CN117870701A - Lane positioning method and device, electronic equipment and storage medium - Google Patents
Lane positioning method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application discloses a lane positioning method, a lane positioning device, electronic equipment and a storage medium, which relate to the technical field of automatic driving and are used for realizing high-precision lane-level positioning according to sensor signals, wherein the method comprises the following steps: firstly, acquiring an initial positioning signal of a current vehicle; then, according to the initial positioning signal and the light-weight lane map information at the current moment, obtaining target positioning information of the current vehicle at the current moment; and finally, matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle. By the method, lane positioning by using a high-precision map is avoided, lane-level positioning is realized by using the vehicle sensor equipment and the lightweight lane map, and the lane positioning accuracy is improved.
Description
Technical Field
The application mainly relates to the technical field of automatic driving, in particular to a lane positioning method, a lane positioning device, electronic equipment and a storage medium.
Background
With the continuous development of intelligent driving technology, the accuracy of vehicle positioning by users is also higher and higher, and lane-level positioning has become a necessary requirement for high-accuracy positioning. The accuracy of high-accuracy positioning is generally in the decimeter level or even in the centimeter level, and a higher-accuracy positioning result can be provided for the vehicle.
When a vehicle starts an automatic driving function and needs to perform operations such as lane changing, it is generally necessary to determine a lane where the vehicle is currently located and then perform lane changing strategies. Thus, lane-level positioning has an indispensable important role in automatic driving.
In the related art, high-precision lane-level positioning is mostly realized by combining real-time data of a vehicle-mounted sensor with high-precision map features. However, the current high-precision map is high in map building maintenance cost and low in scene coverage, so that the high-precision lane-level positioning scheme based on the high-precision map is difficult to apply on a large scale.
Therefore, how to realize high-precision lane-level positioning independent of a high-precision map is a problem to be solved urgently at present.
Disclosure of Invention
The application provides a lane positioning method, a lane positioning device, electronic equipment and a storage medium, which are used for realizing high-precision lane-level positioning according to vehicle sensor signals.
In a first aspect, the present application provides a lane positioning method, including:
acquiring an initial positioning signal of a current vehicle; the initial positioning signal is used for indicating the current running direction of the current vehicle;
obtaining target positioning information of a current vehicle at the current time according to the initial positioning signal and the light-weight lane map information at the current time; the target positioning information is used for indicating a lane group where the current vehicle is located at the current moment.
In an alternative embodiment, before matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle, the method further includes:
acquiring sensing data acquired by sensor equipment;
and constructing a lane topological relation corresponding to the current moment based on the perception data.
In an alternative embodiment, constructing the lane topology corresponding to the current time based on the perceived data includes:
processing the perception data to obtain lane line information and lane attribute information of each lane; the lane line information comprises the slope, curvature and lane line type of the lane line, and the lane attribute information comprises the width of the lane line, the geometric arrangement of the lane line, steering information and road edge information;
and constructing a lane topological relation corresponding to the current moment based on the lane attribute information and the lane line information of the adjacent lanes.
In an alternative embodiment, matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle includes:
respectively obtaining lane perception results under light lane map information and lane topological relation;
calculating the matching score of the current vehicle under each lane of the lane topological relation by adopting a preset algorithm;
sorting the matching scores, and determining a first matching score and a second matching score with the maximum two matching scores;
and if the ratio of the first matching score to the second matching score is larger than a preset threshold, taking the lane corresponding to the first matching score as the lane positioning result of the current vehicle.
In a second aspect, the present application provides a lane positioning apparatus comprising:
the acquisition module is used for acquiring an initial positioning signal of the current vehicle; the initial positioning signal is used for indicating the current running direction of the current vehicle;
the processing module is used for obtaining target positioning information of the current vehicle at the current time according to the initial positioning signal and the light-weight lane map information at the current time; the target positioning information is used for indicating a lane group where a current vehicle is located at the current moment;
and the matching module is used for matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle.
In an alternative embodiment, before matching the target positioning information with the lane topology relationship to obtain the lane positioning result of the current vehicle, the processing module is further configured to:
acquiring sensing data acquired by sensor equipment;
and constructing a lane topological relation corresponding to the current moment based on the perception data.
In an optional implementation manner, when constructing the lane topology relationship corresponding to the current time based on the perception data, the processing module is specifically configured to:
processing the perception data to obtain lane line information and lane attribute information of each lane; the lane line information comprises the slope, curvature and lane line type of the lane line, and the lane attribute information comprises the width of the lane line, the geometric arrangement of the lane line, steering information and road edge information;
and constructing a lane topological relation corresponding to the current moment based on the lane attribute information and the lane line information of the adjacent lanes.
In an optional implementation manner, when the target positioning information is matched with the lane topological relation to obtain the lane positioning result of the current vehicle, the matching module is specifically configured to:
respectively obtaining lane perception results under light lane map information and lane topological relation;
calculating the matching score of the current vehicle under each lane of the lane topological relation by adopting a preset algorithm;
sorting the matching scores, and determining a first matching score and a second matching score with the maximum two matching scores;
and if the ratio of the first matching score to the second matching score is larger than a preset threshold, taking the lane corresponding to the first matching score as the lane positioning result of the current vehicle.
In a third aspect, the present application provides an electronic device, including:
a memory for storing a computer program;
and the processor is used for realizing the steps of the lane positioning method when executing the computer program stored in the memory.
In a fourth aspect, the present application provides a computer readable storage medium having a computer program stored therein, which when executed by a processor, implements the steps of a lane positioning method as described above.
Through the technical scheme in the above-mentioned one or more embodiments of the present application, the embodiments of the present application have at least the following beneficial effects:
in the lane positioning method provided by the embodiment of the application, an initial positioning signal of a current vehicle is firstly obtained; determining the current running direction of the current vehicle through the initial positioning signal; then, according to the initial positioning signal and the light-weight lane map information at the current moment, obtaining target positioning information of the current vehicle at the current moment, so as to determine a lane group where the current vehicle is located when driving in a road; and finally, matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle. By adopting the mode, the problems of high map construction and maintenance cost and low scene coverage of the high-precision map in the prior art are avoided, the existing sensor signals of the vehicle and the lightweight lane map are fully utilized to perform lane-level positioning, the map construction and maintenance cost can be reduced, and the positioning precision is improved.
The technical effects of each of the second to fourth aspects and the technical effects that may be achieved by each of the aspects are referred to above for the technical effects that may be achieved by each of the first aspect and the various possible aspects of the first aspect, and the detailed description is not repeated here.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it will be apparent that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
fig. 1 is a schematic flow chart of an implementation of a lane positioning method according to an embodiment of the present application;
fig. 2 is a schematic gaussian distribution diagram of a lane according to an embodiment of the present disclosure;
fig. 3 is a gaussian distribution schematic diagram of a predicted lane according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a lane positioning device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the technical solutions of the present application, but not all embodiments. All other embodiments, which can be made by a person of ordinary skill in the art without any inventive effort, based on the embodiments described in the present application are intended to be within the scope of the technical solutions of the present application.
It should be noted that "a plurality of" is understood as "at least two" in the description of the present application. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. A is connected with B, and can be represented as follows: both cases of direct connection of A and B and connection of A and B through C. In addition, in the description of the present application, the words "first," "second," and the like are used merely for distinguishing between the descriptions and not be construed as indicating or implying a relative importance or order.
With the continuous development of intelligent driving technology, the accuracy of vehicle positioning by users is also higher and higher, and lane-level positioning has become a necessary requirement for high-accuracy positioning. The accuracy of high-accuracy positioning is generally in the decimeter level or even in the centimeter level, and a higher-accuracy positioning result can be provided for the vehicle.
When a vehicle starts an automatic driving function and needs to perform operations such as lane changing, it is generally necessary to determine a lane where the vehicle is currently located and then perform lane changing strategies. Thus, lane-level positioning has an indispensable important role in automatic driving.
In the related art, high-precision lane-level positioning is mostly realized by combining real-time data of a vehicle-mounted sensor with high-precision map features. However, the current high-precision map is high in map building maintenance cost and low in scene coverage, so that the high-precision lane-level positioning scheme based on the high-precision map is difficult to apply on a large scale.
In view of this, an embodiment of the present application provides a lane positioning method, including: acquiring an initial positioning signal of a current vehicle; then, according to the initial positioning signal and the light-weight lane map information at the current moment, obtaining target positioning information of the current vehicle at the current moment; and finally, matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle. By the method, the use of a high-precision map is avoided, the lane topological relation is constructed by utilizing the sensor data, the position of the current vehicle on the lightweight lane map is matched with the position of the current vehicle on the lane topological relation, the actual running position of the current vehicle on the lane is obtained, and the positioning precision of automatic driving is improved.
It should be noted that the following description of the preferred embodiments of the present application is given by way of illustration and explanation only, and is not intended to limit the present application, and the features of the embodiments of the present application and the embodiments thereof may be combined with each other without conflict.
Referring to fig. 1, a schematic implementation flow chart of a lane positioning method provided in an embodiment of the present application is shown, where a specific implementation flow chart of the method is as follows:
s1: an initial positioning signal of a current vehicle is obtained.
S2: and obtaining target positioning information of the current vehicle at the current time according to the initial positioning signal and the light-weight lane map information at the current time.
S3: and matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle.
In this embodiment of the present application, the current vehicle may be any vehicle with an autopilot function, and various sensors may be mounted in the current vehicle. The sensor may include any visual sensor having an image capturing and/or video capturing function, such as a camera, an infrared camera, a digital camera (Digital Still Camera, DSC), a single lens reflex camera (Single Lens Reflex Camera, SLRC), etc., and the visual sensor may be mounted outside a cabin of the current vehicle, so that during the running of the current vehicle, image data in the running environment of the current vehicle may be captured based on the mounted visual sensor.
Further, the sensor may also include a radio positioning device with target detection and spatial positioning functions, such as millimeter wave radar, ultrasonic radar, laser radar, and the like. The radar device can acquire the point cloud information in the running environment of the current vehicle.
Further, a high-precision positioning module is further mounted on the current vehicle, where the high-precision positioning module is any one or a combination of electronic devices for precisely positioning the current vehicle, such as an inertial positioning unit (Real time kinematic, RTK), an inertial measurement unit (Inertial Measurement Unit, IMU), a Dead reckoning unit (DR), a global satellite navigation system (Global Navigation Satellite System, GNSS), and other precise positioning devices. The positioning information of the current vehicle can be accurately obtained in real time through the device.
Further, in the running process of the current vehicle, an initial positioning signal of the current vehicle is obtained through the accurate positioning device, the target positioning information can be obtained through the positioning devices such as the GNSS and the IMU, and the initial positioning signal comprises, but is not limited to, longitude and latitude, altitude, heading angle and the like of the current vehicle. After the initial positioning signal is obtained, the driving position of the current vehicle can be positioned and updated based on the road sign information such as the crosswalk, the intersection stop line and the like in the current driving environment acquired by the sensor equipment such as the camera and the like, so that the initial positioning result of the current vehicle is obtained.
After the initial positioning signal of the current vehicle is obtained through the positioning equipment, the target positioning information of the current vehicle at the current time is obtained according to the initial positioning signal and the light-weight lane map information at the current time. Specifically, the target positioning information is used to indicate a lane group in which the current vehicle is currently located, and it should be noted that a lane group has a plurality of lanes therein, each lane being constituted by left and right boundary lines, a lane center line, and the like. The light-weight lane map information can be existing standard map data and can be obtained directly from the cloud. The lightweight lane map information may include lane number information of the current road segment and attribute information of the current road, the lane number distribution condition may be predicted based on the lane number information, and the attribute information of the current road may include attribute information such as steering condition, category, speed limit information, and the like of lanes in the current road segment. Based on the initial positioning signal and the lightweight lane map information, a specific lane group on which the current vehicle runs can be defined, and the specific lane on which the current vehicle runs can be further determined.
In an alternative embodiment, the lane topology relationship corresponding to the current moment is further constructed based on the sensing data by acquiring the sensing data acquired by the sensor device.
Specifically, after the sensing data collected by the sensor device is processed, lane line information and lane attribute information of each lane can be obtained, the lane line information can include a slope of a lane line, a type of a curvature lane line (the lane line is a solid line or a broken line, etc.), a transverse distance between the lane lines, etc., and the lane attribute information includes a width of the lane line, a geometric arrangement of the lane line, steering information, road edge information, etc.
And then, processing the lane line semantic result according to a preset logic to obtain lane attribute information of each lane, such as the width of each lane and the geometric arrangement of a plurality of lanes, fitting and superposing the lane attribute information of each lane, and constructing a lane topological relation corresponding to the current moment based on the lane attribute information and the lane line information of the adjacent lanes. The constructed lane topological relation at least comprises a front-back relation of adjacent lanes, an adjacent relation of left and right lanes, lane distribution condition of the current lane group and the like.
The road level positioning information in the embodiment of the application is obtained by the lightweight lane map, the road level positioning information can comprise the information such as the number and the position of lanes of the current road, the positioning accuracy is low, and the positioning can be generally only accurate to the sub-meter level or meter level road positioning, but the positioning can not be performed to the specific lanes in the current lane group, so that the lightweight lane map can not be independently used for realizing the lane level positioning.
In an optional implementation manner, matching the target positioning information with the lane topological relation to obtain a lane positioning result of the current vehicle specifically includes: firstly, respectively acquiring a lane sensing result of a current vehicle in lightweight lane map information and a lane sensing result under a lane topological relation, so as to determine that the current vehicle is likely to be positioned in the lightweight lane map and the lane topological relation, wherein M possible positions of the current vehicle on the lightweight lane map are provided, the positions of the current vehicle on the lightweight lane map are initialized by overlapping Gaussian distribution, and referring to the figure 2, each lane is equally divided into 4 parts, and is totally divided into 4N, and if the possible positions of the current vehicle are 2, 2 peaks exist under the lane topological relation. Further, referring to fig. 3, the lateral offset of the current vehicle is calculated according to the lateral position of the current vehicle, the angle and curvature of the lane line through which the current road section passes, and the like, and the possible lateral position of the current vehicle in the lane group is determined according to the lateral offset of the current vehicle.
Then, a preset algorithm is adopted to calculate the matching score of the current vehicle under each lane of the lane topological relation and each lane on the lightweight lane map, for example, a Viterbi algorithm can be adopted to calculate the matching score of the current vehicle under each lane of the lane topological relation. The viterbi algorithm can record the maximum probability of all paths arriving at the state every time after the start of the state, and then continue to advance backwards with this maximum as the reference to find the globally optimal path.
Further, sorting all the matching scores, and determining a first matching score and a second matching score with the maximum two matching scores; and if the ratio of the first matching score to the second matching score is larger than a preset threshold, taking the lane corresponding to the maximum matching score (first matching score) as the lane positioning result of the current vehicle. It should be noted that, the preset threshold may be a value set according to an actual application scenario or a working condition, and the embodiment of the present application is not limited specifically herein.
Based on the same inventive concept, the embodiment of the present application further includes a lane positioning device, as shown in fig. 4, where the device includes: an acquisition module 401, a processing module 402, and a matching module 403; wherein,
an acquisition module 401, configured to acquire an initial positioning signal of a current vehicle; the initial positioning signal is used for indicating the current running direction of the current vehicle;
the processing module 402 is configured to obtain target positioning information of a current vehicle at a current time according to the initial positioning signal and the lightweight lane map information at the current time; the target positioning information is used for indicating a lane group where a current vehicle is located at the current moment;
and the matching module 403 is configured to match the target positioning information with the lane topological relation to obtain a lane positioning result of the current vehicle.
In an alternative embodiment, before matching the target positioning information with the lane topology relationship to obtain the lane positioning result of the current vehicle, the processing module 402 is further configured to:
acquiring sensing data acquired by sensor equipment;
and constructing a lane topological relation corresponding to the current moment based on the perception data.
In an alternative embodiment, when constructing the lane topology corresponding to the current time based on the perceived data, the processing module 402 is specifically configured to:
processing the perception data to obtain lane line information and lane attribute information of each lane; the lane line information comprises the slope, curvature and lane line type of the lane line, and the lane attribute information comprises the width of the lane line, the geometric arrangement of the lane line, steering information and road edge information;
and constructing a lane topological relation corresponding to the current moment based on the lane attribute information and the lane line information of the adjacent lanes.
In an alternative embodiment, when the target positioning information is matched with the lane topological relation to obtain the lane positioning result of the current vehicle, the matching module 403 is specifically configured to:
respectively obtaining lane perception results under light lane map information and lane topological relation;
calculating the matching score of the current vehicle under each lane of the lane topological relation by adopting a preset algorithm;
sorting the matching scores, and determining a first matching score and a second matching score with the maximum two matching scores;
and if the ratio of the first matching score to the second matching score is larger than a preset threshold, taking the lane corresponding to the first matching score as the lane positioning result of the current vehicle.
Based on the same inventive concept, the embodiment of the present application further provides an electronic device, where the electronic device may implement the functions of the lane positioning method, and referring to fig. 5, the electronic device includes:
the embodiment of the present application does not limit the specific connection medium between the processor 501 and the memory 502, but the connection between the processor 501 and the memory 502 through the bus 500 is exemplified in fig. 5. The connection between the other components of bus 500 is shown in bold lines in fig. 5, and is merely illustrative and not limiting. Bus 500 may be divided into an address bus, a data bus, a control bus, etc., and is represented by only one thick line in fig. 5 for ease of illustration, but does not represent only one bus or one type of bus. Alternatively, the processor 501 may be referred to as a controller, and the names are not limited.
In the embodiment of the present application, the memory 502 stores instructions executable by the at least one processor 501, and the at least one processor 501 may perform the lane positioning method as described above by executing the instructions stored in the memory 502. The processor 501 may implement the functions of the various modules in the apparatus shown in fig. 4.
The processor 501 is a control center of the device, and various interfaces and lines can be used to connect various parts of the entire control device, and by executing or executing instructions stored in the memory 502 and invoking data stored in the memory 502, various functions of the device and processing data can be performed to monitor the device as a whole.
In one possible design, processor 501 may include one or more processing units, and processor 501 may integrate an application processor and a modem processor, where the application processor primarily processes operating systems, user interfaces, application programs, and the like, and the modem processor primarily processes wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 501. In some embodiments, processor 501 and memory 502 may be implemented on the same chip, or they may be implemented separately on separate chips in some embodiments.
The processor 501 may be a general purpose processor such as a Central Processing Unit (CPU), digital signal processor, application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, and may implement or perform the methods, steps and logic blocks disclosed in embodiments of the present application. The general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the lane positioning method disclosed in connection with the embodiments of the present application may be directly embodied in a hardware processor for execution, or may be executed in a combination of hardware and software modules in the processor.
The memory 502, as a non-volatile computer readable storage medium, may be used to store non-volatile software programs, non-volatile computer executable programs, and modules. The Memory 502 may include at least one type of storage medium, and may include, for example, flash Memory, hard disk, multimedia card, card Memory, random access Memory (Random Access Memory, RAM), static random access Memory (Static Random Access Memory, SRAM), programmable Read-Only Memory (Programmable Read Only Memory, PROM), read-Only Memory (ROM), charged erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory), magnetic Memory, magnetic disk, optical disk, and the like. Memory 502 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 502 in the present embodiment may also be circuitry or any other device capable of implementing a memory function for storing program instructions and/or data.
By programming the processor 501, the code corresponding to the lane positioning method described in the foregoing embodiment may be cured into the chip, so that the chip can execute the steps of the lane positioning method of the embodiment shown in fig. 1 at the time of operation. How to design and program the processor 501 is a technique well known to those skilled in the art, and will not be described in detail herein.
Based on the same inventive concept, the embodiments of the present application also provide a storage medium storing computer instructions that, when run on a computer, cause the computer to perform the lane positioning method discussed previously.
In some possible embodiments, aspects of the lane positioning method provided herein may also be implemented in the form of a program product comprising program code for causing the control apparatus to carry out the steps of the lane positioning method according to the various exemplary embodiments of the present application as described herein above when the program product is run on the device.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (10)
1. A lane positioning method, the method comprising:
acquiring an initial positioning signal of a current vehicle; wherein the initial positioning signal is used for indicating the current running direction of the current vehicle;
obtaining target positioning information of the current vehicle at the current time according to the initial positioning signal and the light-weight lane map information at the current time; the target positioning information is used for indicating a lane group where the current vehicle is located at the current moment;
and matching the target positioning information with a lane topological relation to obtain a lane positioning result of the current vehicle.
2. The method of claim 1, further comprising, prior to said matching said target positioning information with lane topology, obtaining a lane positioning result of said current vehicle:
acquiring sensing data acquired by sensor equipment;
and constructing a lane topological relation corresponding to the current moment based on the perception data.
3. The method of claim 2, wherein constructing a lane topology corresponding to a current time based on the awareness data comprises:
processing the perception data to obtain lane line information and lane attribute information of each lane; the lane line information comprises the slope, curvature and lane line type of a lane line, and the lane attribute information comprises the width of the lane line, the geometric arrangement of the lane line, steering information and road edge information;
and constructing a lane topological relation corresponding to the current moment based on the lane attribute information of the adjacent lanes and the lane line information.
4. The method of claim 1, wherein said matching the target positioning information with a lane topology to obtain a lane positioning result of the current vehicle comprises:
respectively obtaining lane perception results under the light-weight lane map information and the lane topological relation;
calculating the matching score of the current vehicle under each lane of the lane topological relation by adopting a preset algorithm;
sorting the matching scores, and determining a first matching score and a second matching score with the largest matching scores;
and if the ratio of the first matching score to the second matching score is larger than a preset threshold, taking the lane corresponding to the first matching score as a lane positioning result of the current vehicle.
5. A lane positioning apparatus, the apparatus comprising:
the acquisition module is used for acquiring an initial positioning signal of the current vehicle; wherein the initial positioning signal is used for indicating the current running direction of the current vehicle;
the processing module is used for obtaining target positioning information of the current vehicle at the current time according to the initial positioning signal and the light-weight lane map information at the current time; the target positioning information is used for indicating a lane group where the current vehicle is located at the current moment;
and the matching module is used for matching the target positioning information with the lane topological relation to obtain the lane positioning result of the current vehicle.
6. The apparatus of claim 5, wherein prior to matching the target positioning information with a lane topology to obtain a lane positioning result for the current vehicle, the processing module is further to:
acquiring sensing data acquired by sensor equipment;
and constructing a lane topological relation corresponding to the current moment based on the perception data.
7. The apparatus of claim 6, wherein the processing module is specifically configured to, when constructing the lane topology corresponding to the current time based on the awareness data:
processing the perception data to obtain lane line information and lane attribute information of each lane; the lane line information comprises the slope, curvature and lane line type of a lane line, and the lane attribute information comprises the width of the lane line, the geometric arrangement of the lane line, steering information and road edge information;
and constructing a lane topological relation corresponding to the current moment based on the lane attribute information of the adjacent lanes and the lane line information.
8. The apparatus of claim 5, wherein when the matching the target positioning information with the lane topology relationship to obtain the lane positioning result of the current vehicle, the matching module is specifically configured to:
respectively obtaining lane perception results under the light-weight lane map information and the lane topological relation;
calculating the matching score of the current vehicle under each lane of the lane topological relation by adopting a preset algorithm;
sorting the matching scores, and determining a first matching score and a second matching score with the largest matching scores;
and if the ratio of the first matching score to the second matching score is larger than a preset threshold, taking the lane corresponding to the first matching score as a lane positioning result of the current vehicle.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor for implementing the method of any of claims 1-4 when executing a computer program stored on said memory.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a processor, implements the method of any of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410072016.7A CN117870701A (en) | 2024-01-18 | 2024-01-18 | Lane positioning method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202410072016.7A CN117870701A (en) | 2024-01-18 | 2024-01-18 | Lane positioning method and device, electronic equipment and storage medium |
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