CN114279453B - Automatic driving vehicle positioning method and device based on vehicle-road cooperation and electronic equipment - Google Patents
Automatic driving vehicle positioning method and device based on vehicle-road cooperation and electronic equipment Download PDFInfo
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- CN114279453B CN114279453B CN202210205628.XA CN202210205628A CN114279453B CN 114279453 B CN114279453 B CN 114279453B CN 202210205628 A CN202210205628 A CN 202210205628A CN 114279453 B CN114279453 B CN 114279453B
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Abstract
The application discloses a method, a device and electronic equipment for positioning an automatic driving vehicle based on vehicle-road cooperation, wherein the method comprises the following steps: acquiring a reference position information set of a vehicle sent by road side equipment, wherein the reference position information set is obtained based on a grid map established by the road side equipment in a visual range of the road side equipment; determining the reference position information of the vehicle according to the reference position information set of the vehicle; determining absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and the positioning point of the self-vehicle; and performing fusion positioning according to the absolute position information of the self-vehicle to obtain a fusion positioning result of the self-vehicle. According to the automatic driving vehicle positioning method based on vehicle-road cooperation, the position of the vehicle is determined through the position information of all vehicles in the visible range provided by the road side equipment, the final fusion positioning result of the vehicle is obtained through fusion positioning processing, and the positioning accuracy and stability under extreme environments or extreme weather are guaranteed.
Description
Technical Field
The application relates to the technical field of automatic driving, in particular to an automatic driving vehicle positioning method and device based on vehicle-road cooperation and electronic equipment.
Background
High-precision positioning is very important for an autonomous vehicle, and the higher and more stable the positioning precision, the safer the autonomous vehicle will be. Currently, the mainstream positioning scheme mainly combines Navigation, for example, a kalman filter is used to fuse a high-frequency IMU (Inertial Measurement Unit) positioning signal and a low-frequency GNSS (Global Navigation Satellite System) positioning signal, and output a high-frequency positioning result without accumulated error.
With the development of the hardware And multi-sensor fusion positioning technology, the SLAM (synchronous positioning And Mapping) method based on the visual devices such as cameras And laser radars is also gradually adopted to provide auxiliary positioning information, And make up for the deficiency when the GNSS positioning signal is not good.
However, the accuracy of GNSS positioning signals is greatly reduced due to multipath effects caused by tall buildings, viaducts and the like in cities, and the laser SLAM or visual SLAM method is used on the premise that map data such as a map built by laser, a high-precision map or a semantic map is required, and in many scenes, the method cannot obtain reliable results, such as scenes that snow and water exist on the road surface or dynamic objects around the vehicle are more.
Disclosure of Invention
The embodiment of the application provides a method and a device for positioning an automatic driving vehicle based on vehicle-road cooperation and electronic equipment, so as to ensure the positioning accuracy and stability of the automatic driving vehicle in an extreme environment.
The embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides an automatic driving vehicle positioning method based on vehicle-road coordination, where the method includes:
acquiring a reference position information set of a vehicle sent by road side equipment, wherein the reference position information set is obtained based on a grid map established by the road side equipment in a visual range of the road side equipment;
determining the reference position information of the vehicle according to the reference position information set of the vehicle;
determining absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and the positioning point of the self-vehicle;
and performing fusion positioning according to the absolute position information of the self-vehicle to obtain a fusion positioning result of the self-vehicle.
Optionally, the reference position information set is obtained by:
acquiring a road sensing result of road side equipment in a visible range of the road side equipment;
according to the road sensing result of the road side equipment in the visible range of the road side equipment, and the position information and the equipment parameter information of the road side equipment, establishing a grid map of the road side equipment in the visible range of the road side equipment and determining the absolute position of each grid in the grid map;
and generating a reference position information set of the vehicle on the grid map under the condition that the vehicle enters the visible range of the road side equipment.
Optionally, the reference position information set is obtained by:
acquiring high-precision map data corresponding to the road side equipment in a visible range of the road side equipment;
determining an absolute position of each cell in the grid map from the high precision map data.
Optionally, the determining the reference position information of the host vehicle according to the reference position information set of the vehicle includes:
if the reference position information set of the vehicle only contains the reference position information of the vehicle, directly obtaining the reference position information of the vehicle from the reference position information set of the vehicle;
and if the reference position information set of the vehicle comprises the reference position information of a plurality of vehicles, determining the reference position information of the vehicle according to the reference position information of the vehicles and the perception result of the vehicle to the surrounding vehicles.
Optionally, the determining of the absolute position information of the own vehicle according to the reference position information of the own vehicle, the size information of the own vehicle, and the positioning point of the own vehicle includes:
determining an angular point to be corrected in a vehicle projection frame on the grid map according to the driving direction of the vehicle;
correcting the angular point to be corrected according to the size information of the self-vehicle to obtain a corrected self-vehicle projection frame;
and determining the absolute position information of the self-vehicle according to the corrected self-vehicle projection frame and the positioning point of the self-vehicle.
Optionally, after the corner point to be corrected is corrected according to the size information of the vehicle to obtain a corrected vehicle projection frame, the method further includes:
and under the condition that the corrected vehicle projection frame meets the preset precision requirement, the corrected vehicle projection frame is used as the prior information of the vehicle projection frame so as to restrain the subsequently obtained vehicle projection frame according to the prior information of the vehicle projection frame.
Optionally, the performing fusion positioning according to the absolute position information of the own vehicle, and obtaining a fusion positioning result of the own vehicle includes:
acquiring IMU positioning information and GNSS positioning information;
and inputting the absolute position information of the self-vehicle, the IMU positioning information and the GNSS positioning information into an extended Kalman filter for fusion positioning to obtain a fusion positioning result of the self-vehicle.
In a second aspect, an embodiment of the present application further provides an automatic driving vehicle positioning device based on vehicle-road coordination, where the device includes:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a reference position information set of a vehicle sent by road side equipment, and the reference position information set is obtained based on a grid map established by the road side equipment in a visible range of the road side equipment;
a first determination unit configured to determine reference position information of a host vehicle from a reference position information set of the vehicle;
the second determining unit is used for determining the absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and the positioning point of the self-vehicle;
and the fusion positioning unit is used for performing fusion positioning according to the absolute position information of the self-vehicle to obtain a fusion positioning result of the self-vehicle.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform any of the methods described above.
In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium storing one or more programs, which when executed by an electronic device including a plurality of application programs, cause the electronic device to perform any of the methods described above.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects: the method for positioning the automatic driving vehicle based on the vehicle-road cooperation comprises the steps of firstly obtaining a reference position information set of the vehicle sent by road side equipment, wherein the reference position information set is obtained based on a grid map established by the road side equipment in a visible range of the road side equipment; then determining the reference position information of the vehicle according to the reference position information set of the vehicle; then, determining absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and the positioning point of the self-vehicle; and finally, performing fusion positioning according to the absolute position information of the self-vehicle to obtain a fusion positioning result of the self-vehicle. According to the positioning method and the positioning device, the position information of all vehicles in the visible range provided by the roadside equipment end is used for determining the position of the self vehicle, the final fusion positioning result of the self vehicle is obtained through fusion positioning processing, and the positioning accuracy and the stability under extreme environments or extreme weather are guaranteed.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic flow chart illustrating a method for locating an autonomous vehicle based on vehicle-road coordination according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a grid map according to an embodiment of the present application;
FIG. 3 is a schematic structural diagram of an automatic driving vehicle positioning device based on vehicle-road coordination in an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only a few embodiments of the present application, and not all 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 application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
The embodiment of the present application provides an automatic driving vehicle positioning method based on vehicle-road coordination, as shown in fig. 1, a schematic flow diagram of the automatic driving vehicle positioning method based on vehicle-road coordination in the embodiment of the present application is provided, and the method at least includes the following steps S110 to S140:
step S110, a reference position information set of a vehicle sent by road side equipment is obtained, and the reference position information set is obtained based on a grid map established by the road side equipment in a visible range of the road side equipment.
Because the vision sensor of the vehicle has certain limitation in the capture range, and the roadside device can capture the conditions of the vehicle and all vehicles around the vehicle from a relatively wider visual field, the positioning mode based on vehicle-road cooperation can make up for the defect of positioning only by depending on vehicle-end positioning information to a great extent.
Specifically, when positioning an autonomous vehicle, in the embodiment of the present application, a reference position information set of the vehicle sent by the roadside device needs to be obtained first, where the reference position information set may be understood as a set of positioning information of all vehicles primarily sensed by the roadside device based on a grid map established in a visible range of the roadside device, and is called "reference position information", because a sensing result obtained by a vision sensor of the roadside device may have a certain error, and it is difficult to meet a positioning accuracy requirement of the autonomous vehicle when used alone, and therefore, the reference position information is used as the reference information, and further, the sensing results of other sensors are combined to perform fusion positioning, so as to obtain a high-accuracy positioning result.
And step S120, determining the reference position information of the vehicle according to the reference position information set of the vehicle.
Since there may be more than one vehicle entering the visible range of the roadside device at a certain time, which may cause that the reference position information set of the vehicle sent by the roadside device may include the reference position information of multiple vehicles, the reference position information corresponding to the vehicle needs to be determined from the reference position information set after the reference position information set of the vehicle is acquired in the embodiment of the present application.
And step S130, determining absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and the positioning point of the self-vehicle.
After obtaining the reference position information of the self-vehicle, it is further required to calculate an absolute position of the self-vehicle, that is, longitude and latitude coordinates of the self-vehicle, by combining the size of the self-vehicle and a positioning point of the self-vehicle, where the positioning point of the self-vehicle can be understood as a point on the vehicle for representing a specific position of the vehicle, for example, a rear axle center of the autonomous vehicle can be used as the positioning point, and an absolute position of the rear axle center of the autonomous vehicle can be calculated as the absolute position of the self-vehicle. Of course, which position on the vehicle is specifically determined as the positioning point, and those skilled in the art may also flexibly adjust according to actual requirements, and is not specifically limited herein.
And step S140, carrying out fusion positioning according to the absolute position information of the self-vehicle to obtain a fusion positioning result of the self-vehicle.
After the absolute position of the vehicle is obtained, the absolute position of the vehicle can be used as an observation value and is input into an Extended Kalman Filter (EKF for short) together with positioning information sensed by other sensors at the vehicle end to perform fusion positioning, so that a fusion positioning result of the vehicle is obtained.
According to the embodiment of the application, the position information of all vehicles in the visible range provided by the road side equipment end is used for determining the position of the self vehicle, the final fusion positioning result of the self vehicle is obtained through fusion positioning processing, and the positioning accuracy and stability in extreme environments or extreme weather are guaranteed.
In an embodiment of the present application, the set of reference location information is obtained by: acquiring a road sensing result of road side equipment in a visible range of the road side equipment; according to the road sensing result of the road side equipment in the visible range of the road side equipment, and the position information and the equipment parameter information of the road side equipment, establishing a grid map of the road side equipment in the visible range of the road side equipment and determining the absolute position of each grid in the grid map; and generating a reference position information set of the vehicle on the grid map under the condition that the vehicle enters the visible range of the road side equipment.
When the roadside device sends the reference position information set, the following method may be specifically adopted: firstly, calibrating internal parameters and external parameters of a road side camera in road side equipment, then obtaining a road perception result captured by the road side camera in a visible range of the road side camera, for example, a drivable area of a vehicle can be extracted from a road image shot by the road side camera, then establishing a bird's-eye view 2D grid map of the road side equipment in the visible range according to the calibrated internal parameters and external parameters and the road perception result, and then determining the absolute position of each grid, wherein the size of the grid in the grid map can be flexibly set according to the actual situation, for example, the size of the grid is set to be 5cm x 5 cm.
When the autonomous vehicle enters the visible range of the roadside device, if only one autonomous vehicle is in the visible range, the roadside device may directly return the reference position information of the autonomous vehicle on the grid map, which may specifically include the driving direction of the autonomous vehicle and the projection frame of the autonomous vehicle on the grid map. If there are multiple vehicles at this time, the roadside device returns reference position information of all the vehicles on the grid map.
In an embodiment of the present application, the reference position information set is obtained by: acquiring high-precision map data corresponding to the roadside equipment within the visual range of the roadside equipment; determining an absolute position of each cell in the grid map from the high precision map data.
When the absolute position of each grid in the grid map is determined, the position data of the high-precision map corresponding to the road side equipment in the visual range of the road side equipment can be obtained firstly, and then the position data of the high-precision map is combined to assign values to each grid in the grid map, so that the absolute position of each grid is obtained. Of course, if there is no high-precision map data, it is also possible to calculate the absolute position of each cell in advance by means of manual measurement using a handheld positioning device.
In one embodiment of the present application, the determining the reference position information of the own vehicle from the reference position information set of the vehicle includes: if the reference position information set of the vehicle only contains the reference position information of the vehicle, directly obtaining the reference position information of the vehicle from the reference position information set of the vehicle; and if the reference position information set of the vehicle comprises the reference position information of a plurality of vehicles, determining the reference position information of the vehicle according to the reference position information of the vehicles and the perception result of the vehicle to the surrounding vehicles.
As described above, the reference position information set returned by the roadside device may only include the reference position information of the vehicle itself, and may also include the reference position information of the vehicle itself and a plurality of vehicles around the vehicle itself, if only the reference position information of the vehicle itself is included, the subsequent fusion positioning processing may be directly performed, and if the reference position information of a plurality of vehicles is included at the same time, since the position of the vehicle itself is not accurate at this time, it cannot be determined which reference position information in the reference position information set returned by the roadside device is the reference position information of the vehicle itself, at this time, the sensing result of the vehicle itself on the surrounding vehicles may be further obtained, and the reference position information of the vehicle itself may be calculated through the topological relation, that is, the spatial position information of the vehicle itself and the surrounding vehicles.
In one embodiment of the present application, the determining of the absolute position information of the own vehicle according to the reference position information of the own vehicle, the size information of the own vehicle, and the positioning point of the own vehicle includes: determining an angular point to be corrected in a vehicle projection frame on the grid map according to the driving direction of the vehicle; correcting the angular point to be corrected according to the size information of the self-vehicle to obtain a corrected self-vehicle projection frame; and determining the absolute position information of the self-vehicle according to the corrected self-vehicle projection frame and the positioning point of the self-vehicle.
Due to the problems of the shooting angle of the road side equipment or the vehicle shielding, the size of the self vehicle projection frame returned by the road side equipment is not consistent with the size of the actual vehicle, if the fusion positioning is directly carried out in this way, a certain error may be introduced, so in order to further improve the fusion positioning accuracy, after the reference position information of the vehicle returned by the roadside device end is acquired in the embodiment of the application, the driving direction of the self-vehicle can be determined firstly, wherein the driving direction of the self-vehicle is understood to be the driving direction of the self-vehicle relative to the road side equipment, so that the corner point to be corrected in the projection frame of the self-vehicle can be determined according to the driving direction of the self-vehicle, since the size information of the self-vehicle is known, the angular point to be corrected in the self-vehicle projection frame is corrected according to the size information of the self-vehicle, therefore, the more accurate size of the self-vehicle projection frame can be obtained, and finally, the absolute position of the self-vehicle is calculated according to the corrected self-vehicle projection frame and the positioning point of the self-vehicle.
To facilitate understanding of the above embodiments, and as further illustrated in conjunction with fig. 2, fig. 2 provides a schematic diagram of a grid map in an embodiment of the present application, and M1-M2-M3-M4 is an established 2D grid map, and each cell has its own absolute position. Assuming that only one vehicle of the automatically-driven vehicle is in the area currently, P1, P2, P3 and P4 are corner points of a projection frame of the automatically-driven vehicle on a grid map, which is recognized and returned by the roadside device, and assuming that the vehicle drives towards the roadside device, the position of the side P1P2 is relatively accurate according to the driving direction of the vehicle, and the positions P3 and P4 are possibly inaccurate due to occlusion, so that the size of the projection frame of the vehicle, namely the positions P3 and P4 can be corrected according to the sizes of the P1P2 and the vehicle, and finally the absolute position of the vehicle is calculated according to the corrected projection frame, thereby preventing calculation errors caused by vehicle occlusion or the shooting angle of the roadside device.
In an embodiment of the application, after the corner point to be corrected is corrected according to the size information of the own vehicle to obtain a corrected own vehicle projection frame, the method further includes: and under the condition that the corrected self-vehicle projection frame meets the preset precision requirement, the corrected self-vehicle projection frame is used as the prior information of the self-vehicle projection frame, so that the subsequently obtained self-vehicle projection frame is restrained according to the prior information of the self-vehicle projection frame.
Since frequent correction processing inevitably affects the overall positioning efficiency and further may affect the real-time performance of positioning the autonomous vehicle, the correction link of the embodiment of the present application is not a necessary step of each positioning process, and the corrected self-vehicle projection frame obtained based on the foregoing embodiment can be regarded as a stable and reliable result under the condition that the corrected self-vehicle projection frame meets a certain precision requirement and the external conditions are not significantly changed, so as to provide prior information for the calculation of the subsequent self-vehicle projection frame and constrain the calculation of the subsequent self-vehicle projection frame.
In an embodiment of the present application, the performing fusion positioning according to the absolute position information of the own vehicle, and obtaining a fusion positioning result of the own vehicle includes: obtaining IMU positioning information and GNSS positioning information; and inputting the absolute position information of the self-vehicle, the IMU positioning information and the GNSS positioning information into an extended Kalman filter for fusion positioning to obtain a fusion positioning result of the self-vehicle.
After the absolute position of the self-vehicle is calculated based on the self-vehicle reference position information returned by the roadside device, the positioning information acquired by other sensors of the self-vehicle can be further acquired, for example, the positioning information may include IMU positioning information and GNSS positioning information, and of course, the positioning information acquired by other types of sensors may also be acquired, which is not listed here. And finally, inputting the absolute position of the self-vehicle and the error obtained by statistics in advance as an observation value, IMU positioning information and GNSS positioning information into the extended Kalman filter together for fusion and updating, thereby obtaining a high-precision self-vehicle positioning result.
The error obtained through statistics in advance generally refers to an error caused by sensing results of the roadside equipment and the vehicle-end equipment, and the error can be obtained through multiple experimental statistical analysis in advance, namely can be used as an empirical value for measurement updating of subsequent fusion positioning.
The embodiment of the present application further provides an automatic driving vehicle positioning device 300 based on vehicle-road coordination, as shown in fig. 3, which provides a schematic structural diagram of an automatic driving vehicle positioning device based on vehicle-road coordination in the embodiment of the present application, where the device 300 includes: an obtaining unit 310, a first determining unit 320, a second determining unit 330, and a fusion positioning unit 340, wherein:
an obtaining unit 310, configured to obtain a reference position information set of a vehicle sent by a roadside device, where the reference position information set is obtained based on a grid map established by the roadside device within a visible range of the roadside device;
a first determining unit 320 for determining reference position information of the vehicle according to the reference position information set of the vehicle;
a second determining unit 330, configured to determine absolute position information of the host vehicle according to the reference position information of the host vehicle, and size information and a positioning point of the host vehicle;
and the fusion positioning unit 340 is configured to perform fusion positioning according to the absolute position information of the own vehicle to obtain a fusion positioning result of the own vehicle.
In an embodiment of the present application, the reference position information set is obtained by: acquiring a road perception result of road side equipment in a visible range of the road side equipment; according to the road sensing result of the road side equipment in the visible range of the road side equipment, the position information and the equipment parameter information of the road side equipment, establishing a grid map of the road side equipment in the visible range of the road side equipment, and determining the absolute position of each grid in the grid map; and generating a reference position information set of the vehicle on the grid map under the condition that the vehicle enters the visible range of the road side equipment.
In an embodiment of the present application, the reference position information set is obtained by: acquiring high-precision map data corresponding to the roadside equipment within the visual range of the roadside equipment; determining an absolute position of each cell in the grid map from the high-precision map data.
In an embodiment of the present application, the first determining unit 320 is specifically configured to: if the reference position information set of the vehicle only contains the reference position information of the vehicle, directly obtaining the reference position information of the vehicle from the reference position information set of the vehicle; and if the reference position information set of the vehicle comprises the reference position information of a plurality of vehicles, determining the reference position information of the vehicle according to the reference position information of the vehicles and the perception result of the vehicle to the surrounding vehicles.
In an embodiment of the present application, the second determining unit 330 is specifically configured to: determining an angular point to be corrected in a vehicle projection frame on the grid map according to the driving direction of the vehicle; correcting the angular point to be corrected according to the size information of the self-vehicle to obtain a corrected self-vehicle projection frame; and determining the absolute position information of the self-vehicle according to the corrected self-vehicle projection frame and the positioning point of the self-vehicle.
In an embodiment of the present application, the second determining unit 330 is specifically configured to: and under the condition that the corrected vehicle projection frame meets the preset precision requirement, the corrected vehicle projection frame is used as the prior information of the vehicle projection frame so as to restrain the subsequently obtained vehicle projection frame according to the prior information of the vehicle projection frame.
In an embodiment of the present application, the fusion positioning unit 340 is specifically configured to: acquiring IMU positioning information and GNSS positioning information; and inputting the absolute position information of the self-vehicle, the IMU positioning information and the GNSS positioning information into an extended Kalman filter for fusion positioning to obtain a fusion positioning result of the self-vehicle.
It can be understood that, the above-mentioned automatic driving vehicle positioning device based on vehicle-road coordination can realize each step of the automatic driving vehicle positioning method based on vehicle-road coordination provided in the foregoing embodiments, and the relevant explanations about the automatic driving vehicle positioning method based on vehicle-road coordination are applicable to the automatic driving vehicle positioning device based on vehicle-road coordination, and are not repeated here.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 4, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads a corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the automatic driving vehicle positioning device based on the vehicle-road coordination on a logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring a reference position information set of a vehicle sent by road side equipment, wherein the reference position information set is obtained based on a grid map established by the road side equipment in a visible range of the road side equipment;
determining the reference position information of the vehicle according to the reference position information set of the vehicle;
determining absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and the positioning point of the self-vehicle;
and performing fusion positioning according to the absolute position information of the self-vehicle to obtain a fusion positioning result of the self-vehicle.
The method executed by the automatic driving vehicle positioning device based on the vehicle-road coordination disclosed by the embodiment of fig. 1 of the application can be applied to or realized by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, etc. as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the method executed by the automatic driving vehicle positioning device based on vehicle-road coordination in fig. 1, and implement the functions of the automatic driving vehicle positioning device based on vehicle-road coordination in the embodiment shown in fig. 1, which are not described herein again in this application embodiment.
Embodiments of the present application further provide a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by an electronic device including a plurality of application programs, enable the electronic device to perform the method performed by the automatic driving vehicle positioning device based on vehicle-road coordination in the embodiment shown in fig. 1, and are specifically configured to perform:
acquiring a reference position information set of a vehicle sent by road side equipment, wherein the reference position information set is obtained based on a grid map established by the road side equipment in a visual range of the road side equipment;
determining the reference position information of the vehicle according to the reference position information set of the vehicle;
determining absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and the positioning point of the self-vehicle;
and performing fusion positioning according to the absolute position information of the self-vehicle to obtain a fusion positioning result of the self-vehicle.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that 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 like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, 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 above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art to which the present application pertains. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (9)
1. An automatic driving vehicle positioning method based on vehicle-road coordination, wherein the method comprises the following steps:
acquiring a reference position information set of a vehicle sent by road side equipment, wherein the reference position information set is obtained based on a grid map established by the road side equipment in a visual range of the road side equipment;
determining the reference position information of the vehicle according to the reference position information set of the vehicle;
determining absolute position information of the self-vehicle according to the reference position information of the self-vehicle, the size information of the self-vehicle and a positioning point of the self-vehicle, wherein the positioning point of the self-vehicle comprises a rear axle center of the self-vehicle;
inputting the absolute position information of the self vehicle as an observed value and positioning information of other sensors of the self vehicle into an extended Kalman filter together for fusion positioning to obtain a fusion positioning result of the self vehicle;
the determining of the absolute position information of the own vehicle according to the reference position information of the own vehicle, the size information of the own vehicle and the positioning point of the own vehicle comprises:
determining an angular point to be corrected in a vehicle projection frame on the grid map according to the driving direction of the vehicle;
correcting the angular point to be corrected according to the size information of the self-vehicle to obtain a corrected self-vehicle projection frame;
and determining the absolute position information of the self-vehicle according to the corrected self-vehicle projection frame and the positioning point of the self-vehicle.
2. The method of claim 1, wherein the set of reference location information is obtained by:
acquiring a road sensing result of road side equipment in a visible range of the road side equipment;
according to the road sensing result of the road side equipment in the visible range of the road side equipment, the position information and the equipment parameter information of the road side equipment, establishing a grid map of the road side equipment in the visible range of the road side equipment, and determining the absolute position of each grid in the grid map;
and generating a reference position information set of the vehicle on the grid map under the condition that the vehicle enters the visible range of the road side equipment.
3. The method of claim 2, wherein the set of reference location information is obtained by:
acquiring high-precision map data corresponding to the roadside equipment within the visual range of the roadside equipment;
determining an absolute position of each cell in the grid map from the high precision map data.
4. The method of claim 1, wherein the determining the reference location information for the host vehicle from the set of reference location information for the vehicle comprises:
if the reference position information set of the vehicle only comprises the reference position information of the vehicle, directly obtaining the reference position information of the vehicle from the reference position information set of the vehicle;
and if the reference position information set of the vehicle comprises the reference position information of a plurality of vehicles, determining the reference position information of the vehicle according to the reference position information of the vehicles and the perception result of the vehicle to the surrounding vehicles.
5. The method as claimed in claim 1, wherein after the corner points to be corrected are corrected according to the size information of the own vehicle, so as to obtain a corrected own vehicle projection frame, the method further comprises:
and under the condition that the corrected vehicle projection frame meets the preset precision requirement, the corrected vehicle projection frame is used as the prior information of the vehicle projection frame so as to restrain the subsequently obtained vehicle projection frame according to the prior information of the vehicle projection frame.
6. The method of claim 1, wherein the performing the fusion localization according to the absolute position information of the own vehicle, and obtaining the fusion localization result of the own vehicle comprises:
obtaining IMU positioning information and GNSS positioning information;
and inputting the absolute position information of the self vehicle, the IMU positioning information and the GNSS positioning information into an extended Kalman filter for fusion positioning to obtain a fusion positioning result of the self vehicle.
7. An autonomous vehicle positioning apparatus based on vehicle-to-road coordination, wherein the apparatus comprises:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a reference position information set of a vehicle sent by road side equipment, and the reference position information set is obtained based on a grid map established by the road side equipment in a visual range of the road side equipment;
a first determination unit configured to determine reference position information of a host vehicle from a set of reference position information of the vehicle;
a second determining unit, configured to determine absolute position information of the vehicle according to the reference position information of the vehicle, the size information of the vehicle, and a positioning point of the vehicle, where the positioning point of the vehicle includes a center of a rear axle of the vehicle;
the fusion positioning unit is used for inputting the absolute position information of the self vehicle as an observed value and positioning information of other sensors of the self vehicle into an extended Kalman filter together for fusion positioning to obtain a fusion positioning result of the self vehicle;
the reference position information of the own vehicle includes a driving direction of the own vehicle and an own vehicle projection frame on the grid map, and the second determination unit is specifically configured to:
determining an angular point to be corrected in a vehicle projection frame on the grid map according to the driving direction of the vehicle;
correcting the angular point to be corrected according to the size information of the self-vehicle to obtain a corrected self-vehicle projection frame;
and determining the absolute position information of the self-vehicle according to the corrected self-vehicle projection frame and the positioning point of the self-vehicle.
8. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of any of claims 1 to 6.
9. A computer readable storage medium storing one or more programs which, when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method of any of claims 1-6.
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| CN115900732A (en) * | 2023-01-05 | 2023-04-04 | 武汉大学 | Combined navigation method and system based on roadside camera and vehicle-mounted unit |
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