Intelligent driving data processing method and system

Abstract

The invention relates to an intelligent driving data processing method and system, and relates to the technical field of intelligent driving. The method is applied to a vehicle end sensing module and comprises the steps of collecting intelligent driving data; according to a cdr serialization method corresponding to the intelligent driving data, serializing the intelligent driving data to obtain cdr serialized intelligent driving data; and sending the intelligent driving data subjected to cdr serialization to a data acquisition program in a FastDDS shared memory mode. The method is applied to a data acquisition program, and comprises the following steps: receiving cdr serialized intelligent driving data sent by a vehicle end sensing module; deserializing the intelligent driving data subjected to cdr serialization into intelligent driving data according to a cdr deserialization method corresponding to the intelligent driving data; according to a protobuf serialization method corresponding to the intelligent driving data, serializing the intelligent driving data to obtain protobuf serialized intelligent driving data; and storing the protobuf serialized intelligent driving data in a database according to a preset format for playing and recharging simulation.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and in particular to a method and system for processing intelligent driving data. Background Art

[0002] At present, with the continuous development of intelligent driving technology, the data processing requirements of vehicle intelligent driving programs are becoming increasingly complex, and a large amount of perception data and algorithm intermediate results need to be transmitted between modules. To meet this demand, common technical solutions often use data serialization and deserialization technology to achieve efficient data transmission and storage.

[0003] FastDDS is a real-time data distribution middleware based on the DDS standard, which is widely used in embedded systems and intelligent driving fields. It supports the serialization method of cdr format, which can quickly and efficiently convert complex data structures into binary data for transmission between modules through shared memory or network. In the vehicle-side intelligent driving program, FastDDS is often used to distribute sensor data and intermediate algorithm results in real time. protobuf is a lightweight, high-performance data serialization tool. Unlike cdr, protobuf has higher language compatibility during serialization and deserialization, and is suitable for back-end systems (such as Java servers) for data parsing and processing. Although the cdr serialization method used by FastDDS is efficient, it lacks direct compatibility when interacting with non-embedded systems (such as Java back-end services). The Java system does not support the cdr deserialization method, which complicates the data exchange process.

[0004] Due to compatibility issues in the serialization method, it is difficult to quickly display the collected data on the web page during the development and testing of intelligent driving. Developers need to use offline analysis and other means, which is inefficient. In the process of data re-injection, it is also impossible to directly support the re-input of historical collected data into the vehicle-side system for algorithm simulation, resulting in high development and tuning costs for intelligent driving programs, and lack of flexibility and efficiency. Summary of the invention

[0005] Based on this, it is necessary to provide a method and system for processing intelligent driving data to address the above technical issues.

[0006] In a first aspect, a method for processing intelligent driving data is provided, the method being applied to a vehicle-side perception module, the method comprising:

[0007] Collect intelligent driving data;

[0008] According to the CDR serialization method corresponding to the intelligent driving data, the intelligent driving data is serialized to obtain CDR serialized intelligent driving data;

[0009] The cdr-serialized intelligent driving data is sent to the data acquisition program via FastDDS shared memory.

[0010] As an optional implementation, the method further includes:

[0011] Classifying the intelligent driving data according to data topics;

[0012] For each of the data topics, a CDR serialization method and a CDR deserialization method of the intelligent driving data are generated according to the IDL file corresponding to the data topic;

[0013] For each of the data topics, a protobuf serialization method and a protobuf deserialization method of the intelligent driving data are generated according to the proto file corresponding to the data topic.

[0014] In a second aspect, a method for processing intelligent driving data is provided, the method being applied to a data collection program, the method comprising:

[0015] Receive CDR serialized intelligent driving data sent by the vehicle-side perception module;

[0016] Deserializing the CDR-serialized intelligent driving data into the intelligent driving data according to the CDR deserialization method corresponding to the intelligent driving data;

[0017] Serializing the intelligent driving data according to the protobuf serialization method corresponding to the intelligent driving data to obtain protobuf serialized intelligent driving data;

[0018] The protobuf-serialized intelligent driving data is stored in the database according to a preset format.

[0019] As an optional implementation, the preset format is .db3 format, and the database is a SQLite database.

[0020] In a third aspect, a method for processing intelligent driving data is provided, the method being applied to a Java backend program, the method comprising:

[0021] Accessing a database and reading protobuf-serialized intelligent driving data in the database;

[0022] According to the protobuf deserialization method corresponding to the intelligent driving data, the protobuf-serialized intelligent driving data is deserialized into the intelligent driving data and used for intelligent driving data playback.

[0023] In a fourth aspect, a method for processing intelligent driving data is provided, the method being applied to a recharging program, the method comprising:

[0024] Accessing a database and reading protobuf-serialized intelligent driving data in the database;

[0025] Deserializing the protobuf serialized intelligent driving data in the database into the intelligent driving data according to the protobuf deserialization method corresponding to the intelligent driving data;

[0026] According to the CDR serialization method corresponding to the intelligent driving data, the intelligent driving data is serialized to obtain CDR serialized intelligent driving data;

[0027] The cdr-serialized intelligent driving data is sent to the vehicle-side simulation program via FastDDS shared memory.

[0028] In a fifth aspect, a method for processing intelligent driving data is provided, the method being applied to a vehicle-side simulation program, the method comprising:

[0029] Receive the CDR serialized intelligent driving data sent by the recharging program;

[0030] According to the CDR deserialization method corresponding to the intelligent driving data, the CDR-serialized intelligent driving data is deserialized into the intelligent driving data and used for intelligent driving data simulation.

[0031] In a sixth aspect, a system for processing intelligent driving data is provided, the system comprising a vehicle-side perception module as described in any one of the first aspect, a data acquisition program as described in any one of the second aspect, a Java back-end program as described in the third aspect, a re-injection program as described in the fourth aspect, and a vehicle-side simulation program as described in the fifth aspect.

[0032] The present application provides a method and system for processing intelligent driving data. The technical solution provided by the embodiments of the present application brings at least the following beneficial effects: the method is applied to a vehicle-side perception module, and the method includes: collecting intelligent driving data; serializing the intelligent driving data according to the cdr serialization method corresponding to the intelligent driving data to obtain cdr-serialized intelligent driving data; sending the cdr-serialized intelligent driving data to a data acquisition program via FastDDS shared memory. The method is applied to a data acquisition program, and the method includes: receiving cdr-serialized intelligent driving data sent by a vehicle-side perception module; deserializing the cdr-serialized intelligent driving data into the intelligent driving data according to the cdr deserialization method corresponding to the intelligent driving data; serializing the intelligent driving data according to the protobuf serialization method corresponding to the intelligent driving data to obtain protobuf-serialized intelligent driving data; storing the protobuf-serialized intelligent driving data in a database according to a preset format. The method is applied to a Java backend program, and the method includes: accessing a database and reading the protobuf-serialized intelligent driving data in the database; deserializing the protobuf-serialized intelligent driving data into the intelligent driving data according to the protobuf deserialization method corresponding to the intelligent driving data, and using it for intelligent driving data playback. The method is applied to a refill program, and the method includes: accessing a database and reading the protobuf-serialized intelligent driving data in the database; deserializing the protobuf-serialized intelligent driving data in the database into the intelligent driving data according to the protobuf deserialization method corresponding to the intelligent driving data; serializing the intelligent driving data according to the cdr serialization method corresponding to the intelligent driving data to obtain cdr-serialized intelligent driving data; and sending the cdr-serialized intelligent driving data to the vehicle-side simulation program via FastDDS shared memory. The method is applied to a vehicle-side simulation program, and the method includes: receiving CDR-serialized intelligent driving data sent by a recharging program; deserializing the CDR-serialized intelligent driving data into the intelligent driving data according to a CDR deserialization method corresponding to the intelligent driving data, and using the intelligent driving data for intelligent driving data simulation. This application realizes the efficient collection, transmission, storage and application of intelligent driving data through standardized data processing procedures and flexible storage management methods, and improves the overall performance and adaptability of the system.

[0033] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 A schematic diagram of the structure of a system for processing intelligent driving data provided in an embodiment of the present application;

[0036] Figure 2 A flowchart of a method for processing intelligent driving data applied to a vehicle-side perception module provided in an embodiment of the present application;

[0037] Figure 3 A flowchart of another method for processing intelligent driving data applied to a vehicle-side perception module provided in an embodiment of the present application;

[0038] Figure 4 A flowchart of a method for processing intelligent driving data applied to a data acquisition program provided in an embodiment of the present application;

[0039] Figure 5 A flowchart of a method for processing intelligent driving data applied to a Java backend program provided in an embodiment of the present application;

[0040] Figure 6 A flowchart of a method for processing intelligent driving data applied to a recharging program provided in an embodiment of the present application;

[0041] Figure 7 A flowchart of a method for processing intelligent driving data applied to a vehicle-side simulation program provided in an embodiment of the present application;

[0042] Figure 8 A flowchart of an example of a method for processing intelligent driving data provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0044] The method for processing intelligent driving data provided in the embodiment of the present application can be applied to an intelligent driving data processing system. Figure 1As shown, the system includes a vehicle-side perception module 110, a data acquisition program 120, a Java backend program 130, a re-injection program 140 and a vehicle-side simulation program 150. In the intelligent driving data processing system, the vehicle-side perception module 110 is used to collect intelligent driving data, and serialize the data according to the corresponding cdr (common data representation, CommonDataRepresentation) serialization method to obtain cdr-serialized intelligent driving data. The data acquisition program 120 receives the cdr-serialized intelligent driving data sent by the vehicle-side perception module 110 through the FastDDS shared memory method. The Java backend program 130 accesses the database, reads the protobuf-serialized intelligent driving data therein, and deserializes it for playback of intelligent driving data. The re-injection program 140 accesses the database, reads the protobuf-serialized intelligent driving data therein, deserializes it, and then serializes it according to the corresponding cdr serialization method to obtain cdr-serialized intelligent driving data. The vehicle-side simulation program 150 receives the cdr serialized intelligent driving data sent by the recharging program 140 through the FastDDS shared memory mode, and after deserialization, it is used for the simulation of intelligent driving data. Through the collaborative work of the above modules, the functions of intelligent driving data collection, transmission, storage, playback and simulation are realized.

[0045] The following will describe in detail a method for processing intelligent driving data provided by an embodiment of the present application in combination with a specific implementation method. Figure 2 A flowchart of a method for processing intelligent driving data applied to a vehicle-side perception module provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the specific steps are as follows:

[0046] Step 201, collecting intelligent driving data.

[0047] In practice, the vehicle-side perception module can collect intelligent driving data about the vehicle's surrounding environment and its own status in real time through sensors (such as cameras, radars, lidars, etc.). Intelligent driving data can include: environmental perception data (such as road conditions, obstacle locations, information about pedestrians and other vehicles), vehicle status data (such as speed, acceleration, direction, location information) and other algorithm intermediate results.

[0048] Step 202: serialize the intelligent driving data according to the CDR serialization method corresponding to the intelligent driving data to obtain CDR-serialized intelligent driving data.

[0049] In implementation, serialization is the process of converting a data structure or object into a format that can be stored or transmitted. CDR is a standard serialization format used to convert data into a byte stream for transmission between different systems. By serializing the intelligent driving data into the CDR format, the consistency and integrity of the data can be ensured during transmission. For example: The vehicle-side perception module can generate a CDR serialization and deserialization method for the intelligent driving data based on the IDL file of the intelligent driving data. Then, the module calls the generated CDR serialization method to convert the collected intelligent driving data (such as sensor measurements, timestamps, etc.) into a CDR format byte stream in preparation for transmission.

[0050] Step 203: Send the cdr-serialized intelligent driving data to the data acquisition program via FastDDS shared memory.

[0051] In practice, FastDDS uses shared memory, and intelligent driving data can be directly shared between different processes on the same host, reducing the number of data copies and improving transmission efficiency. For example, the vehicle-side perception module writes the cdr-serialized intelligent driving data into the pre-allocated shared memory area, and publishes the data to the specified topic through the shared memory transmission mechanism of FastDDS. The data collection program subscribes to the topic and reads data from the shared memory to achieve efficient inter-process communication.

[0052] As an optional implementation, Figure 3 A flowchart of another method for processing intelligent driving data applied to a vehicle-side perception module provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, after step 201, the following steps are also included:

[0053] Step 301, classify the intelligent driving data according to data topics.

[0054] In implementation, the vehicle-side perception module can divide the intelligent driving data into different topics according to the data type or processing logic for subsequent processing and management. For example, the vehicle-side perception module collects multiple types of data, and the vehicle-side perception module can classify the intelligent driving data into three topics: "radar data", "camera data" and "algorithm calculation results". This classification helps to adopt specific processing methods for each data type, improving processing efficiency and accuracy.

[0055] Step 302: For each data topic, generate a CDR serialization method and a CDR deserialization method for the intelligent driving data according to the IDL file corresponding to the data topic.

[0056] In implementation, the vehicle-side perception module can use the interface definition language (idl) file to define the structure of each data topic, and then generate the corresponding cdr serialization and deserialization methods through the idl compiler to ensure the consistency and compatibility of data when it is transmitted between different systems or modules.

[0057] Step 303: For each data topic, generate a protobuf serialization method and a protobuf deserialization method for the intelligent driving data according to the proto file corresponding to the data topic.

[0058] In implementation, the vehicle-side perception module can use the protocolBuffers (protobuf) definition file (.proto) to describe the structure of each data topic, and then generate the corresponding serialization and deserialization methods through the protobuf compiler, which can provide an efficient and compatible serialization mechanism when interacting with other systems (such as Java backend).

[0059] The present application also provides a method for processing intelligent driving data applied to a data collection program. Figure 4 A flowchart of a method for processing intelligent driving data applied to a data acquisition program provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the specific steps are as follows:

[0060] Step 401, receiving CDR serialized intelligent driving data sent by the vehicle-side perception module.

[0061] In implementation, the data acquisition program can receive the cdr serialized data from the vehicle-side perception module through the FastDDS shared memory mechanism. Through the shared memory method, the data acquisition program can directly read the serialized data sent by the vehicle-side perception module, reducing data copying and improving transmission efficiency.

[0062] Step 402: Deserialize the CDR-serialized intelligent driving data into intelligent driving data according to the CDR deserialization method corresponding to the intelligent driving data.

[0063] In the implementation, the data acquisition program uses the generated CDR deserialization method according to the pre-defined IDL (Interface Description Language) file to restore the received CDR serialized data to the original intelligent driving data structure. Among them, CDR is a standard format for data serialization, commonly used in DDS (Data Distribution Service). Through deserialization, the data acquisition program can obtain structured intelligent driving data for subsequent processing.

[0064] Step 403: serialize the intelligent driving data according to the protobuf serialization method corresponding to the intelligent driving data to obtain protobuf-serialized intelligent driving data.

[0065] In the implementation, the data acquisition program uses the generated protobuf serialization method according to the pre-defined proto file to serialize the deserialized intelligent driving data into the protobuf format again. By converting the data into the protobuf format, cross-platform data exchange can be achieved, and subsequent storage and processing can be facilitated.

[0066] Step 404: Store the protobuf-serialized intelligent driving data into a database according to a preset format.

[0067] In implementation, the data collection program can store the intelligent driving data serialized by protobuf in the SQLite database according to the preset .db3 format. SQLite is a lightweight embedded relational database, and .db3 is its commonly used database file extension. By storing data in the SQLite database, the collected intelligent driving data can be easily managed and queried, providing support for subsequent data analysis and processing.

[0068] The present application also provides a method for processing intelligent driving data applied to a Java backend program. Figure 5 A flowchart of a method for processing intelligent driving data applied to a Java backend program provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, the specific steps are as follows:

[0069] Step 501, access the database and read the protobuf serialized intelligent driving data in the database.

[0070] In implementation, the Java backend program can connect to the SQLite database through JDBC, execute SQL queries and read the protobuf serialized data stored in the .db3 file. For example: the Java backend program loads the SQLiteJDBC driver, establishes a database connection, creates an SQL query statement, executes the query and obtains the result set, and reads the protobuf serialized data.

[0071] Step 502 , according to the protobuf deserialization method corresponding to the intelligent driving data, deserialize the protobuf serialized intelligent driving data into intelligent driving data, and use it for intelligent driving data playback.

[0072] In implementation, the Java backend program can read the protobuf serialized smart driving data from the SQLite database, deserialize it into a usable Java object, and use it for playing or displaying the smart driving data. For example: the Java backend program uses the parseFrom method of the Java class generated by protobuf to deserialize the byte array protobufData obtained in step 501 into the corresponding smart driving data object. Then, the object is passed to the front end or other components for playing or display. For example: the data is converted into JSON format and sent to the front end.

[0073] The present application also provides a method for processing intelligent driving data applied to a recharging program. Figure 6 A flowchart of a method for processing intelligent driving data applied to a recharging program provided in an embodiment of the present application is shown in FIG. Figure 6 As shown, the specific steps are as follows:

[0074] Step 601, access the database and read the protobuf serialized intelligent driving data in the database.

[0075] In implementation, the refill program can obtain previously stored smart driving data from the database for subsequent processing. These data are serialized and stored in protobuf format. For example, if the database is SQLite, the refill program can use the SQLite API to connect to the database and execute SQL query statements to read the required protobuf serialized data from the specified table.

[0076] Step 602: Deserialize the protobuf serialized intelligent driving data in the database into intelligent driving data according to the protobuf deserialization method corresponding to the intelligent driving data.

[0077] In implementation, the protobuf serialized data read by the injection program can be converted back to the original smart driving data structure for further processing. The deserialization process parses the binary protobuf data into objects or data structures that can be used by the program.

[0078] Step 603: serialize the intelligent driving data according to the CDR serialization method corresponding to the intelligent driving data to obtain CDR-serialized intelligent driving data.

[0079] In implementation, in order to send the intelligent driving data to the vehicle-side simulation program, the backflow program can convert it into the cdr format. By converting the data structure into binary data in the cdr format, an efficient communication mechanism transmission can be achieved.

[0080] Step 604, the cdr serialized intelligent driving data is sent to the vehicle-side simulation program through FastDDS shared memory.

[0081] In implementation, in order to efficiently transfer data to the vehicle-side simulation program, the backfill program can use the shared memory mechanism of FastDDS. Shared memory allows data to be directly shared between different processes, reducing data copying and transmission delays and improving communication efficiency. For example, the backfill program can use the shared memory transmission mechanism of FastDDS to publish cdr serialized data to a specific topic, and the vehicle-side simulation program can subscribe to the topic and receive data.

[0082] The present application also provides a method for processing intelligent driving data applied to a vehicle-side simulation program. Figure 7 A flowchart of a method for processing intelligent driving data applied to a vehicle-side simulation program provided in an embodiment of the present application is shown in FIG. Figure 7 As shown, the specific steps are as follows:

[0083] Step 701, receiving the CDR-serialized intelligent driving data sent by the recharging program.

[0084] In implementation, the vehicle-side simulation program can receive cdr serialized data from the injection program through the shared memory mechanism of FastDDS. For example, the vehicle-side simulation program configures a FastDDS subscriber to subscribe to the intelligent driving data of a specific topic. When the injection program publishes cdr serialized intelligent driving data, the subscriber directly receives the data through shared memory, thereby reducing data copying and transmission delays.

[0085] Step 702, according to the CDR deserialization method corresponding to the intelligent driving data, the CDR serialized intelligent driving data is deserialized into intelligent driving data, and used for intelligent driving data simulation.

[0086] In the implementation, the vehicle-side simulation program uses the pre-generated CDR deserialization method to convert the received CDR format data back to the original intelligent driving data structure. The vehicle-side simulation program can use the deserialized intelligent driving data to execute the corresponding simulation logic, such as simulating the behavior of the vehicle in a specific environment.

[0087] As an optional implementation, Figure 8 A flowchart of an example of a method for processing intelligent driving data provided in an embodiment of the present application is shown in FIG. Figure 8 As shown, the specific steps are as follows:

[0088] Step 801: The vehicle-side perception module divides the perception data and intermediate algorithm results into topics, and generates CDR serialization methods and deserialization methods based on the IDL files of each data structure.

[0089] Step 802: The vehicle-side perception module generates a protobuf serialization and deserialization method based on the proto files of each data structure.

[0090] Step 803: The vehicle-side perception module serializes the intelligent driving data CDR.

[0091] Step 804, the cdr serialized data is sent out using the fastDDS shared memory method.

[0092] Step 805: The data collection program receives the data and performs CDR deserialization, and then serializes the data into the data type stored in the SQLite database using protobuf.

[0093] Step 806: The data acquisition program writes the intelligent driving data into the database according to the received timestamp and saves it as a db3 file.

[0094] Step 807, the refill program opens the data packet db3 file, reads data from the database according to the timestamp, and deserializes it using the protobuf deserialization method corresponding to the topic.

[0095] Step 808, the re-injection program serializes the protobuf deserialized data using the cdr serialization method.

[0096] Step 809, the refill program uses the fastDDS shared memory method to send out the cdr serialized data.

[0097] Step 810, the vehicle-side simulation program receives data, deserializes the CDR, and performs algorithm simulation.

[0098] Step 811, the Java backend program opens the data packet db3 file, reads data from the database according to the timestamp, deserializes it using the protobuf deserialization method corresponding to the topic, and parses and displays it on the web page.

[0099] The embodiment of the present application provides a method for processing intelligent driving data, which is applied to a vehicle-side perception module, and the method includes: collecting intelligent driving data; serializing the intelligent driving data according to the cdr serialization method corresponding to the intelligent driving data to obtain cdr serialized intelligent driving data; sending the cdr serialized intelligent driving data to the data acquisition program through the FastDDS shared memory method. The method is applied to the data acquisition program, and the method includes: receiving the cdr serialized intelligent driving data sent by the vehicle-side perception module; deserializing the cdr serialized intelligent driving data into intelligent driving data according to the cdr deserialization method corresponding to the intelligent driving data; serializing the intelligent driving data according to the protobuf serialization method corresponding to the intelligent driving data to obtain protobuf serialized intelligent driving data; storing the protobuf serialized intelligent driving data in the database according to a preset format. The method is applied to a Java backend program, and the method includes: accessing the database and reading the protobuf serialized intelligent driving data in the database; deserializing the protobuf serialized intelligent driving data into intelligent driving data according to the protobuf deserialization method corresponding to the intelligent driving data, and using it for intelligent driving data playback. The method is applied to a refilling program, and the method includes: accessing a database and reading the protobuf-serialized intelligent driving data in the database; deserializing the protobuf-serialized intelligent driving data in the database into intelligent driving data according to the protobuf deserialization method corresponding to the intelligent driving data; serializing the intelligent driving data according to the cdr serialization method corresponding to the intelligent driving data to obtain cdr-serialized intelligent driving data; and sending the cdr-serialized intelligent driving data to a vehicle-side simulation program via FastDDS shared memory. The method is applied to a vehicle-side simulation program, and the method includes: receiving the cdr-serialized intelligent driving data sent by the refilling program; deserializing the cdr-serialized intelligent driving data into intelligent driving data according to the cdr deserialization method corresponding to the intelligent driving data, and using it for intelligent driving data simulation. In the embodiment of the present application, the vehicle-side perception module serializes the collected intelligent driving data through cdr, and sends it to the data acquisition program using the FastDDS shared memory method, thereby realizing efficient data transmission, reducing delays, and improving real-time performance. By generating cdr serialization and deserialization methods based on idl files, and protobuf serialization and deserialization methods based on proto files, the standardized representation and compatibility of data between different modules are ensured, which facilitates the expansion and maintenance of the system. The data acquisition program converts the received intelligent driving data into protobuf format and stores it in the SQLite database according to the preset format (such as .db3), providing a flexible storage solution to facilitate data management, query and subsequent processing.The stored data can be accessed and deserialized by Java back-end programs for playback and analysis of intelligent driving data; at the same time, the injection program can read data from the database and send it to the vehicle-side simulation program after processing for algorithm simulation testing, meeting a variety of application requirements.

[0100] It should be understood that although Figures 2 to 8 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figures 2 to 8 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0101] It can be understood that the same / similar parts between the various embodiments of the above method in this specification can refer to each other, and each embodiment focuses on the differences from other embodiments. For related points, please refer to the description of other method embodiments.

[0102] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (pROM), electrically programmable ROM (EpROM), electrically erasable programmable ROM (EEpROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0103] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0104] It should also be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0105] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0106] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0107] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for processing intelligent driving data, characterized in that: The method is applied to a vehicle-side perception module, and the method includes: Collect intelligent driving data; According to the CDR serialization method corresponding to the intelligent driving data, the intelligent driving data is serialized to obtain CDR serialized intelligent driving data; The cdr-serialized intelligent driving data is sent to the data acquisition program via FastDDS shared memory.

2. The method according to claim 1, characterized in that: The method further comprises: Classifying the intelligent driving data according to data topics; For each of the data topics, a CDR serialization method and a CDR deserialization method of the intelligent driving data are generated according to the IDL file corresponding to the data topic; For each of the data topics, a protobuf serialization method and a protobuf deserialization method of the intelligent driving data are generated according to the proto file corresponding to the data topic.

3. A method for processing intelligent driving data, characterized in that: The method is applied to a data acquisition program, and the method comprises: Receive CDR serialized intelligent driving data sent by the vehicle-side perception module; Deserializing the CDR-serialized intelligent driving data into the intelligent driving data according to the CDR deserialization method corresponding to the intelligent driving data; Serializing the intelligent driving data according to the protobuf serialization method corresponding to the intelligent driving data to obtain protobuf serialized intelligent driving data; The protobuf-serialized intelligent driving data is stored in the database according to a preset format.

4. The method according to claim 3, characterized in that The preset format is .db3 format, and the database is a SQLite database.

5. A method for processing intelligent driving data, characterized in that: The method is applied to a Java backend program, and the method comprises: Accessing a database and reading protobuf-serialized intelligent driving data in the database; According to the protobuf deserialization method corresponding to the intelligent driving data, the protobuf-serialized intelligent driving data is deserialized into the intelligent driving data and used for intelligent driving data playback.

6. A method for processing intelligent driving data, characterized in that: The method is applied to a recharging procedure, and the method comprises: Accessing a database and reading protobuf-serialized intelligent driving data in the database; Deserializing the protobuf serialized intelligent driving data in the database into the intelligent driving data according to the protobuf deserialization method corresponding to the intelligent driving data; According to the CDR serialization method corresponding to the intelligent driving data, the intelligent driving data is serialized to obtain CDR serialized intelligent driving data; The cdr-serialized intelligent driving data is sent to the vehicle-side simulation program via FastDDS shared memory.

7. A method for processing intelligent driving data, characterized in that: The method is applied to a vehicle-side simulation program, and the method comprises: Receive the CDR serialized intelligent driving data sent by the recharging program; According to the CDR deserialization method corresponding to the intelligent driving data, the CDR-serialized intelligent driving data is deserialized into the intelligent driving data and used for intelligent driving data simulation.

8. A system for processing intelligent driving data, characterized in that: The system includes the vehicle-side perception module as described in any one of claims 1-2, the data acquisition program as described in any one of claims 3-4, the Java back-end program as described in claim 5, the re-injection program as described in claim 6 and the vehicle-side simulation program as described in claim 7.

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