Scene priority determination method and apparatus

Abstract

A scene priority determination method and apparatus. The method comprises: acquiring preset priorities of a plurality of scene features (S201); acquiring evaluation information for a driving scene, wherein the evaluation information for the driving scene is used for describing the priorities of the plurality of scene features in the driving scene (S202); and on the basis of the preset priorities of the plurality of scene features and a plurality of pieces of evaluation information for a plurality of driving scenes, determining the priorities of the plurality of driving scenes (S203). Therefore, the accuracy of the evaluated priority for a driving scene can be improved.

Description

A method and device for determining scene priority

[0001] This application claims priority to the Chinese patent application filed with the China National Intellectual Property Administration on August 15, 2023, with application number 202311035386.5 and application name “A Method and Device for Determining Scenario Priority”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of intelligent driving, and in particular to a method and device for determining scene priority. Background Art

[0003] Scenario prioritization is crucial for driving scenario testing. Accurately assessing scenario prioritization can improve testing efficiency while reducing testing resources and costs. Currently, scenario prioritization is simply determined by multiplying multiple quantifiable metrics, resulting in inaccurate scenario prioritization.

[0004] Summary of the Invention

[0005] The present application discloses a method and device for determining scene priority, which can improve the accuracy of the priority of evaluated driving scenes.

[0006] In a first aspect, the present application provides a method for determining scene priorities, the method comprising: obtaining evaluation information of a driving scene, wherein the evaluation information of the driving scene is used to describe the priority of multiple scene features in the driving scene; determining the priorities of the M driving scenes based on the preset priorities of the multiple scene features and M evaluation information of the M driving scenes, where M is an integer greater than 1.

[0007] Exemplarily, scene features may also be referred to as scene assessment criteria, scene evaluation criteria, or scene evaluation parameters.

[0008] Here, the priority of a scene feature in a driving scenario represents the importance of the scene feature within the classification category of that driving scenario. It is understood that the priority of the same scene feature may vary in different driving scenarios. Furthermore, different scene features are assigned different classification categories. The classification category of a scene feature allows for a more refined characterization of the driving scenario.

[0009] Here, the preset priority of a scene feature is used to indicate the importance of the scene feature among the multiple scene features mentioned above. The preset priority of a scene feature is independent of the driving scenario, that is, the preset priority of a scene feature remains unchanged in different driving scenarios. The preset priority of a scene feature can be used to understand the importance ranking of the multiple scene features mentioned above.

[0010] Here, a driving scenario is understood to be, for example, the environment in which the vehicle is located, which may include one or more of the following information: road type, weather conditions, traffic conditions, driving task, etc. Typical driving scenarios may include, for example, a vehicle cutting in, a vehicle cutting out, a vehicle following, or a preceding vehicle braking.

[0011] Here, the M evaluation information for the M driving scenarios means that each driving scenario corresponds to one piece of evaluation information, so there are M evaluation information for the M driving scenarios in total.

[0012] In the above method, the importance ranking among multiple scene features is indicated by the preset priorities of these multiple scene features. The priorities of these multiple scene features in different driving scenarios can be used to more finely characterize different driving scenarios. In this way, the priorities of multiple driving scenarios are comprehensively determined from the two dimensions of the preset priorities of the scene features and the priorities of the scene features in the driving scenarios, which can improve the evaluation accuracy of the priorities of the driving scenarios.

[0013] For example, in the driving scenario assessment information, the priorities of the multiple scenario features for the driving scenario are arranged according to the relative order of their preset priorities. In this way, the driving scenario assessment information not only describes the priorities of the multiple scenario features for the driving scenario but also indicates the relative order of their preset priorities by specifying the order in which they are arranged. This helps improve the efficiency of driving scenario priority assessment.

[0014] Optionally, the method further includes: selecting N driving scenarios from the M driving scenarios for testing using the priorities of the M driving scenarios, where N is a positive integer less than M.

[0015] By implementing the above approach, a subset of driving scenarios can be selected for testing based on their priority, improving the effectiveness of driving scenario testing. Furthermore, the priority of each driving scenario can influence the order of testing; higher-priority driving scenarios are tested first, saving testing resources and costs.

[0016] Optionally, the method further includes: when the test results of the N driving scenarios do not meet the test objectives, adjusting the preset priorities of the multiple scenario features according to the test results of the N driving scenarios.

[0017] Exemplarily, adjusting the preset priorities of the plurality of scene features based on the test result may include adjusting the preset priorities of some or all of the plurality of scene features based on the test result.

[0018] Exemplarily, the test target is related to the number of scenario features involved in evaluating the scenario priority. The test target includes sub-test targets corresponding to each scenario feature in the plurality of scenario features.

[0019] For example, the above-mentioned multiple scene features include scene feature 1, scene feature 2 and scene feature 3, wherein the preset priorities of these multiple scene features are arranged from high to low as follows: scene feature 1>scene feature 2>scene feature 3. Taking the test results of the above-mentioned N driving scenes as an example where the test results do not meet the sub-test target corresponding to scene feature 3 in the above-mentioned test target, in this case, adjusting the preset priorities of these multiple scene features according to the test results can be: raising the preset priority of scene feature 3 among these multiple scene features according to the test results.

[0020] By implementing the above implementation method, the preset priorities of multiple scenario features participating in the scenario priority evaluation are adjusted through test result feedback to change the importance ranking between at least two scenario features, so that the test results of the driving scenario can be more in line with the test objectives.

[0021] Optionally, the multiple scene features include the following: scene complexity, scene danger, scene exposure, scene rationality and scene accuracy.

[0022] For example, the scenario hazard describes the possible impact on the safety of traffic participants and passengers of the autonomous driving system; the scenario exposure is used to describe the frequency of occurrence or appearance of driving scenarios; the scenario complexity is used to describe the degree of difficulty caused by various scenario attributes that may affect the driving task of the autonomous driving system (such as the behavior of participating road users, defined road infrastructure and environmental conditions, etc.); the scenario rationality is used to describe the degree of conformity between the scenario parameter data of the driving scenario used in the simulation test and the real physical world; the scenario accuracy is used to describe the degree of fit or similarity between the scenario extracted based on driving data and the actual scenario.

[0023] Optionally, the preset priorities of the multiple scene features are set based on the confidence levels of the multiple scene features or historical testing experience.

[0024] For example, the higher the confidence level of a scene feature, the higher the preset priority level of the scene feature can be set. In addition, historical test experience can indicate the setting of the preset priority level of each scene feature corresponding to a smaller number of test results. In another implementation, the preset priority levels of multiple scene features can also be set based on multiple factors including the confidence level of the scene feature, historical test experience (or prior experience), and user wishes, which are not specifically limited here.

[0025] By implementing the above implementation method, the preset priority of the scene features is taken into consideration when evaluating the priority of the driving scene, which is conducive to improving the evaluation accuracy of the scene priority.

[0026] Optionally, the multiple scene features include a first feature and a second feature, wherein a preset priority of the first feature is higher than a preset priority of the second feature; the M driving scenes include a first driving scene and a second driving scene, and the priority of the first driving scene and the priority of the second driving scene satisfy any of the following conditions:

[0027] If the priority of the first feature in the first driving scenario is higher than the priority of the first feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or,

[0028] If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is higher than the priority of the second feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or

[0029] If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is the same as the priority of the second feature in the second driving scenario, the priority of the first driving scenario is the same as the priority of the second driving scenario.

[0030] That is to say, the priority of each driving scene can be determined in descending order according to the preset priority of the scene features. Assuming that the preset priority of scene feature 1 is the highest, the preset priority of scene feature 2 is the second highest, and the preset priority of scene feature 3 is the lowest, and the total number of driving scenes is M, where M is an integer greater than 1, then the priorities of scene feature 1 in these M driving scenes are first compared in sequence, and the higher the priority of scene feature 1 in the driving scene, the higher the priority of the driving scene; if the priorities of scene feature 1 in P driving scenes in the M driving scenes are the same, where P is a positive integer less than M, then the priorities of scene feature 2 in these P driving scenes are compared in sequence, and the higher the priority of scene feature 2 in the driving scene, the higher the priority of the driving scene; if the priorities of scene feature 2 in L driving scenes in the P driving scenes are the same, where L is a positive integer less than P, then the priorities of scene feature 3 in these L driving scenes are compared in sequence, and the higher the priority of scene feature 3 in the driving scene, the higher the priority of the driving scene.

[0031] By implementing the above implementation method, the priorities of the corresponding scene features in each driving scenario are compared in order from high to low according to the preset priorities of the scene features to determine the priority of each driving scenario, thereby improving the accuracy of the priority of the evaluated driving scenario.

[0032] Optionally, the total number of the multiple scene features is S, the preset priority of the i-th scene feature is greater than the preset priority of the i+1-th scene feature, i is an integer greater than or equal to 1 and less than S, and the priorities of the M driving scenes are determined according to the preset priorities of the multiple scene features and the M evaluation information of the M driving scenes, including: performing statistics on the preset priorities of the multiple scene features and the M evaluation information through a sorting function to determine the priorities of the M driving scenes; wherein the sorting function is the sum of S parts, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, and the value of each coefficient in the sorting function satisfies the following constraint: the minimum value of the i-th part is greater than the maximum value of the sum of the i+1-th part, the i+2-th part, ...., the S-th part among the S parts.

[0033] In one implementation, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, which means that the i-th part is the product of the i-th coefficient and the priority of the i-th scene feature in the driving scene.

[0034] In another implementation, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, which means that the i-th part is represented as a function with the i-th coefficient as the base and the priority of the i-th scene feature in the driving scene as the exponent.

[0035] It can be understood that the evaluation information of the driving scene is substituted into the above ranking function to obtain the ranking function value corresponding to the driving scene. The larger the ranking function value corresponding to the driving scene, the higher the priority of the driving scene.

[0036] By implementing the above implementation method, by defining the ranking function, the ranking function value corresponding to each driving scenario can be quickly calculated, and the sizes of the ranking function values ​​corresponding to each driving scenario can be compared to determine the priority of each driving scenario. This not only improves the evaluation accuracy of the scenario priority, but also improves the evaluation efficiency of the scenario priority.

[0037] Optionally, the preset priorities of the multiple scene features are user input.

[0038] When the above implementation is implemented, a manual interaction interface may be provided to the user, so that the user can set preset priorities for each of the multiple scene features through the manual interaction interface.

[0039] In a second aspect, the present application provides a device for determining scene priorities, the device comprising: an acquisition unit for acquiring evaluation information of a driving scene, wherein the evaluation information of the driving scene is used to describe the priority of multiple scene features under the driving scene; a processing unit for determining the priority of the M driving scenes based on the preset priorities of the multiple scene features and M evaluation information of the M driving scenes, where M is an integer greater than 1.

[0040] Optionally, in the evaluation information of the driving scene, the priorities of the multiple scene features in the driving scene are arranged according to the size relationship between the preset priorities of the multiple scene features.

[0041] Optionally, the device further includes a testing unit, configured to select N driving scenarios from the M driving scenarios for testing using the priorities of the M driving scenarios, where N is a positive integer less than M.

[0042] Optionally, the testing unit is further configured to: when the test results of the N driving scenarios do not meet the test objectives, adjust the preset priorities of the multiple scenario features according to the test results of the N driving scenarios.

[0043] Optionally, the multiple scene features include the following: scene complexity, scene danger, scene exposure, scene rationality and scene accuracy.

[0044] Optionally, the preset priorities of the multiple scene features are set based on the confidence levels of the multiple scene features or historical testing experience.

[0045] Optionally, the multiple scene features include a first feature and a second feature, wherein a preset priority of the first feature is higher than a preset priority of the second feature; the M driving scenes include a first driving scene and a second driving scene, and the priority of the first driving scene and the priority of the second driving scene satisfy any of the following conditions:

[0046] If the priority of the first feature in the first driving scenario is higher than the priority of the first feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or,

[0047] If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is higher than the priority of the second feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or

[0048] If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is the same as the priority of the second feature in the second driving scenario, the priority of the first driving scenario is the same as the priority of the second driving scenario.

[0049] Optionally, the total number of the multiple scene features is S, the preset priority of the i-th scene feature is greater than the preset priority of the i+1-th scene feature, i is an integer greater than or equal to 1 and less than S, and the processing unit is specifically used to: perform statistics on the preset priorities of the multiple scene features and the M evaluation information through a sorting function to determine the priorities of the M driving scenes; wherein the sorting function is the sum of S parts, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, and the value of each coefficient in the sorting function satisfies the following constraints: the minimum value of the i-th part is greater than the maximum value of the sum of the i+1-th part, the i+2-th part, ...., the S-th part in the S parts.

[0050] Optionally, the preset priorities of the multiple scene features are user input.

[0051] In a third aspect, the present application provides a device for determining scene priority, the device comprising a processor and a memory, wherein the memory is used to store program instructions; the processor calls the program instructions in the memory so that the device executes the method in the first aspect or any possible implementation of the first aspect.

[0052] In a fourth aspect, the present application provides a computer-readable storage medium comprising computer instructions, which, when executed by a processor, implement the method in the above-mentioned first aspect or any possible implementation of the first aspect.

[0053] In a fifth aspect, the present application provides a computer program product that, when executed by a processor, implements the method described in the first aspect or any possible embodiment of the first aspect. The computer program product, for example, may be a software installation package. When the method provided in any possible design of the first aspect is required, the computer program product may be downloaded and executed on a processor to implement the method described in the first aspect or any possible embodiment of the first aspect.

[0054] The technical effects of the second to fifth aspects mentioned above can be referred to the description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] FIG1 is a schematic diagram of the architecture of a priority determination device provided in an embodiment of the present application;

[0056] FIG2 is a flowchart of a method for determining scene priority provided by an embodiment of the present application;

[0057] FIG3 is a schematic diagram of a manual interaction interface provided in an embodiment of the present application;

[0058] FIG4 is a schematic diagram of a process for determining priorities of multiple driving scenarios provided by an embodiment of the present application;

[0059] FIG5 is a schematic diagram of a process for determining the priorities of multiple driving scenarios according to another embodiment of the present application;

[0060] FIG6 is a flowchart of another method for determining scene priority provided in an embodiment of the present application;

[0061] FIG7 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0062] It should be noted that the prefixes such as "first" and "second" used in this application are only for distinguishing different description objects, and do not have any limiting effect on the position, order, priority, quantity or content of the described objects. For example, if the described object is a "field", then the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields", and "first" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the described object is a "level", then the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of described objects is not limited by the prefix and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the described object is a "device," then the "first device" and the "second device" can be the same device, the same type of device, or different types of devices. For another example, if the described object is "information," then the "first information" and the "second information" can be information of the same content or information of different contents. In short, the use of prefixes to distinguish the described objects in the embodiments of this application does not constitute a limitation on the described objects. For the description of the described objects, please refer to the description in the context of the claims or embodiments, and the use of such prefixes should not constitute an unnecessary limitation.

[0063] It should be noted that the descriptions used in the embodiments of the present application, such as "at least one of a1, a2, ..., and an" and the like, include any one of a1, a2, ..., and an existing alone, and any combination of any multiple of a1, a2, ..., and an, each of which can exist alone. For example, the description "at least one of a, b, and c" includes a alone, b alone, c alone, a combination of a and b, a combination of a and c, a combination of b and c, or a combination of ab and c.

[0064] The technical solution in this application will be described below with reference to the accompanying drawings.

[0065] Referring to FIG. 1 , FIG. 1 is a schematic diagram of the structure of a priority determination device provided in an embodiment of the present application. The priority determination device is used to determine the priority of a driving scenario. As shown in FIG. 1 , the priority determination device includes an acquisition unit and an output unit, wherein the acquisition unit and the output unit can communicate wirelessly or wiredly. The priority determination device can be implemented using hardware, software, or a combination of hardware and software.

[0066] Exemplarily, the acquisition unit is used to obtain evaluation information of the driving scene, where the evaluation information of the driving scene is used to describe the priority of multiple scene features in the driving scene; the processing unit is used to determine the priority of the M driving scenes based on the preset priorities of the multiple scene features and M evaluation information of the M driving scenes, where M is an integer greater than 1.

[0067] Here, a driving scenario can be understood as, for example, the environment in which the vehicle is located, which includes one or more of the following information: road type, weather conditions, traffic conditions, driving task, etc. Typical driving scenarios may include, for example, a vehicle cut-in scenario, a vehicle cut-out scenario, a vehicle following scenario, or a preceding vehicle braking scenario.

[0068] Here, the scene feature may also be referred to as a scene assessment criterion, a scene evaluation criterion, or a scene evaluation parameter.

[0069] Here, the priority of the scene feature in the driving scene can also be called the sub-priority of the scene feature. For the convenience of description, the sub-priority of the scene feature below represents the priority of the scene feature in the driving scene.

[0070] As can be seen, the sub-priority of a scene feature is related to the driving scenario. For the same scene feature, the sub-priority of that scene feature may vary in different driving scenarios. However, the preset priority of a scene feature is independent of the driving scenario; the preset priority of the same scene feature is the same in different driving scenarios. For details on the sub-priority and preset priority of scene features, please refer to the relevant descriptions of the following embodiments. For the sake of brevity, we will not elaborate on them here.

[0071] Exemplarily, the priority determination device may be a network-side device. The network-side device may be, for example, a server deployed on the network side (e.g., a scenario priority assessment server, a simulation test server, etc.), or a component or chip in the server, or a system-level device composed of multiple servers. The network-side device may be deployed in a cloud environment or an edge environment, and is not specifically limited here.

[0072] For example, the scenario priority determination method provided in the embodiments of the present application can be applied not only to autonomous driving simulation systems, but also to other simulation test systems that require scenario priority, such as model-in-the-loop test systems, hardware-in-the-loop test systems, etc.

[0073] Here, "autonomous driving" is not limited to fully autonomous driving systems, highly autonomous driving systems, conditional autonomous driving systems, or partially autonomous driving systems. Those skilled in the art can understand that non-fully manual driving systems that provide intelligent driving can be covered under this concept for simulation processing.

[0074] It should be noted that Figure 1 is only an exemplary architectural diagram of a priority determination device, but does not limit the priority determination device to the form shown in Figure 1. The structural diagram of the priority determination device may also include more or fewer units than those shown in Figure 1. In addition, the method provided in the embodiment of the present application can be applied to the priority determination device shown in Figure 1. Of course, the method provided in the embodiment of the present application can also be applied to other priority determination devices, and the embodiment of the present application is not limited to this.

[0075] Before introducing the scene priority determination method provided in the embodiment of the present application, it is necessary to first determine multiple scene features for evaluating scene priorities.

[0076] In one implementation, the multiple scenario features involved in scenario priority assessment can be obtained from scenario features defined by industry standards and / or expert experience. For example, the multiple scenario features involved in scenario priority assessment can be screened from scenario features defined by industry standards and / or expert experience based on the confidence level of the scenario features, or can be customized by the tester. It is understood that the above-mentioned multiple scenario features are pre-set.

[0077] For example, the scenario characteristics defined by industry standards include scenario criticality, scenario exposure, and scenario complexity. Scenario criticality is used to describe the potential impact on the safety of traffic participants and passengers of the automated driving system, scenario exposure is used to describe the frequency or occurrence of driving scenarios, and scenario complexity is used to describe the degree of difficulty caused by various scenario attributes (such as the behavior of participating road users, defined road infrastructure, and environmental conditions) that may affect the automated driving system's driving task.

[0078] For example, for simulation tests, the scenario features defined by expert experience also include scenario rationality and scenario accuracy, where scenario rationality is used to describe the degree of conformity between the scenario parameter data of the driving scenario used in the simulation test and the real physical world, and scenario accuracy is used to describe the degree of fit or similarity between the scenario extracted based on driving data and the actual scenario.

[0079] Here, the number of multiple scene features participating in scene priority evaluation is not limited, for example, it can be 2, 3, 4 or more.

[0080] The following introduces two priorities of scene features defined in the embodiments of the present application: the preset priority of scene features and the sub-priority of scene features.

[0081] (1) Preset priority of scene features

[0082] Exemplarily, the preset priority of a scene feature may also be referred to as the block priority of the scene feature.

[0083] The preset priority of a scene feature is used to indicate the importance of the scene feature among the above-mentioned multiple scene features, and the higher the importance of the scene feature among the above-mentioned multiple scene features, the higher the preset priority of the scene feature.

[0084] For example, multiple scene features include scene feature 1, scene feature 2, and scene feature 3. Assuming that the preset priority of scene feature 1 is higher than the preset priority of scene feature 2, and the preset priority of scene feature 2 is higher than the preset priority of scene feature 3, it means that the importance of these three scene features is as follows, from high to low: scene feature 1 > scene feature 2 > scene feature 3. It can be seen that the importance ranking among the multiple scene features involved in evaluating the scene priority can be known through the preset priority, that is, the impact of each scene feature on the scene evaluation is considered from the dimension of the scene feature dimension through the preset priority, which is conducive to improving the accuracy of evaluating the scene priority.

[0085] In one implementation, the preset priorities of the above-mentioned multiple scene features are set based on the confidence of the scene features or historical testing experience, or can be defined by the user based on the test objectives or his own wishes, which is not specifically limited here.

[0086] Taking multiple scene features including scene complexity, scene danger and scene exposure as an example, illustratively, when it can be determined based on historical testing experience or prior experience that safety is given priority and test complexity is given secondarily, the preset priority of scene danger can be set to be higher than the preset priority of scene complexity and the preset priority of scene complexity can be set to be higher than the preset priority of scene exposure. Exemplarily, the preset priorities of multiple scene features can also be set based on user wishes in order from high to low as follows: scene danger > scene exposure > scene complexity. Exemplarily, the preset priorities of the above-mentioned multiple scene features can also be set based on the principle that the greater the confidence of a scene feature, the higher the preset priority of the scene feature. In some possible embodiments, for example, the preset priorities of multiple scene features can also be determined in combination with multiple items such as the confidence of the scene feature, user wishes, historical testing experience, etc.

[0087] (2) Sub-priority of scene features

[0088] The sub-priority of a scenario feature is the priority of the scenario feature in the driving scenario.

[0089] Here, the sub-priority level of a scene feature represents the importance of the classification category to which the scene feature belongs within the driving scenario. For any driving scenario, the higher the importance of the classification category to which the scene feature belongs within that driving scenario, the higher the sub-priority level of the scene feature. It is understood that if the same scene feature belongs to different classification categories in different driving scenarios, this also indicates that the sub-priority level of the scene feature in different driving scenarios will also be different.

[0090] For example, the classification type of the scene feature may be indicated by a numerical value or by a character.

[0091] Taking the numerical representation of classification types as an example, let's assume that the scene feature is scene danger level. Assuming that scene danger level has three classification types: essentially no danger, slightly dangerous, and very dangerous, and assuming that the higher the importance of the classification type to which the scene danger level belongs in the driving scenario, the larger the sub-priority value of the scene danger level. When the scene feature classification type is essentially no danger, the sub-priority value of the scene danger level is 1; when the scene feature classification type is slightly dangerous, the sub-priority value of the scene danger level is 2; and when the scene feature classification type is very dangerous, the sub-priority value of the scene danger level is 3. It can be seen that the sub-priority value can be further divided into the importance or impact of the same scene feature, and can more finely characterize the importance or impact of the scene feature on the assessment of different driving scenarios.

[0092] It will be appreciated that the three classification types (i.e., not dangerous, slightly dangerous, and very dangerous) for the scene dangerousness feature described above are merely an example of classification. In some possible embodiments, the scene dangerousness may also have four classification types, namely, not dangerous, slightly dangerous, moderately dangerous, and very dangerous. Furthermore, different scene features may have different numbers of classification types, and the number of classification types for each scene feature is not necessarily equal or unequal.

[0093] For example, the classification of scene features can be based on expert experience or measured data (such as motion trajectory data, traffic accident data, etc.), and quantitative methods can also be used to classify scene features, which is not specifically limited here.

[0094] See Figure 2, which is a flow chart of a method for determining scene priority provided by an embodiment of the present application. This method can be applied to the processing device shown in Figure 1. The method includes but is not limited to the following steps:

[0095] S201: Obtaining preset priorities of multiple scene features.

[0096] Here, the plurality of scene features are pre-set priorities for evaluating the driving scene. The preset priority of a scene feature is used to indicate the importance of the scene feature among the plurality of scene features.

[0097] The preset priorities of the above-mentioned driving scenarios and scenario features can be referred to the description of the corresponding contents in the above-mentioned embodiments, which will not be repeated here.

[0098] For example, the multiple scene features include but are not limited to multiple features of scene complexity, scene danger, scene exposure, scene rationality, and scene accuracy, etc. Here, the description of each scene feature can refer to the description of the corresponding scene feature in the above embodiment, and will not be repeated here.

[0099] In one implementation, obtaining the preset priorities of the plurality of scenario features includes: receiving the preset priorities of the plurality of scenario features input by a user, where the user may be, for example, a scenario tester, an autonomous driving system developer, or the like.

[0100] It is understood that obtaining the preset priorities of multiple scene features can be obtaining the values ​​of the preset priorities of multiple scene features, or can be obtaining the size relationship between the preset priorities of multiple scene features, and is not specifically limited here. When obtaining the values ​​of the preset priorities of multiple scene features, the size relationship between the preset priorities of the multiple scene features can be determined by the values ​​of the preset priorities of the multiple scene features. For example, the larger the value of the preset priority of a scene feature, the higher the preset priority of the scene feature.

[0101] Exemplarily, the preset priorities of multiple scene features input by the user may be received through any of the following methods: a touch screen, a keyboard, buttons, voice, etc.

[0102] Refer to Figure 3, which is a schematic diagram of an artificial interaction interface provided by an embodiment of the present application. As can be seen from Figure 3, Figure 3 shows a setting interface for the preset priority of scene features, which includes an input box corresponding to the number of scene features participating in the evaluation, an input box corresponding to the preset priority sorting of scene features from high to low, etc., wherein the user can define the number of scene features through the input box corresponding to the number of scene features participating in the evaluation, and can define the size relationship between the preset priorities of multiple scene features participating in the evaluation through the input box corresponding to the preset priority sorting of scene features from high to low.

[0103] It can be seen that the setting interface of the preset priority of the scene feature in Figure 3 also includes a "Clear" key and a "Confirm" key, wherein the "Clear" key indicates a request to clear the information entered by the user on the setting interface of the preset priority of the scene feature, and the "Confirm" key indicates saving the information entered by the user on the setting interface of the preset priority of the scene feature.

[0104] It can be understood that the setting interface of the preset priority of scene features in Figure 3 is only an example, and does not limit the setting interface of the preset priority of scene features to that shown in Figure 3. For example, it may contain more or less information than the current setting interface of the preset priority. For example, the input box corresponding to the number of scene features participating in the evaluation in Figure 3 can be deleted, or the input box corresponding to the scene feature and the input box corresponding to the preset priority of the scene feature can be added to the setting interface of the preset priority of the scene feature. In some possible embodiments, the input boxes corresponding to the sorting of the preset priorities of scene features from high to low can also be replaced with the input boxes corresponding to the scene features and the input boxes corresponding to the preset priorities of the scene features in the setting interface of the preset priorities of the scene features shown in Figure 3.

[0105] The manual interaction interface shown in FIG3 can be presented on a touch screen. The following is an illustrative explanation of an example in which a user inputs the preset priorities of multiple scene features through a touch screen based on FIG3. In FIG3, it is assumed that the user enters "3" in the input box corresponding to the number of scene features participating in the evaluation, and enters "scene hazard, scene exposure, scene complexity" in the input boxes corresponding to the preset priorities of the scene features from high to low, and then clicks the "Confirm" button. In this case, the control device can obtain the scene features participating in the evaluation, including scene hazard, scene exposure, and scene complexity, wherein the preset priority of scene hazard is higher than the preset priority of scene exposure, and the preset priority of scene exposure is higher than the preset priority of scene complexity.

[0106] S202: Acquire evaluation information of the driving scene, where the evaluation information of the driving scene is used to describe the priorities of the above-mentioned multiple scene features in the driving scene.

[0107] The above sub-priorities can be referred to the description of the corresponding contents of the above embodiment, which will not be repeated here.

[0108] The following scheme is illustrated using multiple scene characteristics, including scene complexity, scene danger, and scene exposure, as examples. Assume that the preset priorities of these scene characteristics are ranked from high to low as follows: scene danger > scene exposure > scene complexity. The sub-priorities of these three scene characteristics can be defined as shown in Table 1 below.

[0109] See Table 1, which shows the correspondence between scene features and sub-priority values. As can be seen from Table 1, the sub-priorities of scene danger, scene exposure, and scene complexity are all defined with four values.

[0110] For example, for the scene feature of scene exposure shown in Table 1, when the sub-priority value of scene exposure is "4", it means that the classification type of scene exposure is very high probability of occurrence; when the sub-priority value of scene exposure is "3", it means that the classification type of scene exposure is medium probability of occurrence; when the sub-priority value of scene exposure is "2", it means that the classification type of scene exposure is low probability of occurrence; when the sub-priority value of scene exposure is "1", it means that the classification type of scene exposure is basically not occurring.

[0111] For example, for the feature of scene complexity shown in Table 1, when the sub-priority value of scene complexity is "4", it indicates that the classification type of scene complexity is basically not complex; when the sub-priority value of scene complexity is "3", it indicates that the classification type of scene complexity is slightly complex; when the sub-priority value of scene complexity is "2", it indicates that the classification type of scene complexity is moderately complex; when the sub-priority value of scene complexity is "1", it indicates that the classification type of scene complexity is very complex.

[0112] In Table 1, the larger the sub-priority value of a scene feature, the higher the sub-priority of the scene feature. For example, when the sub-priority value of the scene hazard is "4", the sub-priority of the scene hazard is the highest compared to other sub-priorities of the scene hazard (e.g., "1", "2", or "3"); when the sub-priority value of the scene hazard is "1", the sub-priority of the scene hazard is the lowest compared to other sub-priorities of the scene hazard (e.g., "4", "2", or "3"); the sub-priority of a scene hazard of "moderate danger" (i.e., a sub-priority of "3") is higher than the sub-priority of a scene hazard of "slight danger" (i.e., a sub-priority of "2").

[0113] Table 1

[0114] It should be understood that Table 1 is merely intended to clearly and intuitively present the possible sub-priority classifications of scene features and does not limit the correspondence between scene features and sub-priority values ​​to that shown in Table 1. In one implementation, different scene features may correspond to different numbers of grading types. For example, the scene feature scene danger has three grading types, so the scene danger sub-priority has three values; the scene feature scene exposure has four grading types, so the scene exposure sub-priority has four values. In another implementation, the lower the sub-priority value of a scene feature, the higher the sub-priority value of that scene feature. In this case, taking scene danger as an example, if the scene danger grading type is "very dangerous," the scene danger sub-priority value is "1"; if the scene danger grading type is "moderately dangerous," the scene danger sub-priority value is "2"; if the scene danger grading type is "slightly dangerous," the scene danger sub-priority value is "3"; and if the scene danger grading type is "essentially no dangerous," the scene danger sub-priority value is "4."

[0115] In some possible embodiments, in the driving scenario evaluation information, the sub-priorities of the multiple scenario features are arranged according to the relative order of the preset priorities of the multiple scenario features. For example, the relative order of the preset priorities of the multiple scenario features may be in ascending order or in descending order of the preset priorities of the multiple scenario features.

[0116] Exemplarily, assuming that the preset priorities of multiple scene features are arranged from high to low as follows: pre-priority of scene dangerousness > pre-priority of scene exposure > pre-priority of scene complexity. Based on the definition of sub-priority of each scene feature shown in Table 1, driving scene 1 belongs to the above-mentioned M driving scenes. Assuming that the evaluation information of driving scene 1 is represented as "431", if the sub-priorities of these multiple scene features in the evaluation information of driving scene 1 are arranged in descending order of the preset priorities of these multiple scene features, it means that in driving scene 1, the sub-priority value of scene dangerousness is "4", the sub-priority value of scene exposure is "3", and the sub-priority value of scene complexity is "1"; if the sub-priorities of these multiple scene features in the evaluation information of driving scene 1 are arranged in ascending order of the preset priorities of these multiple scene features, it means that in driving scene 1, the sub-priority value of scene complexity is "4", the sub-priority value of scene exposure is "3", and the sub-priority value of scene dangerousness is "1".

[0117] In one implementation, obtaining driving scenario evaluation information includes receiving driving scenario evaluation information input by a user. It will be appreciated that the amount of driving scenario evaluation information received is related to the number of driving scenarios. Each driving scenario corresponds to one piece of evaluation information. Therefore, M driving scenarios have M pieces of evaluation information, where M is an integer greater than 1.

[0118] Here, users can be scenario testers, autonomous driving system developers, etc.

[0119] For example, the driving scene evaluation information input by the user may be received through any one of a touch screen, a keyboard, buttons, voice, and the like.

[0120] Referring to FIG3 , FIG3 is a schematic diagram of a manual interaction interface provided in an embodiment of the present application. As can be seen from FIG3 , FIG3 not only shows the setting interface for the preset priority of the scene feature (i.e., the solid box above the dotted box), but also shows the setting interface for the sub-priority of the scene feature (i.e., the priority of the scene feature in the driving scene) (i.e., the dotted box). Among them, the setting interface for the preset priority of the scene feature can refer to the description of the corresponding content in S201 above, and will not be repeated here.

[0121] In Figure 3, the sub-priority setting interface of the scene feature includes a selection box corresponding to the number of the driving scene and an input box for the priority of the corresponding scene feature under the corresponding driving scene. Among them, the number of the driving scene includes the numbers of each driving scene to be evaluated, for example, the driving scenes are numbered 1, 2, 3, ..., M. On the sub-priority setting interface of the scene feature, when the user selects the number "2" of the driving scene, it means that driving scene 2 is selected, and the input box to the right of each scene feature listed in the dotted box in Figure 3 is used to set the priority (i.e., sub-priority) of the corresponding scene feature under driving scene 2. Here, each scene feature displayed on the sub-priority setting interface of the scene feature is generated based on the settings of the user in Figure 3 on the preset priority setting interface of the scene feature shown in Figure 3.

[0122] As can be seen in Figure 3, the sub-priority setting interface for scenario features also includes a "Clear" button and a "Confirm" button. The "Clear" button requests that the user's priorities for each scenario feature set for the currently selected driving scenario be cleared, while the "Confirm" button saves the priorities set for each scenario feature set for the currently selected driving scenario. It can be understood that when the user clicks the "Confirm" button, the evaluation information for the currently selected driving scenario is generated.

[0123] The following example illustrates a user inputting driving scenario assessment information via the touch screen, using FIG3 as an example. In FIG3 , the driving user has set the driving characteristics for evaluation, including "scenario hazard, scenario exposure, and scenario complexity." For example, if the user selects driving scenario number "2," then the right side displays input boxes for the priorities of each scenario characteristic (i.e., scenario hazard, scenario exposure, and scenario complexity) for driving scenario 2. Assuming the user enters "2" in the input box corresponding to scenario hazard, "3" in the input box corresponding to scenario exposure, and "3" in the input box corresponding to scene complexity and then clicks "Confirm," evaluation information for driving scenario 2 is generated. The evaluation information for driving scenario 2 describes the priority of scenario hazard for driving scenario 2 as 2, the priority of scene exposure for driving scenario 2 as 3, and the priority of scene complexity for driving scenario 2 as 2.

[0124] It can be understood that the sub-priority setting interface of the scene feature shown in Figure 3 is only an example, and is not limited to the setting interface of the sub-priority of the scene feature as shown in Figure 3. When the number of driving scenes is multiple, for example, the sub-priority setting interface of the scene feature shown in Figure 3 may not set a number selection box for the driving scene, but directly display the input box for each driving scene and the priority of each scene feature in the corresponding driving scene, or, for example, directly set a text information import box, through which the evaluation information of at least one driving scene can be imported.

[0125] In some possible embodiments, the preset priority setting interface of the scene feature shown in FIG3 and the sub-priority setting interface of the scene feature shown in FIG3 may not be displayed on the same interface, but may be split into multiple interfaces and displayed separately.

[0126] Exemplarily, when the number of driving scenarios to be evaluated is M, based on the manual interaction interface shown in FIG3 , M evaluation information of the M driving scenarios can be obtained.

[0127] Furthermore, to improve the efficiency of subsequent priority evaluation of the M driving scenarios, a unified arrangement of the priorities of the aforementioned multiple scene features within the driving scenarios can be agreed upon in the evaluation information for different driving scenarios. For example, based on the input information shown in FIG3 , the preset priorities of the scene features are determined to be ranked from high to low as follows: scene hazard > scene exposure > scene complexity. For example, the priorities of the multiple scene features within the evaluation information for each driving scenario are arranged in descending order of their preset priorities. If the evaluation information for each driving scenario is represented by an array, the first bit from the left of the array is used to store the priority of the scene hazard for the driving scenario, the second bit from the left of the array is used to store the priority of the scene exposure for the driving scenario, and the third bit from the left of the array is used to store the priority of the scene complexity for the driving scenario. Thus, based on the input information of the priorities of the scene features for driving scenario 2 shown in FIG3 , the evaluation information for driving scenario 2 can be represented by the array "232". In this way, the evaluation information of the driving scene not only describes the priority of the above-mentioned multiple scene features in the driving scene, but also can indicate the size relationship between the preset priorities of these multiple scene features by specifying the arrangement order of the priorities of these multiple scene features in the driving scene. This is conducive to improving the evaluation efficiency of the priority of the driving scene.

[0128] S203: Determine the priorities of the M driving scenarios based on the preset priorities of the multiple scenario features and the M evaluation information of the M driving scenarios, where M is an integer greater than 1.

[0129] Exemplarily, the M evaluation information of the M driving scenarios are input by the user. For example, the user inputs the M evaluation information of the M driving scenarios based on the manual interaction interface shown in FIG3 , that is, each driving scenario corresponds to one piece of evaluation information.

[0130] Here, the preset priorities of the multiple scene features can be user historical settings or user current input. In other words, in different driving scenes, the pre-set priorities of the multiple scene features remain unchanged.

[0131] In an embodiment of the present application, the priorities of the M driving scenes are determined based on the preset priorities of the above-mentioned multiple scene features and the M evaluation information of the M driving scenes, including: comparing the sub-priorities of the corresponding scene features in the M evaluation information in order from high to low according to the preset priorities of the scene features, obtaining the sorting results of the M evaluation information, and determining the priorities of the M driving scenes based on the sorting results of the M evaluation information.

[0132] For example, it is assumed that three scene features are used to evaluate the priority of the driving scene, and the preset priorities of the three scene features are arranged from high to low as follows: scene feature 1 > scene feature 2 > scene feature 3. The specific process of determining the priority of M driving scenarios based on the above-mentioned sorting method can be: for the M evaluation information of these M driving scenarios, first compare the sub-priority of scene feature 1 in each evaluation information, that is, the higher the priority of scene feature 1 in the evaluation information in the driving scenario, the higher the ranking of the evaluation information in these M evaluation information, and the higher the priority of the driving scenario corresponding to the evaluation information; when the sub-priority of scene feature 1 is the same, then compare the sub-priority of scene feature 2, that is, the higher the priority of scene feature 2 in the driving scenario in the evaluation information, the higher the ranking of the evaluation information in these M evaluation information, and the higher the priority of the driving scenario corresponding to the evaluation information; when the sub-priority of scene feature 1 is the same and the sub-priority of scene feature 2 is the same, then compare the sub-priority of scene feature 3, that is, the higher the priority of scene feature 3 in the driving scenario in the evaluation information, the higher the ranking of the evaluation information in these M evaluation information, and the higher the priority of the driving scenario corresponding to the evaluation information. It can be understood that the embodiments of the present application do not limit the number of scene features. When the number of scene features used to evaluate the scene priority can also be 2, 4, 5 or other values, the priority of the M driving scenes can also be determined by the sorting idea of ​​the above method.

[0133] In one implementation, the multiple scenario features include a first feature and a second feature, wherein a preset priority of the first feature is higher than a preset priority of the second feature. After determining the priorities of M driving scenarios based on the above method, for any two driving scenarios among the M driving scenarios, taking the first driving scenario and the second driving scenario as examples, the priority of the first driving scenario and the priority of the second driving scenario satisfy any of the following conditions:

[0134] Case 1: The priority of the first feature in the first driving scenario is higher than the priority of the first feature in the second driving scenario, so the priority of the first driving scenario is higher than the priority of the second driving scenario;

[0135] Case 2: If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is higher than the priority of the second feature in the second driving scenario, then the priority of the first driving scenario is higher than the priority of the second driving scenario; or

[0136] Case 3: If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is the same as the priority of the second feature in the second driving scenario, then the priority of the first driving scenario is the same as the priority of the second driving scenario.

[0137] In addition to the above cases 1 to 3, it can be understood that if the priority of the first feature in the first driving scenario is lower than the priority of the first feature in the second driving scenario, then the priority of the first driving scenario is lower than the priority of the second driving scenario; if the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is lower than the priority of the second feature in the second driving scenario, then the priority of the first driving scenario is lower than the priority of the second driving scenario.

[0138] The application of the above implementation is described in detail below based on FIG. 4 .

[0139] FIG4 is a schematic diagram of a process for determining the priorities of multiple driving scenarios provided by an embodiment of the present application. Taking multiple scenario features as scenario complexity, scenario danger and scenario exposure as an example, the preset priorities of the three are arranged from high to low as follows: scenario danger > scenario exposure > scenario complexity. As can be seen from FIG4 , FIG4 shows the evaluation information of 20 driving scenarios. The definition of the sub-priority of the scenario features can refer to Table 1 above, and the larger the value of the sub-priority of the scenario feature in Table 1 (i.e., the priority of the scenario feature in the driving scenario), the higher the sub-priority of the scenario feature. Assuming that in the evaluation information of each driving scenario, the priorities of the three scenario features in the driving scenario are arranged from left to right in descending order of the preset priorities of the scenario features, the evaluation information “431” of the driving scenario numbered “1” indicates that the priority of the scenario danger in driving scenario 1 is “4”, the priority of the scene exposure in driving scenario 1 is “3” and the priority of the scene complexity in driving scenario 1 is “1”. For the evaluation information of the 20 driving scenarios shown in Figure 4, these 20 evaluation information are sorted according to the preset priority of the scenario features from high to low based on the sub-priority of the corresponding scenario features in each evaluation information, and a sorting result can be obtained, namely the "sorting of evaluation information" shown in Figure 4 (the first column in the three-column table to the right of the arrow). According to the sorting result of the evaluation information shown in Figure 4, the evaluation information "432" of the driving scene numbered "19" is ranked first, so the driving scene numbered "19" has the highest priority; the evaluation information "121" of the driving scene numbered "14" is ranked last, so the driving scene numbered "14" has the lowest priority; the evaluation information of the three driving scenarios numbered "9", "16" and "20" is the same, so the priorities of the three driving scenarios numbered "9", "16" and "20" are the same.

[0140] It can be understood that Figure 4 is only an example of using three scene features to evaluate the priorities of 20 driving scenarios from two dimensions: the preset priority of the scene features and the priority of the scene features in the driving scenario. It does not limit the number of scene features used in evaluating the priority of the driving scenario and the number of driving scenarios.

[0141] In some possible embodiments, the total number of multiple scene features is S, assuming that the preset priority of the i-th scene feature is greater than the preset priority of the i+1-th scene feature, i is an integer greater than or equal to 1 and less than S, and the priorities of the M driving scenes are determined according to the preset priorities of the above-mentioned multiple scene features and the M evaluation information of the M driving scenes, including: statistically determining the priorities of the M driving scenes by using a ranking function to the preset priorities of the multiple scene features and the M evaluation information of the M driving scenes, wherein the ranking function is the sum of S parts, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, and the value of each coefficient in the ranking function satisfies the following constraint condition: the minimum value of the i-th part is greater than the maximum value of the sum of the i+1-th part, the i+2-th part, ...., the S-th part among the above-mentioned S parts.

[0142] In one implementation, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, which can be: the i-th part is represented as a function with the i-th coefficient as the base and the priority of the i-th scene feature in the driving scene as the exponent. Taking the use of three scene features for evaluating scene priority as an example, in this case, the construction of the ranking function can be expressed as the following formula (1): F1=a1 lp1 +b1 lp2 +c1 lp3 Formula (1)

[0143] Where F1 is the value of the ranking function, lp1 represents the priority of scene feature 1 in the driving scene, lp2 represents the priority of scene feature 2 in the driving scene, and lp3 represents the priority of scene feature 3 in the driving scene. a1, b1, and c1 are the above coefficients. Assuming that the preset priority of scene feature 1 is higher than the preset priority of scene feature 2, and the preset priority of scene feature 2 is higher than the preset priority of scene feature 3, the values ​​of a1, b1, and c1 satisfy the following constraint 1: It can be understood that formula (1) is only an example of expressing a ranking function, and the expression of the ranking function is not limited to that shown in formula (1), and can also be based on some variations of formula (1).

[0144] For example, assuming that scene feature 1 is scene danger, scene feature 2 is scene exposure, and scene feature 3 is scene complexity, the definition of the sub-priority of each scene feature can be referred to as shown in Table 1. From Table 1, it can be seen that the value set of the sub-priority of scene danger is {1, 2, 3, 4}, the value set of the sub-priority of scene exposure is {1, 2, 3, 4}, and the value set of the sub-priority of scene complexity is {1, 2, 3, 4}. Based on constraint condition 1, the process of determining the values ​​of coefficients a1, b1, and c1 in the above formula (1) can be: for (b1 lp2 ) min >(c1 lp3 ) max This constraint, lp2 = 1 and lp3 = 4, first determine the values ​​of coefficients b1 and c1, and then for (a1 lp1 ) min >(b1 lp2 +c1 lp3 ) max This constraint, lp1=1 and lp2=lp3=4, and substituting the values ​​of b1 and c1 above determine the value of coefficient a1.

[0145] In another implementation, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, which can be: the i-th part is represented by the product of the i-th coefficient and the priority of the i-th scene feature in the driving scene. Taking the use of three scene features for evaluating scene priority as an example, in this case, the construction of the ranking function can be expressed as the following formula (2): F2=a2*lp1+b2*lp2+c2*lp3 Formula (2)

[0146] Wherein, F2 is the value of the ranking function, lp1 represents the priority of scene feature 1 in the driving scene, lp2 represents the priority of scene feature 2 in the driving scene, lp3 represents the priority of scene feature 3 in the driving scene, a2, b2, and c2 are the above coefficients. Assuming that the preset priority of scene feature 1 is higher than the preset priority of scene feature 2, and the preset priority of scene feature 2 is higher than the preset priority of scene feature 3, the values ​​of a2, b2, and c2 satisfy the following constraint condition 2: It can be understood that formula (2) is only an example of expressing a ranking function, and the expression of the ranking function is not limited to that shown in formula (2). It can also be some variations based on formula (2), which will not be repeated here.

[0147] For example, assuming that scene feature 1 is scene danger, scene feature 2 is scene exposure, and scene feature 3 is scene complexity, the definition of the sub-priority of each scene feature can be referred to as shown in Table 1. It can be seen from Table 1 that the value set of the sub-priority of scene danger is {1, 2, 3, 4}, the value set of the sub-priority of scene exposure is {1, 2, 3, 4}, and the value set of the sub-priority of scene complexity is {1, 2, 3, 4}. Based on constraint condition 2, the process of determining the values ​​of a2, b2, and c2 in the above formula (2) can be: for (b2*lp2) min >(c2*lp3) max This constraint, lp2 = 1 and lp3 = 4, first determine the values ​​of coefficients b2 and c2, and then for (a2*lp1) min >(b2*lp2+c2*lp3)max, lp1=1 and lp2=lp3=4, and substituting the values ​​of b2 and c2 determined above to determine the value of coefficient a2.

[0148] The application of the above implementation is described in detail below based on FIG5 .

[0149] Figure 5 is a schematic diagram illustrating another process for determining the priorities of multiple driving scenarios, provided in an embodiment of the present application. Taking the multiple scenario characteristics of scenario complexity, scenario risk, and scenario exposure as an example, the preset priorities of the three are ranked from high to low as follows: scenario risk > scenario exposure > scenario complexity. The 20 evaluation information items for the 20 driving scenarios shown in Figure 5 can be found in the corresponding descriptions in Figure 4 and will not be repeated here. For the 20 evaluation information shown in FIG5, for example, the ranking function F2 shown in the above formula (2) is used, where, in formula (2), lp1 corresponds to the scene danger, lp2 corresponds to the scene exposure, and lp3 corresponds to the scene complexity. The values ​​of the coefficients a2, b2, and c2 are taken as a set of values ​​a2 = 25 and b2 = and c2 = 1 that satisfy the above constraint condition 2. The ranking function F2 is used to perform statistics on the preset priorities of the three scene features and the 20 evaluation information to obtain the ranking function value corresponding to each driving scene; the ranking function values ​​corresponding to the driving scenes are sorted from large to small. The larger the ranking function value corresponding to the driving scene, the higher the priority of the driving scene. In this way, the priority of the 20 driving scenes can be determined. From the sorting result of F2 shown in FIG5, it can be seen that the driving scene numbered "19" has the highest priority, the driving scene numbered "14" has the lowest priority, and the three driving scenes numbered "9", "16" and "20" have the same priority.

[0150] It can be understood that Figure 5 is only an example of using three scene features to evaluate the priorities of 20 driving scenarios from two dimensions: the preset priority of the scene features and the priority of the scene features in the driving scenario. It does not limit the number of scene features used in evaluating the priority of the driving scenario and the number of driving scenarios.

[0151] It can be seen that, in the implementation of the embodiment of the present application, the importance ranking among the multiple scene features involved in the evaluation is indicated by defining the preset priorities of the multiple scene features. The priority information of the multiple scene features in different driving scenarios can be used to more finely characterize different driving scenarios. In this way, the priority of multiple driving scenarios is comprehensively determined from the two dimensions of the preset priority of the scene features and the priority of the scene features in the driving scenarios, which can improve the evaluation accuracy of the priority of the driving scenario.

[0152] In some possible embodiments, the priority of driving scenarios may be applied to the screening of test scenarios.

[0153] See Figure 6, which is a flow chart of another method for determining scene priority provided by an embodiment of the present application. This method can be applied to the processing device shown in Figure 1. The specific steps S601-S603 in the method shown in Figure 6 can refer to the relevant descriptions of S201-S203 in the embodiment of Figure 2 above, and will not be repeated here. In addition, the method also includes the following steps:

[0154] S604: Select N driving scenarios from the M driving scenarios for testing using the priorities of the M driving scenarios, where N is a positive integer smaller than M.

[0155] In one implementation, based on the priorities of the M driving scenarios, N driving scenarios with higher priorities are selected from the M driving scenarios for testing. Here, the N driving scenarios with higher priorities can be determined based on a ranking of the M driving scenarios from high to low priority. In this way, when testing resources and costs are limited, the priority ranking of multiple driving scenarios can be used to select the more important driving scenarios for testing, thereby improving driving scenario testing efficiency.

[0156] For example, if the N driving scenarios include a first driving scenario and a second driving scenario, and the first driving scenario has a higher priority than the second driving scenario, then the first driving scenario is tested before the second driving scenario. In this way, the priority of the driving scenarios affects the order in which they are tested, allowing the higher-priority driving scenarios to be tested first.

[0157] S605: When the test results of the N driving scenarios do not meet the test objectives, adjust the preset priorities of the multiple scenario features according to the test results.

[0158] Here, the test target is related to the scenario characteristics. For example, the test target includes sub-test targets corresponding to the above-mentioned multiple scenario characteristics.

[0159] Exemplarily, adjusting the preset priorities of the plurality of scene features based on the test result may include adjusting the preset priorities of some or all of the plurality of scene features based on the test result.

[0160] Exemplarily, the above-mentioned multiple scene features include scene feature 1, scene feature 2, and scene feature 3, wherein the preset priorities of these multiple scene features are ranked from high to low as follows: scene feature 1>scene feature 2>scene feature 3. Taking the test results of the above-mentioned N driving scenes as an example where the test results do not meet the sub-test target corresponding to scene feature 3 in the above-mentioned test target, in this case, adjusting the preset priorities of these multiple scene features according to the test results can be: raising the preset priority of scene feature 3 among these multiple scene features according to the test results. For example, after the above-mentioned adjustment, the preset priorities of these multiple scene features can be ranked from high to low as follows: scene feature 1>scene feature 3>scene feature 2, or scene feature 3>scene feature 1>scene feature 2, or scene feature 3>scene feature 2>scene feature 1, which is not specifically limited here.

[0161] For example, scenario feature 3 is scenario complexity, and the sub-test objective corresponding to scenario feature 3 may be that the scenario coverage must reach a preset threshold.

[0162] Here, the test results of the above-mentioned N driving scenarios may be a statistical result obtained based on the test outputs of these N driving scenarios, or may refer to the test output of at least one driving scenario among these N driving scenarios.

[0163] As can be seen, by implementing the embodiments of the present application, by selecting a portion of driving scenarios with higher priority from multiple driving scenarios for testing based on their priority, this can save testing resources and costs for the driving scenarios and improve testing efficiency. Furthermore, by adjusting the preset priorities of multiple scenario features involved in the scenario priority assessment based on test result feedback to change the importance ranking of at least two scenario features, the test results of the driving scenarios can be made more consistent with the test objectives.

[0164] In the embodiment of the present application, the priority determination device shown in Figure 1 can be implemented by hardware, software, or a combination of hardware and software.

[0165] Exemplarily, the priority determination apparatus shown in Figure 1 may be used to implement the method described in the embodiment of Figure 2. In the embodiment of Figure 2, the acquisition unit may be used to execute S201 and S202, and the processing unit may be used to execute S203.

[0166] In some possible embodiments, the priority determination apparatus shown in FIG1 further includes a testing unit. In this case, the priority determination apparatus shown in FIG1 can also implement the method described in the embodiment of FIG6. In the embodiment of FIG6, the acquisition unit can be used to perform S601 and S602, the processing unit can be used to perform S603, and the testing unit can be used to perform S604 and S605.

[0167] It should be understood that the division of the various units in the priority determination device shown in Figure 1 above is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. In addition, the units in the device can be implemented in the form of a processor calling software; for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or realize the functions of the various units of the device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units can be realized by designing the hardware circuits. The hardware circuit can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units by designing the logical relationship of the components in the circuit. For another example, in another implementation, the hardware circuit can be implemented by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units. All units of the above devices can be implemented in the form of software called by the processor, or in the form of hardware circuits, or in part by software called by the processor, and the rest by hardware circuits.

[0168] In an embodiment of the present application, a processor is a circuit with a signal processing capability. In one implementation, the processor can be a circuit with instruction reading and execution capability, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationship of a hardware circuit. The logical relationship of the hardware circuit is fixed or reconfigurable, such as a hardware circuit implemented by a processor as an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the processor loads a configuration document to implement the process of hardware circuit configuration, which can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0169] It can be seen that each unit in the above device can be one or more processors (or processing circuits) configured to implement the above method, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0170] In addition, the various units in the above devices can be fully or partially integrated together, or can be implemented independently. In one implementation, these units are integrated together and implemented in the form of a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or implementing the functions of the various units of the device. The type of the at least one processor can be different, for example, including a CPU and FPGA, a CPU and an artificial intelligence processor, a CPU and a GPU, etc.

[0171] Referring to Figure 7 , Figure 7 is a schematic diagram of the structure of a computing device provided in an embodiment of the present application. As shown in Figure 7 , computing device 40 includes a processor 401, a communication interface 402, a memory 403, and a bus 404. Processor 401, memory 403, and communication interface 402 communicate with each other via bus 404. It should be understood that this application does not limit the number of processors and memories in computing device 40.

[0172] In one implementation, the computing device 40 may be a network-side device. The network-side device may be, for example, a server deployed on the network side (e.g., a scenario priority assessment server, a simulation test server, etc.), or a component or chip in the server, or a system-level device composed of multiple servers. The network-side device may be deployed in a cloud environment or an edge environment, and is not specifically limited here.

[0173] Bus 404 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, among others. Buses may be classified as address buses, data buses, control buses, and the like. For ease of illustration, FIG7 illustrates a single bus line, but this does not imply a single bus or type of bus. Bus 404 may include a path for transmitting information between various components of computing device 40 (e.g., memory 403, processor 401, and communication interface 402).

[0174] The processor 401 can refer to the relevant description of the processor in the above embodiment, which will not be repeated here.

[0175] Memory 403 is used to provide storage space for storing data such as the operating system and computer programs. Memory 403 can be one or a combination of random access memory (RAM), erasable programmable read-only memory (EPROM), read-only memory (ROM), or compact disc read-only memory (CD-ROM). Memory 403 can exist independently or be integrated into processor 401.

[0176] The communication interface 402 can be used to provide information input or output for the processor 401. Alternatively, the communication interface 402 can be used to receive data transmitted externally and / or transmit data externally. It can be a wired link interface such as an Ethernet cable, or a wireless link interface (such as Wi-Fi, Bluetooth, general wireless transmission, etc.). Alternatively, the communication interface 402 can also include a transmitter (such as a radio frequency transmitter, antenna, etc.) or a receiver coupled to the interface.

[0177] In some possible embodiments, the computing device 40 further includes a display 405. The display 405 is connected or coupled to the processor 401 via a bus 404. The display 405 can be used to present a manual interaction interface to the user. For example, the user can input the preset priorities of the aforementioned multiple scene features and M evaluation information for the aforementioned M driving scenarios through the manual interaction interface, where M is an integer greater than 1. The display 405 can be a display screen, which can be a liquid crystal display (LCD), an organic or inorganic light-emitting diode (OLED), an active matrix organic light-emitting diode (AMOLED), etc.

[0178] The processor 401 in the computing device 40 is used to read the computer program stored in the memory 403 to execute the aforementioned method, such as the method described in FIG. 2 or FIG. 6 .

[0179] In one possible design, the computing device 40 may be one or more modules in an execution entity that executes the method shown in FIG. 2 , and the processor 401 may be configured to read one or more computer programs stored in a memory to perform the following operations:

[0180] Acquiring, by an acquisition unit, evaluation information of a driving scene, wherein the evaluation information of the driving scene is used to describe the priority of multiple scene features in the driving scene;

[0181] The priorities of the M driving scenarios are determined according to the preset priorities of the multiple scenario features and the M evaluation information of the M driving scenarios, where M is an integer greater than 1.

[0182] In the embodiments described above, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant descriptions of other embodiments. In addition, in the various embodiments of this application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between the various embodiments are consistent and can be referenced to each other. The technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0183] It should be noted that, those skilled in the art can see that all or part of the steps in the various methods of the above embodiments can be completed by a program to instruct relevant hardware. The program can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0184] The technical solution of the present application may essentially or contribute to the part or all or part of the technical solution in the form of a software product. The computer program product is stored in a storage medium and includes a number of instructions for enabling a device (which may be a personal computer, a server, or a network device, a robot, a single-chip microcomputer, a chip, a robot, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

Claims

1. A method for determining scene priority, characterized in that: The method comprises: Acquiring evaluation information of a driving scenario, wherein the evaluation information of the driving scenario is used to describe the priority of multiple scenario features in the driving scenario; The priorities of the M driving scenarios are determined according to the preset priorities of the multiple scenario features and the M evaluation information of the M driving scenarios, where M is an integer greater than 1.

2. The method according to claim 1, characterized in that The method further comprises: N driving scenarios are selected from the M driving scenarios for testing using the priorities of the M driving scenarios, where N is a positive integer less than M.

3. The method according to claim 2, characterized in that The method further comprises: When the test results of the N driving scenarios do not meet the test objectives, the preset priorities of the multiple scenario features are adjusted according to the test results of the N driving scenarios.

4. The method according to any one of claims 1 to 3, characterized in that: The multiple scene features Including the following: Scenario complexity, scenario danger, scenario exposure, scenario rationality and scenario accuracy.

5. The method according to any one of claims 1 to 4, characterized in that: The preset priorities of the multiple scene features are set based on the confidence levels of the multiple scene features or historical testing experience.

6. The method according to any one of claims 1 to 5, characterized in that: The multiple scene features include a first feature and a second feature, wherein a preset priority of the first feature is higher than a preset priority of the second feature; the M driving scenes include a first driving scene and a second driving scene, and the priority of the first driving scene and the priority of the second driving scene satisfy any of the following conditions: If the priority of the first feature in the first driving scenario is higher than the priority of the first feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or, If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is higher than the priority of the second feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or, If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is the same as the priority of the second feature in the second driving scenario, the priority of the first driving scenario is the same as the priority of the second driving scenario.

7. The method according to any one of claims 1 to 5, characterized in that: The total number of the multiple scene features is S, the preset priority of the i-th scene feature is greater than the preset priority of the i+1-th scene feature, i is an integer greater than or equal to 1 and less than S, Determining priorities of the M driving scenarios according to the preset priorities of the multiple scene features and the M evaluation information of the M driving scenarios, comprising: performing statistics on the preset priorities of the multiple scene features and the M evaluation information through a ranking function to determine the priorities of the M driving scenarios; The ranking function is the sum of S parts, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, and the value of each coefficient in the ranking function satisfies the following constraints: The minimum value of the i-th part is greater than the maximum value of the sum of the i+1-th part, the i+2-th part, ..., the S-th part among the S parts.

8. The method according to any one of claims 1 to 7, characterized in that: The preset priorities of the multiple scene features are input by the user.

9. A device for determining scene priority, characterized in that: The device comprises: An acquisition unit, configured to acquire evaluation information of a driving scene, wherein the evaluation information of the driving scene is used to describe the priority of multiple scene features in the driving scene; A processing unit is used to determine the priorities of the M driving scenarios according to the preset priorities of the multiple scene features and the M evaluation information of the M driving scenarios, where M is an integer greater than 1.

10. The device according to claim 9, characterized in that The device also includes a testing unit: The testing unit is used to select N driving scenarios from the M driving scenarios for testing using the priorities of the M driving scenarios, where N is a positive integer less than M.

11. The device according to claim 10, characterized in that The test unit is also used to: When the test results of the N driving scenarios do not meet the test objectives, the preset priorities of the multiple scenario features are adjusted according to the test results of the N driving scenarios.

12. The device according to any one of claims 9 to 11, characterized in that: The multiple scene features Including the following: Scenario complexity, scenario danger, scenario exposure, scenario rationality and scenario accuracy.

13. The device according to any one of claims 9 to 12, characterized in that: The preset priorities of the multiple scene features are set based on the confidence levels of the multiple scene features or historical testing experience.

14. The device according to any one of claims 9 to 13, characterized in that: The multiple scene features include a first feature and a second feature, wherein a preset priority of the first feature is higher than a preset priority of the second feature; the M driving scenes include a first driving scene and a second driving scene, and the priority of the first driving scene and the priority of the second driving scene satisfy any of the following conditions: If the priority of the first feature in the first driving scenario is higher than the priority of the first feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or, If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is higher than the priority of the second feature in the second driving scenario, the priority of the first driving scenario is higher than the priority of the second driving scenario; or, If the priority of the first feature in the first driving scenario is the same as the priority of the first feature in the second driving scenario and the priority of the second feature in the first driving scenario is the same as the priority of the second feature in the second driving scenario, the priority of the first driving scenario is the same as the priority of the second driving scenario.

15. The device according to any one of claims 9 to 13, characterized in that: The total number of the multiple scene features is S, the preset priority of the i-th scene feature is greater than the preset priority of the i+1-th scene feature, i is an integer greater than or equal to 1 and less than S, The processing unit is specifically used to: perform statistics on the preset priorities of the multiple scene features and the M evaluation information through a ranking function to determine the priorities of the M driving scenes; The ranking function is the sum of S parts, the i-th part is represented by the i-th coefficient and the priority of the i-th scene feature in the driving scene, and the value of each coefficient in the ranking function satisfies the following constraints: The minimum value of the i-th part is greater than the maximum value of the sum of the i+1-th part, the i+2-th part, ..., the S-th part among the S parts.

16. The device according to any one of claims 9 to 15, characterized in that: The preset priorities of the multiple scene features are input by the user.

17. A communication device, characterized in that: The device comprises at least one processor and an interface circuit, wherein the processor is used to execute instructions and / or data interaction through the interface circuit, so that the device executes the method according to any one of claims 1 to 8.

18. A computer-readable storage medium, characterized in that: The method comprises computer instructions, which, when executed by a processor, implement the method according to any one of claims 1 to 8.

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