Data preprocessing method and device adaptive to OpenDRIVE compiling, equipment and storage medium

Abstract

The invention provides a data preprocessing method adapted to OpenDRIVE compilation, which comprises the following steps: grouping all lanes in a road in original road data according to length, and taking each group as a common road to be processed; when more than one precursor or successor exists in the common road to be processed, converting the precursor or successor of all non-connection roads into a first connection road; when the successor of the first connection path is a connection path, combining the first connection path and the successor of the first connection path into a second connection path; and when more than one front-driving or subsequent lane exists in the second connecting road, taking each front-driving lane, each lane and each subsequent lane which are communicated as a combination, and taking the lane in each combination as a new connecting road. The original data can be processed into the data format adaptive to the OpenDRIVE specification, so that the compiling of the high-precision map is facilitated, and the compiling efficiency of the high-precision map is improved.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology in autonomous driving technology, and specifically relates to a data preprocessing method, device, equipment and storage medium adapted for OpenDRIVE compilation. Background Art

[0002] The development of autonomous driving technology is advancing rapidly, aiming to enable autonomous navigation and decision-making of vehicles through advanced sensors, algorithms and artificial intelligence. As the "eyes" of the autonomous driving system, high-precision maps provide accurate road geometry information, traffic signs and dynamic road conditions, which are essential for the vehicle to accurately locate, plan paths and perceive the environment. HD map compilation, especially using standardized formats such as OpenDRIVE, ensures the accuracy and consistency of map data, thus providing a solid foundation for the safe and reliable operation of autonomous vehicles in complex traffic environments. In short, HD map compilation not only supports the core functions of autonomous driving technology, but also promotes its evolution to higher levels of automation, and is a key link in realizing the vision of full autonomous driving.

[0003] However, when compiling high-precision maps, the format of the raw data generally obtained is often quite different from the specifications of the OpenDRIVE standardized format. Therefore, it is not possible to simply map the raw data one-to-one. The raw data needs to be preprocessed first to adapt to the specifications of the OpenDRIVE standardized format to meet the compilation requirements of the high-precision map.

[0004] However, the applicant has found through research that there is currently no data preprocessing method that is compatible with OpenDRIVE compilation and can process the acquired raw data into a data format that is compatible with the OpenDRIVE specification to facilitate the compilation of high-precision maps. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned technical problems and provide a data preprocessing method adapted to OpenDRIVE compilation, which can process the original data into a data format adapted to the OpenDRIVE specification to facilitate the compilation of high-precision maps and improve the efficiency of high-precision map compilation.

[0006] In order to solve the above problems, the present invention is implemented according to the following technical solutions:

[0007] In a first aspect, the present invention provides a data preprocessing method adapted for OpenDRIVE compilation, the method comprising:

[0008] S10, grouping all lanes in the road in the original road data according to their lengths, and each grouping is used as an ordinary road to be processed, wherein the ordinary road is a one-way non-branched road containing one or more lanes, and the lane is an area divided in the road for a specific traffic flow;

[0009] S20, when there is more than one predecessor or successor of the ordinary road to be processed, convert the predecessors or successors of all non-connecting roads into a first connecting road, wherein the predecessor is a road or lane with the starting point of the current road or the current lane as the end point, the successor is a road or lane with the end point of the current road or the current lane as the starting point, and the first connecting road is a one-way road including one or more lanes for connecting two ordinary roads;

[0010] S30, when the successor of the first connecting road is a connecting road, merging the first connecting road and the successor of the first connecting road into a second connecting road, where the second connecting road is a one-way road including one or more lanes for connecting two ordinary roads;

[0011] S40: When the second connecting road has more than one preceding or succeeding lane, each connected preceding lane, the lane and the succeeding lane are regarded as a combination, and each lane in the combination is regarded as a new connecting road.

[0012] Preferably, S10, group all lanes in the road in the original road data by length, and treat each group as an ordinary road to be processed; S11, traverse each lane in the ordinary road to be processed, and when there is more than one predecessor or successor of the lane, treat each predecessor or successor as a new road.

[0013] Preferably, in step S10, the length difference ratio of the lanes in each group does not exceed 15%.

[0014] Preferably, in step S40, the new connection path has at most one predecessor and successor.

[0015] In a second aspect, a data preprocessing device adapted to OpenDRIVE compilation is provided, wherein the data preprocessing device adapted to OpenDRIVE compilation is configured to execute the data preprocessing method adapted to OpenDRIVE compilation, and the data preprocessing device adapted to OpenDRIVE compilation includes:

[0016] A lane grouping module, the lane grouping module is used for S10, grouping all lanes in the road in the original road data according to length, each group is used as a common road to be processed, wherein the common road is a one-way non-branched road containing one or more lanes, and the lane is an area divided in the road for a specific traffic flow;

[0017] A module for converting ordinary roads to connecting roads, the module for converting ordinary roads to connecting roads is used in S20, when there is more than one predecessor or successor of the ordinary road to be processed, converting the predecessors or successors of all non-connecting roads into a first connecting road, wherein the predecessor is a road or lane with the starting point of the current road or the current lane as the end point, the successor is a road or lane with the end point of the current road or the current lane as the starting point, and the first connecting road is a one-way road including one or more lanes for connecting two ordinary roads;

[0018] a link road merging module, the link road merging module being used for S30, when the successor of the first link road is a link road, merging the first link road and the successor of the first link road into a second link road, the second link road being a one-way road including one or more lanes for connecting two ordinary roads;

[0019] The connecting road regrouping module is used in S40. When there is more than one predecessor or successor lane in the second connecting road, each connected predecessor, lane and successor is regarded as a combination, and each lane in the combination is regarded as a new connecting road.

[0020] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0021] At least one processor; and a memory in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform any one of the data preprocessing methods adapted to OpenDRIVE compilation according to the first aspect above.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program is used to enable a processor to execute a data preprocessing method adapted to OpenDRIVE compilation as described in any one of the first aspects above.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a data preprocessing method adapted to OpenDRIVE compilation, grouping all lanes in a road in the original road data according to length, and each grouping is used as an ordinary road to be processed; when there is more than one predecessor or successor to the ordinary road to be processed, the predecessors or successors of all non-connecting roads are converted into a first connecting road; when the successor of the first connecting road is a connecting road, the first connecting road and the successor of the first connecting road are merged into a second connecting road; when there is more than one predecessor or successor lane of the second connecting road, each connected predecessor, the lane and the successor is taken as a combination, and the lanes in each of the combinations are taken as a new connecting road.

[0024] Through the method described in the present application, the original data can be processed into a data format adapted to the OpenDRIVE specification to facilitate the compilation of high-precision maps and improve the efficiency of high-precision map compilation.

[0025] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings, wherein:

[0027] Figure 1 is an implementation flow chart of a data preprocessing method adapted to OpenDRIVE compilation according to an embodiment of the present invention;

[0028] Figure 2 is an example diagram of step 101 of a data preprocessing method adapted for OpenDRIVE compilation according to an embodiment of the present invention;

[0029] Figure 3 is an example diagram of a preferred embodiment of step 101 of a data preprocessing method adapted for OpenDRIVE compilation in an embodiment of the present invention;

[0030] Figure 4 is an example diagram of step 103 of a data preprocessing method adapted to OpenDRIVE compilation according to an embodiment of the present invention;

[0031] Figure 5 is an example diagram of step 104 of a data preprocessing method adapted to OpenDRIVE compilation according to an embodiment of the present invention;

[0032] Figure 6 It is a technical structure diagram of a data preprocessing method adapted for OpenDRIVE compilation according to an embodiment of the present invention;

[0033] Figure 7 It is a module diagram of a data preprocessing device adapted for OpenDRIVE compilation according to an embodiment of the present invention;

[0034] Figure 8 It is a structural schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0036] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. Unless otherwise defined, the technical terms or scientific terms used in this specification should be understood by people with ordinary skills in the field to which this application belongs. The words "first", "second" and similar words used in this specification and claims do not indicate any order, quantity or importance, but are only used to distinguish different technical features.

[0037] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0038] High-precision maps provide vehicles with a detailed and accurate static and dynamic environment model in autonomous driving technology, enabling the autonomous driving system to achieve beyond-line-of-sight perception beyond the sensor's perception range, perform precise vehicle positioning, and make safer and more efficient path planning and decisions, thereby significantly enhancing the reliability and safety of autonomous driving.

[0039] However, when compiling high-precision maps, the format of the raw data obtained is often quite different from the OpenDRIVE standardized format specifications. Therefore, it is not possible to simply map the raw data one-to-one. The raw data needs to be preprocessed to adapt to the OpenDRIVE standardized format specifications to meet the compilation requirements of high-precision maps. However, there is currently no data preprocessing method that can adapt to OpenDRIVE compilation, which can process the obtained raw data into a data format that adapts to the OpenDRIVE specification to facilitate the compilation of high-precision maps.

[0040] To this end, the present invention provides a data preprocessing method adapted for OpenDRIVE compilation, which can process the original data into a data format adapted for OpenDRIVE specifications to facilitate the compilation of high-precision maps and improve the efficiency of high-precision map compilation.

[0041] Figure 1 1 is a structural diagram of a data preprocessing method adapted to OpenDRIVE compilation according to the present invention. The method can be executed by a data preprocessing device adapted to OpenDRIVE compilation. The device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0042] Step 101: Group all lanes in the road in the original road data according to their lengths, and each group is regarded as an ordinary road to be processed.

[0043] An example of step 101 is as follows Figure 2 shown.

[0044] It should be noted that ordinary roads are one-way, undivided roads with one or more lanes, and lanes are areas divided in the road for specific traffic flows. In the field of autonomous driving, even ordinary roads need to be mapped and compiled into high-precision maps in detail, because they provide vehicles with driving paths and environmental information, which is essential for achieving safe and efficient autonomous driving. In the compilation of high-precision maps, it is very important to understand and distinguish between roads and lanes, because they together form the basis of the traffic network and support the autonomous driving system and navigation system for accurate path planning and traffic management.

[0045] Specifically, the length difference ratio of the lanes in each group does not exceed 15%.

[0046] It should be noted that the format specification of OpenDRIVE requires that lanes on the same road be aligned to the same reference line, and the lane width is defined by the offset from the lane to the reference line. This requires that the lengths of the lanes cannot differ too much. Step 101 can preliminarily align the lengths of the lanes on the road, and then subsequent processing can enable the lanes to be aligned to the same reference line.

[0047] Preferably, when the compiled OpenDRIVE version requires one-to-one connection between lanes of ordinary roads, each lane in the ordinary road to be processed is traversed, and when there is more than one predecessor or successor of a lane, each predecessor or successor is regarded as a new road. Figure 3 shown.

[0048] Step 102: When there is more than one predecessor or successor of the common road to be processed, convert the predecessors or successors of all non-connected roads into the first connected road.

[0049] It should be noted that the predecessor is the road or lane with the starting point of the current road or the current lane as its end point (that is, the predecessor is the entry point of the current road, and vehicles can enter the current road through these roads or lanes), the successor is the road or lane with the end point of the current road or the current lane as its starting point (that is, the successor is the exit point of the current road, and vehicles can leave the current road through these roads or lanes and continue to the destination), and the first connecting road is a one-way road containing one or more lanes used to connect two ordinary roads.

[0050] It is understandable that in the compilation process of high-precision maps, determining the predecessors and successors of each road is a key step in constructing a road network diagram. This information usually includes the connection points of the roads (such as intersections, ramps, etc.), the types of roads (such as main roads, secondary roads, etc.), and the connection directions between roads. For example, in an urban traffic network, a main road may have multiple predecessors (such as secondary roads or branches from different directions), and multiple successors (such as main roads or highways leading to different areas). High-precision maps need to accurately record this information to support effective path planning and navigation of autonomous driving vehicles. In summary, predecessors and successors represent the connectivity of the road network in high-precision maps, and they are the basis for achieving accurate navigation and path planning.

[0051] Understandably, differentiating between connected and non-connected roads is very important in autonomous driving systems as they affect the vehicle’s navigation decisions and path planning. Autonomous vehicles need to identify connected roads to transition between highways or main roads, while non-connected roads provide detailed information when the vehicle is driving in urban or rural environments, helping the vehicle avoid congested areas or find the shortest path to the destination.

[0052] In this embodiment, since OpenDRIVE requires that when any road has multiple predecessors or successors, all predecessors and successors must be connecting roads, the data format processed in step 102 can meet this requirement of OpenDRIVE, so as to facilitate the subsequent compilation of high-precision maps.

[0053] Step 103: When the successor of the first connection path is a connection path, merge the first connection path and the successor of the first connection path into a second connection path.

[0054] An example of step 103 is as follows Figure 4 shown.

[0055] It should be noted that the second connecting road is a one-way road including one or more lanes for connecting two ordinary roads.

[0056] In this embodiment, the data processed in step 103 can ensure that the predecessor and successor of the connection path are both common paths.

[0057] Step 104: When there is more than one preceding or succeeding lane on the second connecting road, each connected preceding lane, lane and succeeding lane are regarded as a combination, and each lane in the combination is regarded as a new connecting road.

[0058] An example of step 104 is as follows Figure 5 shown.

[0059] Specifically, the new connection path has at most one predecessor and successor.

[0060] In summary, through the method described in this application, the original data can be processed into a data format that is compatible with the OpenDRIVE specification, so as to facilitate the compilation of high-precision maps and improve the efficiency of high-precision map compilation.

[0061] Figure 7 1 is a block diagram of a data preprocessing device adapted to OpenDRIVE compilation according to the present invention. Figure 7 As shown, the module includes:

[0062] 301. Lane grouping module.

[0063] Specifically, the lane grouping module is used to group all lanes in the road in the original road data by length, and each group is used as an ordinary road to be processed, where an ordinary road is a one-way, non-branched road containing one or more lanes, and a lane is an area divided in the road for specific traffic flow.

[0064] 302. Ordinary road to connection road module.

[0065] Specifically, the ordinary road to connecting road module is used to convert the predecessors or successors of all non-connecting roads into the first connecting road when there is more than one predecessor or successor for the ordinary road to be processed, wherein the predecessor is a road or lane with the starting point of the current road or the current lane as the end point, the successor is a road or lane with the end point of the current road or the current lane as the starting point, and the first connecting road is a one-way road containing one or more lanes for connecting two ordinary roads.

[0066] 303. Connection path merging module.

[0067] Specifically, the link road merging module is used to merge the first link road and the successor of the first link road into a second link road when the successor of the first link road is a link road, and the second link road is a one-way road including one or more lanes for connecting two ordinary roads.

[0068] 304. Connection path regrouping module.

[0069] Specifically, the link regrouping module is used to treat each connected predecessor, lane and successor as a combination when there is more than one predecessor or successor lane on the second link, and treat the lanes in each combination as a new link.

[0070] Figure 8 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0071] like Figure 8 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0072] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0073] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as solving a data preprocessing method adapted to OpenDRIVE compilation.

[0074] In some embodiments, a data preprocessing method adapted to OpenDRIVE compilation may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the data preprocessing method adapted to OpenDRIVE compilation described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform a data preprocessing method adapted to OpenDRIVE compilation in any other appropriate manner (e.g., by means of firmware).

[0075] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0076] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0077] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0078] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0079] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0080] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0081] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the computer program implements a data preprocessing method adapted to OpenDRIVE compilation provided by an embodiment of the present invention.

[0082] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0083] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0084] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A data preprocessing method adapted to OpenDRIVE compilation, It is characterized in that The method comprises: S10, grouping all lanes in the road in the original road data according to their lengths, and each grouping is used as an ordinary road to be processed, wherein the ordinary road is a one-way non-branched road containing one or more lanes, and the lane is an area divided in the road for a specific traffic flow; S20, when there is more than one predecessor or successor of the ordinary road to be processed, convert the predecessors or successors of all non-connecting roads into a first connecting road, wherein the predecessor is a road or lane with the starting point of the current road or the current lane as the end point, the successor is a road or lane with the end point of the current road or the current lane as the starting point, and the first connecting road is a one-way road including one or more lanes for connecting two ordinary roads; S30, when the successor of the first connecting road is a connecting road, merging the first connecting road and the successor of the first connecting road into a second connecting road, where the second connecting road is a one-way road including one or more lanes for connecting two ordinary roads; S40: When the second connecting road has more than one preceding or succeeding lane, each connected preceding lane, the lane and the succeeding lane are regarded as a combination, and each lane in the combination is regarded as a new connecting road.

2. According to the data preprocessing method adapted for OpenDRIVE compilation according to claim 1, Features: S10, grouping all lanes in the road in the original road data according to their lengths, and treating each group as an ordinary road to be processed; S11. Traverse each lane in the ordinary road to be processed, and when there is more than one predecessor or successor of the lane, treat each predecessor or successor as a new road.

3. According to the data preprocessing method adapted for OpenDRIVE compilation according to claim 1, Features: In step S10, the length difference ratio of the lanes in each group does not exceed 15%.

4. According to the data preprocessing method adapted for OpenDRIVE compilation according to claim 1, Features: In step S40, the new connection path has at most one predecessor and successor.

5. A data preprocessing device adapted for OpenDRIVE compilation, It is characterized in that The data preprocessing device adapted to OpenDRIVE compilation is configured to execute the data preprocessing method adapted to OpenDRIVE compilation, and the data preprocessing device adapted to OpenDRIVE compilation includes: A lane grouping module, the lane grouping module is used for S10, grouping all lanes in the road in the original road data according to length, each group is used as a common road to be processed, wherein the common road is a one-way non-branched road containing one or more lanes, and the lane is an area divided in the road for a specific traffic flow; A module for converting ordinary roads to connecting roads, the module for converting ordinary roads to connecting roads is used in S20, when there is more than one predecessor or successor of the ordinary road to be processed, converting the predecessors or successors of all non-connecting roads into a first connecting road, wherein the predecessor is a road or lane with the starting point of the current road or the current lane as the end point, the successor is a road or lane with the end point of the current road or the current lane as the starting point, and the first connecting road is a one-way road including one or more lanes for connecting two ordinary roads; a link road merging module, the link road merging module being used for S30, when the successor of the first link road is a link road, merging the first link road and the successor of the first link road into a second link road, the second link road being a one-way road including one or more lanes for connecting two ordinary roads; The connecting road regrouping module is used in S40. When there is more than one predecessor or successor lane in the second connecting road, each connected predecessor, lane and successor is regarded as a combination, and each lane in the combination is regarded as a new connecting road.

6. An electronic device, It is characterized in that The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a data preprocessing method adapted for OpenDRIVE compilation as described in any one of claims 1 to 4.

7. A computer-readable storage medium, It is characterized in that The computer readable storage medium stores a computer program, The computer program is used to enable a processor to implement a data preprocessing method adapted to OpenDRIVE compilation as described in any one of claims 1 to 4 when executed.

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