.The shooting direction of these cameras can be towards headstock direction, to pass through these
Carriageway image determines the road information of vehicle front.
Further, the electronic equipment for executing the present embodiment can control camera collection image, then obtains camera and adopt
The image of collection.In order to be positioned in real time according to the carriageway image of shooting in vehicle travel process, it can control these camera shootings
Head carries out shooting photo with higher frequency, or is continuously recorded a video.
When practical application, if camera shooting is video recording, then electronic equipment can receive the video recording, and with certain
Frequency therefrom extracts frame image, handles frame image.
Wherein, electronic equipment can determine the first correction amount according to carriageway image and initial position message.
Electronic equipment can identify carriageway image after obtaining carriageway image.Determine marker therein, then
Based on marker, the location information of vehicle in the road is determined, to determine with initial position according to the location information
One correction amount.Marker for example can be lane line, can also be that the building etc. in roadside can also be in road such as high building
Direction board.The priority of marker can also be set, such as lane line highest priority is that 5, the preferential level of sign board is a height of
4, the priority of building is 3 etc., can go to determine marker in carriageway image based on priority is suitable, and then be based on marker
Determine the location information of vehicle.
Further, since carriageway image is that the image capture module being arranged on vehicle is shot, according to the figure
As the parameter of acquisition module, distance of the vehicle compared to marker can be determined.When marker is lane line, can determine
The relative position of vehicle and every lane line.When marker is other objects, the phase between vehicle and other objects can be determined
To position.
When practical application, according to the relative position between vehicle and marker, the current location information of vehicle, example can be determined
Such as, vehicle is between Article 2 lane line and Article 3 lane line.For another example 100 meters of vehicle front have traffic sign
To think that vehicle 100 meters of traffic sign rear, can also determine the relative direction of vehicle and traffic sign.
Wherein it is possible to be repaired using the location information determined according to carriageway image to the corresponding information in initial position
Just.It is believed that being also capable of determining that the location information between vehicle and marker according to initial position, therefore, this can be based on
Two location informations determine the first correction amount, are modified further according to the correction amount to initial position.
Further, automatic driving vehicle in motion, depends on high-precision map.High-precision map is auxiliary comprising largely driving
Supplementary information.Such as intersection and road sign position, traffic lights information, the environmental information around road.
When practical application, corresponding position can be determined in high-precision map according to the initial position of vehicle.And according to this
Position, determining in high-precision map, the relative position of the marker in vehicle and carriageway image.It can be according to the two with respect to position
It sets, determines the first correction amount.
Wherein, which may include distance, angle, direction etc..For example, marker is lane line, then phase
Include the relative distance of vehicle Yu every lane line to position, can also include the direction of the lane line nearest apart from vehicle.If
Marker is building etc., then relative position may include vehicle between building at a distance from, can also include vehicle and building
Relative direction between object.The two relative positions can be compared, to obtain the first correction amount.It can also be to the two with respect to position
It sets and is weighted processing, then determine the first correction amount.
Step 103, laser radar scanning data are obtained, according to initial position, laser radar scanning data, determine that position is repaired
Positive quantity.
Further, in method provided in this embodiment, laser radar scanning device can also be set, for obtaining on vehicle
Take the environmental data of surrounding.The laser radar scanning data that the available device of electronic equipment scans.
When practical application, high-precision map is that the data based on high-precision RTK equipment and laser radar acquisition are drawn and obtained, because
This, includes laser radar scanning data in high-precision map.It can be determined according to initial position based on inertia in high-precision map
The current vehicle position that navigation system obtains, the laser radar data around the available position.
Wherein, search range can also be delimited centered on vehicle initial position in high-precision map, in the search range
It is interior, determine the position to match with the laser radar scanning data that currently obtain, and by the position, be determined as current vehicle can
Energy position, at this point it is possible to which the initial position based on the possible position and vehicle, determines position correction amount.It can specifically count
Calculate the weighted sum result of two positions.
Specifically, including that high-precision swashs in order to improve matching precision, in method provided in this embodiment, in high-precision map
Luminous point cloud reflectivity map and high-precision laser point cloud height map.In high-precision laser point cloud reflectivity map, including
The emissivity information of ground or surrounding scenes, in high-precision laser point cloud height map, including ground and surrounding scenes
Elevation information.
It further, can be based on the laser radar of acquisition when determining the possible position of current vehicle in high-precision map
In scan data, including reflectivity information and elevation information, be compared respectively at these information in high-precision map, from
And more accurately determine vehicle possible position.
The timing of step 102 and step 103 is not limited, and can first carry out step 102, can also first carry out step
103.It may also be performed simultaneously the two steps.
Step 104, according to initial position, the first correction amount, position correction amount, the real-time positioning information of vehicle is determined.
, can be on the basis of initial position when practical application, the first correction amount, the position correction amount being superimposed, from
And obtain real-time positioning information.The real-time positioning information is to the revised location information of initial position.
Wherein, in order to keep positioning result more smooth, Extended Kalman filter frame can also be set, by initial position with
Obtained the first correction amount, position correction amount is merged, to obtain final real-time positioning information.
Specifically, as determining that the first correction amount may be different with duration spent by determining position correction amount, it can
First determining correction amount and initial position are inputted Kalman filtering frame, merge it first.The amendment obtained afterwards
Amount then inputs Kalman filtering frame afterwards, is merged again with obtained fusion results, to make real-time location response
Speed is faster.
Further, it after real time position has been determined, can also be inputted in inertial navigation system.So that inertial navigation
Real time position of the system based on calculating, determines the vehicle location of subsequent time.The initial position of i.e. next vehicle.Practical application
When, quickly due to existing processor calculating speed, from initial position is obtained to finally calculating the time of real time position very
It is short, in general less than 0.01 second, for the vehicle for using the real-time positioning information, calculate generated time error not
It will affect the normally travel of vehicle, therefore, they are negligible due to calculating bring time loss.
Wherein, in method provided in this embodiment, initial position can be to be obtained by GPS signal, position hereafter
Positioning result of the information independent of GPS.
For method provided in this embodiment for being positioned in real time to vehicle, this method is provided in this embodiment by being provided with
The equipment of method executes, which realizes usually in a manner of hardware and/or software.
The localization method of vehicle provided in this embodiment determines the initial position of vehicle including obtaining inertial navigation system;
Carriageway image is obtained, the first correction amount is determined according to initial position, carriageway image;Laser radar scanning data are obtained, according to first
Beginning position, laser radar scanning data, determine position correction amount;According to initial position, the first correction amount, position correction amount, really
Determine the real-time positioning information of vehicle.Localization method, device, equipment and the computer-readable storage medium of vehicle provided in this embodiment
Matter is compared according to collected data with the positioning result that inertial navigation system obtains, and is repaired based on comparison result determination
Positive quantity, then on the basis of initial position, the correction amount is merged, to obtain current real time position.It is provided in this embodiment
Method, apparatus, equipment and computer readable storage medium are obtained according to the actual travel situation of vehicle in inertial navigation initial
It is adjusted on the basis of position, to obtain accurately current vehicle location, can be realized the function of positioning in real time.
Fig. 2 is the flow chart of the localization method of the vehicle shown in another exemplary embodiment of the present invention.
As shown in Fig. 2, the localization method of vehicle provided in this embodiment, comprising:
Step 201, the initial position that inertial navigation system determines vehicle is obtained.
Step 201 is similar with the concrete principle of step 101 and implementation, and details are not described herein again.
Step 202, carriageway image is obtained.
Step 202 is similar with the concrete principle of the acquisition carriageway image in step 102 and implementation, no longer superfluous herein
It states.
Step 203, the lane line information in carriageway image is identified according to default Lane detection module.
In method provided in this embodiment, after obtaining carriageway image, vehicle and marker can be determined in carriageway image
Between relative position, to obtain the location information of vehicle, in the present embodiment, the marker of use is lane line.Due to vehicle
Diatom will not be easily changed, and be both provided with lane line in most of road, therefore, can identify the lane in carriageway image
Line information determines the location information of vehicle in the road based on lane line information.
Lane detection module is obtained wherein it is possible to train in advance, for identification the lane line in carriageway image.
Specifically, training dataset can be prepared, for training Lane detection module.Image can be prepared in advance, and
Lane center is marked in pre-set image, which, which can be, is labeled with vehicle visual angle, for example, in advance really
Determine the position of image capture module in vehicle, and first determines vehicle position in pre-set image, then adopt with image in vehicle
Collect the angle of module, marks lane center.
Further, pixel expansion can also be carried out in pre-set image according to lane center, lane line is formed, if vehicle
Diatom be it is white, then can be centered on lane center, to the two sides vertical with lane center simultaneously by pixel
Color is set as white, forms the lane line with one fixed width.In pixel expands, the pixel quantity of expansion with away from
Become remote from vehicle location and reduces.For example, in the color image of 1920*1200 size, close to the nearest position of vehicle, pixel
Expansion amount is 80, and whenever the position on lane line is far from 16 pixels of vehicle, pixel expansion amount just reduces 1, so that obtaining
The pre-set image with lane line be more in line with vehicle visual angle.
When practical application, it is opposite that lane line in pre-set image first position in the picture, lane line can also be marked
Relative position, lane line type in vehicle.Wherein, the first position of lane line in the picture refers to lane line institute in the picture
The location of pixels accounted for.In the picture, two-dimensional coordinate system can be set, abscissa is for marking the position of pixel horizontally
Value, ordinate for marking the positional value of pixel in the longitudinal direction, for example, in the picture (5,4) then indicate laterally upper 5th row and
The pixel of longitudinal upper 4th column intersection.
Wherein, lane line refers to relative to the relative position of vehicle, using vehicle as object of reference, the position of lane line, for example,
For vehicle, the 1st article of left side lane line, the 2nd article of left side lane line, the 1st article of the right lane line, the 2nd article of the right lane
Line etc..It can also include middle lane line if it is supreme that vehicle is in a lane line.
Specifically, lane line type may include a variety of, such as white dashed line, solid white line, dotted yellow line, yellow be real
Line, double blank dotted line, double yellow solid lines, yellow actual situation line, double blank solid line etc..
Further, the first position in the picture of lane line in pre-set image, lane line can be marked relative to vehicle
The information such as the second position, lane line type obtain lane line and according to pre-set image and its markup information training neural network
Identification module.
When practical application, associated losses function can be constructed, and pre-set image is inputted in neural network framework, in conjunction with damage
Lose the backpropagation optimization process that is iterated of function, first for lane line in the picture of continuous strength neural network
It sets, the degree of understanding of the information such as relative position, lane line type of the lane line relative to vehicle.When the degree of understanding of neural network
After reaching certain level, so that it may terminate training, obtain Lane detection module.
Wherein, the carriageway image that will acquire inputs trained Lane detection module, and the module can be made to export the vehicle
The lane line information of road image, lane line information include relative position and/or lane line type of the lane line relative to vehicle.Tool
Body can export the result figure for different lane line types, can also export result figure of the lane line relative to vehicle location.
Specifically, for the lane line of each type, such as dotted line lane line, a width result figure can be exported, it should
In types results figure, including pixel each in carriageway image whether be dotted line lane line result.
Further, the position for lane line relative to vehicle, such as come relative to the 1st article of vehicle left side lane line
It says, a width result figure can be exported, whether each pixel is the 1st article of left side vehicle in the position result figure, including in carriageway image
The result of diatom.
When practical application, the lane line information in carriageway image can be determined in conjunction with several result figures.For example, for
It for one pixel, is shown in result figure, belongs to the 1st article of vehicle left side lane line, and be dotted line, lane figure can be integrated
Multiple pixels as in, determine final lane line.
Wherein, it can also first determine the lane line position in carriageway image for vehicle, that is, determine every vehicle
Diatom, then based on the corresponding lane line classification of pixel in every lane line, determine the final classification of the lane line.
Step 204, vehicle is determined according to the image capture module parameter of the lane line information, the acquisition carriageway image
The first relative position between the lane line.
Specifically, since lane line prints on the ground, it is therefore contemplated that the height value of lane line is 0, and
Vehicle is to travel on road surface, therefore the relative altitude of vehicle and lane line is inconvenient, and then the image capture module on vehicle
It is also constant with the relative altitude of lane line.At this point it is possible to according to position of the lane line in image coordinate system and Image Acquisition
Module parameter determines the relative position information between vehicle and automatic driving vehicle.
It further, can also be according to the image capture module being arranged on vehicle in the relative position of vehicle, more accurately
Determine the relative position of vehicle and automatic driving vehicle.For example, the left side of vehicle and the lane line spacing close to left side, vehicle
The lane line spacing etc. on right side and close right side.
When practical application, the first relative position may be considered the carriageway image currently acquired according to vehicle, obtained vehicle
Relative position between lane line.
Step 205, the second relative position between vehicle and lane line is determined according to initial position.
Wherein, in presetting high-precision map determine initial position, and determine vehicle in initial position, vehicle and lane line
Between the second relative position.
Specifically, identical as the content for including in the first relative position, the second relative position also includes vehicle and lane line
The information such as distance, relative position.Can related data directly be collected in high-precision map.For example, with vehicle in initial bit
The visual angle set obtains the multi-view image in high-precision map, and obtains the second relative position based on the multi-view image.
It is considered that the second relative position is the vehicle obtained based on inertial navigation system and the relative position of lane line.
It determines the first relative position and determines the timing of the second relative position with no restrictions.
Step 206, the first correction amount is determined according to the first relative position, the second relative position.
Further, it in method provided in this embodiment, can be determined based on the first relative position, the second relative position
First correction amount.The relative position of the vehicle and lane line that are namely obtained according to inertial navigation system, and obtained according to vehicle
The relative position of vehicle and lane line that the carriageway image taken obtains, the first obtained correction amount.
When practical application, by the angle of the relative position information of vehicle and lane line available vehicle and lane line,
The direction of vehicle can be determined based on the angle, in addition, the relative position can also include the spacing of vehicle and lane line.Cause
This, in method provided in this embodiment, the first correction amount may include towards two kinds of angle correction, spacing correction amount.
Wherein it is possible to according to the determination of the first relative position and the nearest target lane line of vehicle distances.
Specifically, can be determined nearest with vehicle distances according to the relative position of the lane line and vehicle determined
Target lane line.Target lane line is determined by the carriageway image currently acquired.
It wherein, may include the relative direction and relative distance between lane line and vehicle in first relative position,
For example, lane line, at 0.2 meter of vehicle right side, lane line is at 0.8 meter of vehicle left side.It can determine wherein apart from vehicle
Nearest lane line.
Specifically, can also be determined according to carriageway image the first of target lane line towards angle information.
Further, it is believed that the vertical direction of carriageway image is vehicle sight line direction, and the direction can be with headstock court
To identical.Therefore, Vertical Square of the lane line relative to the carriageway image can be determined in the carriageway image that vehicle visual angle obtains
To angle, as first towards angle information.If vehicle-to-target lane line is parallel, it is believed that angle is 0.
When practical application, in carriageway image, target lane line is a complete lane line, available target lane
The angle of line and carriageway image vertical direction, as first towards angle information.
In presetting high-precision map, determined according to the second relative position the second of target lane line towards angle information.
Wherein it is possible to, in initial position, the second court of target lane line be determined with vehicle visual angle in presetting high-precision map
To angle information.For example it may be predetermined that for obtaining the image capture module of carriageway image and the opposite position of vehicle in vehicle
It sets.Vehicle location, then the position of forecast image acquisition module are determined in high-precision map according to initial position, and are based on the position
It sets, determines the second of target lane line towards angle information.It specifically can be, with the determining target lane line in vehicle visual angle and be somebody's turn to do
The angle of visual angle longitudinal direction.
Specifically, can also be determined towards angle information, second towards angle information towards angle correction according to first.
First may be considered the current target lane line determined based on carriageway image and vehicle court towards angle information
To angle, second towards angle information may be considered based on inertial navigation system determine current target lane line and vehicle
The angle of direction.The data that can be obtained according to different approaches, obtain two towards angle, and are determined according to the two towards angle
Towards angle correction.For example, the two can be subtracted each other towards angle, obtain towards angle correction.
Further, it in method provided in this embodiment, can also be determined according to the first relative position, the second relative position
The distance between vehicle and lane line correction amount out.
When practical application, the first distance between every lane line and vehicle can be determined according to the first relative position.
Specifically the between every lane line and vehicle can be determined first according to the first relative position determined in carriageway image
One distance.For example, vehicle is at a distance from the lane line of first, left side, vehicle at a distance from the Article 2 lane line of left side, vehicle with
The distance of first lane line in right side.
The image spacing between vehicle and lane line first can be determined according to the first relative position, then be converted into world's seat
Mark the spacing of system.For example, the pixel according to shared by lane line and lane line developed width, determine the corresponding reality of a pixel
Border distance determines the actual range between vehicle and lane line so as to be based on the corresponding relationship.
The second distance between every lane line and vehicle is determined according to the second relative position.
Wherein it is possible to find the corresponding initial position of vehicle, and determine vehicle in the position in presetting high-precision map
When, the second distance of vehicle and each lane line.Position herein may include the information such as the coordinate position of vehicle, direction.This
When, lane line should be corresponding with the lane line in first distance is determined.For example, first, above-mentioned left side lane line is lane line A, then
In high-precision map, determine vehicle in initial position, the spacing of vehicle and lane line A;For another example above-mentioned left side Article 2 vehicle
Diatom be lane line B, then in high-precision map, determine vehicle in initial position, the spacing of vehicle and lane line B.
It is believed that the first spacing be according to carriageway image determine current vehicle and each lane line spacing, second
Spacing may be considered the spacing of the current vehicle and each lane line that determine according to inertial navigation positioning result.
Determine that first distance is not limited with the timing for determining second distance.
Specifically, the range correction of vehicle can also be determined according to first distance, second distance.
Further, vehicle can be determined in the vertical direction relative to lane line according to first distance, second distance
On, the difference between different distance.For example, the difference between first distance and second distance can be calculated, it is also based on inertia
The stability of navigation system and the stability of image recognition result determine weighted value, based on weight in the difference for determining the two.
Step 207, laser radar scanning data are obtained.
Step 207 is similar with the concrete principle and implementation that obtain laser radar scanning data in step 103, herein not
It repeats again.
Step 208, region of search is determined in presetting high-precision map according to initial position.
Further, initial position is the vehicle location that inertial navigation system is determined, it is therefore contemplated that vehicle obtains
Laser radar scanning data be consistent with the position around the initial position.Due to the unstability of inertial navigation, it is possible to swash
Optical radar scan data data corresponding with initial position are not inconsistent, still, will not be especially remote apart from the position.It therefore, can be with base
Region of search delimited in initial position, in the area the determining position to match with laser radar scanning data.
When practical application, the size specifically to draw the line can be determined based on the stability of inertial navigation system, if should
The precision of system is higher, such as can delimit 5 meters * 5 meters of range centered on initial position.If the system accuracy is lower,
Such as 20 meters * 20 meters of range can be delimited centered on initial position.The range is also possible to the center of circle, rectangle etc., not right
It is limited.
Ratio, that is, addiction 207 and the timing of step 208 are not limited.
Step 209, according to laser radar scanning data in region of search determine matching position, and according to matching position,
Initial position determines position correction amount.
Can in the region of search, determine with the most matched position of laser radar scanning data, as basis
The current location for the vehicle that laser radar scanning data determine.
Further, initial position and matching position can be compared, so that it is determined that out position correction amount.
It may include reflectivity information in laser radar scanning data when practical application, can also include elevation information.Cause
This, in method provided in this embodiment, can determine to match in high-precision map jointly according to reflectivity information, elevation information
Position.
Wherein it is possible to be determined and highest first matching value of reflectivity information matching degree in region of search.It can be
In the region of search of high-precision map, compares the reflectivity information of each position and the reflectivity in laser radar scanning data is believed
Breath, so that it is determined that the matching degree of each position out.In method provided in this embodiment, can based on vehicle visual angle preset it is high-precision
Reflectivity information around being obtained in map, and be compared with the reflectivity information in laser radar scanning data.
Specifically, highest first matching value can be determined in matching degree, it can also be corresponding by first matching value
Position be determined as the first matching position.
Further, it can also be determined and highest second matching value of elevation information matching degree in region of search.It can
To obtain the elevation information in laser radar scanning data, and compare in the region of search of high-precision map, the height of each position
The elevation information of information and acquisition, so that it is determined that the matching degree of each position out.It is similar, it can also be with vehicle visual angle default
The elevation information in region of search around each position is obtained in high-precision map.
When practical application, available highest second matching value of wherein matching degree can also be by second matching value pair
The position answered is determined as the second matching position.
Wherein it is possible to determine position correction amount according to the first matching value, the second matching value, initial position.
Specifically, final matching position can be determined according to the first matching value, the second batch configuration, further according to the matching
Position, originally determined position correction amount.
Further, the first weighted value, the second weighted value can be determined according to the first matching value, the second matching value.For example,
First matching value is 90%, and the second matching value is 60%, then the first weighted value can beSecond weight
Value can beBoth in method provided in this embodiment, the two matching values can be merged, and determined
Square accounting, accounting is then determined as the corresponding weighted value of two matching values.
Specifically, the accuracy of two matching values can also be measured according to determining weighted value, at this point, power can also be arranged
Weight threshold value abandons its corresponding weighted value, and directly by another weight if the weighted value being calculated is lower than weight threshold
It is worth corresponding matching position as target position, i.e., the current vehicle position determined according to radar scanning data.
It further, can also be according to the first matching value corresponding first if two weighted values are all larger than weight threshold
Corresponding second matching position of matching position, the second matching value, the first weighted value, the second weighted value determine target position.
When practical application, the first matching position or the second matching position can indicate in digital form, for example, x coordinate,
The information such as y-coordinate.The weighted sum of the first matching position and the second matching position can be calculated as a result, to obtain target position
It sets.
Wherein it is possible to calculate separately the x coordinate weighted sum of the first matching position and the second matching position as a result, first
Y-coordinate weighted sum with position and the second matching position is as a result, coordinate as target position.As needed, can also increase
Add z coordinate parameter.First weighted value is the weighted value of the first matching position, and the second weighted value is the weight of the second matching position
Value.
Specifically, can also determine position correction amount according to initial position, target position after obtaining target position.Example
The alternate position spike that two positions can such as be calculated, obtains position correction amount.
Step 210, the first update information, position correction information are merged with initial position, obtains positioning letter in real time
Breath.
It further,, can also be to determining in order to guarantee the flatness of positioning result in method provided in this embodiment
To the first update information, position correction information merged with initial position.Kalman filtering frame specifically can be set, it will
Initial position, the first correction amount, position correction amount input in the frame, to obtain fused real-time positioning information.
When practical application, if the first correction amount is different from the time that position correction measures, it can be repaired what is first obtained
Positive quantity and initial position input Kalman filtering frame.
It wherein, can further include towards angle correction and range correction, at this point, if court in the first correction amount
It is different from the time that range correction obtains to angle correction, the correction result first obtained can also be inputted into Kalman filtering frame
Frame.
Fig. 3 is the structure chart of the positioning device of the vehicle shown in an exemplary embodiment of the invention.
As shown in figure 3, the positioning device of vehicle provided in this embodiment, comprising:
Module 31 is obtained, the initial position of vehicle is determined for obtaining inertial navigation system;
First determining module 32 determines first according to the initial position, the carriageway image for obtaining carriageway image
Correction amount;
Second determining module 33, for obtaining laser radar scanning data, according to the initial position, the laser radar
Scan data determines position correction amount;
Locating module 34, for determining institute according to the initial position, first correction amount, the position correction amount
State the real-time positioning information of vehicle.
It obtains module 31 to be separately connected with the first determining module 32, the second determining module 33, locating module 34 and first is really
Cover half block 32, the second determining module 33 are separately connected.
The positioning device of vehicle provided in this embodiment, comprising:
Module is obtained, the initial position of vehicle is determined for obtaining inertial navigation system;First determining module, for obtaining
Carriageway image determines the first correction amount according to initial position, carriageway image;Second determining module is swept for obtaining laser radar
Data are retouched, according to initial position, laser radar scanning data, determine position correction amount;Locating module, for according to initial bit
It sets, the first correction amount, position correction amount, determines the real-time positioning information of vehicle.The positioning device of vehicle provided in this embodiment,
It is compared according to collected data with the positioning result that inertial navigation system obtains, and is determined and corrected based on comparison result
Amount, then on the basis of initial position, the correction amount is merged, to obtain current real time position.Dress provided in this embodiment
It sets, is adjusted on the basis of the initial position that inertial navigation obtains according to the actual travel situation of vehicle, to obtain accurately
Current vehicle location, can be realized the function of positioning in real time.
The concrete principle and implementation of the positioning device of vehicle provided in this embodiment with embodiment class shown in FIG. 1
Seemingly, details are not described herein again.
Fig. 4 is the structure chart of the positioning device of the vehicle shown in another exemplary embodiment of the present invention.
As shown in figure 4, on the basis of the above embodiments, the positioning device of vehicle provided in this embodiment, described first
Determining module 32, comprising:
Recognition unit 321, for identifying the lane line information in the carriageway image according to default Lane detection module;
Relative position determination unit 322, for the Image Acquisition according to the lane line information, the acquisition carriageway image
Module parameter determines the first relative position between vehicle and the lane line;
The relative position determination unit 322 is also used to determine the vehicle and the lane line according to the initial position
Between the second relative position;
First correction amount determination unit 323, for determining institute according to first relative position, second relative position
State the first correction amount.
Optionally, the lane line information includes relative position and/or lane line class of the lane line relative to the vehicle
Type.
Described device further includes training module 35, is used for:
Lane center is marked in pre-set image, and pixel is carried out in the pre-set image according to the lane center
Expand, forms lane line;
The first position in the picture of lane line described in the pre-set image, the lane line are marked relative to vehicle
The relative position, the lane line type;
According to the pre-set image and its markup information training neural network, the Lane detection module is obtained.
Optionally, the relative position determination unit 322 is specifically used for:
The initial position is determined in presetting high-precision map, and determine vehicle in the initial position, vehicle and institute
State the second relative position between lane line.
Optionally, the first correction amount determination unit 323, is specifically used for:
According to first relative position determination and the nearest target lane line of the vehicle distances;
It is determined according to the carriageway image the first of the target lane line towards angle information;
In presetting high-precision map, determine the target lane line according to second relative position second is believed towards angle
Breath;
It is determined towards angle information, described second towards angle information towards angle correction according to described first.
The first correction amount determination unit 323, is also used to:
The first distance between every lane line and the vehicle is determined according to first relative position;
The second distance between every lane line and the vehicle is determined according to second relative position;
According to the first distance, the second distance, the range correction of the vehicle is determined.
Second determining module 33 includes:
Area determination unit 331, for determining region of search in presetting high-precision map according to the initial position;
Position correction amount determination unit 332, for true in described search region according to the laser radar scanning data
Determine matching position, and the position correction amount is determined according to the matching position, the initial position.
The position correction amount determination unit 332 is specifically used for:
In described search region, determine and highest first matching value of reflectivity information matching degree;
The elevation information in the laser radar scanning data is obtained, in described search region, is determined and the height
Spend highest second matching value of information matches degree;
The position correction amount is determined according to first matching value, second matching value, the initial position.
The position correction amount determination unit 332 is specifically used for:
The first weighted value, the second weighted value are determined according to first matching value, second matching value;
According to corresponding first matching position of first matching value, corresponding second match bit of second matching value
It sets, first weighted value, second weighted value determine target position;
The position correction amount is determined according to the initial position, the target position.
The locating module 34 is specifically used for:
First correction amount, the position correction amount are merged with the initial position, it is described fixed in real time to obtain
Position information.
The concrete principle and implementation of the positioning device of vehicle provided in this embodiment with embodiment class shown in Fig. 2
Seemingly, details are not described herein again.
Fig. 5 is the structure chart of the positioning device of the vehicle shown in an exemplary embodiment of the invention.
As shown in figure 5, the positioning device of vehicle provided in this embodiment includes:
Memory 51;
Processor 52;And
Computer program;
Wherein, the computer program is stored in the memory 51, and be configured to by the processor 52 execute with
Realize the localization method of any vehicle as described above.
The present embodiment also provides a kind of computer readable storage medium, is stored thereon with computer program,
The computer program is executed by processor the localization method to realize any vehicle as described above.
Those of ordinary skill in the art will appreciate that: realize that all or part of the steps of above-mentioned each method embodiment can lead to
The relevant hardware of program instruction is crossed to complete.Program above-mentioned can be stored in a computer readable storage medium.The journey
When being executed, execution includes the steps that above-mentioned each method embodiment to sequence;And storage medium above-mentioned include: ROM, RAM, magnetic disk or
The various media that can store program code such as person's CD.
Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention., rather than its limitations;To the greatest extent
Pipe present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: its according to
So be possible to modify the technical solutions described in the foregoing embodiments, or to some or all of the technical features into
Row equivalent replacement;And these are modified or replaceed, various embodiments of the present invention technology that it does not separate the essence of the corresponding technical solution
The range of scheme.
Claims (14)
1. a kind of localization method of vehicle characterized by comprising
Obtain the initial position that inertial navigation system determines vehicle;
Carriageway image is obtained, the first correction amount is determined according to the initial position, the carriageway image;
Laser radar scanning data are obtained, according to the initial position, the laser radar scanning data, determine position correction
Amount;
According to the initial position, first correction amount, the position correction amount, the real-time positioning letter of the vehicle is determined
Breath.
2. the method according to claim 1, wherein described true according to the initial position, the carriageway image
Fixed first correction amount, comprising:
The lane line information in the carriageway image is identified according to default Lane detection module;
Vehicle and the lane line are determined according to the image capture module parameter of the lane line information, the acquisition carriageway image
Between the first relative position;
The second relative position between the vehicle and the lane line is determined according to the initial position;
First correction amount is determined according to first relative position, second relative position.
3. according to the method described in claim 2, it is characterized in that, the lane line information includes lane line relative to the vehicle
Relative position and/or lane line type.
4. according to the method described in claim 3, it is characterized by further comprising:
Lane center is marked in pre-set image, and pixel expansion is carried out in the pre-set image according to the lane center
It fills, forms lane line;
The first position in the picture of lane line described in the pre-set image, the lane line are marked relative to described in vehicle
Relative position, the lane line type;
According to the pre-set image and its markup information training neural network, the Lane detection module is obtained.
5. according to the method described in claim 2, it is characterized in that, described determine the vehicle and institute according to the initial position
State the second relative position between lane line, comprising:
The initial position is determined in presetting high-precision map, and determine vehicle in the initial position, vehicle and the vehicle
The second relative position between diatom.
6. according to the method described in claim 2, it is characterized in that, described according to first relative position, second phase
First correction amount is determined to position, comprising:
According to first relative position determination and the nearest target lane line of the vehicle distances;
It is determined according to the carriageway image the first of the target lane line towards angle information;
In presetting high-precision map, determined according to second relative position the second of the target lane line towards angle information;
It is determined towards angle information, described second towards angle information towards angle correction according to described first.
7. according to the method described in claim 6, it is characterized in that, described according to first relative position, second phase
First correction amount is determined to position, further includes:
The first distance between every lane line and the vehicle is determined according to first relative position;
The second distance between every lane line and the vehicle is determined according to second relative position;
According to the first distance, the second distance, the range correction of the vehicle is determined.
8. the method according to claim 1, wherein described sweep according to the initial position, the laser radar
It retouches data, determine position correction amount, comprising:
Region of search is determined in presetting high-precision map according to the initial position;
According to the laser radar scanning data in described search region determine matching position, and according to the matching position,
The initial position determines the position correction amount.
9. according to the method described in claim 8, it is characterized in that, described search according to the laser radar scanning data described
Matching position is determined in rope region, comprising:
In described search region, determine and highest first matching value of reflectivity information matching degree;
The elevation information in the laser radar scanning data is obtained, in described search region, determines to believe with the height
Cease highest second matching value of matching degree;
The position correction amount is determined according to first matching value, second matching value, the initial position.
10. according to the method described in claim 9, it is characterized in that, it is described according to first matching value, it is described second matching
Value, the initial position determine the position correction amount, further includes:
The first weighted value, the second weighted value are determined according to first matching value, second matching value;
According to corresponding first matching position of first matching value, corresponding second matching position of second matching value, institute
State the first weighted value, second weighted value determines target position;
The position correction amount is determined according to the initial position, the target position.
11. -10 described in any item methods according to claim 1, which is characterized in that it is described according to the initial position, it is described
First correction amount, the position correction amount, determine the real-time positioning information of the vehicle, comprising:
First correction amount, the position correction amount are merged with the initial position, obtain the real-time positioning letter
Breath.
12. a kind of positioning device of vehicle characterized by comprising
Module is obtained, the initial position of vehicle is determined for obtaining inertial navigation system;
First determining module determines the first amendment according to the initial position, the carriageway image for obtaining carriageway image
Amount;
Second determining module, for obtaining laser radar scanning data, according to the initial position, the laser radar scanning number
According to, determine position correction amount;
Locating module, for determining the vehicle according to the initial position, first correction amount, the position correction amount
Real-time positioning information.
13. a kind of positioning device of vehicle characterized by comprising
Memory;
Processor;And
Computer program;
Wherein, the computer program stores in the memory, and is configured to be executed by the processor to realize such as power
Benefit requires any method of 1-11.
14. a kind of computer readable storage medium, which is characterized in that it is stored thereon with computer program,
The computer program is executed by processor to realize the method as described in claim 1-11 is any.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910147235.6A CN109931939B (en) | 2019-02-27 | 2019-02-27 | Vehicle positioning method, device, equipment and computer readable storage medium |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910147235.6A CN109931939B (en) | 2019-02-27 | 2019-02-27 | Vehicle positioning method, device, equipment and computer readable storage medium |
Publications (2)
Publication Number | Publication Date |
---|---|
CN109931939A true CN109931939A (en) | 2019-06-25 |
CN109931939B CN109931939B (en) | 2020-11-03 |
Family
ID=66986032
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910147235.6A Active CN109931939B (en) | 2019-02-27 | 2019-02-27 | Vehicle positioning method, device, equipment and computer readable storage medium |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109931939B (en) |
Cited By (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110207715A (en) * | 2019-06-28 | 2019-09-06 | 广州小鹏汽车科技有限公司 | The modification method and update the system of vehicle location |
CN110333083A (en) * | 2019-06-27 | 2019-10-15 | 中国第一汽车股份有限公司 | Test method, device, test equipment and the storage medium of vehicle durability test |
CN110530372A (en) * | 2019-09-26 | 2019-12-03 | 上海商汤智能科技有限公司 | Localization method, determining method of path, device, robot and storage medium |
CN110794844A (en) * | 2019-11-18 | 2020-02-14 | 北京百度网讯科技有限公司 | Automatic driving method, device, electronic equipment and readable storage medium |
CN111323802A (en) * | 2020-03-20 | 2020-06-23 | 北京百度网讯科技有限公司 | Vehicle positioning method, device and equipment |
CN111523471A (en) * | 2020-04-23 | 2020-08-11 | 北京百度网讯科技有限公司 | Method, device and equipment for determining lane where vehicle is located and storage medium |
CN112558130A (en) * | 2020-12-07 | 2021-03-26 | 安徽江淮汽车集团股份有限公司 | Method, device and equipment for synchronizing positioning data and storage medium |
CN112556720A (en) * | 2019-09-25 | 2021-03-26 | 上海汽车集团股份有限公司 | Vehicle inertial navigation calibration method and system and vehicle |
WO2021115395A1 (en) * | 2019-12-13 | 2021-06-17 | 北京三快在线科技有限公司 | Map-based fault diagnosis |
CN113219486A (en) * | 2021-04-23 | 2021-08-06 | 北京云迹科技有限公司 | Positioning method and device |
CN113218389A (en) * | 2021-05-24 | 2021-08-06 | 北京航迹科技有限公司 | Vehicle positioning method, device, storage medium and computer program product |
CN113280822A (en) * | 2021-04-30 | 2021-08-20 | 北京觉非科技有限公司 | Vehicle positioning method and positioning device |
CN113566834A (en) * | 2021-07-20 | 2021-10-29 | 广州小鹏汽车科技有限公司 | Positioning method, positioning device, vehicle, and storage medium |
CN114252883A (en) * | 2020-09-24 | 2022-03-29 | 北京万集科技股份有限公司 | Target detection method, apparatus, computer device and medium |
CN114937372A (en) * | 2022-05-18 | 2022-08-23 | 安徽蔚来智驾科技有限公司 | Vehicle positioning system, positioning method, vehicle and storage medium |
CN115112114A (en) * | 2022-06-15 | 2022-09-27 | 苏州轻棹科技有限公司 | Processing method and device for correcting orientation angle of vehicle around self-vehicle |
Citations (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102012016867A1 (en) * | 2012-08-25 | 2013-09-26 | Audi Ag | Park assistance system for automatic parking of car at fixed park position in e.g. garage, has stationary verification and monitoring device connectable with controllers over communication link and for monitoring automatic parking process |
US9081385B1 (en) * | 2012-12-21 | 2015-07-14 | Google Inc. | Lane boundary detection using images |
CN105730443A (en) * | 2016-04-08 | 2016-07-06 | 奇瑞汽车股份有限公司 | Vehicle lane changing control method and system |
CN106778593A (en) * | 2016-12-11 | 2017-05-31 | 北京联合大学 | A kind of track level localization method based on the fusion of many surface marks |
CN107422730A (en) * | 2017-06-09 | 2017-12-01 | 武汉市众向科技有限公司 | The AGV transportation systems of view-based access control model guiding and its driving control method |
CN107643086A (en) * | 2016-07-22 | 2018-01-30 | 北京四维图新科技股份有限公司 | A kind of vehicle positioning method, apparatus and system |
CN108089572A (en) * | 2016-11-23 | 2018-05-29 | 百度(美国)有限责任公司 | For the algorithm and infrastructure of steady and effective vehicle location |
CN108303721A (en) * | 2018-02-12 | 2018-07-20 | 北京经纬恒润科技有限公司 | A kind of vehicle positioning method and system |
CN108732603A (en) * | 2017-04-17 | 2018-11-02 | 百度在线网络技术(北京)有限公司 | Method and apparatus for positioning vehicle |
CN108958266A (en) * | 2018-08-09 | 2018-12-07 | 北京智行者科技有限公司 | A kind of map datum acquisition methods |
CN109059906A (en) * | 2018-06-26 | 2018-12-21 | 上海西井信息科技有限公司 | Vehicle positioning method, device, electronic equipment, storage medium |
CN109186625A (en) * | 2018-10-24 | 2019-01-11 | 北京奥特贝睿科技有限公司 | Intelligent vehicle carries out pinpoint method and system using mixing sampling filter |
CN109325390A (en) * | 2017-08-01 | 2019-02-12 | 郑州宇通客车股份有限公司 | A kind of localization method combined based on map with FUSION WITH MULTISENSOR DETECTION and system |
CN109389046A (en) * | 2018-09-11 | 2019-02-26 | 昆山星际舟智能科技有限公司 | Round-the-clock object identification and method for detecting lane lines for automatic Pilot |
-
2019
- 2019-02-27 CN CN201910147235.6A patent/CN109931939B/en active Active
Patent Citations (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102012016867A1 (en) * | 2012-08-25 | 2013-09-26 | Audi Ag | Park assistance system for automatic parking of car at fixed park position in e.g. garage, has stationary verification and monitoring device connectable with controllers over communication link and for monitoring automatic parking process |
US9081385B1 (en) * | 2012-12-21 | 2015-07-14 | Google Inc. | Lane boundary detection using images |
CN105730443A (en) * | 2016-04-08 | 2016-07-06 | 奇瑞汽车股份有限公司 | Vehicle lane changing control method and system |
CN107643086A (en) * | 2016-07-22 | 2018-01-30 | 北京四维图新科技股份有限公司 | A kind of vehicle positioning method, apparatus and system |
CN108089572A (en) * | 2016-11-23 | 2018-05-29 | 百度(美国)有限责任公司 | For the algorithm and infrastructure of steady and effective vehicle location |
CN106778593A (en) * | 2016-12-11 | 2017-05-31 | 北京联合大学 | A kind of track level localization method based on the fusion of many surface marks |
CN108732603A (en) * | 2017-04-17 | 2018-11-02 | 百度在线网络技术(北京)有限公司 | Method and apparatus for positioning vehicle |
CN107422730A (en) * | 2017-06-09 | 2017-12-01 | 武汉市众向科技有限公司 | The AGV transportation systems of view-based access control model guiding and its driving control method |
CN109325390A (en) * | 2017-08-01 | 2019-02-12 | 郑州宇通客车股份有限公司 | A kind of localization method combined based on map with FUSION WITH MULTISENSOR DETECTION and system |
CN108303721A (en) * | 2018-02-12 | 2018-07-20 | 北京经纬恒润科技有限公司 | A kind of vehicle positioning method and system |
CN109059906A (en) * | 2018-06-26 | 2018-12-21 | 上海西井信息科技有限公司 | Vehicle positioning method, device, electronic equipment, storage medium |
CN108958266A (en) * | 2018-08-09 | 2018-12-07 | 北京智行者科技有限公司 | A kind of map datum acquisition methods |
CN109389046A (en) * | 2018-09-11 | 2019-02-26 | 昆山星际舟智能科技有限公司 | Round-the-clock object identification and method for detecting lane lines for automatic Pilot |
CN109186625A (en) * | 2018-10-24 | 2019-01-11 | 北京奥特贝睿科技有限公司 | Intelligent vehicle carries out pinpoint method and system using mixing sampling filter |
Cited By (30)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110333083A (en) * | 2019-06-27 | 2019-10-15 | 中国第一汽车股份有限公司 | Test method, device, test equipment and the storage medium of vehicle durability test |
CN110333083B (en) * | 2019-06-27 | 2021-12-07 | 中国第一汽车股份有限公司 | Vehicle durability test testing method and device, testing equipment and storage medium |
CN110207715A (en) * | 2019-06-28 | 2019-09-06 | 广州小鹏汽车科技有限公司 | The modification method and update the system of vehicle location |
CN110207715B (en) * | 2019-06-28 | 2021-07-13 | 广州小鹏自动驾驶科技有限公司 | Correction method and correction system for vehicle positioning |
CN112556720A (en) * | 2019-09-25 | 2021-03-26 | 上海汽车集团股份有限公司 | Vehicle inertial navigation calibration method and system and vehicle |
CN112556720B (en) * | 2019-09-25 | 2023-08-18 | 上海汽车集团股份有限公司 | Vehicle inertial navigation calibration method and system and vehicle |
TWI742554B (en) * | 2019-09-26 | 2021-10-11 | 大陸商上海商湯智能科技有限公司 | Positioning method, path determination method, robot and storage medium |
CN110530372B (en) * | 2019-09-26 | 2021-06-22 | 上海商汤智能科技有限公司 | Positioning method, path determining device, robot and storage medium |
WO2021056841A1 (en) * | 2019-09-26 | 2021-04-01 | 上海商汤智能科技有限公司 | Positioning method, path determining method and apparatus, robot, and storage medium |
CN110530372A (en) * | 2019-09-26 | 2019-12-03 | 上海商汤智能科技有限公司 | Localization method, determining method of path, device, robot and storage medium |
CN110794844A (en) * | 2019-11-18 | 2020-02-14 | 北京百度网讯科技有限公司 | Automatic driving method, device, electronic equipment and readable storage medium |
WO2021115395A1 (en) * | 2019-12-13 | 2021-06-17 | 北京三快在线科技有限公司 | Map-based fault diagnosis |
CN111323802A (en) * | 2020-03-20 | 2020-06-23 | 北京百度网讯科技有限公司 | Vehicle positioning method, device and equipment |
CN111323802B (en) * | 2020-03-20 | 2023-02-28 | 阿波罗智能技术(北京)有限公司 | Intelligent driving vehicle positioning method, device and equipment |
CN111523471A (en) * | 2020-04-23 | 2020-08-11 | 北京百度网讯科技有限公司 | Method, device and equipment for determining lane where vehicle is located and storage medium |
CN111523471B (en) * | 2020-04-23 | 2023-08-04 | 阿波罗智联(北京)科技有限公司 | Method, device, equipment and storage medium for determining lane where vehicle is located |
CN114252883A (en) * | 2020-09-24 | 2022-03-29 | 北京万集科技股份有限公司 | Target detection method, apparatus, computer device and medium |
CN114252883B (en) * | 2020-09-24 | 2022-08-23 | 北京万集科技股份有限公司 | Target detection method, apparatus, computer device and medium |
CN112558130B (en) * | 2020-12-07 | 2023-12-19 | 安徽江淮汽车集团股份有限公司 | Synchronization method, device, equipment and storage medium of positioning data |
CN112558130A (en) * | 2020-12-07 | 2021-03-26 | 安徽江淮汽车集团股份有限公司 | Method, device and equipment for synchronizing positioning data and storage medium |
CN113219486A (en) * | 2021-04-23 | 2021-08-06 | 北京云迹科技有限公司 | Positioning method and device |
CN113280822A (en) * | 2021-04-30 | 2021-08-20 | 北京觉非科技有限公司 | Vehicle positioning method and positioning device |
CN113280822B (en) * | 2021-04-30 | 2023-08-22 | 北京觉非科技有限公司 | Vehicle positioning method and positioning device |
CN113218389A (en) * | 2021-05-24 | 2021-08-06 | 北京航迹科技有限公司 | Vehicle positioning method, device, storage medium and computer program product |
CN113218389B (en) * | 2021-05-24 | 2024-05-17 | 北京航迹科技有限公司 | Vehicle positioning method, device, storage medium and computer program product |
CN113566834A (en) * | 2021-07-20 | 2021-10-29 | 广州小鹏汽车科技有限公司 | Positioning method, positioning device, vehicle, and storage medium |
CN114937372A (en) * | 2022-05-18 | 2022-08-23 | 安徽蔚来智驾科技有限公司 | Vehicle positioning system, positioning method, vehicle and storage medium |
CN114937372B (en) * | 2022-05-18 | 2023-09-05 | 安徽蔚来智驾科技有限公司 | Vehicle positioning system, positioning method, vehicle and storage medium |
CN115112114A (en) * | 2022-06-15 | 2022-09-27 | 苏州轻棹科技有限公司 | Processing method and device for correcting orientation angle of vehicle around self-vehicle |
CN115112114B (en) * | 2022-06-15 | 2024-05-03 | 苏州轻棹科技有限公司 | Processing method and device for correcting orientation angle of vehicle around vehicle |
Also Published As
Publication number | Publication date |
---|---|
CN109931939B (en) | 2020-11-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109931939A (en) | Localization method, device, equipment and the computer readable storage medium of vehicle | |
CN108694882B (en) | Method, device and equipment for labeling map | |
CN105512646B (en) | A kind of data processing method, device and terminal | |
JP5057183B2 (en) | Reference data generation system and position positioning system for landscape matching | |
CN109583415B (en) | Traffic light detection and identification method based on fusion of laser radar and camera | |
EP3650814B1 (en) | Vision augmented navigation | |
CN106461402B (en) | For determining the method and system of the position relative to numerical map | |
JP5062498B2 (en) | Reference data generation system and position positioning system for landscape matching | |
CN102208036B (en) | Vehicle position detection system | |
EP3407294A1 (en) | Information processing method, device, and terminal | |
US11625851B2 (en) | Geographic object detection apparatus and geographic object detection method | |
CN113870343B (en) | Relative pose calibration method, device, computer equipment and storage medium | |
CN109164809A (en) | A kind of autonomous following control system of platooning and method | |
CN110275181A (en) | A kind of vehicle-mounted mobile measuring system and its data processing method | |
CN110617821A (en) | Positioning method, positioning device and storage medium | |
KR20210061722A (en) | Method, apparatus, computer program and computer readable recording medium for producing high definition map | |
JPWO2020039937A1 (en) | Position coordinate estimation device, position coordinate estimation method and program | |
CN112735253A (en) | Traffic light automatic labeling method and computer equipment | |
CN113566817B (en) | Vehicle positioning method and device | |
CN116824457A (en) | Automatic listing method based on moving target in panoramic video and related device | |
US20220404170A1 (en) | Apparatus, method, and computer program for updating map | |
CN112651991A (en) | Visual positioning method, device and computer system | |
CN109978953A (en) | Method and system for target three-dimensional localization | |
CN115665553A (en) | Automatic tracking method and device for unmanned aerial vehicle, electronic equipment and storage medium | |
JP5177579B2 (en) | Image processing system and positioning system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |