Data Processing Method and Apparatus

Abstract

An embodiment of the present application provides a data processing method and apparatus. In the embodiment of the present application, rule configuration information provided by an ODD data requester can be obtained; and the rule configuration information is parsed to obtain the ODD conditions expressed by the rule configuration information; at least based on the ODD conditions expressed by the rule configuration information, ODD data is generated. Since the generated ODD data is generated based on the rule configuration information provided by the ODD data requester, therefore, customization of ODD data by the ODD data requester can be realized, and ODD data that can meet the intelligent driving requirements of different ODD data requesters can be generated, and further the requirements of different intelligent driving functions can be met.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and particularly to a data processing method and apparatus. Background Art

[0002] As electronic maps evolve from ordinary maps to high-precision maps, cars are also evolving from manned driving to driverless driving, and intelligent driving is an important stage in this evolution process. Currently, intelligent driving is still in the development stage. To ensure the safety of cars with intelligent driving systems, it is necessary to design an Operational Design Domain (ODD). The ODD defines the conditions under which the intelligent driving system can be started. Once the conditions are not met, the driver takes over the car.

[0003] Since the start-up conditions and applicable scopes of different intelligent driving systems may be different, how to generate ODD data that can meet different intelligent driving systems has become an urgent problem to be solved. Summary of the Invention

[0004] Multiple aspects of this application provide a data processing method and apparatus to provide an ODD data generation method, which can generate ODD data that meets different intelligent driving requirements.

[0005] An embodiment of this application provides a data processing method, which includes:

[0006] Obtain rule configuration information provided by a requester of target ODD data;

[0007] Parse the rule configuration information to determine the Operational Design Domain (ODD) conditions expressed by the rule configuration information;

[0008] Generate the target ODD data based at least on the ODD conditions.

[0009] An embodiment of this application also provides a data processing system, which includes: a client device and a server device; the client device is configured to obtain rule configuration information in response to a rule configuration event; and provide the rule configuration information to the server device;

[0010] The server device is configured to: parse the rule configuration information to obtain the Operational Design Domain (ODD) conditions expressed by the rule configuration information; and generate target ODD data based at least on the ODD conditions.

[0011] Optionally, the data processing system further includes: an intelligent driving device; the server device is configured to provide the target ODD data to the intelligent driving device; the intelligent driving device is configured to perform intelligent driving based on the target ODD data.

[0012] An embodiment of the present application further provides a computer device, which includes: a memory and a processor; the memory is used to store a computer program;

[0013] The processor is coupled to the memory and is used to execute the computer program to perform the steps in the above data processing method.

[0014] An embodiment of the present application further provides a computer-readable storage medium storing computer instructions, wherein when the computer instructions are executed by one or more processors, the one or more processors are caused to perform the steps in the above data processing method.

[0015] An embodiment of the present application further provides a data processing device, which includes:

[0016] An acquisition module, configured to acquire rule configuration information provided by a requester of target operating design domain (ODD) data;

[0017] An analysis module, configured to analyze the rule configuration information to determine the ODD conditions expressed by the rule configuration information;

[0018] A generation module, configured to generate the target ODD data based at least on the ODD conditions.

[0019] In an embodiment of the present application, rule configuration information provided by an ODD data requester can be acquired; the rule configuration information can be analyzed to obtain the ODD conditions expressed by the rule configuration information; and ODD data is generated based at least on the ODD conditions expressed by the rule configuration information. Since the generated ODD data is generated based on the rule configuration information provided by the ODD data requester, customization of ODD data by the ODD data requester can be achieved, ODD data that can meet the intelligent driving requirements of different ODD data requesters can be generated, and thus the requirements of different intelligent driving functions can be met. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0021] Figure 1a is a schematic structural diagram of a data processing system provided by an embodiment of the present application;

[0022] Figure 1b is a schematic page diagram of a rule configuration item provided by an embodiment of the present application;

[0023] Figures 1c - 1eSchematic structural diagram of another data processing system provided by an embodiment of the present application;

[0024] Figure 2 Schematic flowchart of a data processing method provided by an embodiment of the present application;

[0025] Figure 3 Schematic structural diagram of a computer device provided by an embodiment of the present application;

[0026] Figure 4 Schematic structural diagram of a data processing device provided by an embodiment of the present application. Detailed implementation manners

[0027] To make the objectives, technical solutions, and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below in conjunction with specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0028] The classification of vehicle intelligence divides intelligent driving into levels L0 to L5. Before fully intelligent driving functions (level L5), it is necessary to set the ODD to limit the driving environment and driving methods to ensure the safety of intelligent driving. The prerequisite conditions and applicable scopes of different intelligent driving systems may be different. Therefore, how to generate ODD data that can meet different intelligent driving systems has become an urgent problem to be solved.

[0029] In order to meet the requirements for ODD data of different intelligent driving systems, in some embodiments of the present application, rule configuration information provided by the ODD data requester can be obtained; and the rule configuration information can be parsed to obtain the ODD conditions expressed by the rule configuration information; and at least based on the ODD conditions expressed by the rule configuration information, ODD data is generated. Since the generated ODD data is generated based on the rule configuration information provided by the ODD data requester, it is possible to achieve customization of the ODD data by the ODD data requester, generate ODD data that can meet the intelligent driving requirements of different ODD data requesters, and thus meet the requirements of different intelligent driving functions.

[0030] The following will detail the technical solutions provided by each embodiment of the present application in conjunction with the drawings.

[0031] It should be noted that the same reference numerals represent the same object in the following drawings and embodiments. Therefore, once an object is defined in one drawing or embodiment, it does not need to be further discussed in subsequent drawings and embodiments.

[0032] Figure 1aThis is a schematic structural diagram of the data processing system provided by the embodiments of the present application. As Figure 1a shown, the system includes: a client device 11 and a server device 12.

[0033] In this embodiment, the client device 11 refers to a computer device on the side of the ODD data requester. For example, it can be a smartphone, a tablet computer, a personal computer, a wearable device, etc. of the ODD data requester. Among them, the ODD data requester can be a manufacturer or an application party of intelligent driving devices. The intelligent driving device can be a device with intelligent driving functions, such as an intelligent driving vehicle, a drone, a robot, a ship, etc. For an intelligent driving vehicle, it can be a car, a truck, a bus, a construction vehicle, or a delivery vehicle with intelligent driving functions.

[0034] ODD data is a concept in the field of intelligent driving or driverless driving. Specifically, it refers to the conditions for enabling or disabling the intelligent driving function of an intelligent driving device. In some embodiments, the ODD data includes, but is not limited to: one or more of road network conditions for supporting or not supporting the intelligent driving function, geographical conditions for supporting or not supporting the intelligent driving function, traffic conditions for supporting or not supporting the intelligent driving function, weather conditions for supporting or not supporting the intelligent driving function, driving conditions for supporting or not supporting the intelligent driving function, etc. "Multiple" means 2 or more. The road network conditions for supporting or not supporting the intelligent driving function can be: highways, ordinary roads, lanes or sections, etc. that support or do not support intelligent driving; one or more of areas that support or do not support intelligent driving.

[0035] The geographical conditions for supporting or not supporting the intelligent driving function can be: the geographical location information (such as longitude and latitude coordinates, etc.) of the area that supports or does not support the intelligent driving function, or the geographical environment that supports or does not support the intelligent driving function. The geographical environment can refer to whether it is a city or a mountain area, or a geographical fence (Geo-fence) enclosed by a virtual fence or the surrounding environment to set conditions, etc.

[0036] The driving conditions for supporting or not supporting the intelligent driving function can include: driving speed conditions for supporting or not supporting the intelligent driving function, driver continuous driving duration conditions for supporting or not supporting the intelligent driving function, etc.

[0037] In this embodiment, the server device 12 refers to a computer device that can perform data processing, respond to service requests from the client device 11, and provide services related to data processing for ODD data requesters. Generally, it has the ability to undertake and guarantee services. The server device 12 can be a single server device, a cloudified server array, or a virtual machine (VM) running in a cloudified server array. Additionally, the server device 12 can also refer to other computing devices with corresponding service capabilities, such as terminal devices (running service programs) like computers, etc.

[0038] Among them, the connection between the client device 11 and the server device 12 can be wireless or wired. Optionally, the client device 11 can communicate with the server device 12 through a mobile network. Correspondingly, the network mode of the mobile network can be any one of 2G (GSM), 2.5G (GPRS), 3G (WCDMA, TD - SCDMA, CDMA2000, UTMS), 4G (LTE), 4G+ (LTE+), 5G, WiMax, etc. Optionally, the client device 11 can also communicate with the server device 12 through Bluetooth, WiFi, infrared, etc.

[0039] In this embodiment, the server device 12 can respond to the request of the client device 11 and provide services related to data processing to the client device 11. In this embodiment, the data processing service is mainly for services related to ODD data, such as customization and storage of ODD data. The following is an exemplary description of the data processing process of the data processing system provided in this application embodiment.

[0040] In this embodiment, the ODD data requester can customize the target ODD data that meets its intelligent driving requirements. To meet the autonomous customization of the target ODD data by the ODD data requester, the ODD data requester can set rule configuration information. Among them, the rule configuration information refers to rules or conditions that can reflect the rules for restricting the support or non - support of intelligent driving functions. Such as "Intelligent driving cannot be enabled within a certain number of meters from an intersection", "Intelligent driving is enabled when the weather visibility is lower than a certain threshold", or "Intelligent driving is enabled after the driver has driven continuously for a certain period of time", etc.

[0041] For the client device 11, it can respond to the rule configuration event, obtain the rule configuration information associated with the rule configuration event, and provide the rule configuration information to the server device 12. In the embodiment of this application, the specific implementation form of the rule configuration event is not limited.

[0042] In some embodiments, the client device 11 may provide a rule configuration interface through which the ODD data requester can provide rule configuration information. Optionally, the ODD data requester can upload or input rule configuration information through the rule configuration interface. Correspondingly, the client device 11 may obtain the information provided through the rule configuration interface in response to a rule configuration event generated by a trigger event for the rule configuration interface, as the rule configuration information associated with the rule configuration event. Optionally, the rule configuration information may include: rule configuration items and the corresponding rule configuration information for the rule configuration items. The rule configuration items can be one or more. More than one means two or more. Each rule configuration item corresponds to a setting rule for ODD data, which is used to reflect the conditions for supporting or not supporting the intelligent driving function. Such as "Intelligent driving cannot be enabled within a certain number of meters from an intersection", "Intelligent driving is enabled when the weather visibility is lower than a certain threshold", or "Intelligent driving is enabled after the driver has been driving continuously for a certain period of time", etc.

[0043] In some other embodiments, the client device 11 may provide at least one rule configuration item for the user to select. Preferably, the client device 11 provides multiple rule configuration items. Correspondingly, as Figure 1a shown, the client device 11 may display at least one rule configuration item.

[0044] In the embodiments of the present application, the classification criteria for the rule configuration items are not limited. Optionally, as Figure 1a shown, the rule configuration items can be classified according to the influencing factors of the ODD data. Figure 1a Only four rule configuration items, such as road network condition rules, driving rules, weather condition rules, and traffic condition rules, are illustrated for at least one rule configuration item, which does not limit the specific content and quantity of the rule configuration items. Or, as Figure 1b shown, the rule configuration items can also be classified according to the ODD data requester. As Figure 1b shown, different ODD data requesters correspond to different rule configuration items. Such as the configuration items corresponding to car manufacturers A - D respectively. Optionally, as Figure 1b shown, the client device 11 may also display the status of each rule configuration item, etc.

[0045] Optionally, the client device 11 may provide a rule configuration request to the server device 12. In some embodiments, the client device 11 may display a rule configuration control, and the ODD data requester can trigger the rule configuration control to request rule configuration items. Correspondingly, the client device 11 may provide a rule configuration request to the server device 12 in response to the trigger operation for the rule configuration control.

[0046] Accordingly, the server device 12 can provide at least one rule configuration item to the client device 11 in response to a rule configuration request. The client device 11 can receive at least one rule configuration item and display at least one rule configuration item. The ODD data requester can select a rule configuration item by triggering the area corresponding to the rule configuration item.

[0047] For a rule configuration item, it can include a fixed part and a variable part. Among them, the variable part is mainly the rule configuration parameter, that is, the parameter corresponding to the rule configuration item. For example, within a certain number of meters from a reference object, intelligent driving cannot or is allowed to be turned on, etc.; among them, the reference object, the distance from the reference object, and the supported driving mode are the rule configuration parameters of this rule configuration item. Another example is that intelligent driving is turned on after the driver has driven continuously for a certain period of time. Among them, the duration of the driver's continuous driving is the rule configuration parameter of this rule configuration item, and so on. Among them, the driving mode can be an intelligent driving mode or a driver driving mode (that is, the intelligent driving mode is turned off).

[0048] Accordingly, as Figure 1a shown, the client device 11 can display the configurable parameters of the selected target rule configuration item in response to a selection operation for the rule configuration item. The ODD data requester can set the value of the configurable parameter (abbreviated as the configurable parameter value) through the setting control of the configurable parameter. Figure 1a Only the weather condition rule is illustrated as the target rule configuration item, but it does not constitute a limitation. The configurable parameters corresponding to the weather condition rule can include, but are not limited to, meteorology, rainfall level, wind force, temperature, visibility, and supported driving mode, etc.

[0049] As Figure 1b shown, when the ODD data requester configures the target rule configuration item, it can trigger the configuration control corresponding to the rule configuration item (such as Figure 1b the "Process" control shown). Accordingly, the client device 11 can, in response to the triggering operation for the configuration control, use the rule configuration item corresponding to the triggered configuration control as the target rule configuration item and display the configurable parameters of the selected target rule configuration item.

[0050] Accordingly, the client device 11 can obtain the configurable parameter value by responding to the setting operation for the configurable parameter, fill the configurable parameter value into the corresponding position of the target rule configuration item to obtain the target rule configuration item, and use the information of the target rule configuration item as the rule configuration information. In this embodiment, the rule configuration event can be implemented as a rule configuration event generated by a selection operation for a rule configuration item.

[0051] Among them, the specific implementation form and quantity of the target rule configuration items can be independently selected by the ODD data requester according to its intelligent driving requirements. Optionally, the client device 11 can also provide multiple rule configuration methods, and the ODD data requester can set the configurable parameter values corresponding to each of the multiple rule configuration items. As Figure 1a shown, the client device 11 can provide a continue configuration control and a configuration completion control. After the ODD data requester completes the parameter configuration of the current rule configuration item, it can select whether to continue the configuration or complete the configuration through the continue configuration control and the configuration completion control. Optionally, if the ODD data requester selects to complete the configuration, the configuration completion control can be triggered. Correspondingly, the client device 11 can obtain the rule configuration information corresponding to the rule configuration item with the configuration completed in response to the trigger operation for the configuration completion control.

[0052] Furthermore, the client device 11 can provide the rule configuration information to the server device 12. The server device 12 can receive the rule configuration information. The above embodiments only take the server device 12 obtaining the rule configuration information provided by the ODD data requester in real time as an example to exemplarily illustrate the implementation manner of the server device 12 obtaining the rule configuration information. Of course, the server device 12 can also pre-store the rule configuration information provided by the ODD data requester; and in response to the request of the ODD data requester, obtain the rule configuration information provided by the ODD data requester from the pre-stored rule configuration information. Among them, for the specific implementation manner of the ODD data requester providing the rule configuration information, reference can be made to the relevant content of the above embodiments, which will not be elaborated here.

[0053] Furthermore, the server device 12 parses the obtained rule configuration information to obtain the ODD conditions expressed by the rule configuration information. Among them, the ODD conditions refer to the conditions for setting ODD data, and these conditions can limit the timing or conditions for the intelligent driving device to turn on or off the intelligent driving function.

[0054] Furthermore, the server device 12 can generate ODD data at least based on the ODD conditions expressed by the rule configuration information.

[0055] In the data processing system provided in this embodiment, the client device and the server device cooperate with each other to obtain the rule configuration information provided by the ODD data requester; and parse the rule configuration information to obtain the ODD conditions expressed by the rule configuration information; then, generate ODD data at least based on the ODD conditions reflected by the rule configuration information. Since the generated ODD data is generated based on the rule configuration information provided by the ODD data requester, the customization of ODD data by the ODD data requester can be realized, and ODD data that can meet the intelligent driving requirements of different ODD data requesters can be generated, so as to meet the requirements of different intelligent driving functions.

[0056] In the embodiment of the present application, the rule configuration information obtained by the server device 12 may include: the rule configuration information corresponding to one or more rule configuration items. "Multiple" means two or more. The content and quantity of specific rule configuration items can be set by the ODD data requester.

[0057] For the case where the rule configuration information obtained by the server device 12 includes multiple rule configuration items and the rule configuration information corresponding to the multiple rule configuration items, the server device 12 may further obtain the rule configuration information corresponding to each target rule configuration item from the rule configuration information and generate a rule configuration list. In the embodiment of the present application, the data structure form of the rule configuration list is not limited. Optionally, the rule configuration list can be stored in the form of a list or a key-value pair, but not limited thereto. Among them, in the rule configuration list, each target rule configuration item corresponds one-to-one to its corresponding rule configuration information. In this way, when the server device 12 performs ODD data compilation, it can read the rule configuration information corresponding to the rule configuration item from the rule configuration list; and parse the rule configuration information corresponding to each rule configuration item to obtain the ODD condition corresponding to the rule configuration item; then, at least based on the ODD condition corresponding to each rule configuration item, generate the ODD data corresponding to the rule configuration item.

[0058] Optionally, when the server device 12 parses the rule configuration information, the server device 12 may parse out the configurable parameter value corresponding to the rule configuration item from the rule configuration information corresponding to the rule configuration item; and determine the ODD condition corresponding to the rule configuration information at least according to the configurable parameter value corresponding to the rule configuration item.

[0059] Furthermore, the ODD conditions corresponding to different rule configuration items may be different. For safety considerations, it can be set that intelligent driving is allowed when the ODD conditions corresponding to each rule configuration information are met. Based on this, the ODD conditions corresponding to the rule configuration items can be fused and calculated to determine the ODD condition expressed by the rule configuration information corresponding to the rule configuration item, that is, the ODD condition corresponding to the rule configuration item. Optionally, the ODD conditions corresponding to all or part of the rule configuration items can be fused and calculated to obtain the ODD condition corresponding to the rule configuration item. Further, the ODD data can be generated at least based on the ODD conditions corresponding to multiple rule configuration items.

[0060] Optionally, when the server device 12 fuses and calculates the ODD conditions corresponding to the rule configuration items, it can obtain the ODD conditions in the same dimension from the ODD conditions corresponding to the rule configuration items; and calculate the intersection ODD condition of the ODD conditions in the same dimension; then, it can determine the union of the intersection ODD conditions in all dimensions as the ODD condition expressed by the rule configuration information of the multiple rule configuration items.

[0061] Among them, the dimension of the ODD condition corresponding to the rule configuration item refers to: the ODD condition is used to turn on or off the intelligent driving function limited by which dimension. The dimension of the ODD condition may include: geographical information dimension, time dimension, speed dimension, weather dimension, driver's continuous driving duration dimension, etc. For example, the ODD conditions respectively expressed by the rule configuration items participating in the fusion calculation may be: these rule configuration items respectively support the target area of intelligent driving. Correspondingly, the common area of the target areas of intelligent driving supported by the rule configuration items participating in the fusion calculation can be calculated as the area condition reflected by the rule configuration items participating in the fusion calculation, etc.

[0062] Optionally, the rule configuration items participating in the fusion calculation may be all the rule configuration items among multiple rule configuration items, or may be some of the rule configuration items among multiple rule configuration items. For the case where the rule configuration items participating in the fusion calculation are some of the rule configuration items among multiple rule configuration items, the server device 12 may perform a fusion calculation on the ODD conditions corresponding to some of the rule configuration items among multiple rule configuration items to obtain the ODD conditions corresponding to the part of the rule configuration items participating in the fusion calculation, and combine the ODD conditions corresponding to the remaining part of the rule configuration items that do not participate in the fusion calculation among multiple rule configuration items to obtain the ODD conditions corresponding to multiple rule configuration items.

[0063] In practical applications, some ODD data is fixed or remains fixed for a long time. Such ODD data can be called static ODD data. For example, the ODD data determined based on the road network conditions remains unchanged when the road network does not change. And the road network is almost fixed, at least fixed for a long period of time. Therefore, the ODD data determined based on the road network conditions can be static ODD data. Another example is that the ODD data determined based on the driving conditions remains unchanged when the driving conditions do not change. And the driving conditions are set by the ODD data requester and generally do not change. Therefore, the ODD data determined based on the driving conditions can also be static ODD data.

[0064] Correspondingly, of course, there are also some ODD data that change in real time. Such ODD data can be called dynamic ODD data. For example, the ODD data determined based on weather conditions will change with the change of weather conditions because the weather conditions in each place change in real time. Therefore, the ODD data determined based on weather conditions can be dynamic ODD data. Another example is the ODD data determined based on traffic conditions. Since the real-time traffic conditions on each road change in real time, the ODD data determined based on traffic conditions will also change with the change of weather conditions. Therefore, the ODD data determined based on traffic conditions can also be dynamic ODD data.

[0065] In the embodiments of the present application, for the convenience of description and distinction, the rule configuration items for generating static ODD data are defined as static rule configuration items; and the rule configuration items for generating dynamic ODD data are defined as dynamic rule configuration items. Correspondingly, all the above rule configuration items can be all static rule configuration items, or all dynamic rule configuration items; of course, the above rule configuration items can also include: static rule configuration items and dynamic rule configuration items.

[0066] For the case where the rule configuration items include: static rule configuration items and dynamic rule configuration items, when performing the fusion calculation on the ODD conditions corresponding to the rule configuration items, the ODD conditions corresponding to the static rule configuration items in multiple rule configuration items can be fused and calculated. The specific implementation method is: the ODD conditions corresponding to the static rule configuration items and the dynamic rule configuration items can be obtained from the ODD conditions reflected by multiple rule configuration items; and the ODD conditions corresponding to the static rule configuration items are fused and calculated to determine the ODD conditions corresponding to the static rule configuration items. For the dynamic configuration rule items, no fusion calculation is required, but the ODD conditions corresponding to each dynamic rule configuration item are calculated independently.

[0067] Correspondingly, static ODD data can be generated at least based on the ODD conditions corresponding to the static rule configuration items. For the case of fusing and calculating the ODD conditions corresponding to multiple static rule configuration items, static ODD data can be generated at least based on the fused ODD conditions. For the dynamic rule configuration items, dynamic ODD data corresponding to the dynamic rule configuration items can be generated at least based on the ODD conditions corresponding to the dynamic rule configuration items.

[0068] In the embodiments of the present application, the specific implementation methods for generating static ODD data and dynamic ODD data are not limited. Among them, different static rule configuration items correspond to different ODD conditions, and the implementation methods for generating static ODD data are different. The following is an exemplary description in combination with several static rule configuration items.

[0069] Embodiment A: In some embodiments, the configurable parameter values corresponding to the static rule configuration items include: road network condition parameter values and the driving modes supported by the road network condition parameter values. In the embodiments of the present application, for the convenience of description, the driving mode supported by the road network condition parameter value is defined as the first driving mode. Optionally, the first driving mode may be: supporting intelligent driving or not supporting intelligent driving. Correspondingly, the target area supporting the first driving mode can be determined according to the road network condition parameter value; and the target area supporting the first driving mode and the first driving mode are used as the ODD conditions corresponding to the static rule configuration item.

[0070] Furthermore, at least the geographical location information of the target area and the identifier of the first driving mode can be used as the static ODD data corresponding to the static rule configuration item. Of course, the geographical location information of other areas in the road network except the target area and the identifier of another driving mode except the first driving mode can also be used as the static ODD data corresponding to the static rule configuration item. If the first driving mode is an intelligent driving mode; then the other driving mode is a non-intelligent driving mode, also known as the driver driving mode; conversely, if the first driving mode is the driver driving mode, then the other driving mode is the intelligent driving mode.

[0071] Alternatively, the static ODD data corresponding to the static rule configuration item may include: the geographical location information of the target area supporting the first driving mode and the identifier of the first driving mode; and the geographical location information of other areas in the road network except the target area and the identifier of another driving mode except the first driving mode. Among them, the identifier of the driving mode (referred to as the driving mode identifier) refers to the information that uniquely identifies a driving mode, such as it can be the unique number corresponding to the driving mode, or the name of the driving mode, etc.

[0072] Among them, different road network condition parameters result in different implementation manners for determining the ODD conditions corresponding to the static rule configuration items. The following provides an exemplary description in combination with specific road network parameter conditions.

[0073] Embodiment A1: In some embodiments, the road network condition parameter values include: the target road network element as a reference and the distance from the reference. For example, within 100 meters of a traffic light intersection, the target road network element as a reference is the traffic light intersection, and the distance range from the reference is within 100 meters.

[0074] Accordingly, the server device 12 can obtain the topological relationship of the road network, and determine the geographical location information of the target road network elements included in the road network based on the topological relationship of the road network and the target road network elements used as references. Thereafter, based on the geographical location information of the target road network elements included in the road network and the topological relationship of the road network, the target road segments whose distances from the target road network elements included in the road network are within the above distance range can be determined; and the target road segments are determined as the target areas supporting the first driving mode.

[0075] For example, if the intelligent driving function cannot be enabled within 100 meters of a traffic light intersection, the first driving mode supported by this static rule configuration item is: not supporting intelligent driving, that is, the driver drives, then the road segment within 100 meters of the traffic light intersection can be determined as the target area not supporting intelligent driving. In Embodiment A1, the topological relationship of the road network mainly refers to: the road topological relationship of the road network, which may include: the names, geographical location information of the road network elements included in the road network, and the spatial distribution of the roads. The server device 12 can calculate the topological relationship of the road network in real time, or can also pre-store the topological relationship of the road network. For the case where the server device 12 pre-stores the topological relationship of the road network, for different rule configuration items, or even different ODD data requesters, the topological relationship of the road network can be reused without repeated calculation.

[0076] In this embodiment, whether the server device 12 calculates the topological relationship of the road network in real time or pre-stores the topological relationship of the road network, map data can be obtained; and path calculation is performed on the map data to obtain the topological relationship of the road network.

[0077] Optionally, when the server device 12 performs path calculation on the map data, it can obtain the geographical location information of the road segments included in the road network from the map data; and splice the road segments included in the road network according to the geographical location information of the road segments included in the road network; thereafter, based on the spatial distribution of the spliced road segments, the topological relationship of the road network is determined.

[0078] In the embodiments of the present application, in addition to setting ODD for road segments, ODD can also be set for regions. The following is an exemplary description in combination with Embodiment A2.

[0079] Embodiment A2: In some embodiments, it is possible to support intelligent driving or not support intelligent driving according to different regional attributes. The regional attribute can be the usage attribute of the region, such as residential area, industrial park, etc.; or, the regional attribute can also be the road attribute, such as highway, ordinary road, sidewalk, motor vehicle lane or dedicated lane for intelligent driving, etc. Accordingly, the road network condition parameter value includes: regional attribute. The region with the regional attribute as the regional attribute in the road network condition parameters can support the above first driving mode.

[0080] Based on the above road network condition parameters, the server device 12 can obtain, from the map data, a first area whose attribute is the area attribute in the road network condition parameter values; and determine the first area as the target area that supports the first driving mode.

[0081] In the embodiments of the present application, in addition to setting the geographical location information, the ODD data can also set the ODD data for driving conditions, such as for driving speed, driver's continuous driving duration, and so on. The following is an exemplary description in combination with Embodiment B.

[0082] Embodiment B: In some embodiments, the configurable parameter values corresponding to the static rule configuration items include: driving conditions and the driving modes supported by the driving conditions. In the embodiments of the present application, for the convenience of description and distinction, the driving modes supported by the driving conditions can be defined as the second driving mode. Among them, the second driving mode can be an intelligent driving mode or a driver driving mode. Correspondingly, the server device 12 can determine the target driving conditions that support intelligent driving according to the driving conditions and the second driving mode; and determine the target conditions as the target conditions corresponding to the static rule configuration items.

[0083] Optionally, if the second driving mode supported by the driving conditions is the intelligent driving mode, the driving conditions included in the configurable parameter values of the static rule configuration item can be directly used as the target driving conditions that support intelligent driving. For example, if the driving condition is that the driver's continuous driving duration is greater than or equal to N hours to support intelligent driving, the target driving condition is that the driver's continuous driving duration is greater than or equal to N hours.

[0084] If the second driving mode supported by the driving conditions does not support intelligent driving, that is, the second driving mode is the driver driving mode, the reverse condition of the driving conditions can be determined as the target driving conditions that support intelligent driving. Among them, the reverse condition of the driving conditions mainly refers to the condition opposite to the driving conditions. For example, if the driving condition is that the driving speed is greater than X km / s and does not support intelligent driving, the reverse condition of the driving conditions is that the driving speed is less than or equal to X km / s and supports intelligent driving.

[0085] Furthermore, the server device 12 can at least use the target driving conditions that support intelligent driving and the driving mode identifier corresponding to intelligent driving as the static ODD data.

[0086] In some embodiments, if the driving condition is the driving speed condition, when the second driving mode supported by the driving conditions is the intelligent driving mode, the driving speed condition can be used as the target driving conditions that support intelligent driving for the static rule configuration item. Correspondingly, when the second driving mode supported by the driving conditions is a non-intelligent driving mode, that is, the driver driving mode, the reverse condition of the driving speed condition can be used as the ODD condition corresponding to the static rule configuration item.

[0087] In some other embodiments, the driving condition may be the condition of the driver's continuous driving duration. Then, when the driving mode supported by the driving condition is the intelligent driving mode, the condition of the driver's continuous driving duration is used as the ODD condition corresponding to the static rule configuration item. Correspondingly, when the second driving mode supported by the driving condition is a non-intelligent driving mode (also known as the driver driving mode), the reverse condition of the driver's continuous driving duration can be used as the ODD condition corresponding to the static rule configuration item.

[0088] The static rule configuration items listed in the above embodiments are only for illustrative purposes. In the actual process of making ODD data, there may be other static rule configuration items, which will not be listed one by one in the embodiments of the present application.

[0089] In addition to the above static rule configuration items, the above multiple rule configuration items may further include: dynamic rule configuration items. Among them, different dynamic rule configuration items express different ODD conditions, and the implementation methods for generating dynamic ODD data are somewhat different. The following is an exemplary description in combination with several dynamic rule configuration items.

[0090] Embodiment C: In some embodiments, the dynamic rule configuration item is set based on the traffic condition. Correspondingly, the configurable parameter values corresponding to the dynamic rule configuration item include: traffic condition parameter values and the driving mode supported by the traffic condition parameter values. For the convenience of description, the driving mode supported by the traffic condition parameter values is defined as the third driving mode. Among them, the third driving mode may be an intelligent driving mode or a non-intelligent driving mode. Among them, the traffic condition parameters may include: traffic congestion degree, traffic events, etc. Among them, the traffic events may be road repairs, road closures, and so on.

[0091] Correspondingly, the server device 12 can obtain the real-time traffic condition of the road network. Further, according to the real-time traffic condition of the road network and the traffic condition parameter values in the dynamic rule configuration item, the section where the real-time traffic condition matches the traffic condition parameter values can be determined as the target area that supports the third driving mode, and it can be determined that the target area is the ODD condition corresponding to the dynamic rule configuration item. Further, the server device 12 can use the geographical location information of the area determined based on the traffic condition and the identifier of the third driving mode as the dynamic ODD data. Optionally, the server device 12 can also use the geographical location information of the area that supports another driving mode other than the third driving mode determined based on the traffic condition and the identifier of the other driving mode as the dynamic ODD data.

[0092] Among them, if the third driving mode is the intelligent driving mode; then the other driving mode is the non-intelligent driving mode, also known as the driver driving mode; conversely, if the third driving mode is the driver driving mode, then the other driving mode is the intelligent driving mode.

[0093] Embodiment D: In some embodiments, the dynamic rule configuration item is set based on weather conditions. Accordingly, the configurable parameter values corresponding to the dynamic rule configuration item include: the weather condition parameter value and the fourth driving mode supported by the weather parameter value. The fourth driving mode may be an intelligent driving mode or a non-intelligent driving mode. The weather condition parameters may include: meteorology, temperature, visibility, etc.

[0094] Accordingly, the server device 12 can obtain the real-time weather conditions of the corresponding area of the road network; and determine the area where the real-time weather conditions match the weather condition parameter values according to the real-time weather conditions of the corresponding area of the road network and the weather condition parameter values, as the target area supporting the fourth driving mode. Further, the target area can be determined as the ODD condition corresponding to the dynamic rule configuration item. Further, the server device 12 can use the geographical location information of the target area of the fourth driving mode determined based on the weather and road conditions and the identifier of the fourth driving mode as the dynamic ODD data. Optionally, the server device 12 can also use the geographical location information of the area supporting another driving mode other than the fourth driving mode determined based on the weather and road conditions and the identifier of another driving mode as the dynamic ODD data.

[0095] Among them, if the fourth driving mode is an intelligent driving mode; then the other driving mode is a non-intelligent driving mode, also known as the driver driving mode; conversely, if the fourth driving mode is the driver driving mode, then the other driving mode is an intelligent driving mode.

[0096] The embodiments for determining the static ODD data and the dynamic ODD data provided in the above embodiments are only exemplary descriptions and do not constitute limitations. After determining the static ODD data and the dynamic ODD data, the server device 12 can determine the static ODD data and the dynamic ODD data as the target ODD data that meets the requirements of the ODD data requester.

[0097] Further, the server device 12 can separately store the static ODD data and the dynamic ODD data. Optionally, for the dynamic ODD data corresponding to the dynamic rule configuration items respectively, a correspondence between the dynamic rule configuration items and the dynamic ODD data can be established. In this way, if the ODD data corresponding to a certain dynamic rule configuration item changes, the target storage location corresponding to the dynamic rule configuration item for which the ODD data has changed can be determined from the storage space of the dynamic ODD data, and the dynamic ODD data at the target storage location can be updated to the new dynamic ODD data. That is, if the ODD data corresponding to a certain dynamic rule configuration item changes, only the ODD data corresponding to this dynamic rule configuration item needs to be modified correspondingly, and there is no need to modify the ODD data of the static ODD data and the dynamic rule configuration items of other ODD data that have not changed, which can reduce the repeated calculation of the static ODD data and other unchanged dynamic ODD data and help save computing resources.

[0098] Of course, the server device 12 can also perform a fusion calculation on the static ODD data and the dynamic ODD data and store the ODD data after the fusion calculation. In this way, when the dynamic ODD data changes, it is necessary to repeatedly perform the fusion calculation of the static ODD data and the dynamic ODD data, resulting in a relatively high consumption of computing resources.

[0099] Further, after the server device 12 generates the target ODD data that meets the requirements of the ODD data requester, it can also verify the target ODD data. Among them, verifying the target ODD data can include, but is not limited to, verifying the accuracy and rationality of the target ODD data. The process of the server device 12 verifying the target ODD data will be exemplarily described below.

[0100] Optionally, the server device 12 can perform statistical analysis on the target ODD data to obtain the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data; and verify the target ODD data at least based on the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data to obtain a verification result. Among them, the continuous statistical parameter refers to a parameter that requires continuous statistics, such as mileage, duration, frequency, etc.

[0101] Further, the server device 12 can also provide the verification result to the client device 11. Correspondingly, the client device 11 can display the verification result.

[0102] In the embodiments of the present application, the computing framework structure for the server device 12 to perform statistical analysis on the target ODD data is not limited. Optionally, the server device 12 may adopt a Spark computing framework, or a Graphx computing framework based on Spark, etc., to perform statistical analysis on the target ODD data, and can calculate and statistically output the continuous statistical results reflected by the ODD data of the entire road network in a relatively short time and with relatively small resource overhead. Optionally, the server device 12 can also output the continuous statistical structure reflected by the target ODD data to relevant technical personnel for analysis, etc.

[0103] In the embodiments of the present application, the mileage reflected by the target ODD data may include: one or more of the total mileage supporting intelligent driving, the mileage of each route continuously supporting intelligent driving, the maximum mileage, the minimum mileage, and the average mileage continuously supporting intelligent driving, etc.; it may also include: one or more of the total mileage not supporting intelligent driving, the mileage of each route continuously not supporting intelligent driving, the maximum mileage, the minimum mileage, and the average mileage continuously supporting intelligent driving, etc.

[0104] The duration reflected by the target ODD data may include: one or more of the total duration of using the intelligent driving mode, the maximum duration, the minimum duration, and the average duration of continuously driving in the intelligent driving mode; it may also include: one or more of the total duration of using the driver driving mode, the maximum duration, the minimum duration, and the average duration of continuously driving in the driver driving mode.

[0105] The frequency reflected by the target ODD data may be the switching frequency of the driving mode, such as one or more of the average switching frequency, the maximum switching frequency, and the latest switching frequency of the driving mode.

[0106] In some embodiments, the server device 12 may verify the target ODD data based on the parameter values corresponding to the continuous statistical parameters reflected by the above target ODD data. In some other embodiments, when verifying the target ODD data, the server device 12 may also perform statistical analysis on the topological relationship of the road network to obtain the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network; and verify the accuracy of the target ODD data according to the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data and the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network, so as to obtain the accuracy verification result of the target ODD data. The following is an exemplary description of the specific implementation manner for the server device 12 to verify the accuracy of the target ODD data.

[0107] Optionally, the server device 12 may obtain the geographical location information supporting intelligent driving and the geographical location information not supporting intelligent driving from the target ODD data. Further, the server device 12 may calculate the total mileage supporting intelligent driving based on the geographical location information supporting intelligent driving; and may calculate the total mileage not supporting intelligent driving based on the geographical location information not supporting intelligent driving.

[0108] Optionally, the server device 12 may obtain the geographical location information of each section supporting intelligent driving and the geographical location information of each section not supporting intelligent driving from the target ODD data. Further, the server device 12 may calculate the mileage of each section supporting intelligent driving based on the geographical location information of each section supporting intelligent driving; and calculate the sum of the mileage of each section supporting intelligent driving to obtain the total mileage supporting intelligent driving. Correspondingly, the server device 12 may calculate the mileage of each section not supporting intelligent driving based on the geographical location information of each section not supporting intelligent driving; and calculate the sum of the mileage of each section not supporting intelligent driving to obtain the total mileage not supporting intelligent driving.

[0109] Further, the server device 12 may use the mileage supporting intelligent driving and the mileage not supporting intelligent driving as the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data.

[0110] Correspondingly, the server device 12 may calculate the total mileage of the road network based on the topological relationship of the road network, as the parameter value corresponding to the continuous statistical parameter reflected by the topological relationship of the road network.

[0111] Further, the server device 12 may calculate the sum of the total mileage supporting intelligent driving and the total mileage not supporting intelligent driving; and determine whether the sum of the total mileage supporting intelligent driving and the total mileage not supporting intelligent driving matches the total mileage of the road network; if the judgment result is yes, it is determined that the target ODD data passes the accuracy verification. Optionally, it may be determined whether the error between the sum of the total mileage supporting intelligent driving and the total mileage not supporting intelligent driving and the total mileage of the road network is less than or equal to a set error threshold; if the judgment result is yes, it is determined that the sum of the total mileage supporting intelligent driving and the total mileage not supporting intelligent driving matches the total mileage of the road network.

[0112] In some other embodiments, the server device 12 may also verify the rationality of the target ODD data at least based on the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data. The following is an exemplary description of the specific implementation manner of the server device 12 for verifying the rationality of the target ODD data.

[0113] Optionally, when obtaining the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data, the server device 12 may obtain the geographical location information supporting intelligent driving and the geographical location information not supporting intelligent driving from the target ODD data; and calculate the switching frequency of the driving mode reflected by the target ODD data based on the geographical location information supporting intelligent driving, the geographical location information not supporting intelligent driving, and the predicted driving speed, as the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data.

[0114] Correspondingly, if the switching frequency of the driving mode reflected by the target ODD data meets the set switching frequency requirement, it is determined that the switching frequency reflected by the target ODD data passes the rationality verification.

[0115] In some other embodiments, when obtaining the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data, the server device 12 may obtain the geographical location information supporting intelligent driving and the geographical location information not supporting intelligent driving from the target ODD data; and calculate the continuous driving duration of the driver reflected by the target ODD data based on the geographical location information not supporting intelligent driving and the predicted driving speed, as the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data.

[0116] Correspondingly, if the continuous driving duration of the driver reflected by the target ODD data meets the set continuous driving duration requirement, it is determined that the continuous driving duration reflected by the target ODD data passes the rationality verification.

[0117] If the target ODD data fails the verification, the server device 12 may also output the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data for the requester of the target ODD data to analyze the reason why the target ODD data fails the verification. Optionally, the server device 12 may provide the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data to the client device 11. Correspondingly, the client device 11 may display the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data. In this way, the requester of the target ODD data can view the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data and analyze the reason why the target ODD data fails the verification based on the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data.

[0118] Optionally, the server device 12 may also provide the parameter value of the continuity statistical parameter for which the target ODD data fails to pass the verification to the client device 11. Correspondingly, the client device 11 may obtain the parameter value of the continuity statistical parameter for which the target ODD data fails to pass the verification. In this way, the requester of the target ODD data can view the parameter value of the continuity statistical parameter for which the target ODD data fails to pass the verification, and analyze the reason why the target ODD data fails to pass the verification based on the parameter value of the continuity statistical parameter for which the target ODD data fails to pass the verification.

[0119] In some other embodiments, the server device 12 may also determine the target continuity statistical parameter for which the target ODD data fails to pass the verification; analyze the reason why the target ODD data fails to pass the verification according to the parameter value corresponding to the target continuity statistical parameter for which the target ODD data fails to pass the verification; and provide the reason why the target ODD data fails to pass the verification to the client device 11. Correspondingly, the client device 11 may display the reason why the ODD data fails to pass the verification. In this way, the requester of the target ODD data can view the reason why the target ODD data fails to pass the verification, which can provide a reference basis for the requester of the target ODD data to modify the rule configuration information.

[0120] In some embodiments, as Figure 1c shown, after the target ODD data is produced, the server device 12 may provide the target ODD data to the requester of the target ODD data, that is, the server device 12 may provide the target ODD data to the client device 11. The client device 11 may receive the target ODD data, and the requester of the target ODD data may obtain the target ODD data from the client device 11 and store the obtained target ODD data in the intelligent driving device 13 used for its production or use. In this way, the intelligent driving device 13 may perform intelligent driving based on the ODD data.

[0121] For dynamic ODD data, the server device 12 may provide the dynamically generated dynamic ODD data to the client device 11; the client device 11 and provide the dynamic ODD data to the intelligent driving device 13. In this way, the client device 11 may perform intelligent driving based on the static ODD data and the new dynamic ODD data.

[0122] In some other embodiments, as Figure 1d shown, after the target ODD data is produced, the server device 12 may provide the target ODD data to the intelligent driving device 13 of the requester of the target ODD data. The intelligent driving device 13 receives the target ODD data and may perform intelligent driving based on the target ODD data. Optionally, the server device 12 may provide the target ODD data to the intelligent driving device 13 in response to the ODD data request of the intelligent driving device 13.

[0123] Optionally, the intelligent driving device 13 may perform intelligent driving based on static ODD data and dynamic ODD data. Accordingly, the intelligent driving device 13 may obtain static ODD data and dynamic ODD data from the server device 12; and perform fusion calculation on the static ODD data and the dynamic ODD data to obtain the fused ODD data. After that, the intelligent driving device 13 may perform intelligent driving based on the fused ODD data.

[0124] Alternatively, the intelligent driving device 13 may send an ODD data request to the server device 12. The server device 12 may, in response to the ODD data request, obtain static ODD data and dynamic ODD data from the storage space; perform fusion calculation on the static ODD data and the dynamic ODD data to obtain the fused ODD data; and provide the fused ODD data to the intelligent driving device 13. After that, the intelligent driving device 13 may perform intelligent driving based on the fused ODD data.

[0125] In this embodiment, the intelligent driving device 13 may be an intelligent driving device produced or actually used by the ODD data requester. To improve the accuracy and rationality of the ODD data, the server device 12 may also obtain the driving track actually executed by the intelligent driving device 13 during the process of performing intelligent driving based on the ODD data; and use the driving track actually executed by the intelligent driving device 13 to update the ODD data. Further, the server device 12 may provide the updated ODD data to the intelligent driving device 13, and the intelligent driving device 13 may perform intelligent driving based on the updated ODD data.

[0126] Among them, the driving track actually executed by the intelligent driving device 13 may include: the geographical location information, time information, etc. of the intelligent driving device 13 actually performing intelligent driving. Accordingly, the server device 12 may use the geographical location information of the intelligent driving device 13 actually performing intelligent driving as the new geographical location information supporting intelligent driving, and update the geographical location information supporting intelligent driving in the ODD data to the new geographical location information supporting intelligent driving, etc.

[0127] Or, such as Figure 1eAs shown, the client device 11 can obtain the driving trajectory actually executed during the intelligent driving of the intelligent driving device 13 based on the target ODD data; and provide the driving trajectory actually executed by the intelligent driving device 13 to the server device 12. Accordingly, the server device 12 can use the driving trajectory actually executed by the intelligent driving device to determine whether it is necessary to update the ODD data. Optionally, the server device 12 can obtain the target ODD data and map the target ODD data into the map data to determine the geographical fence defined by the target ODD data; further, the driving trajectory actually executed by the intelligent driving device can also be mapped into the map data to determine the geographical fence used by the intelligent driving device during actual intelligent driving. Further, the server device 12 can determine whether the geographical fence defined by the target ODD data matches the geographical fence used by the intelligent driving device during actual intelligent driving; if the judgment result is negative, the geographical fence defined by the target ODD data and the geographical fence used by the intelligent driving device during actual intelligent driving can be provided to the client device 11. Further, the client device 11 can render the geographical fence defined by the target ODD data and the geographical fence used by the intelligent driving device during actual intelligent driving on the electronic map for the requester of the target ODD data to view the matching result between the geographical fence defined by the target ODD data and the geographical fence used by the intelligent driving device during actual intelligent driving.

[0128] Optionally, the requester of the target ODD data can independently decide whether to update the ODD data or update the rule configuration information, etc. according to the matching result between the geographical fence defined by the target ODD data and the geographical fence used by the intelligent driving device during actual intelligent driving, that is Figure 1e the update rule shown.

[0129] Further, the client device 11 can provide an update request to the server device 12 in response to an update event. Accordingly, the server device 12 can update the target ODD data stored locally to the updated ODD data in response to the update request. Or, the server device 12 generates the target ODD data at least based on the updated rule configuration information in response to the update request; etc.

[0130] Optionally, as Figure 1eAs shown in the figure, the client device 11 and the server device 12 provided in the embodiments of the present application cooperate with each other, and can also provide functions such as user authentication, feedback generation, update suggestion, update rule, layer update, and update publishing. Among them, the user authentication function can authenticate the identity of the ODD data requester; the feedback generation function means that the client device 11 can receive and display information such as the verification result of the ODD data fed back by the server device 12. The update suggestion function means that the client device 11 can provide update suggestions for the rule configuration information set for the ODD data requester. The update rule function means that the client device 11 can provide a function for updating the rule configuration information. The layer update function means that the client device 11 can determine whether the updated rule configuration item is a dynamic rule configuration item or a static rule configuration item. The update publishing function means that the client device 11 can provide the rule configuration information corresponding to the updated rule configuration item to the server device 12.

[0131] In addition to the above system embodiments, the embodiments of the present application also provide a data processing method. An exemplary description of the data processing method provided in the embodiments of the present application is given below.

[0132] Figure 2 It is a schematic flowchart of the data processing method provided in the embodiments of the present application. As Figure 2 shown, the method includes:

[0133] 201. Obtain the rule configuration information of the requester of the target ODD data.

[0134] 202. Parse the rule configuration information to determine the ODD conditions expressed by the rule configuration information.

[0135] 203. Generate the target ODD data based at least on the ODD conditions expressed by the rule configuration information.

[0136] In this embodiment, the ODD data requester can independently provide or configure the rule configuration information for generating the ODD data. The rule configuration information can reflect the ODD conditions. Based on this, in step 201, the rule configuration information provided by the requester of the target ODD data can be obtained.

[0137] Optionally, if the computer device executing the data processing method is the computer device of the ODD data requester, an alternative implementation of step 201 is: display at least one rule configuration item; and in response to a selection operation on the rule configuration item, display the configurable parameters and the setting controls of the configurable parameters of the selected target rule configuration item; and in response to a setting operation on the configurable parameters, obtain the configurable parameter values; and fill the configurable parameter values into the corresponding positions of the target rule configuration item to obtain the rule configuration information.

[0138] The computer device may be a terminal device such as a smart phone, a tablet computer, a personal computer, a wearable device, or a server device of an ODD data demander. For the implementation form of the server device, please refer to the relevant content of the above system embodiment, which will not be repeated here.

[0139] In other embodiments, the computer device that executes the above-mentioned data processing method is a server-side device of a cloud service provider. Optionally, the data processing method provided in the embodiment of the present application can also be deployed in the cloud and implemented as a SaaS service. For the server-side device that deploys the SaaS service or the data processing method provided in the embodiment of the present application, another optional implementation method of step 201 is: in response to a rule configuration request, at least one rule configuration item is provided to the computer device that initiates the rule configuration request, so that the computer device displays at least one rule configuration item; further, rule configuration information provided by the computer device that initiates the rule configuration request can be received. Among them, regarding the specific implementation method of the computer device that initiates the rule configuration request to obtain the rule configuration information, please refer to the relevant content of the above-mentioned computer device of the ODD data demander obtaining the rule configuration information, which will not be repeated here.

[0140] Of course, the computer device may also pre-store the rule configuration information provided by the ODD data demander; and obtain the rule configuration information provided by the target ODD data demander from the pre-stored rule configuration information according to the identifier of the target ODD data demander.

[0141] Regardless of who is executing the data processing method, in step 202, the rule configuration information may be parsed to obtain the ODD conditions expressed by the rule configuration information. The ODD conditions refer to the conditions for setting the ODD data, which may limit the timing or conditions for the intelligent driving device to turn on or off the intelligent driving function.

[0142] Further, in step 203, target ODD data may be generated based at least on the ODD condition expressed by the rule configuration information.

[0143] In this embodiment, the rule configuration information provided by the ODD data demander can be obtained; and the rule configuration information is parsed to obtain the ODD conditions expressed by the rule configuration information; then, ODD data is generated based on at least the ODD conditions expressed by the rule configuration information. Since the generated ODD data is generated based on the rule configuration information provided by the ODD data demander, the ODD data demander can customize the ODD data, and can generate ODD data that can meet the intelligent driving needs of different ODD data demanders, thereby meeting the needs of different intelligent driving functions.

[0144] In the embodiments of the present application, the rule configuration information may include: rule configuration items and the rule configuration information corresponding to the rule configuration items. The number of rule configuration items may be one or more. "More than one" means two or more. The content and quantity of specific rule configuration items may be set by the ODD data requirer.

[0145] Correspondingly, step 202 may be implemented as follows: the configurable parameter values corresponding to the rule configuration items may be parsed from the rule configuration information corresponding to the rule configuration items; and at least based on the configurable parameter values corresponding to the rule configuration items, the ODD conditions corresponding to the rule configuration items may be determined; further, the ODD conditions corresponding to the rule configuration items may be fusion-calculated to determine the ODD conditions expressed by the rule configuration information corresponding to the rule configuration items; and at least based on the ODD conditions expressed by the rule configuration items, the target ODD data may be generated.

[0146] Optionally, when performing the fusion calculation on the ODD conditions corresponding to the rule configuration items, the ODD conditions belonging to the same dimension may be obtained from the ODD conditions corresponding to the rule configuration items; and the intersection ODD conditions of the ODD conditions in the same dimension may be calculated; then, the union of the intersection ODD conditions of all dimensions may be calculated as the ODD conditions expressed by the rule configuration information corresponding to the rule configuration items. For the description of the dimension of the ODD conditions, reference may be made to the relevant content of the above system embodiments, which will not be elaborated here.

[0147] Optionally, the rule configuration items participating in the fusion calculation may be all the rule configuration items among the multiple rule configuration items, or may be some of the rule configuration items among the multiple rule configuration items. For the case where the rule configuration items participating in the fusion calculation are some of the rule configuration items among the multiple rule configuration items, the ODD conditions corresponding to some of the rule configuration items among the multiple rule configuration items may be fusion-calculated to obtain the ODD conditions corresponding to the part of the rule configuration items participating in the fusion calculation, and combined with the ODD conditions corresponding to the remaining part of the rule configuration items among the multiple rule configuration items that do not participate in the fusion calculation, to obtain the ODD conditions corresponding to the multiple rule configuration items.

[0148] In practical applications, some ODD data is fixed or remains fixed for a long time. Such ODD data may be referred to as static ODD data. Correspondingly, of course, there is also some ODD data that changes in real time. Such ODD data may be referred to as dynamic ODD data.

[0149] In the embodiments of the present application, for the convenience of description and distinction, the rule configuration items that generate static ODD data are defined as static rule configuration items; and the rule configuration items that generate dynamic ODD data are defined as dynamic rule configuration items. Correspondingly, the above rule configuration items may all be static rule configuration items, or may all be dynamic rule configuration items; of course, the above rule configuration items may also include: static rule configuration items and dynamic rule configuration items.

[0150] For the case where the rule configuration items include static rule configuration items and dynamic rule configuration items, when performing fusion calculation on the ODD conditions respectively corresponding to at least some of the multiple rule configuration items as described above, only the ODD conditions corresponding to the static rule configuration items among the multiple rule configuration items can be fused and calculated. The specific implementation method is as follows: The ODD conditions respectively corresponding to the static rule configuration items and the dynamic rule configuration items can be obtained from the ODD conditions corresponding to the multiple rule configuration items; and the ODD conditions corresponding to the static rule configuration items are fused and calculated to determine the ODD conditions corresponding to the static rule configuration items. For the dynamically configured rule items, the ODD conditions corresponding to the dynamic rule configuration items are used as the ODD conditions corresponding to the dynamic rule configuration items.

[0151] Correspondingly, static ODD data can be generated at least based on the ODD conditions corresponding to the static rule configuration items. For the case of fusing and calculating the ODD conditions corresponding to multiple static rule configuration items, static ODD data can be generated at least based on the ODD conditions after fusion calculation. For the dynamic rule configuration items, dynamic ODD data corresponding to the dynamic rule configuration items can be generated at least based on the ODD conditions corresponding to the dynamic rule configuration items.

[0152] In the embodiments of the present application, the specific implementation methods for generating static ODD data and dynamic ODD data are not limited. Among them, different static rule configuration items correspond to different ODD conditions, and the implementation methods for generating static ODD data are different. Several static rule configuration items are exemplarily described below.

[0153] Embodiment A: In some embodiments, the configurable parameter values corresponding to the static rule configuration items include: road network condition parameter values and the driving modes supported by the road network condition parameter values. In the embodiments of the present application, for the convenience of description, the driving modes supported by the road network condition parameter values are defined as the first driving mode. Optionally, the first driving mode may be: supporting intelligent driving or not supporting intelligent driving. Correspondingly, the target area supporting the first driving mode can be determined according to the road network condition parameter values; and the target area supporting the first driving mode is used as the ODD condition corresponding to the static rule configuration item.

[0154] Further, at least the geographical location information of the target area and the identifier of the first driving mode can be used as the static ODD data corresponding to this static rule configuration item. Of course, the geographical location information of other areas in the road network except the target area and the identifier of another driving mode except the first driving mode can also be used as the static ODD data corresponding to this static rule configuration item. If the first driving mode is an intelligent driving mode, then the other driving mode is a non-intelligent driving mode, also known as the driver driving mode; conversely, if the first driving mode is the driver driving mode, then the other driving mode is the intelligent driving mode.

[0155] Alternatively, the static ODD data corresponding to the static rule configuration item may include: the geographical location information of the target area that supports the first driving mode and the identifier of the first driving mode; and, the geographical location information of other areas in the road network except the target area and the identifier of another driving mode except the first driving mode. Among them, for the description of the identifier of the driving mode, reference can be made to the relevant content of the above system embodiment.

[0156] Among them, since the road network condition parameters are different, the implementation manners for determining the ODD conditions corresponding to the static rule configuration items are different. The following is an exemplary description in combination with specific road network parameter conditions.

[0157] Implementation manner A1: In some embodiments, the road network condition parameter values include: the target road network element used as a reference and the distance from the reference object. Correspondingly, the topological relationship of the road network can be obtained, and based on the topological relationship of the road network and the target road network element used as a reference, the geographical location information of the target road network elements included in the road network can be determined. Then, based on the geographical location information of the target road network elements included in the road network and the topological relationship of the road network, the target road segments whose distances from the target road network elements included in the road network are within the above distance range can be determined; and it is determined that the target road segments are the target areas that support the first driving mode. Among them, for the specific implementation manner of obtaining the topological relationship of the road network, reference can be made to the relevant content of the above system embodiment, which will not be elaborated here.

[0158] In the embodiments of the present application, in addition to setting ODDs for road segments, ODDs can also be set for areas. The following is an exemplary description in combination with implementation manner A2.

[0159] Implementation manner A2: In some embodiments, it is possible to set whether to support intelligent driving or not for different area attributes. Correspondingly, the road network condition parameter values include: area attributes. The areas whose area attributes are the area attributes in the road network condition parameters can support the above first driving mode.

[0160] Based on the above road network condition parameters, the first area whose attribute is the area attribute in the road network condition parameter value can be obtained from the map data; and it is determined that the first area is the target area that supports the first driving mode.

[0161] In the embodiments of the present application, in addition to setting geographical location information for ODD data, ODD data can also be set for driving conditions, such as driving speed, driver's continuous driving duration, and so on. The following will give an exemplary description in combination with Embodiment B.

[0162] Embodiment B: In some embodiments, the configurable parameter values corresponding to the static rule configuration items include: driving conditions and the driving modes supported by the driving conditions. In the embodiments of the present application, for the convenience of description and distinction, the driving modes supported by the driving conditions can be defined as the second driving mode. Among them, the second driving mode can be an intelligent driving mode or a driver driving mode. Correspondingly, according to the driving conditions and the second driving mode, the target driving conditions for supporting intelligent driving of the static rule configuration item can be determined; and it can be determined that the target driving conditions are the target driving conditions reflected by the static rule configuration item.

[0163] Optionally, if the second driving mode supported by the driving conditions is the intelligent driving mode, the driving conditions can be directly used as the target driving conditions for supporting intelligent driving.

[0164] If the second driving mode supported by the driving conditions does not support intelligent driving, that is, the second driving mode is the driver driving mode, the reverse conditions of the driving conditions can be used as the target driving conditions for supporting intelligent driving. Further, at least the target driving conditions for supporting intelligent driving and the driving mode identifier corresponding to intelligent driving can be used as the static ODD data.

[0165] For the specific examples of Embodiment B, reference can be made to the relevant content of the above system embodiments, which will not be elaborated here.

[0166] The static rule configuration items listed in the above embodiments are only for exemplary illustration. In the actual process of making ODD data, there may be other static rule configuration items, which will not be listed one by one in the embodiments of the present application.

[0167] In addition to the above static rule configuration items, the above multiple rule configuration items may further include: dynamic rule configuration items. Among them, different dynamic rule configuration items reflect different ODD conditions, and the implementation methods for generating dynamic ODD data are different. The following will give an exemplary description in combination with several dynamic rule configuration items.

[0168] Embodiment C: In some embodiments, the dynamic rule configuration item is set based on the traffic conditions. Correspondingly, the configurable parameter values corresponding to the dynamic rule configuration item include: traffic condition parameter values and the driving modes supported by the traffic condition parameter values. For the convenience of description, the driving modes supported by the traffic condition parameter values are defined as the third driving mode. Among them, the third driving mode can be an intelligent driving mode or a non-intelligent driving mode.

[0169] Accordingly, the real-time traffic conditions of the road network can be obtained. Further, based on the real-time traffic conditions of the road network and the traffic condition parameter values in the dynamic rule configuration item, the sections where the real-time traffic conditions match the traffic condition parameter values can be determined as the target areas that support the third driving mode, and the target areas can be determined as the ODD conditions corresponding to the dynamic rule configuration item. Further, the geographical location information of the area determined based on the traffic condition and the identifier of the third driving mode can be used as the dynamic ODD data. Optionally, the geographical location information of the area that supports another driving mode other than the third driving mode determined based on the traffic condition and the identifier of the other driving mode can also be used as the dynamic ODD data.

[0170] Embodiment D: In some embodiments, the dynamic rule configuration item is set based on the weather condition. Accordingly, the configurable parameter values corresponding to the dynamic rule configuration item include: the weather condition parameter value and the fourth driving mode supported by the weather parameter value. Among them, the fourth driving mode can be an intelligent driving mode or a non-intelligent driving mode. The weather condition parameters can include: meteorology, temperature, visibility, etc.

[0171] Accordingly, the real-time weather conditions of the corresponding area of the road network can be obtained; and based on the real-time weather conditions of the corresponding area of the road network and the weather condition parameter values, the areas where the real-time weather conditions match the weather condition parameter values can be determined as the target areas that support the fourth driving mode. Further, the target areas can be used as the ODD conditions reflected by the dynamic rule configuration item. Further, the geographical location information of the area of the fourth driving mode determined based on the weather condition and the identifier of the fourth driving mode can be used as the dynamic ODD data. Optionally, the geographical location information of the area that supports another driving mode other than the fourth driving mode determined based on the weather condition and the identifier of the other driving mode can also be used as the dynamic ODD data.

[0172] Further, the static ODD data and the dynamic ODD data can be determined as the target ODD data.

[0173] Optionally, the static ODD data and the dynamic ODD data can be stored separately. For the description of this part, reference can be made to the relevant content of the above system embodiment, which will not be elaborated here.

[0174] Further, after generating the target ODD data that meets the requirements of the requester of the target ODD data, the target ODD data can also be verified. Among them, verifying the target ODD data can include: verifying the accuracy and rationality of the target ODD data, but not limited to this. The process of verifying the target ODD data is exemplarily described below.

[0175] Optionally, statistical analysis can be performed on the target ODD data to obtain the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data; and the target ODD data can be verified at least based on the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data to obtain a verification result.

[0176] Further, if the execution entity of the data processing method is a server device in the cloud, the verification result can also be provided to the client device. Correspondingly, the client device can display the verification result. If the execution entity of the data processing method is a computer device of the target ODD data requester, the verification result can be directly displayed.

[0177] In some embodiments, the target ODD data can be verified based on the parameter values corresponding to the continuous statistical parameters reflected by the above target ODD data. In other embodiments, when verifying the target ODD data, statistical analysis can also be performed on the topological relationship of the road network to obtain the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network; and the accuracy of the target ODD data can be verified according to the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data and the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network to obtain the accuracy verification result of the target ODD data. Among them, the specific implementation manner of verifying the accuracy of the target ODD data can refer to the relevant content of the above system embodiments and will not be elaborated here.

[0178] In some embodiments, the target ODD data can also be provided to the requester of the target ODD data, that is, the target ODD data can be provided to the client device. The client device can receive the target ODD data, and the target ODD data requester can obtain the target ODD data from the client device and store the obtained target ODD data in the intelligent driving device it produces or uses. In this way, the intelligent driving device can perform intelligent driving based on the target ODD data.

[0179] For dynamic ODD data, the dynamically generated dynamic ODD data can be provided to the client device; the client device then provides the dynamic ODD data to the intelligent driving device. In this way, the client device can perform intelligent driving based on the static ODD data and the new dynamic ODD data.

[0180] In other embodiments, the target ODD data can be provided to the intelligent driving device of the target ODD data requester. The intelligent driving device receives the target ODD data and can perform intelligent driving based on the ODD data. Optionally, in response to the ODD data request of the intelligent driving device, the target ODD data can be provided to the intelligent driving device.

[0181] In this embodiment, the intelligent driving device may be the intelligent driving device produced or actually used by the requester of the target ODD data. In order to improve the accuracy and rationality of the target ODD data, it is also possible to obtain the driving trajectory actually executed during intelligent driving when the intelligent driving device performs intelligent driving based on the target ODD data; and use the driving trajectory actually executed by the intelligent driving device to update the target ODD data. Further, the updated ODD data can be provided to the intelligent driving device, and the intelligent driving device can perform intelligent driving based on the updated ODD data.

[0182] It should be noted that the execution subject of each step of the method provided in the above embodiment can be the same device, or the method can also be executed by different devices as the execution subject. For example, the execution subject of steps 201 and 202 can be device A; for another example, the execution subject of step 201 can be device A, and the execution subject of step 202 can be device B; and so on.

[0183] In addition, in some of the processes described in the above embodiments and the accompanying drawings, there are multiple operations that appear in a specific order. However, it should be clearly understood that these operations can be executed not in the order in which they appear in this document or in parallel. The operation numbers such as 201, 202, etc. are only used to distinguish different operations, and the numbers themselves do not represent any execution order. In addition, these processes can include more or fewer operations, and these operations can be executed in sequence or in parallel.

[0184] Correspondingly, an embodiment of the present application also provides a computer-readable storage medium storing computer instructions. When the computer instructions are executed by one or more processors, one or more processors are caused to execute the steps in the above data processing method.

[0185] Figure 3 It is a schematic structural diagram of a computer device provided by an embodiment of the present application. As Figure 3 shown, the computer device includes: a memory 30a and a processor 30b. The memory 30a is used to store computer programs.

[0186] The processor 30b is coupled to the memory 30a and is used to execute the computer program to: obtain the rule configuration information provided by the requester of the target ODD data; parse the rule configuration information to determine the operating design domain ODD conditions expressed by the rule configuration information; and generate the target ODD data at least based on the ODD conditions.

[0187] In some embodiments, the computer device is the computer device on the side of the requester of the target ODD data. The computer device may further include: a screen 30c. Correspondingly, when obtaining the rule configuration information, the processor 30b is specifically configured to: display at least one rule configuration item on the screen 30c; respond to a selection operation on the rule configuration item, and display the configurable parameters of the selected target rule configuration item on the screen 30c; and, respond to a setting operation on the configurable parameters, obtain the configurable parameter values; and fill the configurable parameter values into the corresponding positions of the target rule configuration item to obtain the rule configuration information.

[0188] In some embodiments, the computer device is the computer device on the side of the ODD data service provider, and may further include: a communication component 30d. When obtaining the rule configuration information, the processor 30b is specifically configured to: respond to a rule configuration request, and provide at least one rule configuration item to the client device through the communication component 30d for the ODD data requester on the client device side to set the rule configuration information of the rule configuration item based on the at least one rule configuration item and return it; and receive the rule configuration information returned by the client device through the communication component 30d.

[0189] In some embodiments, the rule configuration information includes: a plurality of rule configuration items and the rule configuration information corresponding to the plurality of rule configuration items. Correspondingly, when parsing the rule configuration information, the processor 30b is specifically configured to: parse out the configurable parameter values corresponding to the rule configuration items from the rule configuration information corresponding to the rule configuration items; determine the ODD conditions corresponding to the rule configuration items at least according to the configurable parameter values corresponding to the rule configuration items; and perform a fusion calculation on the ODD conditions corresponding to the rule configuration items to determine the ODD conditions expressed by the rule configuration information corresponding to the plurality of rule configuration items.

[0190] Optionally, when performing a fusion calculation on the ODD conditions corresponding to the rule configuration items, the processor 30b is specifically configured to: obtain the ODD conditions belonging to the same dimension from the ODD conditions corresponding to the rule configuration items; calculate the intersection ODD conditions of the ODD conditions of the same dimension; and calculate the union of the intersection ODD conditions of all dimensions as the ODD conditions expressed by the rule configuration information corresponding to the rule configuration items.

[0191] In some embodiments, the rule configuration items include: static rule configuration items and dynamic rule configuration items. When the processor 30b performs a fusion calculation on the ODD conditions corresponding to the rule configuration items respectively, it specifically is used for: obtaining the ODD conditions corresponding to the static rule configuration items and the dynamic rule configuration items respectively from the ODD conditions corresponding to multiple rule configuration items; performing a fusion calculation on the ODD conditions corresponding to the static rule configuration items to determine the ODD conditions corresponding to the static rule configuration items; and using the ODD conditions corresponding to the dynamic rule configuration items as the ODD conditions corresponding to the dynamic rule configuration items.

[0192] Further, when the processor 30b generates the target ODD data, it specifically is used for: generating the static ODD data corresponding to the static rule configuration items based at least on the ODD conditions corresponding to the static rule configuration items; and generating the dynamic ODD data corresponding to the dynamic rule configuration items respectively based at least on the ODD conditions corresponding to the dynamic rule configuration items; determining the dynamic ODD data and the dynamic ODD data as the target ODD data.

[0193] Optionally, the processor 30b is further used for: separately storing the static ODD data and the dynamic ODD data.

[0194] Correspondingly, the processor 30b is further used for: for the dynamic rule configuration items for which the ODD data has changed, determining the target storage location corresponding to the dynamic rule configuration items for which the ODD data has changed from the storage space of the dynamic ODD data; and updating the dynamic ODD data at the target storage location to the new dynamic ODD data.

[0195] In some embodiments, the configurable parameter values corresponding to the static rule configuration items include: road network condition parameter values and the first driving mode supported by the road network condition parameter values. When the processor 30b determines the ODD conditions corresponding to the rule configuration items, it specifically is used for: determining the first target area that supports the first driving mode according to the road network condition parameter values; and determining the first target area and the first driving mode as the ODD conditions corresponding to the static rule configuration items.

[0196] Correspondingly, when the processor 30b generates the static ODD data, it specifically is used for: using at least the geographical location information of the first target area and the identifier of the first driving mode as the static ODD data.

[0197] In some alternative embodiments, the road network condition parameter value includes: a target road network element as a reference and a distance range between the reference and other elements; the processor 30b is further configured to: obtain the topological relationship of the road network. Accordingly, when determining the first target area that supports the first driving mode, the processor 30b is specifically configured to: determine the geographical location information of the target road network elements included in the road network according to the topological relationship of the road network and the target road network element as a reference; and determine the target road segments whose distances from the target road network elements included in the road network are within the distance range according to the geographical location information of the target road network elements included in the road network and the topological relationship of the road network; and use the target road segments as the first target area that supports the first driving mode.

[0198] In some alternative embodiments, the road network condition parameter value includes: regional attributes. When determining the first target area that supports the first driving mode, the processor 30b includes: obtaining, from the map data, a first area whose attribute is the regional attribute in the road network condition parameter value; and determining the first area as the first target area that supports the first driving mode.

[0199] In some other embodiments, the configurable parameter value corresponding to the static rule configuration item includes: driving conditions and a second driving mode supported by the driving conditions. When determining the ODD conditions corresponding to the rule configuration item, the processor 30b is specifically configured to: determine the target driving conditions that support intelligent driving according to the driving conditions and the second driving mode; and determine the target driving conditions as the ODD conditions corresponding to the static rule configuration item.

[0200] Accordingly, when generating the static ODD data, the processor 30b is specifically configured to: use at least the target driving conditions and the driving mode identifier corresponding to intelligent driving as the static ODD data.

[0201] In some embodiments, the driving conditions include: driving speed conditions. When determining the target driving conditions that support intelligent driving for the static rule configuration item, the processor 30b is specifically configured to: when the second driving mode supports intelligent driving, use the driving speed conditions as the ODD conditions reflected by the static rule configuration item; and when the second driving mode does not support intelligent driving, use the reverse conditions of the driving speed conditions as the ODD conditions corresponding to the static rule configuration item.

[0202] In some other embodiments, the driving conditions include: the driver's continuous driving duration conditions. When determining the target driving conditions that support intelligent driving for the static rule configuration item, the processor 30b is specifically configured to: when the second driving mode supports intelligent driving, use the driver's continuous driving duration conditions as the ODD conditions corresponding to the static rule configuration item; and when the second driving mode does not support intelligent driving, use the reverse conditions of the driver's continuous driving duration conditions as the ODD conditions corresponding to the static rule configuration item.

[0203] In some embodiments, the configurable parameter values corresponding to the dynamic rule configuration items include: traffic condition parameter values and a third driving mode supported by the traffic condition parameter values. When determining the ODD condition corresponding to the rule configuration item, the processor 30b is specifically configured to: obtain the real-time traffic condition of the road network; and determine, according to the real-time traffic condition of the road network and the traffic condition parameter values, a section of the road network where the real-time traffic condition matches the traffic condition parameter values as a second target area that can support the third driving mode; and determine the second target area as the ODD condition corresponding to the dynamic rule configuration item.

[0204] In some other embodiments, the configurable parameter values corresponding to the dynamic rule configuration items include: weather condition parameter values and a fourth driving mode supported by the weather parameter values. When determining the ODD condition reflected by the rule configuration item, the processor 30b is specifically configured to: obtain the real-time weather condition of the area corresponding to the road network; determine, according to the real-time weather condition of the area corresponding to the road network and the weather condition parameter values, an area where the real-time weather condition matches the weather condition parameter values as a third target area that supports the fourth driving mode; and determine the third target area as the ODD condition reflected by the dynamic rule configuration item.

[0205] In the embodiment of the present application, the processor 30b is further configured to: perform statistical analysis on the target ODD data to obtain the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data; verify the target ODD data at least according to the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data to obtain a verification result.

[0206] Optionally, the processor 30b is further configured to: perform statistical analysis on the topological relationship of the road network to obtain the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network.

[0207] When verifying the target ODD data, the processor 30b is specifically configured to: verify the accuracy of the target ODD data according to the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data and the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network to obtain the accuracy verification result of the target ODD data.

[0208] Further, when performing statistical analysis on the target ODD data, the processor 30b is specifically configured to: obtain, from the target ODD data, the geographical location information that supports intelligent driving and the geographical location information that does not support intelligent driving; calculate the total mileage that supports intelligent driving according to the geographical location information that supports intelligent driving; and calculate the total mileage that does not support intelligent driving according to the geographical location information that does not support intelligent driving; and use the total mileage that supports intelligent driving and the total mileage that does not support intelligent driving as the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data.

[0209] Optionally, when the processor 30b performs statistical analysis on the topological relationship of the road network, it is specifically configured to: calculate the total mileage of the road network according to the topological relationship of the road network, and use it as the parameter value corresponding to the continuity statistical parameter reflected by the topological relationship of the road network.

[0210] Optionally, when the processor 30b verifies the accuracy of the target ODD data, it is specifically configured to: calculate the sum of the mileage of the total mileage supported for intelligent driving and the total mileage not supported for intelligent driving; determine whether the sum of the mileage of the total mileage supported for intelligent driving and the total mileage not supported for intelligent driving matches the total mileage of the road network; if the judgment result is yes, it is determined that the target ODD data passes the accuracy verification.

[0211] In some other embodiments, when the processor 30b performs statistical analysis on the target ODD data, it is specifically configured to: obtain the geographical location information supported for intelligent driving and the geographical location information not supported for intelligent driving from the target ODD data; and calculate the switching frequency of the driving mode reflected by the target ODD data according to the geographical location information supported for intelligent driving, the geographical location information not supported for intelligent driving, and the predicted driving speed, and use it as the parameter value corresponding to the continuity statistical parameter reflected by the ODD data.

[0212] Optionally, when the processor 30b verifies the target ODD data, it is specifically configured to: if the switching frequency of the execution status of intelligent driving reflected by the target ODD data meets the set switching frequency requirement, it is determined that the target ODD data passes the rationality verification.

[0213] Optionally, the processor 30b is further configured to: if the target ODD data fails to pass the verification, output the parameter value corresponding to the continuity statistical parameter reflected by the target ODD data, so that the requester of the target ODD data can analyze the reason why the target ODD data fails to pass the verification.

[0214] In the embodiment of the present application, the processor 30b is further configured to: provide the target ODD data to the intelligent driving device through the communication component 30d, so that the intelligent driving device can perform intelligent driving based on the target ODD data.

[0215] Optionally, the processor 30b is further configured to: obtain the driving trajectory of the actual execution of intelligent driving by the intelligent driving device during the process of performing intelligent driving based on the target ODD data; use the driving trajectory of the actual execution of intelligent driving by the intelligent driving device to update the target ODD data; and provide the updated ODD data to the intelligent driving device through the communication component 30d, so that the intelligent driving device can perform intelligent driving based on the updated ODD data.

[0216] In some alternative embodiments, such as Figure 3As shown, the computer device may further include components such as a power supply component 30e. If the computer device is the computer device on the side of the ODD data requester, it may further include components such as an audio component 30f. Figure 3 Only some components are schematically shown, which does not mean that the computer device must include Figure 3 all the components shown, nor does it mean that the computer device can only include Figure 3 the components shown.

[0217] The computer device provided in this embodiment can obtain the rule configuration information provided by the ODD data requester; parse the rule configuration information to obtain the ODD conditions expressed by the rule configuration information; and generate ODD data based at least on the ODD conditions expressed by the rule configuration information. Since the generated ODD data is generated based on the rule configuration information provided by the ODD data requester, the customization of ODD data by the ODD data requester can be realized, and ODD data that can meet the intelligent driving needs of different ODD data requesters can be generated, thereby meeting the needs of different intelligent driving functions.

[0218] In the embodiment of the present application, the memory is used to store computer programs and can be configured to store various other data to support operations on the device where it is located. Among them, the processor supports the computer programs stored in the memory to implement corresponding control logic. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0219] In the embodiments of the present application, the processor may be any hardware processing device that supports the above method logic. Optionally, the processor may be a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), or a Microcontroller Unit (MCU); it may also be a programmable device such as a Field-Programmable Gate Array (FPGA), a Programmable Array Logic (PAL), a General Array Logic (GAL), or a Complex Programmable Logic Device (CPLD); or it may be an Advanced RISC Machines (ARM) or a System on Chip (SOC), etc., but not limited thereto.

[0220] In the embodiments of the present application, the communication component is configured to facilitate communication between the device where it is located and other devices in a wired or wireless manner. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G, 5G, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component can also be implemented based on technologies such as Near Field Communication (NFC) technology, Radio Frequency Identification (RFID) technology, Infrared Data Association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, or other technologies.

[0221] In the embodiments of the present application, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can sense not only the boundaries of touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operation.

[0222] In the embodiments of the present application, the power supply component is configured to provide power to various components of the device where it is located. The power supply component may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the device where the power supply component is located.

[0223] In the embodiments of the present application, the audio component may be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC). When the device where the audio component is located is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive external audio signals. The received audio signals may be further stored in a memory or sent via a communication component. In some embodiments, the audio component further includes a speaker for outputting audio signals. For example, for a device with a language interaction function, voice interaction with the user can be implemented through the audio component and the like.

[0224] Figure 4 It is a schematic structural diagram of the data processing device provided by the embodiments of the present application. As Figure 4 shown, the data processing device includes: an acquisition module 40a, an analysis module 40b, and a generation module 40c.

[0225] The acquisition module 40a is configured to acquire rule configuration information provided by a requester of target operating design domain (ODD) data.

[0226] The analysis module 40b is configured to analyze the rule configuration information to determine the ODD conditions expressed by the rule configuration information.

[0227] The generation module 40c is configured to generate target ODD data at least based on the ODD conditions.

[0228] In some embodiments, the rule configuration information includes: a plurality of rule configuration items and the rule configuration information corresponding to the plurality of rule configuration items. When analyzing the rule configuration information, the analysis module 40b is specifically configured to: parse out the configurable parameter values corresponding to the rule configuration items from the rule configuration information corresponding to the rule configuration items; determine the ODD conditions corresponding to the rule configuration items at least according to the configurable parameter values corresponding to the rule configuration items; and perform a fusion calculation on the ODD conditions corresponding to the rule configuration items to determine the ODD conditions expressed by the rule configuration information corresponding to the rule configuration items.

[0229] Optionally, when performing a fusion calculation on the ODD conditions corresponding to the rule configuration items, the analysis module 40b is specifically configured to: obtain the ODD conditions of the same dimension from the ODD conditions corresponding to the rule configuration items; calculate the intersection ODD conditions of the ODD conditions of the same dimension; and determine the union of the intersection ODD conditions of all dimensions as the ODD conditions expressed by the rule configuration information of the plurality of rule configuration items.

[0230] In some other embodiments, the rule configuration items include: static rule configuration items and dynamic rule configuration items. When the parsing module 40b performs a fusion calculation on the ODD conditions corresponding to the rule configuration items, it is specifically configured to: obtain the ODD conditions corresponding to the static rule configuration items and the dynamic rule configuration items respectively from the ODD conditions corresponding to multiple rule configuration items; perform a fusion calculation on the ODD conditions corresponding to the static rule configuration items to determine the ODD conditions corresponding to the static rule configuration items; and use the ODD conditions corresponding to the dynamic rule configuration items as the ODD conditions corresponding to the dynamic rule configuration items.

[0231] Correspondingly, when the generation module 40c generates the target ODD data, it is specifically configured to: generate static ODD data corresponding to the static rule configuration items based at least on the ODD conditions corresponding to the static rule configuration items; and generate dynamic ODD data corresponding to the dynamic rule configuration items based at least on the ODD conditions corresponding to the dynamic rule configuration items.

[0232] In some embodiments, the configurable parameter values corresponding to the static rule configuration items include: road network condition parameter values and the first driving mode supported by the road network condition parameter values. When the parsing module 40b determines the ODD conditions corresponding to the rule configuration items, it is specifically configured to: determine a first target area that supports the first driving mode according to the road network condition parameter values; and use the first target area and the first driving mode as the ODD conditions corresponding to the static rule configuration items.

[0233] Correspondingly, when the generation module 40c generates the static ODD data, it is specifically configured to: use at least the geographical location information of the first target area and the identifier of the first driving mode as the static ODD data.

[0234] Optionally, the road network condition parameter values include: a target road network element as a reference object and a distance range from the reference object. When the parsing module 40b determines the first target area that supports the first driving mode, it is specifically configured to: obtain the topological relationship of the road network; determine the geographical location information of the target road network elements included in the road network according to the topological relationship of the road network and the target road network element as the reference object; determine a target road segment whose distance from the target road network elements included in the road network is within the distance range according to the geographical location information of the target road network elements included in the road network and the topological relationship of the road network; and determine that the target road segment is the first target area that supports the first driving mode.

[0235] Optionally, the road network condition parameter values include: regional attributes. When the parsing module 40b determines the first target area that supports the first driving mode, it is specifically configured to: obtain a first area whose attribute in the map data is the regional attribute in the road network condition parameter values; and determine that the first area is the first target area that supports the first driving mode.

[0236] In some other embodiments, the configurable parameter values corresponding to the static rule configuration items include: driving conditions and the second driving mode supported corresponding to the driving conditions. When determining the ODD conditions corresponding to the rule configuration items, the parsing module 40b is specifically configured to: determine the target driving conditions supporting intelligent driving according to the driving conditions and the second driving mode; and determine that the target driving conditions are the ODD conditions corresponding to the static rule configuration items. Correspondingly, when generating the static ODD data, the generating module 40c is specifically configured to: use at least the target driving conditions and the driving mode identifier corresponding to intelligent driving as the static ODD data.

[0237] In still some other embodiments, the configurable parameter values corresponding to the dynamic rule configuration items include: traffic condition parameter values and the third driving mode supported corresponding to the traffic condition parameter values. When determining the ODD conditions corresponding to the rule configuration items, the parsing module 40b is specifically configured to: obtain the real-time traffic conditions of the road network; determine the sections where the real-time traffic conditions match the traffic condition parameter values according to the real-time traffic conditions of the road network and the traffic condition parameter values, as the second target areas that support the third driving mode; and determine that the second target areas are the ODD conditions corresponding to the dynamic rule configuration items.

[0238] Optionally, the configurable parameter values corresponding to the dynamic rule configuration items include: weather condition parameter values and the fourth driving mode supported corresponding to the weather parameter values. When determining the ODD conditions corresponding to the rule configuration items, the parsing module 40b is specifically configured to: obtain the real-time weather conditions of the corresponding area of the road network; determine the areas where the real-time weather conditions match the weather condition parameter values according to the real-time weather conditions of the corresponding area of the road network and the weather condition parameter values, as the third target areas that support the fourth driving mode; determine that the third target areas are the ODD conditions corresponding to the dynamic rule configuration items.

[0239] In the embodiments of the present application, as Figure 4 shown, the data processing device may further include: a verification module 40d. The verification module 40d is configured to: perform statistical analysis on the target ODD data to obtain the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data; verify the target ODD data at least according to the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data, to obtain a verification result.

[0240] Optionally, when verifying the target ODD data, the verification module 40d is specifically configured to: perform statistical analysis on the topological relationship of the road network to obtain the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network; verify the accuracy of the target ODD data according to the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data and the parameter values corresponding to the continuous statistical parameters reflected by the topological relationship of the road network, to obtain the accuracy verification result of the target ODD data.

[0241] The data processing device provided in this embodiment can obtain the rule configuration information provided by the ODD data requester; and parse the rule configuration information to obtain the ODD conditions expressed by the rule configuration information; and generate ODD data based at least on the ODD conditions expressed by the rule configuration information. Since the generated ODD data is generated based on the rule configuration information provided by the ODD data requester, therefore, the customization of ODD data by the ODD data requester can be realized, and ODD data that can meet the intelligent driving needs of different ODD data requesters can be generated, and further the needs of different intelligent driving functions can be met.

[0242] It should be noted that the descriptions such as "first" and "second" in this article are used to distinguish different messages, devices, modules, etc., and do not represent the order, nor do they limit that "first" and "second" are of different types.

[0243] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0244] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be realized by computer program instructions, and the combination of the processes and / or blocks in the flowchart and / or block diagram can also be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in one or more processes in the flowchart and / or one or more blocks in the block diagram.

[0245] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in one or more processes in the flowchart and / or one or more blocks in the block diagram.

[0246] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are executed on the computer or other programmable apparatus to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process or multiple processes in the flowchart and / or one block or multiple blocks in the block diagram.

[0247] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0248] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.

[0249] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology for information storage. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0250] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising a..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0251] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various modifications and changes can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A data processing method, wherein, Including: Obtaining rule configuration information provided by a requester for target Operational Design Domain (ODD) data; wherein, the rule configuration information refers to rules or conditions that can reflect the limitations for supporting or not supporting intelligent driving functions; the rule configuration information includes: a plurality of rule configuration items and the rule configuration information corresponding to the plurality of rule configuration items; Parsing, from the rule configuration information corresponding to the rule configuration item, the configurable parameter value corresponding to the rule configuration item; Determining, at least based on the configurable parameter value corresponding to the rule configuration item, the ODD condition corresponding to the rule configuration item; Performing a fusion calculation on the ODD conditions corresponding to the rule configuration item to determine the ODD condition expressed by the rule configuration information corresponding to the rule configuration item; Generating target ODD data, at least based on the ODD condition; Providing the target ODD data to the requester.

2. The method according to claim 1, wherein The performing a fusion calculation on the ODD conditions corresponding to the rule configuration item includes: Obtaining the ODD conditions of the same dimension from the ODD conditions corresponding to the rule configuration item; calculating the intersection ODD condition of the ODD conditions of the same dimension; Determining the union of the intersection ODD conditions of all dimensions as the ODD condition expressed by the rule configuration information of the plurality of rule configuration items.

3. The method according to claim 1, wherein, The rule configuration item includes: a static rule configuration item and a dynamic rule configuration item; the performing a fusion calculation on the ODD conditions corresponding to the rule configuration item includes: Obtaining the ODD conditions corresponding to the static rule configuration item and the dynamic rule configuration item respectively from the ODD conditions corresponding to the plurality of rule configuration items; Performing a fusion calculation on the ODD conditions corresponding to the static rule configuration item to determine the ODD condition corresponding to the static rule configuration item; Taking the ODD condition corresponding to the dynamic rule configuration item as the ODD condition corresponding to the dynamic rule configuration item.

4. The method according to claim 3, wherein, The generating the target ODD data, at least based on the ODD condition, includes: Generating the static ODD data corresponding to the static rule configuration item, at least based on the ODD condition corresponding to the static rule configuration item; Generating the dynamic ODD data corresponding to the dynamic rule configuration item, at least based on the ODD condition corresponding to the dynamic rule configuration item.

5. The method according to claim 4, wherein, The configurable parameter value corresponding to the static rule configuration item includes: a road network condition parameter value and a first driving mode supported by the road network condition parameter value; The determining, at least based on the configurable parameter value corresponding to the rule configuration item, the ODD condition corresponding to the rule configuration item includes: Determining, according to the road network condition parameter value, a first target area that supports the first driving mode; taking the first target area and the first driving mode as the ODD condition corresponding to the static rule configuration item; The generating the static ODD data, at least based on the ODD condition corresponding to the static rule configuration item, includes: Taking at least the geographical location information of the first target area and the identifier of the first driving mode as the static ODD data.

6. The method according to claim 5, wherein The road network condition parameter value includes: a target road network element as a reference and a distance range from the reference; the method further includes: Obtain the topological relationship of the road network; The determining the first target area that supports the first driving mode according to the road network condition parameter values includes: Determine the geographical location information of the target road network elements included in the road network according to the topological relationship of the road network and the target road network elements used as references; Determine the target road segments whose distances from the target road network elements included in the road network are within the distance range according to the geographical location information of the target road network elements included in the road network and the topological relationship of the road network; Determine that the target road segments are the first target area that supports the first driving mode.

7. The method according to claim 5, wherein, The road network condition parameter values include: regional attributes; the determining the first target area that supports the first driving mode according to the road network condition parameter values includes: Obtain the first area with the regional attribute in the road network condition parameter values from the map data; Determine that the first area is the first target area that supports the first driving mode.

8. The method according to claim 4, wherein The configurable parameter values corresponding to the static rule configuration items include: driving conditions and the second driving mode supported by the driving conditions; The determining the ODD conditions corresponding to the rule configuration items according to at least the configurable parameter values corresponding to the rule configuration items includes: Determine the target driving conditions that support intelligent driving according to the driving conditions and the second driving mode; and determine that the target driving conditions are the ODD conditions corresponding to the static rule configuration items; The generating the static ODD data based at least on the ODD conditions corresponding to the static rule configuration items includes: At least use the target driving conditions and the driving mode identifier corresponding to intelligent driving as the static ODD data.

9. The method according to claim 4, wherein The configurable parameter values corresponding to the dynamic rule configuration items include: traffic condition parameter values and the third driving mode supported by the traffic condition parameter values; the determining the ODD conditions corresponding to the rule configuration items according to at least the configurable parameter values corresponding to the rule configuration items includes: Obtain the real-time traffic conditions of the road network; Determine the road segments where the real-time traffic conditions match the traffic condition parameter values according to the real-time traffic conditions of the road network and the traffic condition parameter values, as the second target area that can support the third driving mode; Determine that the second target area is the ODD conditions corresponding to the dynamic rule configuration items.

10. The method according to claim 4, wherein, The configurable parameter values corresponding to the dynamic rule configuration items include: weather condition parameter values and the fourth driving mode supported by the weather condition parameter values; the determining the ODD conditions corresponding to the rule configuration items according to at least the configurable parameter values corresponding to the rule configuration items includes: Obtain the real-time weather conditions of the corresponding area of the road network; Determine the area where the real-time weather conditions match the weather condition parameter values according to the real-time weather conditions of the corresponding area of the road network and the weather condition parameter values, as the third target area that supports the fourth driving mode; Determine that the third target area is the ODD conditions corresponding to the dynamic rule configuration items.

11. The method according to claim 1, wherein, It also includes: Conduct statistical analysis on the target ODD data to obtain the parameter values corresponding to the continuous statistical parameters reflected by the target ODD data; The continuous statistical parameter refers to a parameter that requires continuous statistics. Verify the target ODD data at least according to the parameter value corresponding to the continuous statistical parameter reflected by the target ODD data to obtain a verification result. Verifying the target ODD data includes: verifying the accuracy and rationality of the target ODD data.

12. The method according to claim 11, wherein, It also includes: Statistically analyze the topological relationship of the road network to obtain the parameter value corresponding to the continuous statistical parameter reflected by the topological relationship of the road network. The step of verifying the target ODD data at least according to the parameter value corresponding to the continuous statistical parameter reflected by the target ODD data to obtain a verification result further includes: Verify the accuracy of the target ODD data according to the parameter value corresponding to the continuous statistical parameter reflected by the target ODD data and the parameter value corresponding to the continuous statistical parameter reflected by the topological relationship of the road network to obtain the accuracy verification result of the target ODD data.

13. A data processing device, wherein, It includes: An acquisition module, configured to acquire rule configuration information provided by a requester of target Operational Design Domain (ODD) data; wherein, the rule configuration information refers to rules or conditions that can reflect the limitation of supporting or not supporting intelligent driving functions; the rule configuration information includes: a plurality of rule configuration items and the rule configuration information corresponding to the plurality of rule configuration items. An analysis module, configured to parse out the configurable parameter value corresponding to the rule configuration item from the rule configuration information corresponding to the rule configuration item; determine the ODD condition corresponding to the rule configuration item at least according to the configurable parameter value corresponding to the rule configuration item; perform a fusion calculation on the ODD conditions corresponding to the rule configuration items to determine the ODD condition expressed by the rule configuration information corresponding to the rule configuration item. A generation module, configured to generate target ODD data at least based on the ODD condition and provide the target ODD data to the requester.

Images