CN108303721B - Vehicle positioning method and system - Google Patents
Vehicle positioning method and system Download PDFInfo
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- CN108303721B CN108303721B CN201810145213.1A CN201810145213A CN108303721B CN 108303721 B CN108303721 B CN 108303721B CN 201810145213 A CN201810145213 A CN 201810145213A CN 108303721 B CN108303721 B CN 108303721B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
- G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
Abstract
The invention discloses a vehicle positioning method and a system, wherein the positioning system comprises the following steps: the vehicle positioning system comprises a GPS module, an IMU module, a camera module, a laser module and a controller module, wherein when a vehicle runs in a traffic sheltering environment, the positioning accuracy of the GPS module on the vehicle is lower than the preset positioning accuracy, the controller module starts the camera module and the laser module, and the vehicle is preliminarily positioned by utilizing a road environment image acquired by the camera module; determining a local map corresponding to the preliminary positioning result from a pre-stored map; 3D point cloud data of the surrounding environment of the vehicle scanned by the laser module are utilized to carry out three-dimensional map reconstruction; and matching the reconstructed three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle. The invention effectively avoids the problems of inaccurate positioning and accumulated errors of the GPS module in the traffic sheltering environment, thereby improving the accuracy of vehicle positioning.
Description
Technical Field
The invention relates to the technical field of vehicle positioning, in particular to a vehicle positioning method and system.
Background
Positioning and navigation are two important technologies for realizing automatic driving of an intelligent vehicle, and in practical application, vehicle navigation is generally realized through a high-precision map, and the high-precision map generally stores abundant environmental information, so that the intelligent vehicle navigation system has lane-level guiding capability. Positioning is used as a basis of navigation, and becomes a main research direction for realizing automatic driving of the intelligent vehicle.
Currently, the GPS (Global Positioning System) technology is widely used in the field of vehicle Positioning. The GPS can provide information such as three-dimensional position, speed, time and the like of the vehicle all weather in real time, and the vehicle can be positioned. However, when the vehicle runs in a tunnel, an overpass or other traffic-blocking environment for a long time, the GPS may be blocked by the satellite positioning signal, which may result in inaccurate positioning or even failure.
In order to overcome the disadvantages of the GPS, various combined positioning schemes have been proposed, such as GPS/DR (Dead Reckoning) vehicle combined positioning, GPS/IMU (Inertial Measurement Unit) vehicle combined positioning, and the like. However, in both DR and IMU, when GPS is in an inaccurate positioning condition in a traffic-blocking environment, and even when the time of failure is long, there is a case of accumulated errors.
Disclosure of Invention
In view of the above, the present invention discloses a vehicle positioning method and system, so as to solve the problems of inaccurate positioning and accumulated errors of a GPS module in a traffic-blocking environment in the conventional scheme.
A vehicle positioning system, comprising:
the GPS module is used for acquiring longitude and latitude information of the vehicle from a satellite system;
the inertial measurement unit IMU module is used for acquiring the acceleration and the angular acceleration of the vehicle in a three-dimensional space;
the camera module is used for acquiring a road environment image in the running process of the vehicle;
a laser module for scanning 3D point cloud data of the vehicle surroundings;
the controller module is respectively connected with the GPS module, the IMU module, the camera module and the laser module, and is used for starting the camera module and the laser module when the positioning precision of the GPS module on the vehicle is determined to be lower than the preset positioning precision, extracting a target area and identifying an artificial road sign from the road environment image acquired by the camera module, wherein the position of the artificial road sign in a world coordinate system is known, and preliminarily positioning the vehicle to obtain a preliminary positioning result; determining a local map corresponding to the preliminary positioning result from a pre-stored map; analyzing and processing the 3D point cloud data scanned by the laser module to obtain environment corner characteristic parameter data, and performing three-dimensional map reconstruction by using the environment corner characteristic parameter data; and matching the reconstructed three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle.
Preferably, the controller module is further configured to:
and when the positioning accuracy of the GPS module to the vehicle is determined to be not lower than the preset positioning accuracy, closing the camera module and the laser module, and obtaining the actual position information and the course angle information of the vehicle according to the longitude and latitude information of the vehicle obtained by the GPS module and the acceleration and the angular acceleration of the vehicle in a three-dimensional space obtained by the IMU module.
A vehicle positioning method is applied to a controller module in the vehicle positioning system, and comprises the following steps:
acquiring positioning state data of a vehicle, which is sent by a GPS module;
judging whether the positioning precision of the vehicle in the positioning state data is lower than a preset positioning precision or not;
when the positioning accuracy is judged to be lower than the preset positioning accuracy, starting a camera module and a laser module;
extracting a target area and identifying an artificial road sign from a road environment image acquired by the camera module in the driving process of the vehicle, and performing primary positioning on the vehicle to obtain a primary positioning result, wherein the position of the artificial road sign in a world coordinate system is known;
determining a local map corresponding to the preliminary positioning result from a pre-stored map;
analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module to obtain environment corner characteristic parameter data;
carrying out three-dimensional map reconstruction by using the environment corner characteristic parameter data to obtain a three-dimensional map;
and matching the three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle.
Preferably, the determining whether the positioning accuracy of the vehicle in the positioning state data is lower than a preset positioning accuracy specifically includes:
judging whether the time of GPS signal loss in the positioning state data is greater than preset time or not; or from the moment when the GPS signal is lost, whether the accumulated running distance of the vehicle is greater than a preset distance or not is judged;
correspondingly, when judging that the positioning accuracy is lower than the preset positioning accuracy, opening the camera module and the laser module specifically comprises:
when the GPS signal loss time is judged to be greater than the preset time; or starting the camera module and the laser module when the accumulated running distance of the vehicle is greater than the preset distance from the moment when the GPS signal is lost.
Preferably, the step of performing target area extraction and artificial road sign recognition in the road environment image acquired by the camera module during the vehicle driving process to perform preliminary positioning on the vehicle to obtain a preliminary positioning result specifically includes:
extracting a target area containing an artificial road sign from the road environment image;
identifying the artificial road sign from the target area, and obtaining an image coordinate of the artificial road sign in the road environment image;
according to the image coordinates and the position information of the artificial road signs known in advance in a world coordinate system, carrying out primary positioning on the vehicle to obtain a primary positioning result of the vehicle, wherein the primary positioning result comprises: absolute position information of the vehicle in a world coordinate system.
Preferably, the analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module to obtain environment corner characteristic parameter data specifically includes:
extracting all straight line segments under a vehicle coordinate system from the 3D point cloud data by adopting a linear regression method, wherein the straight line segments have characteristic parameters: the vertical distance from the origin of the vehicle coordinate system to the straight line segment, the included angle between the vertical line and the axis of the vehicle running direction in the vehicle coordinate system and the length of the straight line segment;
and obtaining corner characteristic parameter data of the corresponding corner by using the characteristics of the three intersected straight line segments.
Preferably, the environment corner feature parameter data includes: the three-dimensional coordinates of the angular point, the included angle between the angular point coordinate system and the world coordinate system, the length of three sides of the angular point and the concavity and convexity of the angular point.
Preferably, the pre-stored map is a sub-meter-scale map, and the sub-meter-scale map includes: three-dimensional environment characteristics and absolute coordinates of points in the environment.
Preferably, the matching of the three-dimensional map and the local map to obtain the actual position information and the course angle information of the vehicle specifically includes:
taking the corner points contained in the three-dimensional map as first corner points, taking the corner points contained in the local map as second corner points, and respectively matching each first corner point contained in the three-dimensional map with all the second corner points contained in the local map and having the same concavity and convexity;
when the local map comprises second corner points matched with the current first corner points, respectively calculating the Mahalanobis distance between each second corner point matched with the current first corner point and the current first corner point;
judging whether the Mahalanobis distance with the shortest distance in all the Mahalanobis distances is smaller than a preset threshold value or not;
if the Mahalanobis distance with the shortest distance is smaller than the preset threshold, judging that the current first corner is matched with the second corner in the local map;
and when the number of the corner points of the three-dimensional map matched with the local map reaches a preset matching threshold value and the proportion of the number of the corner points to the number of all the corner points contained in the three-dimensional map reaches a preset proportion threshold value, judging that the three-dimensional map is successfully matched with the local map, and obtaining the actual position information and the course angle information of the vehicle.
Preferably, the step of including a second corner matched with the current first corner in the local map includes:
and the local map comprises a second corner point which is the same as the current first corner point in type.
From the above technical solution, the present invention discloses a vehicle positioning method and system, wherein the positioning system comprises: the vehicle positioning system comprises a GPS module, an IMU module, a camera module, a laser module and a controller module, wherein when a vehicle runs in a traffic environment such as a tunnel, an overpass and the like which shields GPS signals, the positioning precision of the GPS module on the vehicle is lower than the preset positioning precision, under the condition, the controller module starts a combined positioning module consisting of the camera module and the laser module, target area extraction and artificial road sign recognition are carried out from a road environment image collected by the camera module, and the vehicle is preliminarily positioned to obtain a preliminary positioning result; determining a local map corresponding to the preliminary positioning result from a pre-stored map; analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module to obtain environment corner characteristic parameter data, and reconstructing a three-dimensional map by using the environment corner characteristic parameter data; and matching the reconstructed three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle. Therefore, the invention effectively avoids the problems of inaccurate positioning and accumulated errors of the GPS module in the traffic sheltering environment, thereby improving the accuracy of vehicle positioning.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the disclosed drawings without creative efforts.
FIG. 1 is a schematic structural diagram of a vehicle positioning system according to an embodiment of the present invention;
FIG. 2 is a flowchart of a vehicle positioning method disclosed in an embodiment of the present invention;
FIG. 3 is a flowchart of a method for matching a three-dimensional map with a local map to obtain actual position information and course angle information of a vehicle according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention discloses a vehicle positioning method and a vehicle positioning system, which aim to solve the problems of inaccurate positioning and accumulated errors of a GPS module in a traffic sheltering environment in the traditional scheme.
Referring to fig. 1, a schematic structural diagram of a vehicle positioning system disclosed in an embodiment of the present invention includes: a GPS (Global Positioning System) module 11, an IMU (Inertial measurement unit) module 12, a controller module 13, a camera module 14, and a laser module 15.
Wherein:
the GPS module 11 is provided on the vehicle and is used to acquire latitude and longitude information of the vehicle from a satellite system.
The IMU module 12 is provided on the vehicle for acquiring acceleration and angular acceleration of the vehicle in three-dimensional space.
It should be noted that, in this embodiment, the GPS module 11 and the IMU module 12 form a GPS/IMU vehicle combined positioning module, and the controller module 13 uses algorithms such as kalman filtering and particle filtering to fuse the longitude and latitude information of the vehicle acquired by the GPS module 11 with the acceleration and angular acceleration of the vehicle in the three-dimensional space acquired by the IMU module 12, so as to obtain a fused positioning result, that is, obtain the actual position information and the heading angle information of the vehicle.
The artificial road sign is a mark specially used for positioning a vehicle, the position of the artificial road sign in a world coordinate system, longitude and latitude information of the artificial road sign is displayed on the road sign in the forms of numbers, graphs, two-dimensional codes, special codes and the like, and the artificial road sign is usually placed in a road range which can be reached by the visual field of a camera module 14 of the vehicle to provide rough positioning for the vehicle with a vehicle-mounted camera.
In this embodiment, since the position of the artificial road sign in the world coordinate system is known in advance, coarse positioning of the vehicle can be achieved according to the relative position relationship between the vehicle and the artificial road sign in the same image and the position of the artificial road sign in the world coordinate system.
It should be noted that, in practical applications, a plurality of artificial road signs may be arranged on a driving road of a vehicle to realize coarse positioning of the vehicle.
The camera module 14 is used for collecting a road environment image during the running process of the vehicle, so as to provide a basis for the following controller module 13 to perform coarse positioning on the vehicle.
The laser module 15 is used for scanning 3D point cloud data of the vehicle surroundings, and each point in the 3D point cloud data includes coordinate information of x, y, and z directions.
It should be noted that the camera module 14 and the laser module 15 constitute a vision/laser vehicle combination positioning module. When the GPS signal is good, the positioning accuracy of the GPS/IMU vehicle combined positioning module can reach centimeter level, and at the moment, the controller module 13 controls the GPS/IMU vehicle combined positioning module to position the vehicle; when the GPS module 11 is shielded for a long time in a traffic environment, the positioning accuracy of the GPS/IMU vehicle combination positioning module is reduced to 10 meters or even worse, and in this case, the controller module 13 starts the vision/laser vehicle combination positioning module, and the vision/laser vehicle combination positioning module positions the vehicle, wherein, during the time when the vision/laser vehicle combination positioning module positions the vehicle, the GPS/IMU vehicle combination positioning module still collects data, and only the controller module 13 does not process the data collected by the GPS/IMU vehicle combination positioning module.
The process of the controller module 13 controlling the vision/laser vehicle combination positioning module to position the vehicle is as follows:
the controller module 13 is respectively connected with the GPS module 11, the IMU module 12, the camera module 14 and the laser module 15, the controller module 13 is used for starting the camera module 14 and the laser module 15 when the positioning accuracy of the GPS module 11 to the vehicle is determined to be lower than the preset positioning accuracy, target area extraction and artificial road sign recognition are carried out from the road environment image collected by the camera module 14, the vehicle is preliminarily positioned, namely the vehicle is roughly positioned, the positioning accuracy is in a meter level, and a preliminary positioning result is obtained; determining a local map corresponding to the preliminary positioning result from a pre-stored map; analyzing and processing the 3D point cloud data scanned by the laser module 15 to obtain environment corner characteristic parameter data, and performing three-dimensional map reconstruction by using the environment corner characteristic parameter data; and matching the reconstructed three-dimensional map with the local map, so that the positioning accuracy of the vehicle is improved to a centimeter level, and the actual position information and the course angle information of the vehicle are obtained.
It should be noted that, when the vehicle runs in a tunnel, an overpass, or the like, which blocks a traffic environment, the GPS module 11 may have inaccurate positioning or even failure due to the blocking of the signal, so that the positioning accuracy of the GPS module 11 for the vehicle is reduced. In this embodiment, a preset positioning accuracy is preset, a value of the preset positioning accuracy is determined according to actual needs, and when the controller module 13 determines that the positioning accuracy of the GPS module 11 for the vehicle is lower than the preset positioning accuracy, it is determined that the vehicle is currently running in a traffic-sheltered environment, in this case, the controller module 13 starts the vision/laser vehicle combined positioning module, and the vision/laser vehicle combined positioning module positions the vehicle.
In this embodiment, the map prestored in the controller module 13 is a high-precision map, where the features of the three-dimensional space environment and the absolute coordinates of each point in the environment are stored in the high-precision map, and the map precision of the high-precision map is in the sub-meter level, which includes: accurate road shape information, lane line information, and other information such as traffic participants, wherein the road shape information includes: the number, gradient, curvature, course, elevation, side inclination and the like of lanes; the lane line information includes: the color and line type of the lane line, and other information such as other traffic participants includes: traffic lights, signs, speed limit signs, pedestrian crossings, isolation zones, road teeth, roadside vegetation, buildings and the like. The high-precision map stores the characteristic information in a manner of basic elements such as points and lines.
In summary, according to the vehicle positioning method system disclosed by the invention, when a vehicle runs in a tunnel, an overpass and other sheltered traffic environments, the positioning accuracy of the vehicle by the GPS module 11 is lower than the preset positioning accuracy, in this case, the controller module 13 starts the combined positioning module formed by the camera module 14 and the laser module 15, and performs target area extraction and artificial landmark identification from the road environment image collected by the camera module 14, and performs preliminary positioning on the vehicle to obtain a preliminary positioning result; determining a local map corresponding to the preliminary positioning result from a pre-stored map; analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module 15 to obtain environment corner characteristic parameter data, and reconstructing a three-dimensional map by using the environment corner characteristic parameter data; and matching the reconstructed three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle. Therefore, the invention effectively avoids the problems of inaccurate positioning and accumulated errors of the GPS module 11 in the traffic sheltering environment, thereby improving the accuracy of vehicle positioning.
It should be noted that, although the vision/laser vehicle combined positioning module can accurately position the vehicle when the GPS module 11 is in the traffic-blocking environment, compared with the GPS/IMU vehicle combined positioning module for positioning the vehicle, the data processing amount of the controller module 13 for the vision/laser vehicle combined positioning module is much larger than that for the GPS/IMU vehicle combined positioning module, and therefore, when the GPS module 11 is not in the traffic-blocking environment, that is, the positioning accuracy of the GPS module 11 is not lower than the preset positioning accuracy, the vehicle still uses the GPS/IMU vehicle combined positioning module to position the vehicle.
Therefore, to further optimize the above embodiment, the controller module 13 is further configured to:
when the positioning accuracy of the GPS module 11 to the vehicle is determined to be not lower than the preset positioning accuracy, the camera module 14 and the laser module 15 are closed, and the actual position information and the course angle information of the vehicle are obtained according to the longitude and latitude information of the vehicle acquired by the GPS module 11 and the acceleration and the angular acceleration of the vehicle in the three-dimensional space acquired by the IMU module 12, so that the vehicle is positioned.
Specifically, the controller module 13 applies algorithms such as kalman filtering and particle filtering to fuse the longitude and latitude information of the vehicle acquired by the GPS module 11 with the acceleration and angular acceleration of the vehicle in the three-dimensional space acquired by the IMU module 12 to obtain a fused positioning result, that is, to obtain the actual position information and the course angle information of the vehicle, thereby positioning the vehicle.
In summary, according to the vehicle positioning system disclosed by the invention, when the GPS signal is good and the positioning accuracy of the GPS module 11 to the vehicle is not lower than the preset positioning accuracy, the vehicle is positioned by adopting the GPS/IMU vehicle combined positioning module; when the GPS signals are poor and the positioning accuracy of the GPS module 11 for the vehicle is lower than the preset positioning accuracy, the vehicle is positioned by adopting the vision/laser vehicle combined positioning module, and the controller module 13 identifies artificial road signs arranged beside the road according to the road environment images collected by the camera module 14, so that the coarse positioning of the vehicle is realized, and the accuracy is in a meter level; the controller module 13 reconstructs a three-dimensional map by using the 3D point cloud data of the vehicle surrounding environment scanned by the laser module 15, and the reconstructed three-dimensional map is matched with a local map determined on the high-precision map, so that the positioning precision of the vehicle is improved to a centimeter level, the high-precision positioning of the vehicle is realized, and the real-time performance is good.
Corresponding to the vehicle positioning system, the invention also discloses a vehicle positioning method.
Referring to fig. 2, a flowchart of a vehicle positioning method disclosed in an embodiment of the present invention is applied to a vehicle positioning system in the above embodiment, and is particularly applied to a controller module in the vehicle positioning system, and the vehicle positioning method includes the steps of:
s101, acquiring positioning state data of a vehicle, which is sent by a GPS module;
it should be noted that, in practical application, the GPS module sends the longitude and latitude information of the vehicle acquired from the satellite system to the controller module, and also sends the positioning state data of the vehicle to the controller module, and the controller module can determine the positioning accuracy of the GPS module for the vehicle according to the positioning state data, so as to determine whether the vehicle is running in a traffic-blocking environment, and further determine whether the vision/laser vehicle combined positioning module formed by the camera module 14 and the laser module 15 needs to be started.
Step S102, judging whether the positioning precision of the vehicle in the positioning state data is lower than the preset positioning precision, if so, executing step S103, otherwise, returning to step S101, and continuously acquiring the positioning state data of the vehicle sent by the GPS module;
when a vehicle runs in a tunnel, an overpass and other sheltered traffic environments, the GPS module can be inaccurate in positioning and even invalid due to signal sheltering, and therefore the positioning accuracy of the GPS module on the vehicle is reduced. In the embodiment, a preset positioning accuracy is preset, the value of the preset positioning accuracy is determined according to actual needs, and when the controller module determines that the positioning accuracy of the GPS module on the vehicle is lower than the preset positioning accuracy, the controller module determines that the vehicle is currently running in a traffic sheltering environment.
In practical application, the controller module may determine whether the positioning accuracy of the vehicle in the positioning state data is lower than the preset positioning accuracy by any one of the following determination methods:
(1) judging whether the GPS signal loss time in the positioning state data is greater than a preset time, such as 10s, and when the GPS signal loss time in the positioning state data is greater than the preset time, judging that the positioning precision of the GPS module on the vehicle is lower than the preset positioning precision, wherein the value of the preset time is determined according to actual needs;
(2) and judging whether the accumulated running distance of the vehicle is greater than a preset distance, such as 100m, from the moment when the GPS signal is lost, and when the accumulated running distance of the vehicle is greater than the preset distance, judging that the positioning precision of the GPS module on the vehicle is lower than the preset positioning precision, wherein the value of the preset distance is determined according to actual needs.
Of course, in practical application, other determination methods may be adopted according to needs, and are not listed here.
Step S103, starting a camera module and a laser module;
step S104, extracting a target area and identifying an artificial road sign from a road environment image collected by a camera module in the driving process of the vehicle, and performing primary positioning on the vehicle to obtain a primary positioning result;
wherein, carry out preliminary location to the vehicle in this step, also carry out coarse positioning to the vehicle, positioning accuracy is at the meter level, obtains preliminary location result.
It should be noted that the position of the artificial road sign in the world coordinate system, that is, the longitude and latitude information, is known in advance.
The implementation process of step S104 is specifically as follows:
(1) extracting a target area containing an artificial road sign from a road environment image;
(2) identifying an artificial road sign from the target area, and obtaining an image coordinate of the artificial road sign in the road environment image;
(3) according to the image coordinates of the artificial road signs and the position information of the known artificial road signs in the world coordinate system in advance, the vehicle is preliminarily positioned, and a preliminary positioning result of the vehicle is obtained, wherein the preliminary positioning result comprises: absolute position information of the vehicle in the world coordinate system.
It should be noted that the camera module is used for shooting the road environment image according to the vehicle view angle, so that the position of the vehicle in the road environment image can be regarded as the origin position, the geometric relationship between the artificial road sign and the vehicle can be determined by determining the image coordinate of the artificial road sign in the image, and the absolute position and the course angle information of the vehicle in the world coordinate system can be obtained according to the position information of the artificial road sign in the world coordinate system.
Step S105, determining a local map corresponding to the preliminary positioning result from a pre-stored map;
the pre-stored map in this step specifically refers to a high-precision map, and the map precision is in the sub-meter level, that is, the map pre-stored by the controller module is a sub-meter level map, and the sub-meter level map includes: three-dimensional environment characteristics and absolute coordinates of points in the environment. For detailed information included in the sub-scale map, reference may be made to the corresponding parts of the above system embodiments, which are not described herein again.
S106, analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module to obtain environment corner characteristic parameter data;
by corner point is meant a right angle point in the environment. The environment corner characteristic parameter data comprises: the three-dimensional coordinates of the angular point, the included angle between the angular point coordinate system and the world coordinate system, the length of three sides of the angular point, the concavity and the convexity of the angular point and the like. Wherein, the unevenness of the corner points is defined as: the angular point of the convex origin is a convex angular point, and the angular point of the concave origin is a concave angular point.
Specifically, the controller module adopts a linear regression method for 3D point cloud data of the vehicle surrounding environment scanned by the laser module, and extracts all linear segments under a vehicle coordinate system from the 3D point cloud data, wherein the linear segments have characteristic parameters: the vertical distance from the origin of the vehicle coordinate system to the straight line segment, the included angle between the vertical line and the axis of the vehicle running direction in the vehicle coordinate system and the length of the straight line segment; and then, obtaining corner characteristic parameter data of the corresponding corner by using the characteristics of the three intersected straight line segments.
In the vehicle coordinate system, the vehicle running direction is an x axis, the direction of the left side of the vehicle is a y axis, the vertical upward direction is a z axis, and the origin is the center of a rear axle of the vehicle.
The specific process of obtaining the corner feature parameter data of the corresponding corner by using the features of the three intersected straight line segments can be referred to in the prior art, and is not described herein again.
S107, reconstructing a three-dimensional map by using the environmental corner characteristic parameter data to obtain the three-dimensional map;
the process of reconstructing the three-dimensional map by using the environmental corner feature parameter data can refer to the prior art scheme, and is not described herein again.
And S108, matching the three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle.
The method for matching the three-dimensional map with the local map in the step is as follows: and realizing map matching based on the corner features, wherein a nearest neighbor method based on the Mahalanobis distance is used in the matching.
Mahalanobis distance (Mahalanobis distance) represents the covariance distance of the data. Mahalanobis distance is an effective way to calculate the similarity between two unknown sample sets.
Referring to fig. 3, a flowchart of a method for matching a three-dimensional map with a local map to obtain actual position information and heading angle information of a vehicle according to an embodiment of the present invention is disclosed, and the method includes the steps of:
step S201, taking the corner points contained in the three-dimensional map as first corner points, taking the corner points contained in the local map as second corner points, and respectively matching each first corner point contained in the three-dimensional map with all the second corner points contained in the local map;
the principle of matching the first corner point and the second corner point is as follows: and whether the types of the first corner point and the second corner point are the same or not indicates that the first corner point and the second corner point are matched when the types of the first corner point and the second corner point are the same. The type referred to herein refers to a concave corner point or a convex corner point, that is, when both the first corner point and the second corner point are concave corner points or convex corner points, it is stated that the first corner point and the second corner point are the same type, and the first corner point and the second corner point are matched.
Step S202, when a local map comprises second corner points matched with the current first corner points, respectively calculating the Mahalanobis distance between each second corner point matched with the current first corner point and the current first corner point;
the local map including a second corner matched with the current first corner comprises: the local map comprises a second corner point which is the same as the current first corner point in type.
Step S203, judging whether the Mahalanobis distance with the shortest distance in all the Mahalanobis distances is smaller than a preset threshold value, if so, executing step S204, and if not, executing step S206;
the value of the preset threshold is determined according to actual needs, and the invention is not limited herein.
Step S204, judging that the current first corner is matched with a second corner in the local map;
and S205, when the number of the corner points of the three-dimensional map and the local map reaches a preset matching threshold value and the ratio of the number of the corner points to the number of all the corner points contained in the three-dimensional map reaches a preset ratio threshold value, judging that the three-dimensional map and the local map are successfully matched and obtaining the actual position information and the course angle information of the vehicle.
The values of the preset matching threshold and the preset proportional threshold are determined according to actual needs, and the present invention is not limited herein.
And step S206, judging that the current first corner is not matched with the second corner in the local map.
In summary, according to the vehicle positioning method disclosed by the invention, when a vehicle runs in a tunnel, an overpass and other sheltered traffic environments, the positioning accuracy of the GPS module to the vehicle is lower than the preset positioning accuracy, under the condition, the controller module can start the combined positioning module formed by the camera module and the laser module, and extract a target area and recognize artificial road signs from a road environment image acquired by the camera module, so as to perform preliminary positioning on the vehicle and obtain a preliminary positioning result; determining a local map corresponding to the preliminary positioning result from a pre-stored map; analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module to obtain environment corner characteristic parameter data, and reconstructing a three-dimensional map by using the environment corner characteristic parameter data; and matching the reconstructed three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle. Therefore, the invention effectively avoids the problems of inaccurate positioning and accumulated errors of the GPS module in the traffic sheltering environment, thereby improving the accuracy of vehicle positioning.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A vehicle positioning system, comprising:
the GPS module is used for acquiring longitude and latitude information of the vehicle from a satellite system;
the inertial measurement unit IMU module is used for acquiring the acceleration and the angular acceleration of the vehicle in a three-dimensional space;
the camera module is used for acquiring a road environment image in the running process of the vehicle;
a laser module for scanning 3D point cloud data of the vehicle surroundings;
the controller module is respectively connected with the GPS module, the IMU module, the camera module and the laser module, and is used for starting the camera module and the laser module when the positioning precision of the GPS module on the vehicle is determined to be lower than the preset positioning precision, extracting a target area and identifying an artificial road sign from the road environment image acquired by the camera module, wherein the position of the artificial road sign in a world coordinate system is known, and preliminarily positioning the vehicle to obtain a preliminary positioning result; determining a local map corresponding to the preliminary positioning result from a pre-stored map; analyzing and processing the 3D point cloud data scanned by the laser module to obtain environment corner characteristic parameter data, and performing three-dimensional map reconstruction by using the environment corner characteristic parameter data; matching the reconstructed three-dimensional map with the local map to obtain the actual position information and course angle information of the vehicle;
the method comprises the following steps of analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module to obtain environment corner characteristic parameter data, and specifically comprises the following steps:
extracting all straight line segments under a vehicle coordinate system from the 3D point cloud data by adopting a linear regression method, wherein the straight line segments have characteristic parameters: the vertical distance from the origin of the vehicle coordinate system to the straight line segment, the included angle between the vertical line and the axis of the vehicle running direction in the vehicle coordinate system and the length of the straight line segment;
and obtaining corner characteristic parameter data of the corresponding corner by using the characteristics of the three intersected straight line segments.
2. The vehicle positioning system of claim 1, wherein the controller module is further configured to:
and when the positioning accuracy of the GPS module to the vehicle is determined to be not lower than the preset positioning accuracy, closing the camera module and the laser module, and obtaining the actual position information and the course angle information of the vehicle according to the longitude and latitude information of the vehicle obtained by the GPS module and the acceleration and the angular acceleration of the vehicle in a three-dimensional space obtained by the IMU module.
3. A vehicle positioning method applied to a controller module in the vehicle positioning system according to claim 1, the vehicle positioning method comprising:
acquiring positioning state data of a vehicle, which is sent by a GPS module;
judging whether the positioning precision of the vehicle in the positioning state data is lower than a preset positioning precision or not;
when the positioning accuracy is judged to be lower than the preset positioning accuracy, starting a camera module and a laser module;
extracting a target area and identifying an artificial road sign from a road environment image acquired by the camera module in the driving process of the vehicle, and performing primary positioning on the vehicle to obtain a primary positioning result, wherein the position of the artificial road sign in a world coordinate system is known;
determining a local map corresponding to the preliminary positioning result from a pre-stored map;
analyzing and processing the 3D point cloud data of the vehicle surrounding environment scanned by the laser module to obtain environment corner characteristic parameter data, and specifically comprising the following steps: extracting all straight line segments under a vehicle coordinate system from the 3D point cloud data by adopting a linear regression method, wherein the straight line segments have characteristic parameters: the vertical distance from the origin of the vehicle coordinate system to the straight line segment, the included angle between the vertical line and the axis of the vehicle running direction in the vehicle coordinate system and the length of the straight line segment; obtaining corner characteristic parameter data of a corresponding corner by using the characteristics of three intersected straight line segments;
carrying out three-dimensional map reconstruction by using the environment corner characteristic parameter data to obtain a three-dimensional map;
and matching the three-dimensional map with the local map to obtain the actual position information and the course angle information of the vehicle.
4. The vehicle positioning method according to claim 3, wherein the determining whether the positioning accuracy of the vehicle in the positioning state data is lower than a preset positioning accuracy specifically comprises:
judging whether the time of GPS signal loss in the positioning state data is greater than preset time or not; or from the moment when the GPS signal is lost, whether the accumulated running distance of the vehicle is greater than a preset distance or not is judged;
correspondingly, when judging that the positioning accuracy is lower than the preset positioning accuracy, opening the camera module and the laser module specifically comprises:
when the GPS signal loss time is judged to be greater than the preset time; or starting the camera module and the laser module when the accumulated running distance of the vehicle is greater than the preset distance from the moment when the GPS signal is lost.
5. The vehicle positioning method according to claim 3, wherein the step of performing target area extraction and artificial road sign recognition from the road environment image collected by the camera module during the vehicle driving process to perform preliminary positioning on the vehicle to obtain a preliminary positioning result specifically comprises:
extracting the target area containing the artificial road sign from the road environment image;
identifying the artificial road sign from the target area, and obtaining an image coordinate of the artificial road sign in the road environment image;
according to the image coordinates and the position information of the artificial road signs known in advance in a world coordinate system, carrying out primary positioning on the vehicle to obtain a primary positioning result of the vehicle, wherein the primary positioning result comprises: absolute position information of the vehicle in a world coordinate system.
6. The vehicle positioning method according to claim 3, wherein the environment corner feature parameter data comprises: the three-dimensional coordinates of the angular point, the included angle between the angular point coordinate system and the world coordinate system, the length of three sides of the angular point and the concavity and convexity of the angular point.
7. The vehicle positioning method according to claim 3, wherein the pre-stored map is a sub-meter scale map, and the sub-meter scale map includes: three-dimensional environment characteristics and absolute coordinates of points in the environment.
8. The vehicle positioning method according to claim 3, wherein the matching of the three-dimensional map and the local map to obtain the actual position information and the heading angle information of the vehicle specifically comprises:
taking the corner points contained in the three-dimensional map as first corner points, taking the corner points contained in the local map as second corner points, and respectively matching each first corner point contained in the three-dimensional map with all the second corner points contained in the local map and having the same concavity and convexity;
when the local map comprises second corner points matched with the current first corner points, respectively calculating the Mahalanobis distance between each second corner point matched with the current first corner point and the current first corner point;
judging whether the Mahalanobis distance with the shortest distance in all the Mahalanobis distances is smaller than a preset threshold value or not;
if the Mahalanobis distance with the shortest distance is smaller than the preset threshold, judging that the current first corner is matched with the second corner in the local map;
and when the number of the corner points of the three-dimensional map matched with the local map reaches a preset matching threshold value and the proportion of the number of the corner points to the number of all the corner points contained in the three-dimensional map reaches a preset proportion threshold value, judging that the three-dimensional map is successfully matched with the local map, and obtaining the actual position information and the course angle information of the vehicle.
9. The vehicle positioning method according to claim 8, wherein the step of including the second corner point matching the current first corner point in the local map comprises:
and the local map comprises a second corner point which is the same as the current first corner point in type.
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