CN109325390B - Positioning method and system based on combination of map and multi-sensor detection - Google Patents
Positioning method and system based on combination of map and multi-sensor detection Download PDFInfo
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- CN109325390B CN109325390B CN201710647293.6A CN201710647293A CN109325390B CN 109325390 B CN109325390 B CN 109325390B CN 201710647293 A CN201710647293 A CN 201710647293A CN 109325390 B CN109325390 B CN 109325390B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
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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
Abstract
The invention provides a positioning method and a positioning system based on combination of a map and multi-sensor detection, wherein a road traffic marking near a vehicle is selected as a reference marking, and the type of the reference marking is identified; identifying the form information of the reference marking by taking the current position of the vehicle as a visual angle; determining the area of the vehicle in the high-precision map according to the positioning information of the vehicle, searching for the road traffic marking in the area, and finding the road traffic marking corresponding to the type of the reference marking stored in the high-precision map according to the type of the reference marking; and according to the one-to-one correspondence relationship between the form information of the road traffic marking and the position, finding the position corresponding to the form information, and taking the position as the position of the vehicle to be determined. The invention can accurately identify the type of the target and has the advantage of high position detection precision of the laser radar on the target by simultaneously adopting the vision sensor, thereby greatly improving the positioning precision of the vehicle and meeting the requirements of intelligent driving of the vehicle.
Description
Technical Field
The invention belongs to the technical field of intelligent driving, and particularly relates to a positioning method and system based on combination of a map and multi-sensor detection.
Background
With the development of computer science and robot technology, the intelligent driving vehicle is widely applied to military, civil and scientific research and other aspects, integrates the latest research results of multiple subjects such as structure science, electronics, control theory, artificial intelligence and the like, and has wide application prospect.
Positioning system is the indispensable component part among the intelligence driving system, and positioning system relies on the satellite signal to fix a position usually, when tunnel, overpass etc. shelter from occasionally when positioning system fixes a position, can't receive the satellite signal to cause deviation and drift to appear in the positioning signal of positioning system output, can not carry out accurate positioning. The positioning system that uses only the satellite to perform positioning cannot solve the positioning problem under all working conditions, and therefore needs to perform auxiliary positioning by means of other means.
The disclosure number is "CN 102779280A", entitled "positioning method and system based on driving safety map and binocular traffic sign recognition", and the patent document uses a binocular camera to recognize and detect the distance between the traffic sign and the vehicle, and compares the distance with the coordinates of the corresponding traffic sign on the high-precision map to realize the positioning of the vehicle, but the method of detecting the distance between the traffic sign and the vehicle by using the binocular camera has low accuracy in detecting the distance, so the positioning precision is affected.
Disclosure of Invention
The invention aims to provide a positioning method and a positioning system based on combination of a map and multi-sensor detection, which are used for solving the problem of low positioning accuracy of an intelligent driving vehicle.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a positioning method based on combination of map and multi-sensor detection comprises the following steps:
1) selecting a road traffic marking near a vehicle as a reference marking, and identifying the type of the reference marking, wherein the type comprises the shape and color characteristics of the road marking;
2) recognizing the form information of the reference marking by taking the current position of the vehicle as a visual angle;
3) determining the area of the vehicle in the high-precision map according to the positioning information of the vehicle, searching for the road traffic marking in the area, and finding the road traffic marking corresponding to the type of the reference marking stored in the high-precision map according to the type of the reference marking; finding out the position corresponding to the form information according to the one-to-one correspondence relationship between the form information of the road traffic marking and the position, and taking the position as the position of the vehicle to be determined; the high-precision map stores road traffic marking lines and form information of the road traffic marking lines obtained by taking different positions as visual angles.
Further, the type of the reference marking is identified in step 1) by a vision sensor.
Further, the morphological information of the reference marking is identified in the step 2) through a laser radar.
Further, the morphological information is represented as a curve in a plane.
Further, the road traffic marking line comprises a longitudinal lane line, a stop line, a zebra crossing, a left-right turning and straight running indicating line and a character indicating line.
Further, in the step 1), the shape and the color of each road traffic marking are collected by using a deep learning method, a sample set comprising the shape and the color of each road traffic marking is obtained, and the type of the reference marking is identified by comparing the currently collected road traffic marking with the sample set.
Further, the curve in the plane is denoted as y ═ ax3+bx2+ cx + d, wherein x, y respectively represent: the center of the vehicle is taken as the origin of coordinates, the transverse distance and the longitudinal distance of each point on the road traffic marking line relative to the vehicle are respectively represented by a, b, c and d which respectively represent corresponding coefficients.
The invention also provides a positioning system based on the combination of the map and the multi-sensor detection, which comprises the following units:
a unit for selecting a road traffic marking near a vehicle as a reference marking and identifying the type of the reference marking, wherein the type comprises the shape and color characteristics of the road marking;
means for identifying morphological information of the reference reticle with a current position of the vehicle as a perspective;
the road traffic marking system is used for determining the area of the vehicle in the high-precision map according to the positioning information of the vehicle, searching the road traffic marking in the area, and finding the road traffic marking which is stored in the high-precision map and corresponds to the type of the reference marking according to the type of the reference marking; finding out the position corresponding to the form information according to the one-to-one correspondence relationship between the form information of the road traffic marking and the position, and taking the position as the position of the vehicle to be determined; and the high-precision map is stored with road traffic marking lines and form information of the road traffic marking lines obtained by taking different positions as visual angles.
Further, the morphological information is represented as a curve in a plane.
Furthermore, the road traffic marking line comprises a longitudinal lane line, a stop line, a zebra crossing, a left-right turning indicating line, a straight indicating line and a character indicating line.
The invention has the beneficial effects that:
the method includes the steps that a road traffic marking near a vehicle is selected as a reference marking, and the type of the reference marking is identified, wherein the type comprises the shape and color characteristics of the road marking; recognizing the form information of the reference marking by taking the current position of the vehicle as a visual angle; determining the area of the vehicle in the high-precision map according to the positioning information of the vehicle, searching for the road traffic marking in the area, and finding the road traffic marking corresponding to the type of the reference marking stored in the high-precision map according to the type of the reference marking; finding out the position corresponding to the form information according to the one-to-one correspondence relationship between the form information of the road traffic marking and the position, and taking the position as the position of the vehicle to be determined; the high-precision map stores road traffic marking lines and form information of the road traffic marking lines obtained by taking different positions as visual angles. According to the invention, the vision sensor and the laser radar are adopted simultaneously, and the vision sensor can accurately identify the type of the target, but the position detection precision is low; the laser radar has high target position detection precision, but is difficult to identify the target type, and the invention fully utilizes the advantages of the two sensors, improves the positioning precision of the vehicle and meets the requirements of intelligently driving the vehicle.
Drawings
Fig. 1 is a flow chart of a positioning method based on a combination of a map and multi-sensor detection according to the present invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings:
the embodiment of the positioning method based on the combination of the map and the multi-sensor detection comprises the following steps:
a positioning method based on a combination of a map and multi-sensor detection, as shown in fig. 1, includes the following steps:
1. the method comprises the steps of selecting a road traffic marking near a vehicle as a reference marking, and identifying the type of the road traffic marking by using a vision sensor, namely identifying the characteristics of the road traffic marking such as shape, color and the like by using the vision sensor, so as to distinguish the category of the road traffic marking. The step of distinguishing the categories of the road traffic marking refers to the steps of collecting the shapes and the colors of various road traffic markings by using a deep learning method, generating a sample set, and determining the categories of the road traffic markings contained in the current frame by comparing the sample set.
When the reference marking is selected, if there are several markings with the same or similar types near the vehicle, and one marking is different from or similar to the other types, then the marking different from the other types is selected as the reference marking, and the type of the reference marking is further identified through the vision sensor, for example, the type of the reference marking is identified as a left-turn curve through the vision sensor. The road traffic marking of the embodiment comprises a longitudinal lane line, a stop line, a zebra crossing, a left-right turning and straight running indicating line and a character indicating line.
2. Recognizing the form information of the reference marking by using a laser radar by taking the current position of the vehicle as a visual angle; the form information is a curve in a plane and can describe a mathematical model equation of the road traffic marking, and the embodiment adopts a cubic equation y as ax3+bx2+ cx + d, where x, y respectively represent: the center of the vehicle is taken as the origin of coordinates, the transverse distance and the longitudinal distance of each point on the road traffic marking line relative to the vehicle are respectively represented by a, b, c and d which respectively represent corresponding coefficients. For a road traffic marking that cannot be described using a parametric model, its segmentation will be described.
3. According to the positioning information of the vehicle (the positioning information of the previous frame of the vehicle, the time interval between the current frame and the previous frame is short, and the moving distance of the vehicle in the interval time is short, so that the positioning information of the previous frame of the vehicle can be used as a reference area of the current position of the vehicle), determining the area of the vehicle in the high-precision map, searching the road traffic marking in the area, and finding the road traffic marking stored in the high-precision map according to the type of the reference marking; and according to the one-to-one correspondence relationship between the form information of the road traffic marking and the position, finding the position corresponding to the form information, and taking the position as the position of the vehicle to be determined.
The high-precision map of the embodiment stores road traffic marking lines and form information of the road traffic marking lines obtained by taking different positions as viewing angles; for example, for a left turn marking, different cubic equation models can be obtained when the left turn marking is seen from different angles, and parameters of the cubic equation models may not be equal.
Since the form information of the road traffic marking from different visual angles (including the position of the vehicle as the visual angle) is stored in the high-precision map, when the reference marking is seen from the vehicle as the visual angle, the obtained cubic equation of the reference marking is consistent with the cubic equation of the reference marking stored in the map, the cubic equation of the reference marking searched in the map at the moment is obtained by taking the current position of the vehicle as the visual angle, and at the moment, the position of the vehicle can be searched in the high-precision map.
According to the method, when the satellite signals in the positioning system are shielded and cannot be accurately positioned, the positioning system can be assisted to position by adopting a mode of combining the vision sensor and the laser radar, so that the transverse and longitudinal positioning accuracy is kept within 10cm, and the requirement of intelligent driving is met.
The invention also provides a positioning system based on the combination of the map and the multi-sensor detection, which comprises the following units:
a unit for selecting a road traffic marking near a vehicle as a reference marking and identifying the type of the reference marking, wherein the type comprises the shape and color characteristics of the road marking;
means for identifying morphological information of the reference reticle with a current position of the vehicle as a perspective;
the road traffic marking system is used for determining the area of the vehicle in the high-precision map according to the positioning information of the vehicle, searching the road traffic marking in the area, and finding the road traffic marking which is stored in the high-precision map and corresponds to the type of the reference marking according to the type of the reference marking; finding out the position corresponding to the form information according to the one-to-one correspondence relationship between the form information of the road traffic marking and the position, and taking the position as the position of the vehicle to be determined; and the high-precision map is stored with road traffic marking lines and form information of the road traffic marking lines obtained by taking different positions as visual angles.
The positioning system serves as a software framework, and each unit of the positioning system is a process or a program corresponding to the steps 1 to 3 of the positioning method. Therefore, the positioning system will not be described in detail.
As a program, the positioning system can assist the positioning system in positioning by adopting a mode of combining a visual sensor and a laser radar when the satellite signal in the positioning system is shielded and cannot be accurately positioned, so that the transverse and longitudinal positioning accuracy is kept within 10cm, and the requirement of intelligent driving is met.
The specific embodiments are given above, but the present invention is not limited to the above-described embodiments. The basic idea of the present invention lies in the above basic scheme, and it is obvious to those skilled in the art that no creative effort is needed to design various modified models, formulas and parameters according to the teaching of the present invention. Variations, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, and still fall within the scope of the invention.
Claims (7)
1. A positioning method based on combination of a map and multi-sensor detection is characterized by comprising the following steps:
1) selecting a road traffic marking near a vehicle as a reference marking, and identifying the type of the reference marking, wherein the type comprises the shape and color characteristics of the road marking;
2) identifying morphological information of the reference marking with a current position of the vehicle as a viewing angle, the morphological information being represented as a curvilinear model within a plane, the curvilinear model within the planeThe line model is expressed as a cubic equation y ═ ax3+bx2+ cx + d, wherein x, y respectively represent: taking the center of the vehicle as a coordinate origin, and the transverse distance and the longitudinal distance of each point on the road traffic marking relative to the vehicle, wherein a, b, c and d respectively represent corresponding coefficients;
3) determining the area of the vehicle in the high-precision map according to the positioning information of the vehicle, searching for the road traffic marking in the area, and finding the road traffic marking corresponding to the type of the reference marking stored in the high-precision map according to the type of the reference marking; the high-precision map is stored with road traffic marking lines and a cubic equation of form information of the road traffic marking lines obtained by taking different positions as visual angles;
4) and comparing the cubic equation of the road traffic marking corresponding to the type of the reference marking stored in the high-precision map with the cubic equation of the reference marking form information in the step 2), and taking the position corresponding to the cubic equation which is consistent with the cubic equation of the reference marking and stored in the high-precision map as the position of the vehicle to be determined.
2. The map-based positioning method combined with multi-sensor detection according to claim 1, wherein the type of the reference reticle is identified in step 1) by a visual sensor.
3. The method of claim 1, wherein the step 2) is performed by identifying the shape information of the reference mark line through laser radar.
4. The map-based positioning method combined with multi-sensor detection as claimed in claim 1, wherein the road traffic markings comprise longitudinal lane lines, stop lines, zebra stripes, left-right turn and straight indication lines, and text indication lines.
5. The positioning method based on the combination of the map and the multi-sensor detection as claimed in claim 1, wherein in step 1), the shape and the color of each road traffic marking are collected by a deep learning method, a sample set comprising the shape and the color of each road traffic marking is obtained, and the type of the reference marking is identified by comparing the currently collected road traffic marking with the sample set.
6. A positioning system based on a map and multi-sensor detection is characterized in that the positioning system comprises the following units in a vision sensor and a laser radar system:
a unit for selecting a road traffic marking near a vehicle as a reference marking and identifying the type of the reference marking, wherein the type comprises the shape and color characteristics of the road marking;
a unit for identifying a cubic equation of the morphological information of the reference marking with a current position of the vehicle as a viewing angle;
the road traffic marking system is used for determining the area of the vehicle in the high-precision map according to the positioning information of the vehicle, searching the road traffic marking in the area, and finding the road traffic marking which is stored in the high-precision map and corresponds to the type of the reference marking according to the type of the reference marking; the high-precision map is stored with road traffic marking lines and form information of the road traffic marking lines obtained by taking different positions as visual angles; and comparing the cubic equation of the road traffic marking corresponding to the type of the reference marking stored in the high-precision map with the cubic equation of the form information of the reference marking, and taking the position corresponding to the cubic equation which is consistent with the cubic equation of the reference marking and stored in the high-precision map as a unit of the position of the vehicle to be determined.
7. The map-based positioning system in combination with multi-sensor detection as claimed in claim 6, wherein the road traffic markings comprise longitudinal lane lines, stop lines, zebra stripes, left-right turn and go straight indicator lines, text indicator lines.
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| CN109931939B (en) * | 2019-02-27 | 2020-11-03 | 杭州飞步科技有限公司 | Vehicle positioning method, device, equipment and computer readable storage medium |
| CN109752008B (en) * | 2019-03-05 | 2021-04-13 | 长安大学 | Intelligent vehicle multi-mode cooperative positioning system and method and intelligent vehicle |
| CN110700131B (en) * | 2019-10-12 | 2023-03-14 | 山东科技大学 | Long tunnel distance information identification device based on visual features and use method |
| CN110992813B (en) * | 2019-12-25 | 2021-07-09 | 江苏徐工工程机械研究院有限公司 | Map creation method and system for unmanned surface mine system |
| CN113971846B (en) * | 2020-07-22 | 2023-05-09 | 宇通客车股份有限公司 | Positioning failure detection method and device for automatic driving vehicle |
| CN114743395B (en) * | 2022-03-21 | 2024-03-08 | 中汽创智科技有限公司 | Signal lamp detection method, device, equipment and medium |
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