A method for determining BEV map coverage and coverage position and related apparatus

Abstract

The application discloses a BEV map coverage rate and coverage position determination method and related device, associates and matches BEV map data with preset traffic area data to determine to-be-matched BEV map data, obtains a BEV map lane group boundary data set, associates and matches navigation map data with the preset traffic area data to obtain to-be-matched navigation map link data, and obtains planning road network link data and planning road network intersection data to associate to obtain intersection link association data set, matches the BEV map lane group boundary data set with the planning road network link data to obtain an effective coverage data set of the BEV map, and determines the BEV map coverage rate and coverage position based on the intersection link association data set and the effective coverage data set. The application realizes reduction of human time cost, and improvement of the accuracy of the BEV map coverage rate and coverage position.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a method and related apparatus for determining BEV map coverage and coverage location. Background Technology

[0002] In fields such as autonomous driving and robot navigation, BEV (Bird's Eye View) maps are an important way to represent the environment. They provide a top-down view of the vehicle or robot, facilitating tasks such as path planning and obstacle detection. Calculating BEV map coverage and coverage areas is crucial for evaluating the performance of autonomous driving systems.

[0003] However, there is currently no unified, standardized method for calculating BEV map coverage and coverage locations. Two common methods are: First, spatial matching based on navigation map data, directly matching road network spatial data with BEV map data to determine BEV map coverage and coverage locations. Second, manually annotating navigation map data that matches BEV map data to determine BEV map coverage and coverage locations. The first spatial matching method is limited by inherent errors in navigation map data, making it prone to matching errors and omissions. The second manual annotation method suffers from high labor and time costs, and the possibility of errors in the annotated data.

[0004] Therefore, how to provide a method for determining BEV map coverage and coverage location, so as to improve the accuracy of BEV map coverage and coverage location calculation results while reducing manpower and time costs, has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of the above problems, this application provides a method and related apparatus for determining BEV map coverage and coverage location, so as to improve the accuracy of BEV map coverage and coverage location calculation results while reducing manpower and time costs. The specific solution is as follows:

[0006] A method for determining BEV map coverage and coverage location, comprising:

[0007] The BEV map data is associated and matched with the preset traffic area data. The successfully matched BEV map data is determined as the BEV map data to be matched, and the BEV map lane group boundary data set is obtained from the BEV map data to be matched.

[0008] The navigation map data is associated and matched with the preset traffic area data. The successfully matched navigation map data is determined as the navigation map link data to be matched, and the planned road network link data and planned road network intersection data are obtained from the navigation map link data to be matched.

[0009] The planned road network link data and the planned road network intersection data are associated with intersection topology to obtain an intersection link associated data set.

[0010] The BEV map lane group boundary data set and the planned road network link data are matched to obtain the effective coverage data set of the BEV map in the preset traffic area.

[0011] The BEV map coverage and BEV map coverage location are determined based on the intersection link association data set and the effective coverage data set.

[0012] Optionally, the step of associating and matching BEV map data with preset traffic area data, determining successfully matched BEV map data as BEV map data to be matched, and obtaining a set of BEV map lane group boundary data from the BEV map data to be matched includes:

[0013] The spatial planar positions of the lane line elements contained in the BEV map data are associated and matched with the preset traffic area data, and the successfully matched BEV map data is determined as the BEV map data to be matched.

[0014] Valid BEV map data is filtered out from the BEV map data to be matched;

[0015] The valid BEV map data is parsed to obtain the BEV map lane group boundary data set.

[0016] Optionally, the step of filtering valid BEV map data from the BEV map data to be matched includes:

[0017] The number of times the automatic assisted navigation driving exits is counted for each lane group of BEV data in the BEV map data to be matched within the first preset period.

[0018] Lane group BEV data with fewer than a certain number of automatic assisted navigation exits are identified as valid BEV map data.

[0019] Optionally, parsing the valid BEV map data to obtain the BEV map lane group boundary data set includes:

[0020] Traverse the BEV data of each lane group in the effective BEV map data, and filter out the leftmost lane line data and the rightmost lane line data.

[0021] The lane group polygon data formed by multiple pairs of the leftmost lane line data and the rightmost lane line data constitutes the lane group boundary data set of the BEV map.

[0022] Optionally, the step of associating and matching navigation map data with the preset traffic area data, determining successfully matched navigation map data as navigation map link data to be matched, and obtaining planned road network link data and planned road network intersection data from the navigation map link data to be matched, includes:

[0023] The spatial planar positions of the lane line elements contained in the navigation map data are associated and matched with the preset traffic area data, and the successfully matched navigation map data is determined as the navigation map link data to be matched.

[0024] The first navigation map link data set is obtained by filtering out each target navigation map link data that meets the preset road level from the navigation map link data to be matched;

[0025] The first navigation map link data set is filtered by traffic popularity to obtain the second navigation map link data set;

[0026] The link data in the second navigation map link data set is determined as the planned road network link data;

[0027] The intersections of the links in the second navigation map link data set are determined as the intersection data of the planned road network.

[0028] Optionally, the step of filtering the first navigation map link data set by traffic popularity to obtain the second navigation map link data set includes:

[0029] The number of vehicles passing through each link in the first navigation map link data set within the second preset period is counted.

[0030] Link data with a vehicle count greater than the vehicle count threshold is identified as the second navigation map link data set.

[0031] Optionally, the step of associating the planned road network link data and the planned road network intersection data with intersection topology to obtain an intersection link association data set includes:

[0032] Each intersection point in the planned road network intersection data is used as an endpoint, and each endpoint is associated with each link data in the planned road network link data to obtain the intersection link associated data set.

[0033] Optionally, the BEV map lane group boundary data set and the planned road network link data are matched to obtain an effective coverage data set of the BEV map in a preset traffic area, including:

[0034] Project each lane group polygon data in the BEV map lane group boundary data set and the planned road network link data into the same Cartesian coordinate system, and determine multiple boundary matching datasets in the planned road network link data in the Cartesian coordinate system. Each boundary matching dataset includes a link data and target lane group polygon data that intersects with the link data.

[0035] For each boundary matching dataset, determine the length of the link vector within the target lane group polygon data where the included link data is located;

[0036] Calculate the ratio of the length of the link vector to the total length of the link vectors;

[0037] Among all the ratios, the target link data and target lane group polygon data corresponding to the target ratio that is greater than the preset ratio are used to form the link BEV lane group matching combination;

[0038] Each link data in the link BEV lane group matching combination and the planned road network intersection data associated with that link data are selected as the effective coverage data set.

[0039] Optionally, determining the BEV map coverage and BEV map coverage location based on the intersection link association data set and the effective coverage data set includes:

[0040] All link data in the effective coverage data set are taken as effective link data, and the actual geographical location corresponding to the effective link data is determined as the BEV map coverage location.

[0041] The ratio of the cumulative length of the effective link data in the effective coverage data set to the cumulative length of all planned road network link data is determined as the planned road network coverage rate.

[0042] The ratio of the cumulative length of the valid link data in the intersection link association data set to the cumulative length of the link data associated with all planned road network intersections is determined as the planned road network intersection coverage rate.

[0043] The planned road network coverage rate and the planned road network intersection coverage rate are determined as the BEV map coverage rate.

[0044] A device for determining BEV map coverage and coverage location, comprising:

[0045] The BEV map association and matching unit is used to associate and match BEV map data with preset traffic area data, determine the successfully matched BEV map data as BEV map data to be matched, and obtain the BEV map lane group boundary data set from the BEV map data to be matched.

[0046] The navigation map association and matching unit is used to associate and match navigation map data with the preset traffic area data, determine the successfully matched navigation map data as navigation map link data to be matched, and obtain the planned road network link data and the planned road network intersection data from the navigation map link data to be matched.

[0047] The intersection topology relationship determination unit is used to associate the planned road network link data and the planned road network intersection data with the intersection topology relationship to obtain the intersection link associated data set;

[0048] The coverage set determination unit is used to match the BEV map lane group boundary data set with the planned road network link data to obtain the effective coverage data set of the BEV map in the preset traffic area.

[0049] The coverage and coverage location determination unit is used to determine the BEV map coverage and BEV map coverage location based on the intersection link association data set and the effective coverage data set.

[0050] A computer program product includes computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the method for determining BEV map coverage and coverage location as described above.

[0051] An electronic device includes at least one processor and a memory connected to the processor, wherein:

[0052] The memory is used to store computer programs;

[0053] The processor is used to execute the computer program so that the electronic device can implement the method for determining BEV map coverage and coverage location as described above.

[0054] A computer storage medium carrying one or more computer programs, which, when executed by an electronic device, enable the electronic device to implement the method for determining BEV map coverage and coverage location as described above.

[0055] As can be seen from the above technical solution, the method and related apparatus for determining the coverage rate and coverage location of a BEV map provided in this application involve: associating and matching BEV map data with preset traffic area data to determine the successfully matched BEV map data as the BEV map data to be matched; obtaining the BEV map lane group boundary data set from the BEV map data to be matched; associating and matching navigation map data with preset traffic area data to determine the successfully matched navigation map data as the navigation map link data to be matched; obtaining planned road network link data and planned road network intersection data from the navigation map link data to be matched; associating the planned road network link data and planned road network intersection data with intersection topology to obtain an intersection link association data set; matching the BEV map lane group boundary data set with the planned road network link data to obtain an effective coverage data set of the BEV map in the preset traffic area; and determining the BEV map coverage rate and BEV map coverage location based on the intersection link association data set and the effective coverage data set. This application enables automatic matching of BEV map data and navigation map data within a preset traffic area, and automatic determination of BEV map coverage and coverage location, thereby reducing manpower and time costs and solving the problem of errors caused by human intervention. By matching the BEV map lane group boundary data set in the BEV map data with the planned road network link data in the navigation map data, and associating the planned road network link data and planned road network intersection data in the navigation map data with intersection topology relationships, the matching accuracy and the correlation between BEV map data and navigation map data are improved. This effectively avoids matching errors and omissions caused by error factors inherent in the navigation map data itself, thereby improving the accuracy of the BEV map coverage and coverage location calculation results. Attached Figure Description

[0056] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0057] Figure 1 A schematic diagram of a system architecture is provided for this application;

[0058] Figure 2 A schematic diagram of an optional hardware structure for a terminal provided in this application;

[0059] Figure 3 A schematic diagram of the structure of a server provided in this application;

[0060] Figure 4 A flowchart illustrating a method for determining BEV map coverage and coverage location provided in an embodiment of this application;

[0061] Figure 5 A schematic diagram of a device for determining BEV map coverage and coverage location provided in an embodiment of this application;

[0062] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0063] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0064] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0065] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0066] See Figure 1 , Figure 1 A schematic diagram of a system architecture is shown. The system may include a terminal 100 and a server 200. The server 200 may include one or more servers (…). Figure 1 (The example includes a server), and the server 200 can provide the method provided in the embodiments of this application to one or more terminals.

[0067] The terminal 100 may have a third-party system application installed on it. The application and webpage can provide an interface. The terminal 100 can receive relevant parameters input by the user on the interface and send the parameters to the server 200. The server 200 can obtain the processing result based on the received parameters and return the processing result to the terminal 100.

[0068] It should be understood that in some optional implementations, the terminal 100 can also complete the action of obtaining the processing result based on the received parameters on its own, without the need for the server to cooperate. This application embodiment is not limited to this.

[0069] The following description Figure 1 The product form of the mid-terminal 100;

[0070] In this application embodiment, the terminal 100 can be a vehicle-mounted device, etc., and this application embodiment does not impose any restrictions on it.

[0071] Figure 2 A schematic diagram of an optional hardware structure for terminal 100 is shown.

[0072] refer to Figure 2 As shown, the terminal 100 may include a radio frequency unit 110, a memory 120, an input unit 130, a display unit 140, a camera 150 (optional), an audio circuit 160 (optional), a speaker 161 (optional), a microphone 162 (optional), a headphone jack 163 (optional), a processor 170, an external interface 180, a power supply 190, and other components. Those skilled in the art will understand that... Figure 2 These are merely examples of terminals or multi-functional devices and do not constitute a limitation on terminals or multi-functional devices. They may include more or fewer components than shown in the illustration, or combine certain components, or use different components.

[0073] The input unit 130 can be used to receive input numerical or character information, and to generate key signal inputs related to user settings and function control of the portable multi-functional device. Specifically, the input unit 130 may include a touchscreen 131 (optional) and / or other input devices 132. The touchscreen 131 can collect touch operations performed by the user on or near it (such as operations performed by the user using fingers, knuckles, styluses, or any suitable object on or near the touchscreen), and drive the corresponding connection devices according to a pre-set program. The touchscreen can detect the user's touch actions, convert the touch actions into touch signals and send them to the processor 170, and can receive and execute commands sent by the processor 170; the touch signal includes at least touch point coordinate information. The touchscreen 131 can provide an input interface and an output interface between the terminal 100 and the user. In addition, various types of touchscreens, such as resistive, capacitive, infrared, and surface acoustic wave, can be used to implement the touchscreen. Besides the touchscreen 131, the input unit 130 may also include other input devices. Specifically, other input devices 132 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0074] Among them, the input device 132 can receive input data, etc.

[0075] The display unit 140 can be used to display information input by the user or information provided to the user, various menus of the terminal 100, interactive interfaces, file display, and / or playback of any multimedia file.

[0076] The memory 120 can be used to store instructions and data. The memory 120 may primarily include an instruction storage area and a data storage area. The data storage area can store various types of data, such as multimedia files and text. The instruction storage area can store software units such as operating systems, applications, and instructions required for at least one function, or subsets or extended sets thereof. It may also include non-volatile random access memory. It provides the processor 170 with hardware, software, and data resources for managing the computing device, supporting control software and applications. It is also used for storing multimedia files, as well as storing running programs and applications.

[0077] The processor 170 is the control center of the terminal 100. It connects various parts of the terminal 100 via various interfaces and lines. By running or executing instructions stored in the memory 120 and calling data stored in the memory 120, it performs various functions and processes data of the terminal 100, thereby controlling the terminal device as a whole. Optionally, the processor 170 may include one or more processing units; preferably, the processor 170 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 170. In some embodiments, the processor and memory can be implemented on a single chip; in some embodiments, they can also be implemented separately on independent chips. The processor 170 can also be used to generate corresponding operation control signals, send them to the corresponding components of the computing processing device, read and process data in the software, especially read and process data and programs in the memory 120, so that the various functional modules therein perform corresponding functions, thereby controlling the corresponding components to act according to the instructions.

[0078] The memory 120 can be used to store software code related to the method for determining BEV map coverage and coverage location. The processor 170 can execute the steps of the method for determining BEV map coverage and coverage location, and can also schedule other units (such as the above-mentioned input unit 130 and display unit 140) to achieve the corresponding functions.

[0079] The radio frequency unit 110 (optional) can be used for receiving and transmitting signals during information transmission or calls. For example, it can receive downlink information from the base station and process it for the processor 170; additionally, it can transmit uplink data to the base station. Typically, the RF circuit includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier (LNA), a duplexer, etc. Furthermore, the radio frequency unit 110 can also communicate wirelessly with network devices and other devices. This wireless communication can use any communication standard or protocol, including but not limited to Global System for Mobile Communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), etc.

[0080] In this embodiment of the application, the radio frequency unit 110 can send data to the server 200 and receive the processing results sent by the server 200.

[0081] It should be understood that the radio frequency unit 110 is optional and can be replaced with other communication interfaces, such as a network port.

[0082] The terminal 100 also includes a power supply 190 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 170 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system.

[0083] Terminal 100 also includes an external interface 180, which can be a standard Micro USB interface or a multi-pin connector, which can be used to connect terminal 100 to other devices for communication or to connect a charger to charge terminal 100.

[0084] Although not shown, terminal 100 may also include a flash, a Wireless Fidelity (WiFi) module, a Bluetooth module, sensors with various functions, etc., which will not be described in detail here. Some or all of the methods described below can be applied to, for example... Figure 2 In the terminal 100 shown.

[0085] The following description Figure 1 The product form of the mid-range server 200;

[0086] Figure 3 A structural diagram of a server 200 is provided, as follows: Figure 3 As shown, server 200 includes bus 201, processor 202, communication interface 203, and memory 204. Processor 202, memory 204, and communication interface 203 communicate with each other via bus 201.

[0087] Bus 201 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0088] The processor 202 can be any one or more of the following processors: a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0089] Memory 204 may include volatile memory, such as random access memory (RAM). Memory 204 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0090] The memory 204 can be used to store software code related to the method for determining BEV map coverage and coverage location. The processor 202 can execute the steps of the chip's method for determining BEV map coverage and coverage location, and can also schedule other units to achieve the corresponding functions.

[0091] It should be understood that the aforementioned terminal 100 and server 200 can be centralized or distributed devices. The processors (e.g., processor 170 and processor 202) in the aforementioned terminal 100 and server 200 can be hardware circuits (such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), general-purpose processors, DSPs, microprocessors, or microcontrollers, etc.) or combinations of these hardware circuits. For example, the processor can be a hardware system with instruction execution capabilities, such as a CPU or DSP, or a hardware system without instruction execution capabilities, such as an ASIC or FPGA, or a combination of the aforementioned hardware systems without instruction execution capabilities and hardware systems with instruction execution capabilities.

[0092] This application provides a method for determining BEV map coverage and coverage location, which can be applied to... Figure 1 Taking the computer device in the figure as an example, the computer device can specifically be the terminal 100 in the figure above, or a system composed of terminal 100 and server 200. The method for determining the BEV map coverage and coverage location of the present application embodiment will be described in detail below with reference to the accompanying drawings.

[0093] Reference Figure 4 , Figure 4 A flowchart illustrating a method for determining BEV map coverage and coverage location provided in this application embodiment, the method comprising:

[0094] Step S401: Associate and match the BEV map data with the preset traffic area data, determine the successfully matched BEV map data as the BEV map data to be matched, and obtain the BEV map lane group boundary data set from the BEV map data to be matched.

[0095] The preset traffic area data refers to the relevant data for traffic areas where it is necessary to determine the BEV map coverage and BEV map coverage location. The traffic area can be a complex traffic area with diverse traffic organization forms, complex traffic supply, and diverse traffic conflicts; or an ordinary traffic area with moderate traffic flow, relatively simple traffic organization forms, and no prominent traffic conflicts, depending on actual needs.

[0096] In this application, BEV map data that is associated with preset traffic area data will be used as BEV map data to be matched with navigation map data to be matched.

[0097] The BEV map lane group boundary data set contains multiple lane group polygon data composed of the leftmost lane line data and the rightmost lane line data.

[0098] Step S402: Associate and match the navigation map data with the preset traffic area data, determine the successfully matched navigation map data as the navigation map link data to be matched, and obtain the planned road network link data and the planned road network intersection data from the navigation map link data to be matched.

[0099] In this application, navigation map data that is associated with preset traffic area data is used as navigation map link data to be matched with BEV map data to be matched.

[0100] A link refers to a road segment between two nodes, connecting two or more nodes, and is the basic unit of the road model in a navigation system.

[0101] It should be noted that in this application, the BEV map data and navigation map data are associated and matched with the same preset traffic area data to ensure that when calculating the BEV map coverage and coverage location, the BEV map data and navigation map data are data from the same traffic area.

[0102] Link data in road network planning refers to the data used to describe road segments and their connections in road network planning. This data is the basic building block of road network models and is crucial for applications such as route planning, traffic flow analysis, and navigation systems. In a planned road network, a link typically refers to a road segment with a clearly defined start and end point; it is a fundamental component of the road network. Link data includes various attributes describing this road segment, such as road class, length, direction, and capacity.

[0103] Road network intersection data refers to the dataset used in road traffic network planning to describe road intersections and their related attributes. This data is a crucial component of road network models and is of great significance for applications such as urban traffic planning, route planning, traffic flow analysis, and navigation systems.

[0104] Step S403: Associate the planned road network link data and the planned road network intersection data with intersection topology to obtain an intersection link association data set.

[0105] Intersection topology refers to the topological relationships between intersections (or nodes) in a road traffic network, formed by the interconnection and interweaving of road segments (or links). This relationship describes the spatial location, connection method, and accessibility between intersections, and is the foundation for applications such as road network planning, traffic flow analysis, and navigation system design.

[0106] In this embodiment, each intersection point in the planned road network intersection data is taken as an endpoint, and each endpoint is associated with each link data in the planned road network link data to obtain an intersection link associated data set.

[0107] Step S404: Match the BEV map lane group boundary data set with the planned road network link data to obtain the effective coverage data set of the BEV map in the preset traffic area.

[0108] BEV maps, by converting visual information from multiple cameras or radars into a bird's-eye view, provide a wider field of view and more accurate road information. This application further refines road information and improves the accuracy and reliability of the navigation system by matching lane group boundary data from the BEV map with planned road network link data.

[0109] In addition, the planned road network link data usually contains key information such as road geometry, traffic flow direction and traffic rules. By matching the lane group boundary data of the BEV map with the planned road network link data, a more refined route planning scheme can be generated, taking into account the actual separation between lanes and turning restrictions, thereby avoiding unnecessary turns and detours.

[0110] Step S405: Determine the BEV map coverage rate and BEV map coverage location based on the intersection link association data set and the effective coverage data set.

[0111] In the fields of autonomous driving and robotics, BEV map coverage is one of the important indicators for measuring the ability of autonomous driving systems or robots to perceive and understand their surroundings. High BEV map coverage means that the system can acquire and analyze environmental information more comprehensively and accurately, thereby making more precise decisions and plans.

[0112] In practical applications, BEV map coverage usually refers to the proportion or degree to which a BEV map can accurately and completely cover and represent the actual traffic environment and its elements (such as roads, intersections, obstacles, traffic signs, etc.) in a specific traffic area or scenario.

[0113] BEV map coverage locations refer to the specific geographical locations in the actual traffic environment that are accurately represented and covered in the BEV map. These locations typically include key elements such as roads, intersections, obstacles, and traffic signs, which are crucial for the environmental perception, decision-making, and planning of autonomous driving and robotic systems.

[0114] In summary, this invention discloses a method for determining BEV map coverage and coverage location. The method involves associating and matching BEV map data with preset traffic area data, identifying successfully matched BEV map data as BEV map data to be matched, and obtaining a set of BEV map lane group boundary data from the BEV map data to be matched. Navigation map data is then associating and matching with preset traffic area data, identifying successfully matched navigation map data as navigation map link data to be matched, and obtaining planned road network link data and planned road network intersection data from the navigation map link data to be matched. The planned road network link data and planned road network intersection data are then associated with intersection topology relationships to obtain an intersection link association data set. Finally, the BEV map lane group boundary data set is matched with the planned road network link data to obtain an effective coverage data set of the BEV map in the preset traffic area. Based on the intersection link association data set and the effective coverage data set, the BEV map coverage and BEV map coverage location are determined. This application enables automatic matching of BEV map data and navigation map data within a preset traffic area, and automatic determination of BEV map coverage and coverage location, thereby reducing manpower and time costs and solving the problem of errors caused by human intervention. By matching the BEV map lane group boundary data set in the BEV map data with the planned road network link data in the navigation map data, and associating the planned road network link data and planned road network intersection data in the navigation map data with intersection topology relationships, the matching accuracy and the correlation between BEV map data and navigation map data are improved. This effectively avoids matching errors and omissions caused by error factors inherent in the navigation map data itself, thereby improving the accuracy of the BEV map coverage and coverage location calculation results.

[0115] In one embodiment, step S401 may specifically include:

[0116] (1) The spatial planar position of the lane line elements contained in the BEV map data is associated and matched with the preset traffic area data, and the successfully matched BEV map data is determined as the BEV map data to be matched.

[0117] The lane line elements included in the BEV map data include, but are not limited to, lane lines, deceleration lines, and road markings.

[0118] The spatial planar position of lane line elements in BEV map data refers to the layout and positioning of each lane line element on the road level. For example, in road design, the spatial planar position of lane lines is determined by the road plan design, which includes the design of the planar positions of road alignment, intersections, drainage facilities, and various road ancillary facilities.

[0119] (2) Filter out valid BEV map data from the BEV map data to be matched.

[0120] Specifically, the number of times the automatic navigation on autopilot (NOA) exits is counted for each lane group of BEV data in the BEV map data to be matched within the first preset period. The lane group BEV data corresponding to the lane group whose number of NOA exits is less than the threshold number is determined as valid BEV map data.

[0121] The number of times the automated navigation assistance function (ADAS) exits refers to the number of times the ADAS function exits or degrades during its operation due to various reasons, such as human intervention, system degradation, or encountering complex road conditions that cannot be handled. The number of times the ADAS function exits is an important indicator for measuring its stability and reliability.

[0122] In this application, lane group BEV data with fewer than a threshold number of automatic assisted navigation exits are identified as valid BEV map data; conversely, lane group BEV data with a threshold number of automatic assisted navigation exits are identified as invalid BEV map data.

[0123] The values ​​of the first preset period and the number of times threshold are determined according to actual needs, and are not limited in this invention.

[0124] (3) Parse the valid BEV map data to obtain the BEV map lane group boundary data set.

[0125] Specifically, iterate through the BEV data of each lane group in the valid BEV map data and filter out the leftmost lane line data and the rightmost lane line data.

[0126] The lane group polygon data formed by multiple pairs of the leftmost lane line data and the rightmost lane line data constitutes the BEV map lane group boundary data set.

[0127] In practical applications, the leftmost lane line data and the rightmost lane line data can be filtered out from each lane group data in the effective BEV map data. Each pair of leftmost lane line data and rightmost lane line data can form a lane group polygon data. Multiple lane group polygon data constitute the BEV map lane group boundary data set.

[0128] In one embodiment, step S402 may specifically include:

[0129] (1) The spatial planar position of the lane line elements contained in the navigation map data is associated and matched with the preset traffic area data, and the successfully matched navigation map data is determined as the navigation map link data to be matched.

[0130] The lane line elements included in the navigation map data include, but are not limited to, road links.

[0131] The spatial planar location of lane line elements in navigation map data refers to the layout and positioning of each lane line element on the road level. This information is an important component of navigation maps, used to indicate the path and lanes that vehicles should follow when traveling on the road.

[0132] (2) Select each target navigation map link data that meets the preset road level from the navigation map link data to be matched, and obtain the first navigation map link data set.

[0133] The preset road grades include, but are not limited to, expressways, urban expressways, national highways, urban arterial road networks, and county roads.

[0134] (3) Filter the first navigation map link data set by traffic popularity to obtain the second navigation map link data set.

[0135] Traffic volume is a quantitative indicator used to describe the traffic conditions of a specific road or part of a traffic network. It reflects the frequency or activity of vehicle use of a road or part of a traffic network within a certain period of time.

[0136] This application, after filtering the navigation map link data to be matched by road level to obtain a first navigation map link data set, further filters the first navigation map link data set by traffic popularity to obtain a second navigation map link data set. The terms "first" in the first navigation map link data set and "second" in the second navigation map link data set are used only to distinguish that the first and second navigation map link data sets are two different data sets.

[0137] Specifically, the number of times each link in the first navigation map link data set passes through within a second preset period is counted; the link data with a number of vehicle passes exceeding a threshold is identified as the second navigation map link data set.

[0138] The values ​​of the second preset period and the vehicle frequency threshold are determined according to actual needs, and are not limited herein.

[0139] (4) The link data in the second navigation map link data set is determined as the planned road network link data.

[0140] (5) The intersection of the links in the second navigation map link data set is determined as the planned road network intersection data.

[0141] In navigation map data and road network planning, "link intersections" typically refer to the points where two or more road segments (i.e., links) intersect or connect. These intersections play a crucial role in the road network model; they are not only nodes in the road network but also key locations where vehicles may turn or change paths during their journey. Based on this, this application identifies the link intersections in the second navigation map link dataset as the intersection data for the planned road network.

[0142] In one embodiment, step S404 may specifically include:

[0143] (1) Project each lane group polygon data in the BEV map lane group boundary data set and the planned road network link data into the same Cartesian coordinate system, and determine multiple boundary matching datasets in the planned road network link data in the Cartesian coordinate system. Each boundary matching dataset includes a link data and target lane group polygon data that intersects with the link data.

[0144] The Cartesian coordinate system is a collective term for rectangular and oblique coordinate systems, consisting of two or three number lines that intersect at the origin.

[0145] This application achieves data fusion and unification by projecting the polygonal data of each lane group in the BEV map lane group boundary data set and the planned road network link data into the same Cartesian coordinate system. This eliminates coordinate differences between different data, allowing these data to be analyzed and processed within the same framework, thereby improving the accuracy of navigation and route planning.

[0146] In this application, there are many link data in the planned road network link data. Each link data and each lane group polygon data in the BEV map lane group boundary data set that has an intersection relationship is determined as the target lane group polygon data. Each link and its corresponding target lane group polygon data constitute a boundary matching dataset, and multiple boundary matching datasets constitute a boundary matching data set.

[0147] (2) For each boundary matching dataset, determine the length of the link vector within the target lane group polygon data of the included link data.

[0148] In this application, the link data in the boundary matching dataset intersects with the corresponding target lane group polygon data. The length of the link vector contained in the target lane group polygon data is actually the vector length between the intersection points of the link data and the target lane group polygon data.

[0149] (3) Calculate the ratio of the length of the link vector to the total length of the link vector.

[0150] The total link vector length refers to the length of the shape point data contained in the link data of the planned road network.

[0151] (4) Among all the ratios, the target link data corresponding to the target ratio that is greater than the preset ratio and the target lane group polygon data corresponding to the target link data constitute the link BEV lane group matching combination.

[0152] The value of the preset ratio is determined according to actual needs, and this invention does not limit it.

[0153] (5) Select each link data in the link BEV lane group matching combination and the planned road network intersection data associated with the link data as the effective coverage data set of the BEV map in the preset traffic area.

[0154] The Link data and the intersection data associated with the Link data in this application fully describe the various parts of the traffic network and the relationships between them. Based on this, this application uses each Link data in the Link BEV lane group matching combination and the planned road network intersection data associated with the Link data as the effective coverage data set of the BEV map in the preset traffic area.

[0155] In one embodiment, step S405 may include:

[0156] (1) Take all link data in the effective coverage data set as effective link data, and determine the actual geographical location corresponding to the effective link data as the BEV map coverage location.

[0157] BEV map coverage locations refer to the specific geographical locations in the actual traffic environment that are accurately represented and covered in the BEV map. These locations typically include key elements such as roads, intersections, obstacles, and traffic signs, which are crucial for the environmental perception, decision-making, and planning of autonomous driving and robotic systems.

[0158] (2) The ratio of the cumulative length of the effective link data in the effective coverage data set to the cumulative length of all planned road network link data is determined as the planned road network coverage rate.

[0159] The planned road network coverage rate is an indicator used to measure the quality of transportation planning. It reflects the degree to which transportation planning meets regional traffic demand, as well as the distribution and accessibility of the road network within the region. It typically refers to the ratio of the actual mileage covered by the road network designed according to the transportation plan to the total mileage of the region. This application defines the planned road network coverage rate as the ratio of the cumulative length of valid link data in the effective coverage dataset to the cumulative length of all planned road network link data.

[0160] (3) The ratio of the cumulative length of the valid link data in the intersection link association data set to the cumulative length of the link data associated with all planned road network intersections is determined as the planned road network intersection coverage rate.

[0161] The planned road network intersection coverage rate is an indicator used to evaluate the quality of traffic planning. It is an important basis for measuring the rationality and accessibility of intersection layout in traffic planning. Specifically, it refers to the ratio of the number of intersections actually covered according to the traffic plan within a specific area to the total number of intersections that should be covered in that area. Based on this, this application determines the planned road network intersection coverage rate as the ratio of the cumulative length of valid link data in the intersection link association data set to the cumulative length of link data associated with all planned road network intersections.

[0162] (4) The planned road network coverage rate and the planned road network intersection coverage rate are determined as the BEV map coverage rate.

[0163] The above describes a method for determining BEV map coverage and coverage location provided by embodiments of this application. The following describes the apparatus for performing the above method for determining BEV map coverage and coverage location.

[0164] Please see Figure 5 , Figure 5 This is a schematic diagram of a device for determining BEV map coverage and coverage location, provided as an embodiment of this application. Figure 5 As shown, the device includes:

[0165] BEV map association and matching unit 501 is used to associate and match BEV map data with preset traffic area data, determine the successfully matched BEV map data as BEV map data to be matched, and obtain the BEV map lane group boundary data set from the BEV map data to be matched.

[0166] The preset traffic area data refers to the relevant data for traffic areas where it is necessary to determine the BEV map coverage and BEV map coverage location. The traffic area can be a complex traffic area with diverse traffic organization forms, complex traffic supply, and diverse traffic conflicts; or an ordinary traffic area with moderate traffic flow, relatively simple traffic organization forms, and no prominent traffic conflicts, depending on actual needs.

[0167] In this application, BEV map data that is associated with preset traffic area data will be used as BEV map data to be matched with navigation map data to be matched.

[0168] The BEV map lane group boundary data set contains multiple lane group polygon data composed of the leftmost lane line data and the rightmost lane line data.

[0169] The navigation map association matching unit 502 is used to associate and match navigation map data with the preset traffic area data, determine the successfully matched navigation map data as navigation map link data to be matched, and obtain planned road network link data and planned road network intersection data from the navigation map link data to be matched.

[0170] In this application, navigation map data that is associated with preset traffic area data is used as navigation map link data to be matched with BEV map data to be matched.

[0171] A link refers to a road segment between two nodes, connecting two or more nodes, and is the basic unit of the road model in a navigation system.

[0172] It should be noted that in this application, the BEV map data and navigation map data are associated and matched with the same preset traffic area data to ensure that when calculating the BEV map coverage and coverage location, the BEV map data and navigation map data are data from the same traffic area.

[0173] Link data in road network planning refers to the data used to describe road segments and their connections in road network planning. This data is the basic building block of road network models and is crucial for applications such as route planning, traffic flow analysis, and navigation systems. In a planned road network, a link typically refers to a road segment with a clearly defined start and end point; it is a fundamental component of the road network. Link data includes various attributes describing this road segment, such as road class, length, direction, and capacity.

[0174] Road network intersection data refers to the dataset used in road traffic network planning to describe road intersections and their related attributes. This data is a crucial component of road network models and is of great significance for applications such as urban traffic planning, route planning, traffic flow analysis, and navigation systems.

[0175] The intersection topology relationship determination unit 503 is used to associate the planned road network link data and the planned road network intersection data with the intersection topology relationship to obtain the intersection link associated data set.

[0176] Intersection topology refers to the topological relationships between intersections (or nodes) in a road traffic network, formed by the interconnection and interweaving of road segments (or links). This relationship describes the spatial location, connection method, and accessibility between intersections, and is the foundation for applications such as road network planning, traffic flow analysis, and navigation system design.

[0177] In this embodiment, each intersection point in the planned road network intersection data is taken as an endpoint, and each endpoint is associated with each link data in the planned road network link data to obtain an intersection link associated data set.

[0178] The coverage set determination unit 504 is used to match the BEV map lane group boundary data set with the planned road network link data to obtain the effective coverage data set of the BEV map in a preset traffic area.

[0179] BEV maps, by converting visual information from multiple cameras or radars into a bird's-eye view, provide a wider field of view and more accurate road information. This application further refines road information and improves the accuracy and reliability of the navigation system by matching lane group boundary data from the BEV map with planned road network link data.

[0180] In addition, the planned road network link data usually contains key information such as road geometry, traffic flow direction and traffic rules. By matching the lane group boundary data of the BEV map with the planned road network link data, a more refined route planning scheme can be generated, taking into account the actual separation between lanes and turning restrictions, thereby avoiding unnecessary turns and detours.

[0181] The coverage and coverage location determination unit 505 is used to determine the BEV map coverage and BEV map coverage location based on the intersection link association data set and the effective coverage data set.

[0182] In the fields of autonomous driving and robotics, BEV map coverage is one of the important indicators for measuring the ability of autonomous driving systems or robots to perceive and understand their surroundings. High BEV map coverage means that the system can acquire and analyze environmental information more comprehensively and accurately, thereby making more precise decisions and plans.

[0183] In practical applications, BEV map coverage usually refers to the proportion or degree to which a BEV map can accurately and completely cover and represent the actual traffic environment and its elements (such as roads, intersections, obstacles, traffic signs, etc.) in a specific traffic area or scenario.

[0184] BEV map coverage locations refer to the specific geographical locations in the actual traffic environment that are accurately represented and covered in the BEV map. These locations typically include key elements such as roads, intersections, obstacles, and traffic signs, which are crucial for the environmental perception, decision-making, and planning of autonomous driving and robotic systems.

[0185] In summary, this invention discloses a device for determining BEV map coverage and coverage location. It involves associating and matching BEV map data with preset traffic area data, identifying successfully matched BEV map data as BEV map data to be matched, and obtaining a set of BEV map lane group boundary data from the BEV map data to be matched. It also involves associating and matching navigation map data with preset traffic area data, identifying successfully matched navigation map data as navigation map link data to be matched, and obtaining planned road network link data and planned road network intersection data from the navigation map link data to be matched. The planned road network link data and planned road network intersection data are then associated with intersection topology relationships to obtain an intersection link association data set. Finally, the BEV map lane group boundary data set is matched with the planned road network link data to obtain an effective coverage data set of the BEV map in the preset traffic area. Based on the intersection link association data set and the effective coverage data set, the BEV map coverage and BEV map coverage location are determined. This application enables automatic matching of BEV map data and navigation map data within a preset traffic area, and automatic determination of BEV map coverage and coverage location, thereby reducing manpower and time costs and solving the problem of errors caused by human intervention. By matching the BEV map lane group boundary data set in the BEV map data with the planned road network link data in the navigation map data, and associating the planned road network link data and planned road network intersection data in the navigation map data with intersection topology relationships, the matching accuracy and the correlation between BEV map data and navigation map data are improved. This effectively avoids matching errors and omissions caused by error factors inherent in the navigation map data itself, thereby improving the accuracy of the BEV map coverage and coverage location calculation results.

[0186] In one embodiment, the BEV map association matching unit 501 may specifically include:

[0187] The first association matching subunit is used to associate and match the spatial planar position of the lane line elements contained in the BEV map data with the preset traffic area data, and to determine the successfully matched BEV map data as the BEV map data to be matched.

[0188] A filtering subunit is used to filter out valid BEV map data from the BEV map data to be matched.

[0189] The parsing subunit is used to parse the valid BEV map data to obtain the BEV map lane group boundary data set.

[0190] In one embodiment, the filtering subunit can specifically be used for:

[0191] The number of times the automatic assisted navigation driving exits is counted for each lane group of BEV data in the BEV map data to be matched within the first preset period.

[0192] The lane group BEV data corresponding to the lane group where the number of times the automatic assisted navigation driving exits is less than the threshold number is determined as the valid BEV map data.

[0193] In one embodiment, the parsing subunit can be specifically used for:

[0194] Traverse the BEV data of each lane group in the effective BEV map data, and filter out the leftmost lane line data and the rightmost lane line data.

[0195] The lane group polygon data formed by multiple pairs of the leftmost lane line data and the rightmost lane line data constitutes the lane group boundary data set of the BEV map.

[0196] In one embodiment, the navigation map association matching unit 502 can be specifically used for:

[0197] The spatial planar positions of the lane line elements contained in the navigation map data are associated and matched with the preset traffic area data, and the successfully matched navigation map data is determined as the navigation map link data to be matched.

[0198] The first navigation map link data set is obtained by filtering out each target navigation map link data that meets the preset road level from the navigation map link data to be matched;

[0199] The first navigation map link data set is filtered by traffic popularity to obtain the second navigation map link data set;

[0200] The link data in the second navigation map link data set is determined as the planned road network link data;

[0201] The intersections of the links in the second navigation map link data set are determined as the intersection data of the planned road network.

[0202] In one embodiment, the navigation map association matching unit 502 can be specifically used for:

[0203] The number of vehicles passing through each link in the first navigation map link data set within the second preset period is counted.

[0204] Link data with a vehicle count greater than the vehicle count threshold is identified as the second navigation map link data set.

[0205] In one embodiment, the intersection topology determination unit 503 can be specifically used for:

[0206] Each intersection point in the planned road network intersection data is used as an endpoint, and each endpoint is associated with each link data in the planned road network link data to obtain the intersection link associated data set.

[0207] In one embodiment, the coverage set determination unit 504 can be specifically used for:

[0208] Project each lane group polygon data in the BEV map lane group boundary data set and the planned road network link data into the same Cartesian coordinate system, and determine multiple boundary matching datasets in the planned road network link data in the Cartesian coordinate system. Each boundary matching dataset includes a link data and target lane group polygon data that intersects with the link data.

[0209] For each boundary matching dataset, determine the length of the link vector within the target lane group polygon data where the included link data is located;

[0210] Calculate the ratio of the length of the link vector to the total length of the link vectors;

[0211] Among all the ratios, the target link data and target lane group polygon data corresponding to the target ratio that is greater than the preset ratio are used to form the link BEV lane group matching combination;

[0212] Each link data in the link BEV lane group matching combination and the planned road network intersection data associated with that link data are selected as the effective coverage data set.

[0213] In one embodiment, the coverage and coverage location determination unit 505 can specifically be used for:

[0214] All link data in the effective coverage data set are taken as effective link data, and the actual geographical location corresponding to the effective link data is determined as the BEV map coverage location.

[0215] The ratio of the cumulative length of the effective link data in the effective coverage data set to the cumulative length of all planned road network link data is determined as the planned road network coverage rate.

[0216] The ratio of the cumulative length of the valid link data in the intersection link association data set to the cumulative length of the link data associated with all planned road network intersections is determined as the planned road network intersection coverage rate.

[0217] The planned road network coverage rate and the planned road network intersection coverage rate are determined as the BEV map coverage rate.

[0218] This application also provides an electronic device in its embodiments. (See reference...) Figure 6 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (Personal Digital Assistants), PADs (Portable Application Devices), desktop computers, etc. Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0219] like Figure 6 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in ROM 602 or a program loaded from storage device 608 into RAM 603. When the electronic device is powered on, RAM 603 also stores various programs and data required for the operation of the electronic device. The processing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0220] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, memory cards, hard drives, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have instead.

[0221] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the BEV map coverage and coverage location determination methods provided in this application.

[0222] This application also provides a computer-readable storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the BEV map coverage and coverage location determination methods provided in this application.

[0223] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0224] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0225] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0226] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line, DSL) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs (Digital Versatile Discs)), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A method for determining BEV map coverage and coverage location, characterized in that, include: The BEV map data is associated and matched with the preset traffic area data. The successfully matched BEV map data is determined as the BEV map data to be matched, and the BEV map lane group boundary data set is obtained from the BEV map data to be matched. The navigation map data is associated and matched with the preset traffic area data. The successfully matched navigation map data is determined as the navigation map link data to be matched, and the planned road network link data and planned road network intersection data are obtained from the navigation map link data to be matched. The planned road network link data and the planned road network intersection data are associated with intersection topology to obtain an intersection link associated data set. The BEV map lane group boundary data set and the planned road network link data are matched to obtain the effective coverage data set of the BEV map in the preset traffic area. The BEV map coverage and BEV map coverage location are determined based on the intersection link association data set and the effective coverage data set.

2. The method for determining BEV map coverage and coverage location according to claim 1, characterized in that, The step of associating and matching BEV map data with preset traffic area data, determining successfully matched BEV map data as BEV map data to be matched, and obtaining a set of BEV map lane group boundary data from the BEV map data to be matched includes: The spatial planar positions of the lane line elements contained in the BEV map data are associated and matched with the preset traffic area data, and the successfully matched BEV map data is determined as the BEV map data to be matched. Valid BEV map data is filtered out from the BEV map data to be matched; The valid BEV map data is parsed to obtain the BEV map lane group boundary data set.

3. The method for determining BEV map coverage and coverage location according to claim 2, characterized in that, The step of filtering valid BEV map data from the BEV map data to be matched includes: The number of times the automatic assisted navigation driving exits is counted for each lane group of BEV data in the BEV map data to be matched within the first preset period. Lane group BEV data with fewer than a certain number of automatic assisted navigation exits are identified as valid BEV map data.

4. The method for determining BEV map coverage and coverage location according to claim 2 or 3, characterized in that, The step of parsing the valid BEV map data to obtain the BEV map lane group boundary data set includes: Traverse the BEV data of each lane group in the effective BEV map data, and filter out the leftmost lane line data and the rightmost lane line data. The lane group polygon data formed by multiple pairs of the leftmost lane line data and the rightmost lane line data constitutes the lane group boundary data set of the BEV map.

5. The method for determining BEV map coverage and coverage location according to claim 1, characterized in that, The step of obtaining planned road network link data and planned road network intersection data from the navigation map link data to be matched includes: The spatial planar positions of the lane line elements contained in the navigation map data are associated and matched with the preset traffic area data, and the successfully matched navigation map data is determined as the navigation map link data to be matched. The first navigation map link data set is obtained by filtering out each target navigation map link data that meets the preset road level from the navigation map link data to be matched; The first navigation map link data set is filtered by traffic popularity to obtain the second navigation map link data set; The link data in the second navigation map link data set is determined as the planned road network link data; The intersections of the links in the second navigation map link data set are determined as the intersection data of the planned road network.

6. The method for determining BEV map coverage and coverage location according to claim 5, characterized in that, The step of filtering the first navigation map link data set by traffic popularity to obtain the second navigation map link data set includes: The number of vehicles passing through each link in the first navigation map link data set within the second preset period is counted. Link data with a vehicle count greater than the vehicle count threshold is identified as the second navigation map link data set.

7. The method for determining BEV map coverage and coverage location according to claim 1, characterized in that, The step of associating the planned road network link data and the planned road network intersection data with intersection topology to obtain an intersection link association data set includes: Each intersection point in the planned road network intersection data is used as an endpoint, and each endpoint is associated with each link data in the planned road network link data to obtain the intersection link associated data set.

8. The method for determining BEV map coverage and coverage location according to claim 1 or 7, characterized in that, The BEV map lane group boundary data set and the planned road network link data are matched to obtain the effective coverage data set of the BEV map in the preset traffic area, including: Project each lane group polygon data in the BEV map lane group boundary data set and the planned road network link data into the same Cartesian coordinate system, and determine multiple boundary matching datasets in the planned road network link data in the Cartesian coordinate system. Each boundary matching dataset includes a link data and target lane group polygon data that intersects with the link data. For each boundary matching dataset, determine the length of the link vector within the target lane group polygon data where the included link data is located; Calculate the ratio of the length of the link vector to the total length of the link vectors; Among all the ratios, the target link data corresponding to the target ratio that is greater than the preset ratio and the target lane group polygon data corresponding to the target link data constitute the link BEV lane group matching combination; Each link data in the link BEV lane group matching combination and the planned road network intersection data associated with that link data are selected as the effective coverage data set.

9. The method for determining BEV map coverage and coverage location according to claim 1, characterized in that, The process of determining BEV map coverage and BEV map coverage location based on the intersection link association data set and the effective coverage data set includes: All link data in the effective coverage data set are taken as effective link data, and the actual geographical location corresponding to the effective link data is determined as the BEV map coverage location. The ratio of the cumulative length of the effective link data in the effective coverage data set to the cumulative length of all planned road network link data is determined as the planned road network coverage rate. The ratio of the cumulative length of the valid link data in the intersection link association data set to the cumulative length of the link data associated with all planned road network intersections is determined as the planned road network intersection coverage rate. The planned road network coverage rate and the planned road network intersection coverage rate are determined as the BEV map coverage rate.

10. A device for determining BEV map coverage and coverage location, characterized in that, include: The BEV map association and matching unit is used to associate and match BEV map data with preset traffic area data, determine the successfully matched BEV map data as BEV map data to be matched, and obtain the BEV map lane group boundary data set from the BEV map data to be matched. The navigation map association and matching unit is used to associate and match navigation map data with the preset traffic area data, determine the successfully matched navigation map data as navigation map link data to be matched, and obtain the planned road network link data and the planned road network intersection data from the navigation map link data to be matched. The intersection topology relationship determination unit is used to associate the planned road network link data and the planned road network intersection data with the intersection topology relationship to obtain the intersection link associated data set; The coverage set determination unit is used to match the BEV map lane group boundary data set with the planned road network link data to obtain the effective coverage data set of the BEV map in the preset traffic area. The coverage and coverage location determination unit is used to determine the BEV map coverage and BEV map coverage location based on the intersection link association data set and the effective coverage data set.

11. A computer program product, characterized in that, It includes computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the method for determining BEV map coverage and coverage location as described in any one of claims 1 to 9.

12. An electronic device, characterized in that, It includes at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program to enable the electronic device to implement the method for determining BEV map coverage and coverage location as described in any one of claims 1 to 9.

13. A computer storage medium, characterized in that, The storage medium carries one or more computer programs that, when executed by an electronic device, enable the electronic device to implement the method for determining BEV map coverage and coverage location as described in any one of claims 1 to 9.

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