Risk assessment method for vehicle functional scenario, apparatus, and electronic device

Abstract

A risk assessment method for a vehicle functional scenario, an apparatus, and an electronic device. The method relates to the field of vehicles, and comprises: acquiring functional use cases of an intelligent driving function of a vehicle (S102); analyzing a target behavior of the intelligent driving function in the functional use cases to determine at least one functional scenario comprising a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle (S104); performing risk assessment on the at least one functional scenario on the basis of the vehicle behavior to obtain an assessment result (S106); and generating a vehicle functional scenario of the vehicle on the basis of the assessment result and the at least one functional scenario. The above method solves the technical problem of low accuracy in vehicle intelligent driving functions caused by limits of vehicle intelligent driving functions.

Description

Risk assessment method and device for vehicle function scene and electronic equipment TECHNICAL FIELD

[0001] The present disclosure relates to the field of vehicles, in particular to a risk assessment method and device for a vehicle function scene and electronic equipment. BACKGROUND

[0002] As a product of the "intelligent manufacturing" and "Internet +" era, intelligent driving will lead to the overall upgrade and reshaping of the vehicle industry ecology and business model. The world's major vehicle powers have included intelligent driving in their strategic deployment. However, due to the current limitations of science and technology, intelligent driving, while providing convenience, also brings potential risks, such as system function deficiencies caused by device performance limitations, algorithm defects, and running environment factor interference, and personnel injuries caused by reasonable and foreseeable human misuse. In order to improve the safety of intelligent driving, it is necessary to develop corresponding standards for intelligent driving and perform functions. The vehicle-expected function safety hazard identification and assessment in the related technology are mostly based on function to analyze vehicle behavior, which is one-sided, resulting in low accuracy of vehicle intelligent driving function.

[0003] At present, there is no effective solution to the above problems. SUMMARY

[0004] The embodiments of the present disclosure provide a risk assessment method and device for a vehicle function scene and electronic equipment to at least solve the technical problem of low accuracy of vehicle intelligent driving function caused by one-sided vehicle intelligent driving function.

[0005] According to an aspect of an embodiment of the present disclosure, a risk assessment method for a vehicle function scene is provided, including: obtaining a function use case of an intelligent driving function of a vehicle, wherein the function use case is used to represent conditions that need to be met by the intelligent driving function in different function scenes; analyzing a target behavior of the intelligent driving function in the function use case to determine at least one function scene containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle, wherein the vehicle behavior is formed by an influence of the target behavior on the vehicle, and the target behavior is used to represent a behavior that does not conform to a corresponding expected standard of the intelligent driving function in the use process of the intelligent driving function; performing risk assessment on the at least one function scene based on the vehicle behavior to obtain an assessment result, wherein the assessment result is used to represent whether the at least one function scene conforms to an expected function safety.

[0006] Further, the method further includes: generating a vehicle function scene of the vehicle based on the assessment result and the at least one function scene.

[0007] Further, the vehicle function scenario of the vehicle is generated based on the evaluation result and the at least one function scenario, including: determining a target function scenario in the at least one function scenario based on the evaluation result, wherein the target function scenario is a scenario in the at least one function scenario that does not meet the expected function safety; determining a safety requirement condition of the target function scenario according to a target behavior in the target function scenario, wherein the safety requirement condition is used to represent a condition that needs to be met to cope with the target behavior; and adding a threshold parameter associated with the target behavior to the target function scenario based on the safety requirement condition to obtain the vehicle function scenario.

[0008] Further, the vehicle function scenario of the vehicle is generated based on the evaluation result and the at least one function scenario, including: determining a target function scenario in the at least one function scenario based on the evaluation result, wherein the target function scenario is a scenario in the at least one function scenario that does not meet the expected function safety; determining a safety requirement condition of the target function scenario according to a target behavior in the target function scenario, wherein the safety requirement condition is used to represent a condition that needs to be met to cope with the target behavior; and adding a threshold parameter associated with the target behavior to the target function scenario based on the safety requirement condition to obtain the vehicle function scenario.

[0009] Further, the target behavior of the intelligent driving function in the function case is analyzed, and at least one function scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle are determined, including: determining a behavior containing a preset keyword in a plurality of behaviors corresponding to the intelligent driving function as the target behavior; determining a function scenario in which the target behavior of the intelligent driving function exists under different function scenarios as the at least one function scenario; and determining a vehicle behavior corresponding to the target behavior in the at least one function scenario based on a preset correspondence relationship, wherein the preset correspondence relationship is used to represent a correspondence relationship between the target behavior and the vehicle behavior in different function scenarios.

[0010] Further, the target behavior of the intelligent driving function in the function case is analyzed, and at least one function scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle are determined, including: determining a behavior containing a preset keyword in a plurality of behaviors corresponding to the intelligent driving function as the target behavior; determining a function scenario in which the target behavior of the intelligent driving function exists under different function scenarios as the at least one function scenario; and determining a vehicle behavior corresponding to the target behavior in the at least one function scenario based on a preset correspondence relationship, wherein the preset correspondence relationship is used to represent a correspondence relationship between the target behavior and the vehicle behavior in different function scenarios.

[0011] Further, the target behavior of the intelligent driving function in the function case is analyzed, and at least one function scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle are determined, including: determining a behavior containing a preset keyword in a plurality of behaviors corresponding to the intelligent driving function as the target behavior; determining a function scenario in which the target behavior of the intelligent driving function exists under different function scenarios as the at least one function scenario; and determining a vehicle behavior corresponding to the target behavior in the at least one function scenario based on a preset correspondence relationship, wherein the preset correspondence relationship is used to represent a correspondence relationship between the target behavior and the vehicle behavior in different function scenarios.

[0012] Further, the at least one functional scenario is risk evaluated based on the first score and the second score of the risk factor, to obtain an evaluation result, including: if the first score is greater than a preset value and the second score is greater than a preset value, determining that the evaluation result is that the at least one functional scenario does not conform to the expected functional safety; or if the first score is less than or equal to the preset value, or the first score is less than or equal to the preset value, determining that the evaluation result is that the at least one functional scenario conforms to the expected functional safety.

[0013] According to another aspect of the embodiments of the present disclosure, a risk evaluation device for a vehicle functional scenario is further provided, including: an acquisition module configured to acquire a functional use case of an intelligent driving function of a vehicle, wherein the functional use case is used to represent conditions required to be met by the intelligent driving function in different functional scenarios; an analysis module configured to analyze a target behavior of the intelligent driving function in the functional use case, to determine at least one functional scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle, wherein the vehicle behavior is formed by an influence caused by the target behavior on the vehicle, and the target behavior is used to represent a behavior that does not conform to an expected standard corresponding to the intelligent driving function in a use process of the intelligent driving function; an evaluation module configured to risk evaluate the at least one functional scenario based on the vehicle behavior, to obtain an evaluation result, wherein the evaluation result is used to represent whether the at least one functional scenario conforms to expected functional safety; and a generation module configured to generate a vehicle functional scenario of the vehicle based on the evaluation result and the at least one functional scenario.

[0014] According to another aspect of the embodiments of the present disclosure, an electronic device is further provided, including: a memory storing an executable program; and a processor configured to run the program, wherein the program performs the method in various embodiments of the present disclosure when running.

[0015] According to another aspect of the embodiments of the present disclosure, a computer readable storage medium is further provided, including a stored executable program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to perform the method in various embodiments of the present disclosure when the executable program runs.

[0016] According to another aspect of the embodiments of the present disclosure, a computer program product is further provided, including a computer program, which, when executed by a processor, implements the method in various embodiments of the present disclosure.

[0017] In the embodiments of the present disclosure, a function use case of a smart driving function of a vehicle is acquired; a target behavior of the smart driving function in the function use case is analyzed to determine at least one function scene containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle; a risk assessment is performed on the at least one function scene based on the vehicle behavior to obtain an assessment result; and a vehicle function scene of the vehicle is generated based on the assessment result and the at least one function scene. The present disclosure acquires the function use case to determine the conditions that need to be met by the vehicle smart driving function in different scenes to acquire the conditions for the vehicle to perform the function more comprehensively, determines the target behavior of the vehicle that does not meet the expected standard corresponding to the smart driving function through the function use case, determines the function scene corresponding to the target behavior and the vehicle behavior caused by the influence of the target behavior on the vehicle, performs a risk assessment on the function scene through the vehicle behavior, sets a standard to judge whether the function scene meets the expectation, and generates the vehicle function scene based on the assessment result and the function scene, so that when the function scene does not meet the expectation, the function scene is adjusted to make the function scene meet the expectation, so that the vehicle function scene is more reasonable, the comprehensiveness and rationality of the vehicle function scene are improved, thereby achieving the technical effect of improving the accuracy of the vehicle smart driving function, and further solving the technical problem of low accuracy of the vehicle smart driving function caused by the one-sidedness of the vehicle smart driving function. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the present disclosure, constitute a part of the present disclosure, the illustrative embodiments of the present disclosure and their descriptions serve to explain the present disclosure, and do not constitute an improper limitation on the present disclosure. In the drawings:

[0019] FIG. 1 is a flowchart of a risk assessment method of a vehicle function scene according to an optional embodiment of the present disclosure;

[0020] FIG. 2 is a flowchart of a risk assessment method of a vehicle function scene according to a preferred embodiment of the present disclosure;

[0021] FIG. 3 is a structural schematic diagram of a risk assessment device of a vehicle function scene according to an optional embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] In order for those skilled in the art to better understand the present disclosure scheme, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, not all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present disclosure.

[0023] It should be noted that the terms "first", "second", and the like in the description and claims of the present disclosure and above-described accompanying drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in other than the order illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a list of steps or units does not necessarily limit those steps or units to the clearly listed ones, but can include other steps or units not clearly listed or inherent to such processes, methods, products or devices.

[0024] Embodiment 1

[0025] According to an embodiment of the present disclosure, an embodiment of a risk assessment method for a vehicle function scenario is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0026] FIG. 1 is a flowchart of an optional risk assessment method for a vehicle function scenario according to an embodiment of the present disclosure, as shown in FIG. 1, the method comprises the following steps:

[0027] Step S102, acquiring the function use case of the intelligent driving function of the vehicle, wherein the function use case is used to represent the conditions that need to be met by the intelligent driving function in different function scenarios.

[0028] The above-mentioned vehicle refers to a vehicle containing intelligent driving function, including but not limited to a car, a truck, a van, a bus, etc. containing intelligent driving function.

[0029] The above-mentioned intelligent driving function is a system that improves driving safety and convenience by using advanced technology. These functions enable vehicles to achieve partial or full automation through the integration of sensors, cameras, radars and other devices, as well as artificial intelligence and machine learning algorithms. In the present disclosure, the intelligent driving function of the vehicle needs to be functional, and the safety of the vehicle when starting the intelligent driving function is ensured by the functional intelligent driving function of the vehicle.

[0030] Table 1

[0031] The above function case refers to the function index of the vehicle intelligent driving function in different function scenarios. The more comprehensive the function case of the vehicle intelligent driving function is, the more comprehensive the function index of the vehicle intelligent driving function in different function scenarios is, so that the intelligent driving function of the vehicle is more effective. The function case of the vehicle intelligent driving function includes but is not limited to: version number of the function case, function case brief, vehicle intelligent driving function requirement description, vehicle mode, function case precondition, function case postcondition, path information, non-functional requirement, and vehicle human-machine interface (HMI) requirement.

[0032] The above function scenario refers to a simulated scenario for the function vehicle intelligent driving function. The function scenario can be set according to the conditions that the vehicle may encounter during intelligent driving. Therefore, for different conditions that the vehicle may encounter during intelligent driving, different function scenarios are set, and the vehicle performs the intelligent driving function in the function scenario to determine whether the vehicle intelligent driving function is perfect.

[0033] In an optional embodiment, the function case of the vehicle intelligent driving function can be artificially designed based on experience and actual situation. For example, Table 1 is a function case table of the automatic driving function of the vehicle driver navigation. The function case of the automatic driving function of the vehicle driver navigation (Navigate on Pilot, NOP) is shown in Table 1.

[0034] As shown in Table 1, the function case of the automatic driving function of the vehicle driver navigation is used to indicate the conditions that need to be met when the automatic driving function of the vehicle driver navigation performs functions in different function scenarios.

[0035] In another optional embodiment, the function case of the vehicle intelligent driving function can also be obtained by software calculation. The function case is used to indicate the conditions that need to be met when the intelligent driving function performs functions in different function scenarios.

[0036] In the present disclosure, by obtaining the function case of the vehicle intelligent driving function, the conditions that need to be met when the vehicle performs functions in different function scenarios are more comprehensive, the comprehensiveness of the vehicle function scenario is improved, and the effectiveness of the vehicle intelligent driving function is improved.

[0037] In step S104, the target behavior of the intelligent driving function in the function case is analyzed to determine at least one function scenario containing the trigger condition corresponding to the target behavior and the vehicle behavior of the vehicle. The vehicle behavior is formed by the influence of the target behavior on the vehicle. The target behavior is used to indicate the behavior that does not meet the corresponding expected standard of the intelligent driving function during use of the intelligent driving function.

[0038] The target behavior refers to a behavior of the vehicle that has an impact on the vehicle and has the potential to cause the vehicle to be dangerous when the vehicle uses the intelligent driving function. When the vehicle uses the intelligent driving function, the vehicle can have a behavior that does not meet the expected standard corresponding to the intelligent driving function. This behavior that does not meet the expected standard corresponding to the intelligent driving function can have an impact on the vehicle and cause the vehicle to be dangerous, and therefore the behavior that does not meet the expected standard corresponding to the intelligent driving function is defined as the target behavior.

[0039] The at least one functional scenario containing the trigger condition corresponding to the target behavior refers to a functional scenario containing the trigger condition triggering the target behavior. When the functional scenario contains the trigger condition of the target behavior, the target behavior can occur in the functional scenario. When the functional scenario does not contain the trigger condition of the target behavior, the target behavior cannot occur in the functional scenario.

[0040] The vehicle behavior refers to a vehicle behavior of the vehicle caused by the impact of the target behavior. Since the target behavior has an impact on the vehicle and has the potential to cause the vehicle to be dangerous, after the vehicle is affected by the target behavior, the vehicle can have behaviors such as overspeeding, being out of control, and greatly decelerating. The vehicle behavior can cause the vehicle to be dangerous.

[0041] In an optional embodiment, the target behavior of the intelligent driving function in the functional use case can be analyzed by hazard and operability study. After determining the target behavior that does not meet the expected standard corresponding to the intelligent driving function, the vehicle behavior that can be caused by the target behavior and at least one functional scenario corresponding to the target behavior are determined by hazard and operability study. Hazard and operability study is a structured and systematic process design and operation analysis method for identifying, evaluating and controlling potential risks in the process. In this disclosure, hazard and operability study is used to analyze potential risks in the functional use case to determine the target behavior of the intelligent driving function in the functional use case.

[0042] In this disclosure, by analyzing the target behavior of the intelligent driving function in the functional use case, at least one functional scenario containing the trigger condition corresponding to the target behavior and the vehicle behavior of the vehicle can be determined. The risk of the functional scenario is evaluated based on the vehicle behavior, and then it is judged whether the functional scenario needs to be adjusted. When the risk of the functional scenario is low, the functional scenario does not need to be adjusted. When the risk of the functional scenario is high, the functional scenario needs to be adjusted. The rationality of the functional scenario is improved, and the accuracy of the intelligent driving function of the vehicle is improved.

[0043] In step S106, the at least one function scene is risk evaluated based on the vehicle behavior to obtain an evaluation result, wherein the evaluation result is used to indicate whether the at least one function scene meets the expected function safety.

[0044] The risk evaluation refers to risk evaluation of the at least one function scene based on whether the vehicle behavior will cause an accident or violate traffic rules, etc., to determine whether the risk factor can be accepted. The expected function safety can be a pre-set risk evaluation standard.

[0045] The evaluation result refers to a result obtained after risk evaluation of the at least one function scene, and the evaluation result is that the function scene meets the expected function safety or the function scene does not meet the expected function safety.

[0046] The expected function safety is a pre-set risk standard used to determine whether the function scene needs to be adjusted. When the function scene meets the expected function safety, it is determined that the risk factor is acceptable. When the function scene does not meet the expected function safety, it is determined that the risk factor is not acceptable.

[0047] In an optional embodiment, the at least one function scene is risk evaluated based on the vehicle behavior to obtain an evaluation result. It is determined whether the at least one function scene meets the expected function safety or the at least one function scene does not meet the expected function safety.

[0048] In the present disclosure, the expected function safety is pre-set, and it is determined whether the at least one function scene meets the expected function safety by risk evaluation of the at least one function scene, so that it is determined whether the function scene meets the expected function safety, and the function scene is adjusted to improve the rationality of the vehicle function scene.

[0049] The function use case of the intelligent driving function of the vehicle is obtained through the above steps; the target behavior of the intelligent driving function in the function use case is analyzed to determine at least one function scene containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle; the at least one function scene is risk evaluated based on the vehicle behavior to obtain an evaluation result; and the vehicle function scene of the vehicle is generated based on the evaluation result and the at least one function scene. The disclosure obtains the function use case to determine the conditions that need to be met by the vehicle intelligent driving function in different scenes to obtain the conditions for the vehicle to perform the function more comprehensively, determines the target behavior of the vehicle that does not meet the expected standard of the intelligent driving function through the function use case, determines the function scene corresponding to the target behavior and the vehicle behavior caused by the influence of the target behavior on the vehicle, and evaluates the risk of the function scene through the vehicle behavior, sets a standard to judge whether the function scene meets the expectation, and generates the vehicle function scene based on the evaluation result and the function scene, so that when the function scene does not meet the expectation, the function scene is adjusted to meet the expectation, so that the vehicle function scene is more reasonable, the comprehensiveness and rationality of the vehicle function scene are improved, thereby realizing the technical effect of improving the accuracy of the vehicle intelligent driving function, and further solving the technical problem of poor safety of vehicle intelligent driving caused by low accuracy of the vehicle intelligent driving function.

[0050] Optionally, the method further comprises: generating a vehicle function scene of the vehicle based on the evaluation result and the at least one function scene.

[0051] The vehicle function scene is an adjusted function scene. After obtaining the evaluation result, it is determined whether the at least one function scene needs to be adjusted based on the evaluation result. If there is a function scene in the at least one function scene that does not meet the expected function safety, the function scene that does not meet the expected function safety is adjusted to obtain an adjusted function scene, i.e., the vehicle function scene. If there is no function scene in the at least one function scene that does not meet the expected function safety, the at least one function scene is the vehicle function scene. The vehicle function scene has higher adaptability and is more comprehensive than the function scene.

[0052] In an optional embodiment, the function scene that does not meet the expected function safety in the at least one function scene is determined through the evaluation result. The target behavior in the function scene that does not meet the expected function safety can be determined in a human-determined manner, and the adjustment requirement of the function scene that does not meet the expected function safety is determined according to the target behavior. The function scene that does not meet the expected function safety is adjusted based on the adjustment requirement to obtain the vehicle function scene. If the evaluation result is that there is no function scene in the at least one function scene that does not meet the expected function safety, the at least one function scene does not need to be adjusted, and the vehicle function scene is directly generated.

[0053] In another optional embodiment, the function scene that does not conform to the expected function safety is determined through the evaluation result, and the target behavior in the function scene that does not conform to the expected function safety is also determined through program calculation, and the adjustment requirement of the function scene that does not conform to the expected function safety is artificially determined according to the target behavior, and the function scene that does not conform to the expected function safety is adjusted based on the adjustment requirement to obtain the vehicle function scene. If the evaluation result is that there is no function scene that does not conform to the expected function safety in the at least one function scene, the at least one function scene does not need to be adjusted, and the vehicle function scene is directly generated.

[0054] In the present disclosure, the function scene that does not conform to the expected function safety is adjusted to obtain the function scene that conforms to the expected function safety after adjustment, so that the accuracy of intelligent driving of the vehicle is improved, and the user experience is effectively improved.

[0055] Optionally, the vehicle function scene of the vehicle is generated based on the evaluation result and the at least one function scene, including: determining a target function scene in the at least one function scene based on the evaluation result, wherein the target function scene is a scene that does not conform to the expected function safety in the at least one function scene; determining a safety requirement condition of the target function scene according to a target behavior in the target function scene, wherein the safety requirement condition is used to represent a condition that needs to be met to cope with the target behavior; adding a threshold parameter associated with the target behavior to the target function scene based on the safety requirement condition to obtain the vehicle function scene.

[0056] The target function scene refers to the function scene that does not conform to the expected function safety, wherein since the target behavior can correspond to multiple function scenes, the function scene that does not conform to the expected function safety in the at least one function scene, i.e., the target function scene, is determined through the evaluation result.

[0057] The safety requirement condition refers to a safety requirement condition that needs to be met by the target function scene that does not conform to the expected function safety to conform to the expected function safety, and is also a condition that needs to be met by the target function scene to eliminate the influence brought by the target behavior. The safety requirement condition can be set according to the target behavior and the target function scene, the safety requirement condition can also be artificially set according to experience and requirements, and the safety requirement condition can also be set according to actual application scenarios.

[0058] The threshold parameters refer to some parameters of the vehicle when the vehicle is intelligently driven, including but not limited to: vehicle speed, vehicle torque, vehicle control time, vehicle acceleration, probability of vehicle violation of traffic rules, etc. The threshold parameters include probability type and numerical type thresholds. The threshold parameters can be set according to target behavior and target function scenarios. The threshold parameters can also be set by experience and demand through human setting. The threshold parameters can also be set according to actual application scenarios.

[0059] In an optional embodiment, the target behavior can correspond to multiple function scenarios, i.e., the target behavior corresponds to at least one function scenario of the trigger condition. Based on the vehicle behavior and risk assessment, an evaluation result is obtained, and it is determined whether there is a function scenario that does not meet the expected function safety in the at least one function scenario, i.e., a target function scenario is determined. According to the target behavior in the target function scenario, a safety requirement condition of the target function scenario is artificially determined, and a threshold parameter for adjusting the target function scenario is determined according to the safety requirement condition of the target function scenario, i.e., the threshold parameter associated with the target behavior is increased according to the safety requirement condition of the target function scenario, the adjusted target function scenario is determined, and the vehicle function scenario is determined.

[0060] In the present disclosure, by adjusting the function scenario, the rationality and accuracy of the vehicle function scenario are effectively improved.

[0061] Table 2

[0062] Optionally, the threshold parameter associated with the target behavior is added to the target function scenario based on the safety requirement condition to obtain the vehicle function scenario, including: obtaining the behavior type of the target behavior; determining the threshold type according to the behavior type of the target behavior, wherein the threshold type includes at least one of the following: probability threshold and numerical threshold, the probability threshold is used to represent the threshold corresponding to the probability of occurrence of the target behavior, and the numerical threshold is used to represent the threshold corresponding to the associated numerical value in the target behavior; determining the threshold parameter based on the threshold type and the safety requirement condition; adding the threshold parameter to the target function scenario to obtain the vehicle function scenario.

[0063] The behavior type refers to the type of vehicle motion state determined according to the parameters and types of the vehicle. Each target behavior type corresponds to a threshold type, and the target behavior type is divided into a probability type and a numerical type. The probability type of the target behavior corresponds to a probability threshold, and the numerical type of the target behavior corresponds to a numerical threshold.

[0064] The probability threshold refers to a vehicle target behavior that cannot be determined by a specific numerical value, for example, the probability of a vehicle violating traffic rules. The probability threshold is generally applicable to industry regulations and is used to determine the residual safety risk that still exists when a certain measure is taken during vehicle operation. The probability threshold can be set according to the target behavior and the target functional scenario, and the probability threshold can also be set artificially according to experience and demand, and the probability threshold can also be set according to the actual application scenario.

[0065] The numerical threshold refers to a vehicle target behavior that can be determined by a specific numerical value, for example, the acceleration of the vehicle. The numerical threshold is generally applicable to national and industry standards and is used to determine whether a collision or other traffic accident risk will occur during vehicle operation. The numerical threshold can be set according to the target behavior and the target functional scenario, and the numerical threshold can also be set artificially according to experience and demand, and the numerical threshold can also be set according to the actual application scenario.

[0066] In an optional embodiment, the behavior type of the target behavior is obtained, and it is determined that the behavior type of the target behavior is a probability type or a numerical type. If the behavior type of the target behavior is the probability type, it is determined that the threshold parameter is the probability threshold, the probability threshold is used to represent the threshold corresponding to the probability of the probability type target behavior, the probability threshold is determined based on the threshold type being the probability threshold and the safety requirement condition, and the probability threshold is added to the target functional scenario to obtain the vehicle functional scenario. If the type of the target behavior is the numerical type, it is determined that the threshold parameter is the numerical threshold, the numerical threshold is used to represent the threshold of the numerical type target behavior of the vehicle, the numerical threshold is determined based on the threshold type being the numerical type and the safety requirement condition, and the numerical threshold is added to the target functional scenario to obtain the vehicle functional scenario. For example, Table 2 is a threshold parameter confirmation table corresponding to the vehicle target behavior, and the threshold parameter is determined as shown in Table 2, where the target functional scenario is the vehicle over-the-air diagnostics (ODC) scene of the navigation on pilot (NOP) function. The numerical threshold such as acceleration and displacement deviation is obtained by calculation, for example, Table 3 is a longitudinal acceleration confirmation table, and the longitudinal acceleration ≤ Xm / s 2 is obtained as shown in Table 3.

[0067] The threshold parameter is obtained by the threshold parameter functional use case, and the lane and other parameters are obtained to calculate the specific numerical value of the threshold parameter. Thus, the specific numerical value of the threshold parameter is obtained according to the specific situation. After the threshold parameter is determined, the threshold parameter is added to the target functional scenario to obtain the vehicle functional scenario.

[0068] Table 3

[0069] In the present disclosure, the specific threshold parameter value is obtained through the threshold parameter function use case, so that the threshold parameter acquisition has flexibility, the adaptability of the threshold parameter is improved, and the applicable range of the vehicle function scene is greatly improved.

[0070] Optionally, the target behavior of the intelligent driving function in the function use case is analyzed to determine at least one function scene containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle, including: determining that the behavior containing a preset keyword in the multiple behaviors corresponding to the intelligent driving function is the target behavior; determining that the function scene in which the target behavior of the intelligent driving function exists under different function scenes is at least one function scene; determining the vehicle behavior corresponding to the target behavior in the at least one function scene based on a preset correspondence, wherein the preset correspondence is used to represent the correspondence between the target behavior and the vehicle behavior in different function scenes.

[0071] The above-mentioned preset keyword refers to a keyword of hazard and operability study, which is a keyword of a structured safety evaluation method. The selected keywords of hazard and operability study include but are not limited to: cannot / can not, unexpected, too early, too late, too small / too little, too large / too much, reverse, logical opposite, partial function, simultaneous action with other functions, etc. When the behavior containing the above-mentioned preset keyword in the multiple behaviors corresponding to the intelligent driving function is determined as the target behavior.

[0072] Table 4

[0073] The above-mentioned preset correspondence refers to the correspondence between the target behavior and the vehicle behavior in different function scenes, wherein the above-mentioned preset correspondence can be set according to the target behavior and the vehicle behavior, the above-mentioned preset correspondence can also be set artificially according to experience and demand, and the above-mentioned preset correspondence can also be set according to the actual application scene. In an optional embodiment, the vehicle includes multiple behaviors when the intelligent driving function is started. When the behavior containing the preset keyword in the multiple behaviors is determined as the target behavior. The function scene containing the target behavior is at least one function scene, i.e. the target function scene. Based on the preset preset correspondence, the vehicle behavior corresponding to the target behavior in the at least one function scene is determined. For example, Table 4 is a vehicle behavior confirmation table. The target behavior of the intelligent driving function in the function use case is analyzed to determine at least one function scene containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle as shown in Table 4, wherein the function scene containing the target behavior in Table 4 is under the condition that the navigation assistance function is activated.

[0074] As shown in Table 4, the target behaviors in the functional scenarios containing the target behaviors correspond to vehicle behaviors respectively.

[0075] In the present disclosure, the functional scenarios containing the target behaviors can be quickly indexed through the preset keywords, the functional efficiency of the vehicle functional scenarios is improved, and the vehicle behavior corresponding to the target behavior in the at least one functional scenario can be clearly determined through the preset correspondence relationship, so that the misjudgment situation is prevented.

[0076] In the present disclosure, the functional scenarios containing the target behaviors can be quickly indexed through the preset keywords, the functional efficiency of the vehicle functional scenarios is improved, and the vehicle behavior corresponding to the target behavior in the at least one functional scenario can be clearly determined through the preset correspondence relationship, so that the misjudgment situation is prevented.

[0077] Optionally, the at least one functional scenario is risk evaluated based on the vehicle behavior, and an evaluation result is obtained, including: determining a risk factor of the vehicle behavior according to a road event formed by the vehicle behavior in the at least one functional scenario; and performing risk evaluation on the at least one functional scenario based on a preset road rule and the risk factor to obtain the evaluation result.

[0078] The road event refers to a road event in the at least one functional scenario caused by the vehicle behavior, the target behavior affects the vehicle to appear the vehicle behavior, and after the vehicle appears the vehicle behavior, the road event in the at least one functional scenario is affected.

[0079] The risk factor refers to a risk that the vehicle behavior may cause, including but not limited to a risk of violating traffic rules or causing serious accidents.

[0080] The preset road rule refers to a road rule that is preset on the premise of not violating traffic rules. The preset road rule can be set according to the target behavior and the target functional scenario, the preset road rule can also be set artificially according to experience and demand, and the preset road rule can also be set according to an actual application scenario.

[0081] In an optional embodiment, after the vehicle behavior of the vehicle is determined through the target behavior, the road event formed in the at least one functional scenario is determined through the vehicle behavior, the risk factor of the corresponding vehicle behavior is determined according to the road event. The at least one functional scenario is risk evaluated based on the preset road rule and the risk factor, so as to obtain an evaluation result that the at least one functional scenario meets the expected functional safety or the at least one functional scenario does not meet the expected functional safety.

[0082] In the present disclosure, the risk factor of the corresponding vehicle behavior is determined according to the road event, so that the evaluation result is more accurate.

[0083] Optionally, the risk assessment on the at least one functional scenario based on the preset road rule and the risk factor is performed to obtain an evaluation result, including: if the risk factor does not conform to the preset road rule, determining that the evaluation result is that the at least one functional scenario does not conform to the expected functional safety; and if the risk factor conforms to the preset road rule, performing the risk assessment on the at least one functional scenario based on a first score of the risk factor and a second score of the risk factor to obtain the evaluation result, where the first score is used to represent the severity of the risk factor by a numerical value, and the second score is used to represent the controllability of the risk factor by a numerical value.

[0084] The first score refers to a score of the risk factor based on the severity, and the first score is used to represent the severity of the risk factor. The greater the first score is, the greater the severity of the risk factor is.

[0085] The second score refers to a score of the risk factor based on the controllability, and the second score is used to represent the controllability of the risk factor. The greater the second score is, the less controllable the risk factor is.

[0086] In an optional embodiment, if the risk factor does not conform to the preset road rule, it is determined that the evaluation result is that the at least one functional scenario does not conform to the expected functional safety. If the risk factor conforms to the preset road rule, the risk factor is scored to obtain a first score of the risk factor to determine the severity of the risk factor, and a second score of the risk factor to determine the controllability of the risk factor, and the evaluation result is determined according to the first score and the second score.

[0087] In the present disclosure, the severity and controllability of the risk factor are obtained by scoring the risk factor, so that the vehicle can maintain intelligent driving in the case that the risk is controllable.

[0088] Optionally, the risk assessment on the at least one functional scenario based on the first score and the second score of the risk factor is performed to obtain the evaluation result, including: if the first score is greater than a preset value and the second score is greater than the preset value, determining that the evaluation result is that the at least one functional scenario does not conform to the expected functional safety; and if the first score is less than or equal to the preset value or the second score is less than or equal to the preset value, determining that the evaluation result is that the at least one functional scenario conforms to the expected functional safety.

[0089] The preset value refers to a value preset for determining the severity and controllability of the risk factor. When the first score and the second score are both greater than the preset value, it is determined that the at least one functional scenario does not conform to the expected functional safety. When the first score or the second score is less than or equal to the preset value, it is determined that the at least one functional scenario conforms to the expected functional safety.

[0090] In an optional embodiment, the preset value is set in advance, and in response to the first score and the second score being greater than the preset value, it is determined that the at least one functional scenario does not meet the expected functional safety, and in response to the first score or the second score being less than or equal to the preset value, it is determined that the at least one functional scenario meets the expected functional safety. The first score and the second score of the risk factor are used to perform risk assessment on the at least one functional scenario, and the evaluation result is shown in Table 5, wherein Table 5 is a risk factor evaluation table, and the target functional scenario is a vehicle wireless diagnosis function scenario of a navigation assistance function.

[0091] Table 5

[0092] In the present disclosure, by reasonably setting the preset value and comparing the first score with the preset value and the second score with the preset value, a more accurate determination of the risk factor is obtained to determine the evaluation result, thereby effectively improving the accuracy of the evaluation result and the applicability of the vehicle functional scenario.

[0093] A preferred embodiment of the present disclosure will be described in detail below in combination with FIG. 2, wherein FIG. 2 is a flowchart of a preferred vehicle functional scenario risk assessment method according to an embodiment of the present disclosure, as shown in FIG. 2, the vehicle functional scenario risk assessment method comprises the following steps:

[0094] Step S201, designing a functional use case of an intelligent driving function.

[0095] In an optional embodiment, the functional use case of the intelligent driving function of the vehicle is designed artificially based on experience and actual situation.

[0096] Step S202, obtaining a target behavior of the intelligent driving function.

[0097] In an optional embodiment, the target behavior of the intelligent driving function in the functional use case is analyzed by hazard and operability study, wherein after determining the target behavior that does not meet the expected standard of the intelligent driving function, the vehicle behavior that the target behavior may cause and the at least one functional scenario corresponding to the target behavior are determined by hazard and operability study. The hazard and operability study is a structured and systematic process design and operation analysis method for identifying, evaluating and controlling potential risks in the process. In the present disclosure, the hazard and operability study is used to analyze potential risks in the functional use case to determine the target behavior of the intelligent driving function in the functional use case.

[0098] Step S203, determining vehicle behavior, road event, risk factor and performing risk assessment to determine the evaluation result.

[0099] In an optional embodiment, after determining the vehicle behavior of the vehicle by the target behavior, a road event formed in the at least one functional scenario is determined by the vehicle behavior, and a risk factor corresponding to the vehicle behavior is determined according to the road event. The at least one functional scenario is risk evaluated based on the preset road rule and the risk factor, to obtain an evaluation result that the at least one functional scenario meets the expected functional safety, or the at least one functional scenario does not meet the expected functional safety.

[0100] In step S204, the safety requirement condition and the threshold type are determined.

[0101] In an optional embodiment, the behavior type of the target behavior is acquired, the safety requirement condition of the target functional scenario for eliminating the influence of the target behavior is determined according to the target behavior in the target functional scenario, and the behavior type of the target behavior is determined as a probability type or a numerical type. If the behavior type of the target behavior is the probability type, the threshold type is determined as a probability threshold, and if the type of the target behavior is the numerical type, the threshold type is determined as a numerical threshold.

[0102] In step S205, the threshold parameter is determined.

[0103] In an optional embodiment, if the threshold type is the probability threshold, the probability threshold is used to represent a threshold corresponding to a probability of the target behavior of the probability type, and the specific value of the probability threshold is determined based on the threshold type being the probability threshold and the safety requirement condition. If the threshold type is the numerical threshold, the numerical threshold is used to represent a threshold of the numerical type target behavior of the vehicle, and the specific value of the numerical threshold is determined based on the threshold type being the numerical threshold and the safety requirement condition. The threshold parameter is determined as the specific value of the probability threshold or the numerical threshold.

[0104] In step S206, the vehicle functional scenario is determined based on the threshold parameter.

[0105] In an optional embodiment, if the threshold parameter is the probability threshold, the probability threshold is added to the target functional scenario after the probability threshold is acquired, and the vehicle functional scenario is acquired. If the threshold parameter is the numerical threshold, the numerical threshold is added to the target functional scenario after the numerical threshold is acquired, and the vehicle functional scenario is acquired.

[0106] Embodiment 2

[0107] According to another aspect of the embodiments of the present disclosure, a vehicle functional scenario risk evaluation device is also provided, which can execute the vehicle functional scenario risk evaluation method of the above-mentioned embodiments, and the specific implementation method and preferred application scenarios are the same as those of the above-mentioned embodiments, which will not be repeated here.

[0108] FIG. 3 is a structural schematic diagram of a risk assessment apparatus of an optional vehicle function scenario according to an embodiment of the present disclosure. As shown in FIG. 3, the apparatus comprises: an acquisition module 30 configured to acquire a function use case of an intelligent driving function of a vehicle, wherein the function use case is used to represent conditions required to be met by the intelligent driving function in different function scenarios; an analysis module 32 configured to analyze a target behavior of the intelligent driving function in the function use case, and determine at least one function scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle, wherein the vehicle behavior is formed by an influence of the target behavior on the vehicle, and the target behavior is used to represent a behavior of the intelligent driving function that does not conform to a corresponding expected standard of the intelligent driving function in a use process; and an evaluation module 34 configured to perform risk evaluation on the at least one function scenario based on the vehicle behavior, and obtain an evaluation result, wherein the evaluation result is used to represent whether the at least one function scenario conforms to an expected function safety.

[0109] Optionally, the apparatus further comprises a generation module configured to generate the vehicle function scenario of the vehicle based on the evaluation result and the at least one function scenario.

[0110] Optionally, the generation module comprises: a determination unit configured to determine a target function scenario in the at least one function scenario based on the evaluation result, wherein the target function scenario is a scenario in the at least one function scenario that does not conform to the expected function safety; a safety requirement unit configured to determine a safety requirement condition of the target function scenario according to the target behavior in the target function scenario, wherein the safety requirement condition is used to represent conditions required to be met in response to the target behavior; and a generation unit configured to add a threshold parameter associated with the target behavior to the target function scenario based on the safety requirement condition, and obtain the vehicle function scenario.

[0111] Optionally, the generation unit comprises: an acquisition subunit configured to acquire a behavior type of the target behavior; a type subunit configured to determine a threshold type according to the behavior type of the target behavior, wherein the threshold type comprises at least one of a probability threshold value and a numerical threshold value, the probability threshold value is used to represent a threshold value corresponding to a probability of occurrence of the target behavior, and the numerical threshold value is used to represent a threshold value corresponding to an associated numerical value in the target behavior; a determination subunit configured to determine the threshold parameter based on the threshold type and the safety requirement condition; and a generation subunit configured to add the threshold parameter to the target function scenario, and obtain the vehicle function scenario.

[0112] Optionally, the analysis module comprises: a target unit configured to determine, as a target behavior, a behavior in which a preset keyword is contained in the plurality of behaviors corresponding to the intelligent driving function; a function scenario unit configured to determine, as at least one function scenario, a function scenario in which the target behavior exists under the intelligent driving function in different function scenarios; and a corresponding relationship unit configured to determine, based on a preset corresponding relationship, a vehicle behavior corresponding to the target behavior in the at least one function scenario, where the preset corresponding relationship is used to represent a corresponding relationship between the target behavior and the vehicle behavior in different function scenarios.

[0113] Optionally, the evaluation module comprises: a risk unit configured to determine a risk factor of the vehicle behavior based on a road event formed by the vehicle behavior in the at least one function scenario; and an evaluation unit configured to perform risk evaluation on the at least one function scenario based on a preset road rule and the risk factor, to obtain an evaluation result.

[0114] Optionally, the evaluation unit comprises: a first risk sub-unit configured to, if the risk factor does not conform to the preset road rule, determine that the evaluation result is that the at least one function scenario does not conform to the expected functional safety; and a second risk sub-unit configured to, if the risk factor conforms to the preset road rule, perform risk evaluation on the at least one function scenario based on a first score and a second score of the risk factor, to obtain the evaluation result, where the first score is used to represent the severity of the risk factor by a numerical value, and the second score is used to represent the controllability of the risk factor by a numerical value.

[0115] Optionally, the second risk sub-unit is further configured to, if the first score is greater than a preset value and the second score is greater than the preset value, determine that the evaluation result is that the at least one function scenario does not conform to the expected functional safety; and if the first score is less than or equal to the preset value or the second score is less than or equal to the preset value, determine that the evaluation result is that the at least one function scenario conforms to the expected functional safety.

[0116] Embodiment 3

[0117] Embodiments of the present disclosure further provide an electronic device, comprising: a memory storing an executable program; and a processor configured to run the program, wherein the program, when running, performs the method in the embodiments of the present disclosure.

[0118] Embodiment 4

[0119] Embodiments of the present disclosure further provide a computer-readable storage medium, comprising a stored executable program, wherein the executable program, when running, controls a device where the computer-readable storage medium is located to perform the method in the embodiments of the present disclosure.

[0120] Embodiment 5

[0121] Embodiments of the present disclosure also provide a computer program product comprising a computer program which, when executed by a processor, implements the method in any of the embodiments of the present disclosure.

[0122] Embodiment 6

[0123] Embodiments of the present disclosure also provide a computer program which, when executed by a processor, implements the method in any of the embodiments of the present disclosure.

[0124] The above-mentioned sequence numbers of the embodiments of the present disclosure are only for description, and do not represent advantages or disadvantages of the embodiments.

[0125] In the above-mentioned embodiments of the present disclosure, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0126] In several embodiments provided by the present disclosure, it should be understood that the disclosed technology can be implemented in other ways. Of course, the embodiments described above are only schematic. For example, the division of units can be a logical function division, and there can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, unit or module, and can be electrical or other forms.

[0127] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiments.

[0128] In addition, each functional unit in each embodiment of the present disclosure can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of software functional unit.

[0129] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present disclosure, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present disclosure. The aforementioned storage medium includes various media that can store program codes, such as a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, etc.

[0130] The above only describes the preferred embodiments of the present disclosure, and it should be pointed out that, for those skilled in the art, without departing from the principles of the present disclosure, a number of improvements and refinements can be made, and these improvements and refinements should also be considered as the protection scope of the present disclosure.

Claims

1. A method for risk assessment of a vehicle function scenario, comprising: obtaining a function use case of an intelligent driving function of a vehicle, wherein the function use case is used to represent conditions that need to be met for the intelligent driving function to perform in different function scenarios; analyzing a target behavior of the intelligent driving function in the function use case to determine at least one function scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle, wherein the vehicle behavior is formed by an impact of the target behavior on the vehicle, and the target behavior is used to represent a behavior of the intelligent driving function that does not meet an expected standard of the intelligent driving function during use; performing risk assessment on the at least one function scenario based on the vehicle behavior to obtain an assessment result, wherein the assessment result is used to represent whether the at least one function scenario meets an expected functional safety.

2. The method of risk assessment of vehicle functional scenarios according to claim 1, wherein, The method further comprises: generating a vehicle function scenario of the vehicle based on the assessment result and the at least one function scenario.

3. The method of risk assessment of vehicle functional scenarios according to claim 2, wherein, Generating a vehicle function scenario of the vehicle based on the assessment result and the at least one function scenario comprises: determining a target function scenario in the at least one function scenario based on the assessment result, wherein the target function scenario is a scenario in the at least one function scenario that does not meet the expected functional safety; determining a safety requirement condition of the target function scenario according to the target behavior in the target function scenario, wherein the safety requirement condition is used to represent conditions that need to be met to address the target behavior; adding a threshold parameter associated with the target behavior to the target function scenario based on the safety requirement condition to obtain the vehicle function scenario.

4. The method of risk assessment of vehicle functional scenarios according to claim 3, wherein, Adding a threshold parameter associated with the target behavior to the target function scenario based on the safety requirement condition to obtain the vehicle function scenario comprises: obtaining a behavior type of the target behavior; determining a threshold type according to the behavior type of the target behavior, wherein the threshold type comprises at least one of a probability threshold value and a numerical threshold value, the probability threshold value is used to represent a threshold value corresponding to a probability of occurrence of the target behavior, and the numerical threshold value is used to represent a threshold value corresponding to an associated numerical value in the target behavior; determining the threshold parameter based on the threshold type and the safety requirement condition; adding the threshold parameter to the target function scenario to obtain the vehicle function scenario.

5. The method of risk assessment of a vehicle functional scenario according to claim 4, wherein, The behavior type comprises at least one of a probability type and a numerical type, and determining a threshold type according to the behavior type of the target behavior comprises: in response to the behavior type being the probability type, determining that the threshold type is the probability threshold value; in response to the behavior type being the numerical type, determining that the threshold type is the numerical threshold value.

6. The method of risk assessment of vehicle functional scenarios according to claim 1, wherein, The analyzing of the target behavior of the intelligent driving function in the function use case to determine the at least one function scenario containing the trigger condition corresponding to the target behavior and the vehicle behavior of the vehicle comprises: determining that a behavior containing a preset keyword in a plurality of behaviors corresponding to the intelligent driving function is the target behavior; determining, as the at least one function scenario, a function scenario in which the intelligent driving function has the target behavior in the different function scenarios; determining, based on a preset correspondence relationship, a vehicle behavior corresponding to the target behavior in the at least one function scenario, wherein the preset correspondence relationship is used to represent a correspondence relationship between the target behavior and the vehicle behavior in the different function scenarios.

7. The method of risk assessment of vehicle functional scenarios according to claim 1, wherein, performing risk assessment on the at least one function scenario based on the vehicle behavior, to obtain an evaluation result, including: determining a risk factor of the vehicle behavior based on a road event formed by the vehicle behavior in the at least one function scenario; performing risk assessment on the at least one function scenario based on a preset road rule and the risk factor, to obtain the evaluation result.

8. The method of risk assessment of vehicle functional scenarios according to claim 7, wherein, performing risk assessment on the at least one function scenario based on a preset road rule and the risk factor, to obtain the evaluation result, including: if the risk factor does not conform to the preset road rule, determining that the evaluation result is that the at least one function scenario does not conform to the expected functional safety; if the risk factor conforms to the preset road rule, performing risk assessment on the at least one function scenario based on a first score and a second score of the risk factor, to obtain the evaluation result, wherein the first score is used to represent a severity of the risk factor by a numerical value, and the second score is used to represent a controllability of the risk factor by a numerical value.

9. The method of risk assessment of a vehicle functional scenario according to claim 8, wherein, performing risk assessment on the at least one function scenario based on a first score and a second score of the risk factor, to obtain the evaluation result, including: if the first score is greater than a preset value and the second score is greater than the preset value, determining that the evaluation result is that the at least one function scenario does not conform to the expected functional safety; if the first score is less than or equal to the preset value or the second score is less than or equal to the preset value, determining that the evaluation result is that the at least one function scenario conforms to the expected functional safety.

10. The method of risk assessment of vehicle functional scenarios according to claim 1, wherein, The method further includes: scoring the risk factor to obtain a scoring result; determining a severity of the risk factor based on the scoring result.

11. The method of risk assessment of vehicle functional scenarios according to claim 1, wherein, The method further includes: determining the vehicle behavior, the road event, and the risk factor; performing risk assessment based on the vehicle behavior, the road event, and the risk factor, to obtain the evaluation result.

12. An electronic device, comprising: a memory storing an executable program; The processor is configured to run the program, and the program performs the following method when running: obtaining a function use case of an intelligent driving function of a vehicle, wherein the function use case is used to represent conditions required to be met by the intelligent driving function in different function scenarios; analyzing a target behavior of the intelligent driving function in the function use case, determining at least one function scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle, wherein the vehicle behavior is formed by an influence of the target behavior on the vehicle, and the target behavior is used to represent an action of the intelligent driving function that does not conform to an expected standard corresponding to the intelligent driving function in a use process; performing risk assessment on the at least one function scenario based on the vehicle behavior, to obtain an assessment result, wherein the assessment result is used to represent whether the at least one function scenario conforms to an expected function safety.

13. The electronic device of claim 12, wherein, The program also performs the following method when running: generating a vehicle function scenario of the vehicle based on the assessment result and the at least one function scenario.

14. A computer readable storage medium comprising a stored executable program, wherein, The executable program controls a device in which the storage medium is located to perform the following method when running: obtaining a function use case of an intelligent driving function of a vehicle, wherein the function use case is used to represent conditions required to be met by the intelligent driving function in different function scenarios; analyzing a target behavior of the intelligent driving function in the function use case, determining at least one function scenario containing a trigger condition corresponding to the target behavior and a vehicle behavior of the vehicle, wherein the vehicle behavior is formed by an influence of the target behavior on the vehicle, and the target behavior is used to represent an action of the intelligent driving function that does not conform to an expected standard corresponding to the intelligent driving function in a use process; performing risk assessment on the at least one function scenario based on the vehicle behavior, to obtain an assessment result, wherein the assessment result is used to represent whether the at least one function scenario conforms to an expected function safety.

15. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 11.

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