Method and device for evaluating advanced driver assistance system, vehicle and storage medium

Abstract

The application relates to an evaluation method and device of an advanced driving assistance system, a vehicle and a storage medium, wherein the method comprises the following steps: constructing a chip and sensor model library, and importing at least one important attribute in the chip and sensor model library into a key device database; using devices in the key device database to model an overall system scheme of the advanced driving assistance system, to obtain a modeled system scheme; importing the system scheme and a target function list into a preset evaluation model, and evaluating the advanced driving assistance system according to at least one of computing power, storage, an interface, transmission bandwidth and cost estimation, to generate an evaluation result. Therefore, the problems that, in the related art, the evaluation of the overall technical scheme in the design process of the advanced driving assistance system lacks objectivity, the evaluation scheme is single, the evaluation accuracy is low, the system design process is not comprehensive, the system design efficiency is low, and the design quality cannot be guaranteed are solved.

Description

Technical Field

[0001] This application relates to the field of advanced driver assistance system design technology, and in particular to an evaluation method, device, vehicle and storage medium for an advanced driver assistance system. Background Technology

[0002] In recent years, the automotive industry has developed rapidly, and the level of vehicle intelligence has increased significantly. Roads, traffic, and safety are issues of concern to everyone. How to improve the active safety of vehicles has become a hot topic of attention and research. ADAS (Advanced Driving Assistance System) uses sensors installed in the vehicle to collect environmental data inside and outside the vehicle, and to identify, detect, and track static and dynamic objects. This allows drivers to detect potential dangers in the shortest possible time, thereby drawing their attention and improving safety.

[0003] Among the relevant technologies, one approach is manual evaluation, where professionals independently conduct evaluations and assess various system parameters after the system design is completed; another approach is to utilize an evaluation index system to evaluate the data in the test files.

[0004] However, in the design process of advanced driver assistance systems, the evaluation of the overall technical solution lacks objectivity, the evaluation scheme is singular, the evaluation accuracy is low, and the problem of incomplete system design process is not considered. As a result, the system design efficiency is low and the design quality cannot be guaranteed, which urgently needs to be improved. Summary of the Invention

[0005] This application provides an evaluation method, device, vehicle, and storage medium for an advanced driver assistance system (ADAS) to address the problems in related technologies, such as the lack of objectivity in the evaluation of the overall technical solution during the design process of ADAS, the single evaluation scheme, the low evaluation accuracy, the failure to consider the incomplete system design process, the low system design efficiency, and the inability to guarantee design quality.

[0006] The first aspect of this application provides an evaluation method for an advanced driver assistance system, comprising the following steps: constructing a chip and sensor model library, and importing at least one important attribute from the chip and sensor model library into a key component database; using the components in the key component database to model the overall system scheme of the advanced driver assistance system, obtaining the modeled system scheme; and importing the system scheme and a list of target functions into a preset evaluation model, evaluating the advanced driver assistance system based on at least one of computing power, storage, interface, transmission bandwidth, and cost estimation, and generating an evaluation result.

[0007] Optionally, in one embodiment of this application, after evaluating the advanced driver assistance system based on at least one of computing power, storage, interface, transmission bandwidth, and cost estimates, and generating evaluation results, the method further includes: generating an evaluation report based on the evaluation results, and generating iterative parameters for the advanced driver assistance system based on the evaluation report, so as to iteratively optimize the advanced driver assistance system until a preset iteration stop condition is met, thereby obtaining the final system solution of the advanced driver assistance system.

[0008] Optionally, in one embodiment of this application, the construction of the chip and sensor model library includes: performing chip modeling based on at least one of the following attributes: central processing unit computing power, artificial intelligence computing power, random access memory, memory chip, interface type, and number of interfaces, to obtain a chip model; performing sensor modeling based on at least one of the following attributes: detection distance, field of view, data transmission volume, interface type, and number of interfaces, to obtain a sensor model; and constructing the chip and sensor model library based on the chip model and the sensor model.

[0009] Optionally, in one embodiment of this application, the key component database includes at least one of the attributes of the advanced driver assistance system: functionality, performance, and cost.

[0010] Optionally, in one embodiment of this application, modeling the overall system scheme of the advanced driver assistance system using the devices in the key device database includes: modeling the overall system scheme of the advanced driver assistance system using the hardware architecture and system architecture within the domain controller.

[0011] A second aspect of this application provides an evaluation apparatus for an advanced driver assistance system (ADAS), comprising: a construction module for constructing a chip and sensor model library and importing at least one important attribute from the chip and sensor model library into a key component database; an acquisition module for modeling an overall system scheme of the ADAS using the components in the key component database to obtain a modeled system scheme; and an evaluation module for importing the system scheme and a list of target functions into a preset evaluation model, evaluating the ADAS based on at least one of computing power, storage, interface, transmission bandwidth, and cost estimation, and generating an evaluation result.

[0012] Optionally, in one embodiment of this application, it further includes: an optimization module, configured to evaluate the advanced driver assistance system based on at least one of computing power, storage, interface, transmission bandwidth and cost estimates, generate an evaluation report based on the evaluation results, and generate iterative parameters of the advanced driver assistance system based on the evaluation report, so as to iteratively optimize the advanced driver assistance system until a preset iteration stop condition is met, thereby obtaining the final system solution of the advanced driver assistance system.

[0013] Optionally, in one embodiment of this application, the construction module includes: a first acquisition unit, configured to perform chip modeling based on at least one of the following attributes: central processing unit computing power, artificial intelligence computing power, random access memory, memory chip, interface type, and number of interfaces, to obtain a chip model; a second acquisition unit, configured to perform sensor modeling based on at least one of the following attributes: detection distance, field of view, data transmission volume, interface type, and number of interfaces, to obtain a sensor model; and a construction unit, configured to construct the chip and sensor model library based on the chip model and the sensor model.

[0014] Optionally, in one embodiment of this application, the key component database includes at least one of the attributes of the advanced driver assistance system: functionality, performance, and cost.

[0015] Optionally, in one embodiment of this application, the acquisition module includes: a modeling unit, used to model the overall system scheme of the advanced driver assistance system using the hardware architecture and system architecture within the domain controller.

[0016] A third aspect of this application provides a vehicle including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the evaluation method for an advanced driver assistance system as described in the above embodiments.

[0017] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described evaluation method for an advanced driver assistance system.

[0018] This application embodiment can use components from a key component database to model the overall system solution of an advanced driver assistance system (ADAS). The functional list and system solution are imported into the evaluation model for multi-dimensional evaluation, thereby achieving automated evaluation of the ADAS design and providing optimization suggestions. This improves the efficiency and quality of ADAS design, increases system design efficiency, and reduces the probability of errors. Therefore, it solves the problems in related technologies, such as the lack of objectivity in the evaluation of the overall technical solution during ADAS design, the single evaluation scheme, low evaluation accuracy, and the failure to consider the comprehensiveness of the system design process, resulting in low system design efficiency and inability to guarantee design quality.

[0019] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0020] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0021] Figure 1 This is a flowchart of an evaluation method for an advanced driver assistance system according to an embodiment of this application;

[0022] Figure 2 This is a schematic diagram illustrating the principle of an evaluation method for an advanced driver assistance system according to an embodiment of this application;

[0023] Figure 3 This is a schematic diagram of the structure of an evaluation device for an advanced driver assistance system according to an embodiment of this application;

[0024] Figure 4 This is a structural schematic diagram of a vehicle provided according to an embodiment of this application. Detailed Implementation

[0025] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0026] The following description, with reference to the accompanying drawings, outlines an evaluation method, apparatus, vehicle, and storage medium for an advanced driver assistance system (ADAS) according to embodiments of this application. Addressing the issues raised in the background section regarding the lack of objectivity, simplistic evaluation schemes, low accuracy, and incomplete system design considerations in the design process of ADAS, resulting in low system design efficiency and compromised design quality, this application provides an evaluation method for ADAS. This method utilizes components from a key component database to model the overall system design of the ADAS. The functional list and system design are imported into the evaluation model for multi-dimensional evaluation, thereby automating the evaluation of the ADAS design and providing optimization suggestions. This improves the efficiency and quality of ADAS design, reduces the probability of errors, and enhances system design efficiency. Therefore, this method solves the problems of lack of objectivity, simplistic evaluation schemes, low accuracy, incomplete system design considerations, low system design efficiency, and compromised design quality in the design process of ADAS.

[0027] Specifically, Figure 1 This is a flowchart illustrating an evaluation method for an advanced driver assistance system provided in an embodiment of this application.

[0028] like Figure 1 As shown, the evaluation method for this advanced driver assistance system includes the following steps:

[0029] In step S101, a chip and sensor model library is constructed, and at least one important attribute from the chip and sensor model library is imported into the key device database.

[0030] It is understood that the chip and sensor model library in the embodiments of this application can be created manually.

[0031] In actual implementation, the embodiments of this application can manually create a chip and sensor model library, and import the important attributes in the chip and sensor model library into the overall key device database for use in the design of advanced driver assistance systems.

[0032] This application embodiment can import at least one important attribute from the chip and sensor model library into the key device database, thereby improving the design efficiency of advanced driver assistance systems and reducing the probability of errors.

[0033] Optionally, in one embodiment of this application, constructing a chip and sensor model library includes: performing chip modeling based on at least one of the following attributes: central processing unit computing power, artificial intelligence computing power, random access memory, memory chip, interface type, and number of interfaces, to obtain a chip model; performing sensor modeling based on at least one of the following attributes: detection distance, field of view, data transmission volume, interface type, and number of interfaces, to obtain a sensor model; and constructing a chip and sensor model library based on the chip model and the sensor model.

[0034] It is understandable that, such as Figure 2 As shown, the chip model obtained by the chip modeling embodiments of this application includes attributes such as CPU (Central Processing Unit) computing power, AI (artificial intelligence) computing power, RAM (random access memory), Flash (a type of memory chip), interface type, and number of interfaces; the sensor model obtained by the sensor model obtained by the sensor model of this application includes attributes such as detection distance, FOV (Field of View), data transmission volume, interface type, and number of interfaces.

[0035] In actual implementation, the embodiments of this application can perform chip modeling based on attributes such as central processing unit computing power, artificial intelligence computing power, random access memory, memory chip, interface type and number of interfaces to obtain a chip model. Sensor modeling can be performed based on attributes such as detection distance, field of view, data transmission volume, interface type and number of interfaces to obtain a sensor model. A chip and sensor model library can be constructed based on the chip model and sensor model, thereby greatly improving the efficiency and quality of advanced driver assistance system design, with high intelligence and practicality.

[0036] The embodiments of this application can construct a chip and sensor model library based on chip models and sensor models, providing support for the interaction between the chip and sensor model library and the key component database, thereby improving the efficiency and quality of advanced driver assistance system design.

[0037] Optionally, in one embodiment of this application, the key component database includes at least one of the attributes of advanced driver assistance systems: functionality, performance, and cost.

[0038] It is understood that the key component database in the embodiments of this application includes attributes related to the design of advanced driver assistance systems, which can be vehicle advanced driver assistance systems.

[0039] In actual implementation, the embodiments of this application can further improve the efficiency and quality of advanced driver assistance system (ADAS) design by utilizing the attributes of key component databases such as the functions, performance, and cost of ADAS.

[0040] In step S102, the overall system scheme of the advanced driver assistance system is modeled using the components in the key component database to obtain the modeled system scheme.

[0041] It is understood that the overall system solution in this application embodiment includes a SYSML model, and this application embodiment includes tools, databases and automation scripts that can support SYSML modeling.

[0042] In actual implementation, the embodiments of this application can use the devices in the key device database to model the overall system scheme of the advanced driver assistance system, thereby obtaining the modeled system scheme, thereby improving the efficiency and quality of advanced driver assistance system design, minimizing or eliminating incomplete considerations during the design process through toolchains and automation, and intuitively pointing out the deficiencies in the system design.

[0043] Optionally, in one embodiment of this application, the overall system scheme of the advanced driver assistance system is modeled using the devices in the key device database, including: modeling the overall system scheme of the advanced driver assistance system using the hardware architecture and system architecture within the domain controller.

[0044] It is understood that the domain controller in the embodiments of this application can be one or more domain controllers that can control other servers within the domain, and the hardware architecture and system architecture can be the communication link between the sensor and the domain controller, etc.

[0045] In actual implementation, the embodiments of this application can use the hardware architecture and system architecture inside the domain controller in the key component database to model the overall system solution of the advanced driver assistance system. When designing the hardware architecture inside the domain controller, the TOP10-15 key components can be used. When designing the hardware architecture and system architecture inside the domain controller, the communication link between the sensor and the domain controller can be used.

[0046] This application embodiment can use the hardware architecture and system architecture inside the domain controller to model the overall system solution of the advanced driver assistance system, thereby further improving the efficiency and quality of advanced driver assistance system design, and minimizing or reducing the situation of incomplete consideration during the design process through toolchain and automation.

[0047] In step S103, the system scheme and target function list are imported into the preset evaluation model, and the advanced driver assistance system is evaluated based on at least one of computing power, storage, interface, transmission bandwidth and cost estimation, and evaluation results are generated.

[0048] It is understood that the preset evaluation model in this application embodiment can evaluate advanced driver assistance system solutions from different dimensions based on past project experience values ​​through evaluation algorithms.

[0049] In actual implementation, such as Figure 2 As shown in the embodiments of this application, the system scheme and target function list can be imported into a preset evaluation model. The advanced driver assistance system can be evaluated from multiple dimensions such as computing power, storage, interface, transmission bandwidth and cost estimation, and evaluation results can be generated. Based on the evaluation results, the design of the advanced driver assistance system can be automatically evaluated and optimization suggestions can be proposed to improve the efficiency and quality of system design and reduce the probability of errors.

[0050] For example, in this application embodiment, the total computing power required can be determined based on the target function list and compared with the available computing power calculated by the system design model. For instance, if high-speed NOA (Automatic Navigation Assist) requires more than 10 TOPS of computing power, and the total computing power of the system solution is 8 TOPS (Tera Operations Per Second, a unit of processor computing power), the evaluation result is "not passed." Another example is that in this application embodiment, high-speed NOA requires high-precision maps, which require 16GB of Flash memory. The OS (Operating System) and applications require approximately 16GB, and the system solution provides 40GB of available Flash memory, so the evaluation result is "passed." Yet another example is that in this application embodiment, the system model uses a 7V driving solution, but the chip can only process 6V data simultaneously, so the evaluation result is "not passed."

[0051] The embodiments of this application can evaluate advanced driver assistance systems based on computing power, storage, interfaces, transmission bandwidth, and cost estimates, generate evaluation results, and minimize or avoid incomplete considerations during the design process through toolchains and automation, intuitively pointing out the deficiencies in the system design.

[0052] It should be noted that the preset evaluation model can be set by those skilled in the art according to the actual situation, and no specific restrictions are imposed here.

[0053] Optionally, in one embodiment of this application, after evaluating the advanced driver assistance system based on at least one of computing power, storage, interface, transmission bandwidth and cost estimates, and generating evaluation results, the method further includes: generating an evaluation report based on the evaluation results, and generating iterative parameters for the advanced driver assistance system based on the evaluation report, so as to iteratively optimize the advanced driver assistance system until a preset iteration stop condition is met, thereby obtaining the final system solution of the advanced driver assistance system.

[0054] As one possible implementation, embodiments of this application can generate an evaluation report based on the evaluation results, and generate iterative parameters for the advanced driver assistance system based on the evaluation report, so as to iteratively optimize the advanced driver assistance system and mark the areas that can be optimized in the system scheme until the preset iteration stop condition is met, thereby obtaining the final system scheme of the advanced driver assistance system, thereby improving the efficiency and quality of advanced driver assistance system design, and is expected to save more than 2 / 3 of the design workload.

[0055] The database and evaluation algorithm in this application embodiment can be continuously iterated and upgraded, and the level of the corresponding evaluation system will also be continuously improved, eventually reaching a high-quality professional level, thereby reducing the probability of errors.

[0056] The evaluation method for advanced driver assistance systems (ADAS) proposed in this application can model the overall system design of an ADAS using components from a key component database. The functional list and system design are then imported into the evaluation model for multi-dimensional evaluation. This achieves automated evaluation of ADAS design and provides optimization suggestions, improving the efficiency and quality of ADAS design, increasing system design efficiency, and reducing the probability of errors. This solves the problems in related technologies where the evaluation of the overall technical solution in the ADAS design process lacks objectivity, uses a single evaluation scheme, has low accuracy, fails to consider the comprehensiveness of the system design process, and results in low system design efficiency and an inability to guarantee design quality.

[0057] Next, the evaluation apparatus for an advanced driver assistance system according to an embodiment of this application is described with reference to the accompanying drawings.

[0058] Figure 3 This is a schematic diagram of the structure of an evaluation device for an advanced driver assistance system according to an embodiment of this application.

[0059] like Figure 3 As shown, the evaluation device 10 for the advanced driver assistance system includes: a construction module 100, an acquisition module 200, and an evaluation module 300.

[0060] Specifically, module 100 is used to build a chip and sensor model library and import at least one important attribute from the chip and sensor model library into a key device database.

[0061] The acquisition module 200 is used to model the overall system scheme of the advanced driver assistance system using the components in the key component database, and obtain the modeled system scheme.

[0062] The evaluation module 300 is used to import the system scheme and target function list into the preset evaluation model, evaluate the advanced driver assistance system based on at least one of computing power, storage, interface, transmission bandwidth and cost estimation, and generate evaluation results.

[0063] Optionally, in one embodiment of this application, the evaluation device 10 for the advanced driver assistance system further includes an optimization module.

[0064] The optimization module is used to evaluate the advanced driver assistance system based on at least one of the following: computing power, storage, interface, transmission bandwidth and cost estimation. After generating the evaluation results, it generates an evaluation report based on the evaluation results and generates iterative parameters for the advanced driver assistance system based on the evaluation report. The advanced driver assistance system is then iteratively optimized until a preset iteration stop condition is met, resulting in the final system solution of the advanced driver assistance system.

[0065] Optionally, in one embodiment of this application, the construction module 100 includes: a first acquisition unit, a second acquisition unit, and a construction unit.

[0066] The first acquisition unit is used to perform chip modeling based on at least one of the following attributes: central processing unit computing power, artificial intelligence computing power, random access memory, memory chip, interface type, and number of interfaces, to obtain a chip model.

[0067] The second acquisition unit is used to model the sensor based on at least one of the following attributes: detection distance, field of view, amount of transmitted data, interface type, and number of interfaces, to obtain a sensor model.

[0068] The building unit is used to build a chip and sensor model library based on the chip model and sensor model.

[0069] Optionally, in one embodiment of this application, the key component database includes at least one of the attributes of advanced driver assistance systems: functionality, performance, and cost.

[0070] Optionally, in one embodiment of this application, the acquisition module 200 includes: an establishment unit.

[0071] Among them, the establishment unit is used to model the overall system scheme of the advanced driver assistance system using the hardware architecture and system architecture inside the domain controller.

[0072] It should be noted that the foregoing explanation of the evaluation method embodiment for advanced driver assistance systems also applies to the evaluation device for the advanced driver assistance system in this embodiment, and will not be repeated here.

[0073] The evaluation apparatus for advanced driver assistance systems (ADAS) proposed in this application can model the overall system scheme of the ADAS using components from a key component database. It imports the function list and system scheme into the evaluation model and evaluates the system from multiple dimensions. This achieves automated evaluation of the ADAS design and provides optimization suggestions, thereby improving the efficiency and quality of ADAS design, increasing system design efficiency, and reducing the probability of errors. This solves the problems in related technologies where the evaluation of the overall technical scheme in the ADAS design process lacks objectivity, the evaluation scheme is singular, the evaluation accuracy is low, and the system design process is not comprehensively considered, resulting in low system design efficiency and an inability to guarantee design quality.

[0074] Figure 4 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include:

[0075] The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0076] When processor 402 executes the program, it implements the evaluation method for the advanced driver assistance system provided in the above embodiments.

[0077] Furthermore, the vehicle also includes:

[0078] Communication interface 403 is used for communication between memory 401 and processor 402.

[0079] The memory 401 is used to store computer programs that can run on the processor 402.

[0080] The memory 401 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0081] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 4The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0082] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0083] Processor 402 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0084] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described evaluation method for an advanced driver assistance system.

[0085] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0086] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0087] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0088] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0089] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0090] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0091] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0092] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for evaluating an advanced driver assistance system, characterized in that, Includes the following steps: Construct a chip and sensor model library, and import at least one important attribute from the chip and sensor model library into a key device database; The overall system scheme of the advanced driver assistance system is modeled using the components in the key component database to obtain the modeled system scheme. as well as The system scheme and target function list are imported into a preset evaluation model. The advanced driver assistance system is evaluated based on at least one of computing power, storage, interface, transmission bandwidth and cost estimation, and evaluation results are generated. The construction of the chip and sensor model library includes: performing chip modeling based on at least one of the following attributes: central processing unit computing power, artificial intelligence computing power, random access memory, memory chip, interface type, and number of interfaces, to obtain a chip model; performing sensor modeling based on at least one of the following attributes: detection distance, field of view, data transmission volume, interface type, and number of interfaces, to obtain a sensor model; and constructing the chip and sensor model library based on the chip model and the sensor model. The step of modeling the overall system scheme of the advanced driver assistance system using the devices in the key device database includes: modeling the overall system scheme of the advanced driver assistance system using the hardware architecture and system architecture within the domain controller.

2. The method according to claim 1, characterized in that, After evaluating the advanced driver assistance system based on at least one of the following: computing power, storage, interface, transmission bandwidth, and cost estimates, and generating evaluation results, the process further includes: An evaluation report is generated based on the evaluation results, and iterative parameters for the advanced driver assistance system are generated based on the evaluation report to iteratively optimize the advanced driver assistance system until a preset iteration stop condition is met, thereby obtaining the final system solution of the advanced driver assistance system.

3. The method according to claim 1, characterized in that, The key component database includes at least one of the attributes of the advanced driver assistance system: functionality, performance, and cost.

4. An evaluation device for an advanced driver assistance system, characterized in that, The evaluation method for an advanced driver assistance system as described in any one of claims 1-3 includes: A building module is used to build a chip and sensor model library and import at least one important attribute from the chip and sensor model library into a key device database; The acquisition module is used to model the overall system scheme of the advanced driver assistance system using the components in the key component database, and obtain the modeled system scheme; and The evaluation module is used to import the system scheme and target function list into a preset evaluation model, evaluate the advanced driver assistance system based on at least one of computing power, storage, interface, transmission bandwidth and cost estimation, and generate evaluation results.

5. The apparatus according to claim 4, characterized in that, Also includes: An optimization module is used to evaluate the advanced driver assistance system based on at least one of computing power, storage, interface, transmission bandwidth and cost estimates, generate evaluation results, generate an evaluation report based on the evaluation results, and generate iterative parameters for the advanced driver assistance system based on the evaluation report, so as to iteratively optimize the advanced driver assistance system until a preset iteration stop condition is met, and obtain the final system solution of the advanced driver assistance system.

6. The apparatus according to claim 5, characterized in that, The building module includes: The first acquisition unit is used to perform chip modeling based on at least one of the following attributes: central processing unit computing power, artificial intelligence computing power, random access memory, memory chip, interface type and number of interfaces, to obtain a chip model. The second acquisition unit is used to perform sensor modeling based on at least one of the following attributes: detection distance, field of view, amount of transmitted data, interface type, and number of interfaces, to obtain a sensor model. The construction unit is used to construct the chip and sensor model library based on the chip model and the sensor model.

7. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the evaluation method for an advanced driver assistance system as described in any one of claims 1-3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the evaluation method for the advanced driver assistance system as described in any one of claims 1-3.

Images