Authentication method for high-order function learning of vehicle system and related device
By employing a multi-level learning and certification strategy, the advanced function mastery of drivers is certified at each level, which solves the problem of the disconnect between education programs and real driving scenarios in existing technologies. This improves drivers' learning participation and mastery of advanced functions, reduces accidental misoperation, and enhances the safety and reliability of intelligent driving.
Patent Information
- Application Number
- CN202510888961.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-30
- Publication Date
- 2025-11-04
AI Technical Summary
Existing advanced function education programs are disconnected from real driving scenarios, resulting in low driver user participation and increasing the risk of misoperation and driving accidents.
Through a multi-level learning and certification strategy, including theoretical tests, simulation tests, and real-world driving scenario tests, the advanced function mastery of driver users is certified level by level, ensuring that access to advanced functions is only granted when the certification level reaches the advanced level.
It has improved drivers' initiative and mastery of advanced functions, reduced accidents caused by misoperation, and enhanced the safety and reliability of intelligent driving.
Smart Images
Figure CN120893031A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of new energy commercial vehicle technology, specifically to the technical fields of functional learning hierarchical assessment and certification and incentive conversion, and particularly to a certification method and related device for high-order functional learning of a vehicle system. Background Technology
[0002] In the field of intelligent driving technology, advanced functions are ubiquitous in vehicle systems. Considering that drivers need to master these advanced functions to ensure basic driving safety, existing vehicle systems, or those that have undergone upgrades, will employ online video tutorials or simulator training methods to educate drivers on these advanced functions.
[0003] However, in current advanced function training programs, most drivers neglect to learn advanced functions and easily skip function instructions or simulation training. Some drivers even operate similar advanced functions directly without reading the function instructions, causing driving accidents due to misoperation because they do not fully understand the function boundaries or master the operation of the functions, such as misusing driver assistance functions.
[0004] It is evident that existing functional education programs are disconnected from real-world driving scenarios and have low driver engagement, which can easily lead to misoperation and driving accidents. Summary of the Invention
[0005] This application provides a certification method and related apparatus for upgrading the function learning of a vehicle system, in order to solve the problems that existing function education programs are disconnected from real driving scenarios, and that low driver participation can easily lead to misoperation and driving accidents.
[0006] The technical solution is as follows:
[0007] Firstly, a certification method for high-order function learning in a vehicle system is provided, including:
[0008] In response to a driver user's access request for a target advanced function, query whether the driver user has already learned and certified for the target advanced function;
[0009] If a learned certification is found and the certification level is advanced, then the driver user is allowed to access the target advanced function;
[0010] If no learned certification is found, the first learning certification strategy for the target advanced function is pushed to the driver user so that the driver user can learn and complete the theoretical test of the target advanced function.
[0011] If the theoretical test meets the first authentication condition, record the authentication level of the driver user as primary, and push a second learning authentication strategy of the target high-order function to the driver user, so as to facilitate the driver user to perform a simulation test in a simulation scene constructed based on the second learning authentication strategy; otherwise, automatically exit this access;
[0012] If the operation test meets the second authentication condition, record the authentication level of the driver user as intermediate, and push a third learning authentication strategy of the target high-order function to the driver user, so as to facilitate the driver user to perform a remote supervised operation test in a real road scene; otherwise, automatically exit this access;
[0013] If the remote supervised operation test meets the third authentication condition, record the authentication level of the driver user as advanced, and allow the driver user to access the target high-order function; otherwise, automatically exit this access.
[0014] In a possible implementation, if it is queried that the authentication has been learned, but the authentication level is lower than advanced, the method further includes:
[0015] According to the queried authentication level of the driver user, push a matching learning authentication strategy of the target high-order function to the driver user.
[0016] In a possible implementation, the first authentication condition is that the theoretical test result is all correct; and / or;
[0017] The second authentication condition is that the success rate of the simulation test is not lower than a set first threshold percentage; and / or;
[0018] The third authentication condition is that the scoring result of the remote supervised operation test is not lower than a set second threshold, and / or, the operation proficiency of the remote supervised operation test is not lower than a standard level; wherein, the scoring items of the remote supervised operation test at least include operation error and operation reaction.
[0019] In a possible implementation, after allowing the driver user to access the target high-order function, the method further includes:
[0020] Real-time monitoring of actual operation of the driver on the target high-order function;
[0021] If it is monitored that the actual operation meets a set degradation condition, modify the recorded authentication level of the driver user;
[0022] Wherein, the set degradation condition is that the current actual operation is a violation operation and the number of violation operations reaches a set third threshold, or the current actual operation causes a direct or indirect driving accident.
[0023] In a possible implementation, the method further includes:
[0024] After each test of the driver user is completed, a matching authentication reward is assigned to the driver user according to a test result, where the authentication reward is used by the driver user as an asset exchange right or a service.
[0025] In a second aspect, an authentication device for high-level function learning of a vehicle system is provided, including: a query module, an access module, a theoretical test module, a simulation test module, a real test module, and a quit module; wherein
[0026] The query module is configured to, in response to an access request of a driver user for a target high-level function, query whether the driver user has learned authentication for the target high-level function;
[0027] The access module is configured to, if it is queried that the driver user has learned authentication and the authentication level is advanced, allow the driver user to access the target high-level function;
[0028] The theoretical test module is configured to, if it is not queried that the driver user has learned authentication, push a first learning authentication strategy of the target high-level function to the driver user, so as to facilitate the driver user to learn and complete a theoretical test of the target high-level function;
[0029] The simulation test module is configured to, if the theoretical test meets a first authentication condition, record an authentication level of the driver user as primary, and push a second learning authentication strategy of the target high-level function to the driver user, so as to facilitate the driver user to perform a simulation test in a simulation scene constructed based on the second learning authentication strategy; otherwise, the quit module is executed to automatically quit the access;
[0030] The real test module is configured to, if the operation test meets a second authentication condition, record an authentication level of the driver user as intermediate, and push a third learning authentication strategy of the target high-level function to the driver user, so as to facilitate the driver user to perform a remote supervisory operation test in a real road scene; otherwise, the quit module is executed to automatically quit the access;
[0031] The access module is configured to, if the remote supervisory operation test meets a third authentication condition, record an authentication level of the driver user as advanced, and allow the driver user to access the target high-level function; otherwise, the quit module is executed to automatically quit the access.
[0032] In a third aspect, an electronic device is provided, including:
[0033] at least one processor; and
[0034] a memory in communication connection with the at least one processor; wherein
[0035] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of the aspects and any possible implementation manners described above.
[0036] In a fourth aspect, a computer-readable storage medium is provided, and the storage medium stores at least one instruction, which is loaded and executed by a processor to implement the method of the aspects and any possible implementation manners described above.
[0037] In a fifth aspect, a computer program product is provided, and the computer program product comprises a computer program, which, when executed by a processor, implements the method of the aspects and any possible implementation manners described above.
[0038] In a sixth aspect, an autonomous vehicle is provided, and the autonomous vehicle comprises the electronic device described above.
[0039] The beneficial effects of the technical solutions provided in the present application at least include:
[0040] From the above technical solutions, it can be seen that, in response to an access request of a driver user to a target high-order function, it is determined whether the driver user has learned and authenticated the target high-order function, if the driver user has authenticated the target high-order function and the authentication level is high, the driver user is allowed to access the target high-order function, and if the driver user has not authenticated the target high-order function, the driver user is guided to actively participate in learning the target high-order function through a multi-level learning authentication strategy, and the driver user is assisted to learn and authenticate the target high-order function in stages through theoretical tests, simulation scenarios and real driving scene tests, and after passing the authentication in stages, the driver user is allowed to access the target high-order function. The present application can actively guide the driver user to learn the target high-order function through the learning authentication in stages, and the driver user is allowed to access the target high-order function only when the authentication level is high. Thus, the initiative of the driver user to learn the target high-order function and the mastery of the target high-order function are ensured, the driving accidents caused by the driver user's lack of understanding or lack of proficiency in the target high-order function are reduced, and the safety and reliability of intelligent driving are improved.
[0041] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS
[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description only constitute some of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort belong to the protection scope of the present application.
[0043] Figure 1 is one of the step schematic diagrams of the authentication method for high-level function learning of a vehicle system provided by the embodiments of the present application.
[0044] Figure 2 is another of the step schematic diagrams of the authentication method for high-level function learning of a vehicle system provided by the embodiments of the present application.
[0045] Figure 3 is still another of the step schematic diagrams of the authentication method for high-level function learning of a vehicle system provided by the embodiments of the present application.
[0046] Figure 4 is a structural block diagram of the authentication device for high-level function learning of a vehicle system provided by another embodiment of the present application.
[0047] Figure 5 is a block diagram of the electronic device of the embodiments of the present application. DETAILED DESCRIPTION
[0048] The exemplary embodiments of the present application will be described below with reference to the accompanying drawings, which include various details of the embodiments of the present application to assist in understanding, and should be considered as merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Also, in order to be clear and concise, the description below omits the description of well-known functions and structures.
[0049] Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort belong to the protection scope of the present application.
[0050] It should be noted that the terminal device involved in the embodiments of the present application can include but is not limited to a mobile phone, a personal digital assistant (PDA), a wireless handheld device, a tablet computer, and the like. The display device can include but is not limited to a personal computer, a television, and the like.
[0051] In addition, the term "and / or" in this document merely describes an association relationship of associated objects, which means that there can be three relationships, for example, A and / or B can represent three cases of A alone, A and B together, and B alone. In addition, the character " / " in this document generally represents an "or" relationship between the front and rear associated objects.
[0052] In view of the fact that the existing functional education scheme is disconnected with the real driving scene, and the driver user participation is low, which is easy to cause misoperation driving accidents, therefore, the present application proposes a high-order function learning authentication scheme of a vehicle system, the main invention idea of which is mainly as follows: in response to the access request of the driver user to the target high-order function, it is inquired whether the driver user has learned and authenticated the target high-order function, if the authentication level is high, the access is allowed, if the authentication has not been performed, the driver user is guided to actively participate in learning the high-order function through a multi-level learning authentication strategy, and the driver user is assisted to learn and authenticate step by step in combination with theoretical test, simulation scene and real driving scene test, and after passing the step-by-step authentication, the driver user is allowed to access the high-order function. The present application can let the driver user actively participate in learning the high-order function through step-by-step learning authentication clearance, and the access permission of the high-order function is opened to the driver user only when the authentication level is high, thereby, the initiative of the driver user to learn the high-order function and the mastery degree of the high-order function are ensured, the driving accidents caused by misoperation due to lack of understanding or lack of proficiency of the high-order function are reduced, and the intelligent driving safety and reliability are improved.
[0053] Referring to Figure 1 Fig. 1 shows a step schematic diagram of a high-order function learning authentication method of a vehicle system provided by an embodiment of the present application. The execution subject of the authentication method is an authentication device, which can be a software module or component with functions of data calculation, processing, storage, etc. The authentication device can be deployed on a new energy commercial vehicle to assist in realizing corresponding intelligent driving functions. Alternatively, the authentication device can also be deployed in the cloud and interact with the target commercial vehicle through wireless connection to assist in realizing corresponding intelligent driving functions. It should be understood that the new energy commercial vehicle involved in the present application can be a heavy truck.
[0054] As Figure 1 shown, the high-order function learning authentication method of the vehicle system can include the following steps:
[0055] Step 102: in response to the access request of the driver user to the target high-order function, it is inquired whether the driver user has learned and authenticated the target high-order function.
[0056] In the solution of the present application, the target high-level function can be a functional operation configured on the target commercial vehicle to assist or replace the driver user in implementing some driving skills. For example, automatic auxiliary navigation driving (automatic lane changing and overtaking, on-ramp and off-ramp, speed regulation, etc. on highways / expressways), traffic light recognition and response, memory parking, emergency steering assistance, predictive performance energy recovery (intelligent adjustment of recovery strength based on the slope of the navigation path), etc. The present application only exemplifies the target high-level function, and the scope of the types of functions covered here is not described one by one. It should be understood that the target high-level function in the solution of the present application can also include high-level functions based on the upgrading of the above-mentioned functions in addition to the above-mentioned functions.
[0057] When the driver user wants to start a certain target high-level function during driving the target commercial vehicle, the authentication device on the target commercial vehicle can obtain the access request triggered at the time of starting and respond to the access request. Generally, the access request should carry the identity of the driver user, such as an identity ID or a face image, so that the learning authentication level of the driver user can be queried from the local or cloud database according to the identity to confirm whether the driver user has learned the target high-level function.
[0058] It should be understood that considering that there are multiple high-level functions in the target commercial vehicle, an authentication database can be established locally or in the cloud in advance, and a sub-database can be established for each high-level function in the authentication database. Thus, when a driver user is authenticated step by step through a multi-level learning authentication strategy, the identity of the driver user and the final result of each authentication can be added to and saved in the corresponding sub-database.
[0059] It should be noted that when the driver user accesses the target high-level function, generally only one high-level function is accessed in one access request.
[0060] If it is queried that the learning authentication has been learned and the authentication level is high, step 104 is performed; if it is not queried that the learning authentication has been learned, step 106 is performed.
[0061] Step 104: Allow the driver user to access the target high-level function.
[0062] When the identity of the driver user is queried from the authentication database and the authentication result corresponding to the driver user is high, it means that the driver user has learned and mastered the target high-level function, and the driver is allowed to access the target high-level function, i.e., the driver user is allowed to access the target high-level function.
[0063] Step 106: push a first learning authentication strategy of the target advanced function to the driver user, so as to facilitate the driver user to learn and complete a theoretical test of the target advanced function.
[0064] In the scheme of the present application, the first learning authentication strategy can be to guide the driver user to learn authentication through a theoretical test. In specific implementation, the authentication device can push the driver user with the theoretical test content related to the target advanced function, for example, a plurality of multiple-choice questions determined according to the principle of the target advanced function. The driver user answers the multiple-choice questions to complete the theoretical test of the target advanced function. Specifically, the authentication device can push the theoretical test content to the client held by the driver user, or push the theoretical test content to the display device of the target commercial vehicle.
[0065] If the theoretical test meets the first authentication condition, step 108 is executed; otherwise, the current access is automatically exited.
[0066] Optionally, the first authentication condition is that the theoretical test result is all correct. That is, when the test results of all theory-related multiple-choice questions are all correct, step 108 is executed.
[0067] Step 108: record the authentication level of the driver user as primary, and push a second learning authentication strategy of the target advanced function to the driver user, so as to facilitate the driver user to perform simulation test in a simulation scene constructed based on the second learning authentication strategy.
[0068] After determining that the driver user's theoretical test result is all correct, it is determined that the driver user has basically understood the theoretical content of the target advanced function, and a record is added in the sub-database corresponding to the target advanced function in the authentication database, indicating that the authentication level of the driver user is primary, for example, L1 level.
[0069] Further, after determining that the driver user masters the theoretical content of the target advanced function, the second learning authentication strategy can be further pushed to the driver user, which can be to guide the driver user to test authentication through a simulation driving scene. In specific implementation, the authentication device can send the second learning authentication strategy to the target commercial vehicle, which carries the identifier of the target advanced function, and further can trigger the target commercial vehicle to simulate the driving scene corresponding to the target advanced function through its simulation system (for example, a head-up display device or other systems that can realize simulation), and then prompt the driver user to perform relevant driving operations in the simulated driving scene according to the relevant functions of the target advanced function.
[0070] If the simulation test meets the second authentication condition, step 110 is executed; otherwise, the current access is automatically exited.
[0071] Optionally, the second authentication condition is that a success rate of the simulation test is not lower than a set first threshold percentage. The first threshold percentage can be 80% or 90%, or other values. It should be understood that the relevant driving operation can be repeatedly performed in the simulated driving scene, and the success rate of multiple relevant driving operations is counted to determine whether the operation test meets the second authentication condition.
[0072] Step 110: record the authentication level of the driver user as intermediate, and push a third learning authentication strategy of the target high-level function to the driver user, so as to perform remote supervised operation test of the driver user in a real road scene.
[0073] After determining that the simulation test result of the driver user meets the second authentication condition, it is determined that the driver user has basically mastered the relevant operation of the target high-level function in the simulated driving scene, and a record of the authentication level of the driver user as intermediate, for example, L2 level, is added in the sub-database corresponding to the target high-level function in the authentication database.
[0074] Further, a third learning authentication strategy can be pushed to the driver user, and the third learning authentication strategy can guide the driver user to perform test authentication in a real road scene. In specific implementation, the authentication device can send the third learning authentication strategy to the target commercial vehicle, and the third learning authentication strategy carries the identifier of the target high-level function, and then the driver user can be notified that the target high-level function can be tested in a real road scene, and the test process is supervised remotely by the image acquisition device in the target commercial vehicle, and the remote supervisor scores the authentication test according to the test result.
[0075] If the remote supervised operation test meets the third authentication condition, step 112 is performed; otherwise, the current access is automatically exited.
[0076] Optionally, the third authentication condition is that the score result of the remote supervised operation test is not lower than a set second threshold, and / or the operation proficiency of the remote supervised operation test is not lower than a standard level; wherein the score items of the remote supervised operation test at least include operation error and operation reaction. In specific implementation, the score result of the remote supervised operation test can be not lower than 4.5 points or 5 points, or the operation proficiency of the remote supervised operation test is not lower than level 3, or the score result of the remote supervised operation test can be not lower than 4.5 points and the operation proficiency of the remote supervised operation test is not lower than level 3. It should be understood that the values of the set second threshold and the standard level are only examples and are not limited, and can be flexibly adjusted according to actual needs in specific implementation.
[0077] Step 112: record the authentication level of the driver user as senior, and allow the driver user to access the target high-level function.
[0078] After determining that the remote supervisory test result of the driver user meets the third authentication condition, it is determined that the driver user has basically mastered the operation of the target high-level function in the real road scene, and a record of the authentication level of the driver user as senior, for example, L3 level, is added in the sub-database corresponding to the target high-level function in the authentication database.
[0079] In this way, the learning authentication of the driver user on the target high-level function from understanding to familiarization to mastery can be completed step by step through theoretical test, simulation test and real scene test, the initiative of the driver user in learning the high-level function and the mastery degree of the high-level function are ensured, the driving accidents caused by misoperation due to lack of understanding or lack of familiarity with the high-level function are reduced, and the intelligent driving safety and reliability are improved.
[0080] Optionally, in the scheme of the present application, as shown in Figure 2 If it is found that the driver user has learned the authentication but the authentication level is lower than senior, the following can also be included:
[0081] Step 114: according to the authentication level of the driver user, push the learning authentication strategy of the target high-level function to the driver user.
[0082] In specific implementation, the authentication level of the driver user is determined; if the authentication level is L1, the second learning authentication strategy of the target high-level function is pushed to the driver user; if the authentication level is L2, the third learning authentication strategy of the target high-level function is pushed to the driver user.
[0083] Further, after allowing the driver user to access the target high-level function, the actual operation of the driver on the target high-level function can also be monitored in real time; if the actual operation meets the set degradation condition, the authentication level recorded by the driver user is modified; wherein the set degradation condition is that the current actual operation is a violation operation and the number of violation operations reaches a set third threshold, or the current actual operation directly or indirectly causes a driving accident. The set third threshold can be 3 or 5, which is not limited here. In an actual driving scenario, for example, when it is monitored that the driver performs the operation corresponding to the target high-level function more than 3 times in violation, it is determined that the driver user is not good at mastering the target high-level function, and the operation permission of the driver user on the target high-level function needs to be recovered, at which time the authentication level in the sub-database corresponding to the target high-level function can be modified to L2. When it is monitored that the driver user performs the operation corresponding to the target high-level function directly or indirectly causes a driving accident, it is determined that the driver user is very poor at mastering the target high-level function, and the operation permission of the driver user on the target high-level function needs to be recovered, at which time the authentication level in the sub-database corresponding to the target high-level function can be modified to L1. In this way, the driver user can start learning the authentication from the lowest level, and the initiative of the driver user to participate in learning the high-level function and the degree of mastering the high-level function can be ensured.
[0084] Further, referring to Figure 3 , the authentication method can further include the following steps:
[0085] Step 116: After each test of the driver user is completed, a matching authentication reward is assigned to the driver user according to the test result, wherein the authentication reward is used by the driver user as an asset to exchange interests or services.
[0086] For example, after the driver user obtains the primary authentication level L1, the driver user can be assigned an authentication reward of 50 virtual energy; after the driver user obtains the intermediate authentication level L2, the driver user can be assigned an authentication reward of 300 virtual energy again; and after the driver user obtains the senior authentication level L3, the driver user can be assigned an authentication reward of 200 virtual energy again. These virtual energies can be exchanged for charging services, for example, 1500 energy values exchange 50kWh fast charging coupons; night charging discount: 800 energy values / time. Or exchange hardware upgrade services, for example, 2000 energy values exchange laser radar cleaning service; 500 energy values exchange HUD theme skin, etc.
[0087] In specific implementation, a third-party platform interface can be developed to support the access of external authentication rewards such as charging piles.
[0088] It should be noted that the virtual energy involved in the present application can also be used to characterize the driving skills of the driver, and the driving skills of different drivers are sorted to obtain a driving skill ranking of different driver users, which facilitates display and comparison.
[0089] Example 1 - Highway NOA certification process
[0090] L1 - Theoretical test
[0091] The test can be conducted through 10 multiple-choice questions (such as "What should the driver maintain after NOA activation?"), and if the error rate is <20%, the simulation test is unlocked; or, all correct to unlock the simulation test.
[0092] L2 - Simulation test
[0093] Simulate a virtual scenario: overtaking a slow truck in heavy rain; set evaluation indicators: lane change decision time difference (<0.5 seconds from standard value); steering wheel angle fluctuation rate (<15%); if the condition is met, unlock the real scene test.
[0094] L3 - Real scene test
[0095] Actual highway NOA is turned on, and the safety officer supervises the completion of 3 automatic lane changes and overtaking, 2 entries and exits of ramps, and then the system automatically scores, and decides whether to open the NOA function permission according to the supervision score result.
[0096] Further, after passing the certification, the NOA full function is unlocked, 500 energy values are rewarded (which can be exchanged for advanced driving data reports), the "highway expert" badge is awarded, and the vehicle owner's profile is updated.
[0097] Example 2
[0098] L1 - Theoretical test
[0099] Theoretical test is conducted through 10 scenario-based multiple-choice questions, and if all correct, the theoretical test is passed, and the result simulation test is conducted.
[0100] L2 - Simulation test
[0101] Five types of special scenarios are mainly simulated: red light recognition under strong sunset light, flashing yellow light blocked by trees, large vehicles blocking the view in adjacent lanes, left turn arrow light conflict with straight light, and second reading error calibration.
[0102] L3 - Real scene test
[0103] Route tests are conducted on 3 types of typical intersections: standard crossroads (light group height 15-20 meters), tunnel exit transition zone (light intensity change >10,000 lux), and unprotected left turn intersection (opposite traffic interference).
[0104] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.
[0105] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.
[0106] Figure 4 This application provides a structural block diagram of an authentication device for high-order function learning in a vehicle system, as shown in one embodiment. Figure 4 As shown. This embodiment of a vehicle system's advanced function learning authentication device 400 may include a query module 401, an access module 402, a theoretical testing module 403, a simulation testing module 404, a real testing module 405, and an exit module 406. Specifically, the query module 401 is used to query whether the driver user has already performed learning authentication for the target advanced function in response to the driver user's access request for the target advanced function; the access module 402 is used to allow the driver user to access the target advanced function if learning authentication is found and the authentication level is advanced; the theoretical testing module 403, if no learning authentication is found, pushes a first learning authentication strategy for the target advanced function to the driver user so that the driver user can learn and complete the theoretical test of the target advanced function; the simulation testing module 404, if the theoretical test meets the first authentication condition, records the driver user's authentication level as basic and pushes a second learning authentication strategy for the target advanced function to the driver user so that the driver user can complete the theoretical test of the target advanced function. The driver user performs a simulated test in a simulated scenario constructed based on the second learning and authentication strategy; otherwise, the exit module 406 automatically exits the current access. The real test module 405, if the operation test meets the second authentication condition, records the driver user's authentication level as intermediate and pushes the third learning and authentication strategy of the target advanced function to the driver user, so that the driver user can perform remotely supervised operation testing in a real road scenario; otherwise, the exit module 406 automatically exits the current access. If the remotely supervised operation test meets the third authentication condition, the access module 402 records the driver user's authentication level as advanced, allowing the driver user to access the target advanced function; otherwise, the exit module 406 automatically exits the current access.
[0107] It should be noted that part or all of the authentication device of the high-level function learning of the vehicle system in this embodiment can be an application located at the local terminal, or can also be a functional unit such as a plug-in or a software development kit (Software Development Kit, SDK) arranged in the application located at the local terminal, or can also be a processing engine located in a server on the network side, or can also be a distributed system located on the network side, for example, a processing engine or a distributed system in an automatic driving platform on the network side, and the like, which are not particularly limited in this embodiment.
[0108] It can be understood that the application can be a native application (nativeApp) installed on the local terminal, or can also be a web application (webApp) of a browser on the local terminal, which is not limited in this embodiment.
[0109] Optionally, in a possible implementation manner of this embodiment, the authentication device further includes a selection module, which is configured to, if it is queried that the learning authentication has been learned but the authentication level is lower than the senior, push a learning authentication strategy of the target high-level function matched according to the authentication level of the driver user to the driver user.
[0110] Optionally, in a possible implementation manner of this embodiment, the first authentication condition is that the theoretical test result is all correct; and / or the second authentication condition is that the success rate of the simulation test is not lower than a set first threshold percentage; and / or the third authentication condition is that the scoring result of the remote supervised operation test is not lower than a set second threshold, and / or the operation proficiency of the remote supervised operation test is not lower than a standard level; wherein the scoring items of the remote supervised operation test at least include operation error and operation reaction.
[0111] Optionally, in a possible implementation manner of this embodiment, the authentication device further includes a degradation module, which is configured to, after allowing the driver user to access the target high-level function, monitor the actual operation of the driver on the target high-level function in real time, and modify the authentication level recorded by the driver user when the actual operation meets a set degradation condition; wherein the set degradation condition is that the actual operation is a violation operation and the number of violation operations reaches a set third threshold, or the actual operation causes a direct or indirect driving accident.
[0112] Optionally, in a possible implementation manner of this embodiment, the authentication device further includes an incentive module, which is configured to, after each test of the driver user is completed, allocate a matched authentication reward to the driver user according to the test result, wherein the authentication reward is used by the driver user as an asset to exchange rights or services.
[0113] In this embodiment, in response to a request of the driver user for accessing a target high-level function, it can be determined whether the driver user has passed the learning authentication for the target high-level function. If the driver user has passed the learning authentication and the authentication level is high, the driver user is allowed to access the target high-level function. If the driver user has not passed the learning authentication, the driver user is guided to actively participate in learning the high-level function through a multi-level learning authentication strategy, and is assisted to pass the learning authentication through theoretical tests, simulation scenarios and real driving scenarios. After passing the learning authentication, the driver user is allowed to access the high-level function. The present application can actively guide the driver user to learn the high-level function through the multi-level learning authentication, and only when the authentication level is high, the driver user is allowed to access the high-level function. Thus, the initiative of the driver user to learn the high-level function and the proficiency of the driver user in the high-level function are ensured, and the driving accidents caused by the driver user's lack of understanding or lack of proficiency in the high-level function are reduced, and the safety and reliability of intelligent driving are improved.
[0114] One embodiment of the present application provides a computer readable storage medium, the storage medium storing at least one instruction, the at least one instruction being loaded and executed by a processor to implement the method for authenticating learning of a high-level function of a vehicle system as described above.
[0115] One embodiment of the present application provides an electronic device, the electronic device comprising a processor and a memory, the memory storing at least one instruction, the instruction being loaded and executed by the processor to implement the method for authenticating learning of a high-level function of a vehicle system as described above.
[0116] One embodiment of the present application provides an autonomous vehicle comprising the electronic device as described above. Specifically, the autonomous vehicle can be a vehicle of L2 level and above.
[0117] In the technical solution of the present application, the collection, storage, use, processing, transmission, provision and disclosure of user personal information comply with relevant laws and regulations and do not violate public order and good customs.
[0118] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.
[0119] like Figure 5 As shown, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. The RAM 503 may also store various programs and data required for the operation of the electronic device 500. The computing unit 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.
[0120] Multiple components in electronic device 500 are connected to I / O interface 505, including: input unit 506, such as keyboard, mouse, etc.; output unit 507, such as various types of monitors, speakers, etc.; storage unit 508, such as disk, optical disk, etc.; and communication unit 509, such as network card, modem, wireless transceiver, etc. Communication unit 509 allows electronic device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.
[0121] The computing unit 501 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as the authentication method for higher-order function learning of a vehicle system. For example, in some embodiments, the authentication method for higher-order function learning of a vehicle system can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the authentication method for higher-order function learning of a vehicle system described above can be performed. Alternatively, in other embodiments, computing unit 501 may be configured by any other suitable means (e.g., by means of firmware) to perform authentication methods for learning higher-order functions of the vehicle system.
[0122] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a complex programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
[0123] Program code for carrying out methods of the present application can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces a means for implementing the functions / acts specified in the flowcharts and / or block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, or entirely on a remote machine or server.
[0124] In the context of the present application, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium will include one or more lines of electrical conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0125] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.
[0126] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.
[0127] The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.
[0128] It should be understood that various forms of flow shown above can be used, re-ordered, added to, or deleted from without departing from the spirit of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, in series, or in a different order, without departing from the desired results of the technical solutions of the present disclosure, which are not limited herein.
[0129] The specific embodiments described above are not intended to limit the scope of the present application. Those skilled in the art will understand that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and the principles of the present application. Any further modifications, equivalents, alternatives, and / or improvements made to the specific embodiments relating to the spirit and principles of the present application are to be encompassed within the scope of the present application.
Claims
1. A method of certifying high-order function learning of a vehicle system, characterized by, The method comprises: in response to a driver user's access request for a target high-level function, querying whether the driver user has learned the authentication for the target high-level function; if it is queried that the learning authentication has been learned, and the authentication level is high, the driver user is allowed to access the target high-level function; if it is not queried that the learning authentication has been learned, the driver user is pushed with a first learning authentication strategy of the target high-level function, so as to learn and complete a theoretical test of the target high-level function by the driver user; if the theoretical test meets a first authentication condition, the authentication level of the driver user is recorded as primary, and a second learning authentication strategy of the target high-level function is pushed to the driver user, so as to perform a simulation test by the driver user in a simulation scene constructed based on the second learning authentication strategy; otherwise, automatically exit this access; if the operation test meets a second authentication condition, the authentication level of the driver user is recorded as intermediate, and a third learning authentication strategy of the target high-level function is pushed to the driver user, so as to perform a remote supervisory operation test by the driver user in a real road scene; otherwise, automatically exit this access; if the remote supervisory operation test meets a third authentication condition, the authentication level of the driver user is recorded as high, and the driver user is allowed to access the target high-level function; otherwise, automatically exit this access.
2. The method of claim 1, wherein, If it is queried that the learning authentication has been learned, but the authentication level is lower than high, the method further comprises: according to the authentication level of the driver user queried, the driver user is pushed with a learning authentication strategy of the target high-level function matched.
3. The method of claim 1, wherein, The first authentication condition is that the theoretical test result is all correct; and / or; The second authentication condition is that the success rate of the simulation test is not less than a set first threshold percentage; and / or; The third authentication condition is that the scoring result of the remote supervisory operation test is not less than a set second threshold, and / or, the operation proficiency of the remote supervisory operation test is not less than a standard level; wherein, the scoring items of the remote supervisory operation test at least include operation error and operation reaction.
4. The method of claim 1, wherein, After allowing the driver user to access the target high-level function, the method further comprises: real-time monitoring of the actual operation of the driver on the target high-level function; if a set degradation condition is met in the monitoring of the actual operation, the authentication level recorded by the driver user is modified; wherein, the set degradation condition is that the actual operation at this time is a violation operation and the number of violation operations reaches a set third threshold, or the actual operation at this time causes a direct or indirect driving accident.
5. The method according to any one of claims 1 to 4, wherein The method further comprises: after each test of the driver user is completed, the driver user is assigned with a matched authentication reward according to the test result, wherein the authentication reward is used by the driver user as an asset to exchange interests or services.
6. An authentication device of high-order function learning of a vehicle system, characterized by The method comprises: a querying module, an accessing module, a theoretical test module, a simulation test module, a real test module and an exiting module; wherein, The query module is configured to query whether the driver user has learned and authenticated the target high-level function in response to an access request of the driver user to the target high-level function. The access module is configured to allow the driver user to access the target high-level function if it is queried that the driver user has learned and authenticated the target high-level function and the authentication level is advanced. The theoretical test module is configured to push a first learning authentication strategy of the target high-level function to the driver user if it is not queried that the driver user has learned and authenticated the target high-level function, so as to facilitate the driver user to learn and complete a theoretical test of the target high-level function. The simulation test module is configured to record the authentication level of the driver user as junior if the theoretical test meets a first authentication condition, and push a second learning authentication strategy of the target high-level function to the driver user, so as to facilitate the driver user to perform a simulation test in a simulation scene constructed based on the second learning authentication strategy; otherwise, the exit module is configured to automatically exit the current access. The real test module is configured to record the authentication level of the driver user as intermediate if the operation test meets a second authentication condition, and push a third learning authentication strategy of the target high-level function to the driver user, so as to facilitate the driver user to perform a remote supervisory operation test in a real road scene; otherwise, the exit module is configured to automatically exit the current access. The access module is configured to record the authentication level of the driver user as advanced if the remote supervisory operation test meets a third authentication condition, and allow the driver user to access the target high-level function; otherwise, the exit module is configured to automatically exit the current access.
7. An electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1-5.
8. A non-transitory computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions are used to enable the computer to perform the method according to any one of claims 1-5.
9. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-5.
10. An autonomous vehicle comprising the electronic device according to claim 7.