CN117688750A - Advanced driving assistance system evaluation method, advanced driving assistance system evaluation device, vehicle and storage medium - Google Patents
Advanced driving assistance system evaluation method, advanced driving assistance system evaluation device, vehicle and storage medium Download PDFInfo
- Publication number
- CN117688750A CN117688750A CN202311693673.5A CN202311693673A CN117688750A CN 117688750 A CN117688750 A CN 117688750A CN 202311693673 A CN202311693673 A CN 202311693673A CN 117688750 A CN117688750 A CN 117688750A
- Authority
- CN
- China
- Prior art keywords
- driving assistance
- advanced driving
- assistance system
- evaluation
- chip
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 116
- 230000005540 biological transmission Effects 0.000 claims abstract description 22
- 238000004364 calculation method Methods 0.000 claims abstract description 20
- 238000013210 evaluation model Methods 0.000 claims abstract description 14
- 238000000034 method Methods 0.000 claims description 25
- 230000006870 function Effects 0.000 claims description 20
- 238000005457 optimization Methods 0.000 claims description 16
- 238000012545 processing Methods 0.000 claims description 10
- 238000013473 artificial intelligence Methods 0.000 claims description 9
- 238000010276 construction Methods 0.000 claims description 8
- 238000001514 detection method Methods 0.000 claims description 8
- 238000004590 computer program Methods 0.000 claims description 7
- 238000013461 design Methods 0.000 abstract description 44
- 238000012938 design process Methods 0.000 abstract description 18
- 238000005516 engineering process Methods 0.000 abstract description 8
- 238000004891 communication Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 9
- 230000008676 import Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000003491 array Methods 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 238000013515 script Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Landscapes
- Combined Controls Of Internal Combustion Engines (AREA)
Abstract
The application relates to an evaluation method, an evaluation device, a vehicle and a storage medium of an advanced driving assistance system, wherein the evaluation 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; modeling an overall system scheme of the advanced driving assistance system by using devices in the key device database to obtain a modeled system scheme; and importing the system scheme and the target function list into a preset evaluation model, evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost evaluation, and generating an evaluation result. Therefore, the problems that in the related technology, the evaluation of the whole 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 problem that the system design process is not comprehensive is not considered, the system design efficiency is low, the design quality cannot be guaranteed and the like are solved.
Description
Technical Field
The present disclosure relates to the field of advanced driving assistance system design technologies, and in particular, to an evaluation method and apparatus for an advanced driving assistance system, a vehicle, and a storage medium.
Background
In recent years, the development of the automobile industry is rapid, the intelligent degree of the automobile is greatly improved, the road, traffic and safety are all the problems concerned by everyone, and how to improve the active safety of the automobile becomes a focus of attention and research. ADAS (Advanced Driving Assistance System ) collects the environmental data inside and outside the vehicle by using the sensors installed on the vehicle, and performs identification, detection and tracking of static and dynamic objects, so that a driver can perceive possible danger in the fastest time, thereby attracting attention and improving safety.
In the related technology, on one hand, in the method for manually evaluating, each professional independently evaluates each parameter of the system after the system is designed; on the other hand, the data in the test file can be evaluated by using an evaluation index system.
However, 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 problem of incomplete system design process is not considered, the system design efficiency is low, the design quality cannot be ensured, and improvement is needed.
Disclosure of Invention
The application provides an evaluation method, an evaluation device, a vehicle and a storage medium of an advanced driving assistance system, which are used for solving the problems that in the related technology, the evaluation of an overall technical scheme in the design process of the advanced driving assistance system is lack of objectivity, the evaluation scheme is single, the evaluation accuracy is low, the problem that the system design process is not comprehensive is not considered, the system design efficiency is low, the design quality cannot be guaranteed and the like.
An embodiment of a first aspect of the present application provides a method for evaluating an advanced driving assistance system, including the steps of: 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; modeling an overall system scheme of the advanced driving assistance system by using devices in the key device database to obtain a modeled system scheme; and importing the system scheme and the target function list into a preset evaluation model, evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost evaluation, and generating an evaluation result.
Optionally, in one embodiment of the present application, after evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost estimation, generating an evaluation result further includes: generating an evaluation report according to the evaluation result, and generating iteration parameters of the advanced driving assistance system according to the evaluation report so as to carry out iteration optimization on the advanced driving assistance system until a preset iteration stop condition is met, so as to obtain a final system scheme of the advanced driving assistance system.
Optionally, in an embodiment of the present application, the building a chip and sensor model library includes: performing chip modeling according to at least one attribute of the computing power of the central processing unit, the computing power of the artificial intelligence, the random access memory, the storage chip, the interface type and the interface quantity to obtain a chip model; modeling a sensor according to at least one attribute of the detection distance, the angle of view, the transmission data quantity, the interface type and the interface quantity to obtain a sensor model; and constructing the chip and sensor model library according to the chip model and the sensor model.
Optionally, in one embodiment of the present application, the key device database includes at least one attribute of a function, performance, and cost of the advanced driving assistance system.
Optionally, in an embodiment of the present application, the modeling the overall system scheme of the advanced driving assistance system using the devices in the key device database includes: the overall system scheme of the advanced driving assistance system is modeled using hardware architecture and system architecture inside the domain control.
An embodiment of a second aspect of the present application provides an evaluation device of an advanced driving assistance system, including: the construction module is used for constructing a chip and sensor model library and importing at least one important attribute in the chip and sensor model library into the key device database; the acquisition module is used for modeling the whole system scheme of the advanced driving assistance system by using the devices in the key device database to obtain a modeled system scheme; and the evaluation module is used for importing the system scheme and the target function list into a preset evaluation model, evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost estimation, and generating an evaluation result.
Optionally, in one embodiment of the present application, further includes: and the optimization module is used for evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost estimation, generating an evaluation result, generating an evaluation report according to the evaluation result, generating iteration parameters of the advanced driving assistance system according to the evaluation report, and carrying out iterative optimization on the advanced driving assistance system until a preset iteration stop condition is met, so as to obtain a final system scheme of the advanced driving assistance system.
Optionally, in one embodiment of the present application, the building block includes: the first acquisition unit is used for carrying out chip modeling according to at least one attribute of the computing power of the central processing unit, the computing power of the artificial intelligence, the random access memory, the memory chip, the interface type and the interface quantity to obtain a chip model; the second acquisition unit is used for carrying out sensor modeling according to at least one attribute of the detection distance, the angle of view, the transmission data quantity, the interface type and the interface quantity to obtain a sensor model; and the construction unit is used for constructing the chip and sensor model library according to the chip model and the sensor model.
Optionally, in one embodiment of the present application, the key device database includes at least one attribute of a function, performance, and cost of the advanced driving assistance system.
Optionally, in one embodiment of the present application, the acquiring module includes: and the establishing unit is used for modeling the whole system scheme of the advanced driving assistance system by using the hardware architecture and the system architecture in the domain control.
An embodiment of a third aspect of the present application provides a vehicle, including: the system comprises a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to realize the evaluation method of the advanced driving assistance system as described in the embodiment.
A fourth aspect of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of evaluating an advanced driving assistance system as above.
According to the embodiment of the application, the device in the key device database can be used for modeling the whole system scheme of the advanced driving assistance system, the function list and the system scheme are imported into the evaluation model, and evaluation is carried out from multiple dimensions, so that automatic evaluation of the advanced driving assistance system design is realized, optimization suggestions are provided, efficiency and quality of the advanced driving assistance system design are improved, system design efficiency is improved, and error probability is reduced. Therefore, the problems that in the related technology, the evaluation of the whole 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 problem that the system design process is not comprehensive is not considered, the system design efficiency is low, the design quality cannot be guaranteed and the like are solved.
Additional aspects and advantages of the 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 the application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart of an evaluation method of an advanced driving assistance system provided according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an evaluation method of an advanced driving assistance system according to one embodiment of the present application;
fig. 3 is a schematic structural view of an evaluation device of an advanced driving assistance system according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.
An evaluation method, apparatus, vehicle, and storage medium of an advanced driving assistance system of an embodiment of the present application are described below with reference to the accompanying drawings. Aiming at the problems that in the related art mentioned in the background art, the evaluation of the whole technical scheme is lack of objectivity, the evaluation scheme is single, the evaluation accuracy is low, and the incomplete system design process is not considered, and the system design efficiency is low, and the design quality cannot be guaranteed, the application provides an evaluation method of the advanced driving assistance system, in the method, devices in a key device database can be used for modeling the whole system scheme of the advanced driving assistance system, a function list and the system scheme are imported into an evaluation model, and evaluation is carried out from multiple dimensions, so that the automatic evaluation of the advanced driving assistance system design is realized, optimization suggestions are provided, the efficiency and the quality of the advanced driving assistance system design are improved, the system design efficiency is improved, and the error probability is reduced. Therefore, the problems that in the related technology, the evaluation of the whole 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 problem that the system design process is not comprehensive is not considered, the system design efficiency is low, the design quality cannot be guaranteed and the like are solved.
Specifically, fig. 1 is a flow chart of an evaluation method of an advanced driving assistance system according to an embodiment of the present application.
As shown in fig. 1, the evaluation method of the advanced driving assistance system includes the steps of:
in step S101, a chip and sensor model library is constructed, and at least one important attribute in the chip and sensor model library is imported into the key device database.
It can be appreciated that the chip and sensor model library in the embodiments of the present application may be created manually.
In the actual implementation process, the embodiment of the application can manually create the chip and sensor model library, and import the important attributes in the chip and sensor model library into the integral key device database for use in advanced driving assistance system design.
According to the embodiment of the application, at least one important attribute in the chip and sensor model library can be imported into the key device database, so that the design efficiency of the advanced driving assistance system is improved, and the error probability is reduced.
Optionally, in one embodiment of the present application, constructing a chip and sensor model library includes: performing chip modeling according to at least one attribute of the computing power of the central processing unit, the computing power of the artificial intelligence, the random access memory, the storage chip, the interface type and the interface quantity to obtain a chip model; modeling the sensor according to at least one attribute of the detection distance, the angle of view, the transmission data quantity, the interface type and the interface quantity to obtain a sensor model; and constructing a chip and sensor model library according to the chip model and the sensor model.
It can be appreciated that, as shown in fig. 2, the chip modeling in the embodiment of the present application may obtain a chip model, where the chip model includes attributes such as CPU (Central Processing Unit ) computing power, AI (artificial intelligence, artificial intelligence) computing power, RAM (random access memory ), flash (one of the memory chips), interface type, and interface number; modeling a sensor according to embodiments of the present application may result in a sensor model, where the sensor model includes attributes such as a probe distance, a Field of View (FOV), an amount of transmitted data, an interface type, and an interface number.
In the actual execution process, the embodiment of the application can perform chip modeling according to the attributes such as the computing power of the central processing unit, the computing power of the artificial intelligence, the random access memory, the storage chip, the interface types, the interface quantity and the like, obtain a chip model, perform sensor modeling according to the attributes such as the detection distance, the angle of view, the transmission data quantity, the interface types, the interface quantity and the like, obtain a sensor model, and construct a chip and sensor model library according to the chip model and the sensor model, so that the efficiency and the quality of the design of the advanced driving assistance system are improved greatly, and the intelligent and practical applicability are higher.
According to the embodiment of the application, the chip and sensor model library can be constructed according to the chip model and the sensor model, and support is provided for interaction of the chip, the sensor model library and the key device database, so that the efficiency and the quality of the advanced driving assistance system design are improved.
Optionally, in one embodiment of the present application, the key device database includes at least one attribute of functionality, performance, and cost of the advanced driving assistance system.
It is appreciated that the key device database in embodiments of the present application includes attributes related to advanced driving assistance system design, which may be advanced driving assistance systems for vehicles.
In the actual implementation process, the embodiment of the application can further improve the efficiency and quality of the design of the advanced driving assistance system through the attribute of the key device database such as the function, the performance and the cost of the advanced driving assistance system.
In step S102, the device in the key device database is used to model the overall system scheme of the advanced driving assistance system, and a modeled system scheme is obtained.
It will be appreciated that the overall system solution in embodiments of the present application includes a SYSML model, and embodiments of the present application include tools and databases and automation scripts that can support SYSML modeling.
In the actual execution process, the embodiment of the application can use the devices in the key device database to model the whole system scheme of the advanced driving assistance system, and obtain the modeled system scheme, thereby improving the efficiency and quality of the design of the advanced driving assistance system, avoiding or reducing the condition of incomplete consideration in the design process as much as possible through a tool chain and an automatic mode, and intuitively indicating the defects in the system design.
Optionally, in one embodiment of the present application, modeling the overall system scheme of the advanced driving assistance system using devices in the key devices database includes: the overall system scheme of the advanced driving assistance system is modeled using hardware architecture and system architecture inside the domain control.
It may be understood that the domain control in the embodiments of the present application may be one or more domain controllers capable of controlling other servers in the domain, and the hardware architecture and the system architecture may be a communication link between the sensor and the domain control, etc.
In the actual implementation process, the embodiment of the application can use the hardware architecture and the system architecture in the domain control in the key device database to model the whole system scheme of the advanced driving assistance system, the TOP10-15 key device can be used when the hardware architecture in the domain control is designed, and the communication link between the sensor and the domain control can be used when the hardware architecture and the system architecture in the domain control are designed.
The embodiment of the application can model the whole system scheme of the advanced driving assistance system by using a hardware architecture and a system architecture in the domain control, thereby further improving the efficiency and the quality of the advanced driving assistance system design, and avoiding or reducing the condition of incomplete consideration in the design process as much as possible through a tool chain and an automatic mode.
In step S103, the system scheme and the target function list are imported into a preset evaluation model, and the advanced driving assistance system is evaluated according to at least one of calculation power, storage, interface, transmission bandwidth and cost estimation, and an evaluation result is generated.
It can be appreciated that the preset evaluation model in the embodiment of the present application may evaluate the advanced driving assistance system solution from different dimensions according to past project experience values through an evaluation algorithm.
In the actual execution process, as shown in fig. 2, the embodiment of the application may import the system scheme and the target function list into a preset evaluation model, evaluate the advanced driving assistance system from multiple dimensions according to calculation force, storage, interface, transmission bandwidth, cost evaluation, and the like, and generate an evaluation result, so that according to the evaluation result, automatic evaluation of the advanced driving assistance system design may be realized, and optimization suggestions may be provided, so as to improve efficiency and quality of the system design, and reduce error probability.
For example, the embodiment of the present application may obtain the required total calculation force according to the target function list, and compare the required total calculation force with the available calculation force calculated by the system design model, for example, when the high-speed NOA (automatic assisted navigation driving) requires more than 10TOPS calculation force, the total calculation force of the system scheme is 8TOPS (Tera Operations Per Second, processor calculation capability unit), and the evaluation result is failed; for another example, the high-speed NOA in the embodiment of the present application needs a high-precision map, needs to occupy 16GB of Flash, and os (Operating System) and application needs about 16GB, and the System scheme provides available Flash of 40GB, and at this time, the evaluation result is passed; for another example, a driving 7V scheme is adopted in the system model in the embodiment of the present application, and the chip can only process 6V data at the same time, and the evaluation result is that the data does not pass.
According to the method and the device for evaluating the advanced driving assistance system, the advanced driving assistance system can be evaluated according to calculation force, storage, interfaces, transmission bandwidth, cost evaluation and the like, an evaluation result is generated, incomplete consideration in the design process is avoided or reduced as much as possible through a tool chain and an automatic mode, and the defects in the system design are indicated intuitively.
It should be noted that the preset evaluation model may be set by those skilled in the art according to actual situations, and is not limited herein.
Optionally, in one embodiment of the present application, after evaluating the advanced driving assistance system according to at least one of the calculation force, the storage, the interface, the transmission bandwidth, and the cost estimation, generating the evaluation result further includes: generating an evaluation report according to the evaluation result, and generating iteration parameters of the advanced driving assistance system according to the evaluation report so as to carry out iteration optimization on the advanced driving assistance system until a preset iteration stop condition is met, thereby obtaining a final system scheme of the advanced driving assistance system.
As a possible implementation manner, the embodiment of the application may generate an evaluation report according to an evaluation result, generate iteration parameters of the advanced driving assistance system according to the evaluation report, so as to perform iterative optimization on the advanced driving assistance system, and mark an optimizable place in a system scheme until a preset iteration stop condition is met, so as to obtain a final system scheme of the advanced driving assistance system, thereby improving efficiency and quality of the advanced driving assistance system design, and being expected to save more than 2/3 of design workload.
The database and the evaluation algorithm in the embodiment of the application can be continuously and iteratively upgraded, and the level of a corresponding evaluation system can be continuously improved, so that the high-quality professional level is finally achieved, and the error probability is reduced.
According to the evaluation method of the advanced driving assistance system, devices in the key device database can be used for modeling the whole system scheme of the advanced driving assistance system, the function list and the system scheme are led into the evaluation model to evaluate from multiple dimensions, so that the automatic evaluation of the advanced driving assistance system design is realized, optimization suggestions are provided, the efficiency and the quality of the advanced driving assistance system design are improved, the system design efficiency is improved, and the error probability is reduced. Therefore, the problems that in the related technology, the evaluation of the whole 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 incomplete system design process is not considered, the system design efficiency is low, and the design quality cannot be guaranteed are solved.
Next, an evaluation device of an advanced driving assistance system proposed according to an embodiment of the present application is described with reference to the accompanying drawings.
Fig. 3 is a schematic structural view of an evaluation device of the advanced driving assistance system of the embodiment of the present application.
As shown in fig. 3, the evaluation device 10 of the advanced driving assistance system includes: a construction module 100, an acquisition module 200 and an evaluation module 300.
Specifically, the construction module 100 is configured to construct a chip and sensor model library, and import at least one important attribute in the chip and sensor model library into the key device database.
And the obtaining module 200 is configured to use devices in the key device database to model an overall system scheme of the advanced driving assistance system, so as to obtain a modeled system scheme.
The evaluation module 300 is configured to import the system scheme and the target function list into a preset evaluation model, evaluate the advanced driving assistance system according to at least one of calculation power, storage, interface, transmission bandwidth and cost estimation, and generate an evaluation result.
Optionally, in one embodiment of the present application, the evaluation device 10 of the advanced driving assistance system further includes: and (5) an optimization module.
The optimization module is used for generating an evaluation report according to the evaluation result after evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost evaluation, generating iteration parameters of the advanced driving assistance system according to the evaluation report, and carrying out iteration optimization on the advanced driving assistance system until a preset iteration stop condition is met, so as to obtain a final system scheme of the advanced driving assistance system.
Optionally, in one embodiment of the present application, the building module 100 includes: the device comprises a first acquisition unit, a second acquisition unit and a construction unit.
The first obtaining unit is used for carrying out chip modeling according to at least one attribute of CPU computing power, artificial intelligence computing power, random access memory, storage chip, interface type and interface quantity to obtain a chip model.
The second acquisition unit is used for carrying out sensor modeling according to at least one attribute of the detection distance, the angle of view, the transmission data quantity, the interface type and the interface quantity to obtain a sensor model.
And the construction unit is used for constructing a chip and sensor model library according to the chip model and the sensor model.
Optionally, in one embodiment of the present application, the key device database includes at least one attribute of functionality, performance, and cost of the advanced driving assistance system.
Optionally, in one embodiment of the present application, the obtaining module 200 includes: and establishing a unit.
The system comprises a building unit, a control unit and a control unit, wherein the building unit is used for modeling the whole system scheme of the advanced driving assistance system by using a hardware architecture and a system architecture in a domain control.
It should be noted that the foregoing explanation of the embodiment of the evaluation method of the advanced driving assistance system is also applicable to the evaluation device of the advanced driving assistance system of this embodiment, and will not be repeated here.
According to the evaluation device of the advanced driving assistance system, which is provided by the embodiment of the application, the device in the key device database can be used for modeling the whole system scheme of the advanced driving assistance system, the function list and the system scheme are led into the evaluation model, and evaluation is performed from multiple dimensions, so that the automatic evaluation of the advanced driving assistance system design is realized, the optimization suggestion is provided, the efficiency and the quality of the advanced driving assistance system design are improved, the system design efficiency is improved, and the error probability is reduced. Therefore, the problems that in the related technology, the evaluation of the whole 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 incomplete system design process is not considered, the system design efficiency is low, and the design quality cannot be guaranteed are solved.
Fig. 4 is a schematic structural diagram of a vehicle according to an embodiment of the present application. The vehicle may include:
memory 401, processor 402, and a computer program stored on memory 401 and executable on processor 402.
The processor 402 implements the evaluation method of the advanced driving assistance system provided in the above-described embodiment when executing the program.
Further, the vehicle further includes:
a communication interface 403 for communication between the memory 401 and the processor 402.
A memory 401 for storing a computer program executable on the processor 402.
Memory 401 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 401, the processor 402, and the communication interface 403 are implemented independently, the communication interface 403, the memory 401, and the processor 402 may be connected to each other by a bus and perform communication with each other. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 401, the processor 402, and the communication interface 403 are integrated on a chip, the memory 401, the processor 402, and the communication interface 403 may complete communication with each other through internal interfaces.
The processor 402 may be a central processing unit (Central Processing Unit, abbreviated as CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more integrated circuits configured to implement embodiments of the present application.
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the evaluation method of the advanced driving assistance system as above.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless explicitly defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer cartridge (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (10)
1. A method of evaluating an advanced driving assistance system, comprising the steps of:
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;
modeling an overall system scheme of the advanced driving assistance system by using devices in the key device database to obtain a modeled system scheme; and
and importing the system scheme and the target function list into a preset evaluation model, evaluating the advanced driving assistance system according to at least one of calculation power, storage, interface, transmission bandwidth and cost evaluation, and generating an evaluation result.
2. The method of claim 1, further comprising, after evaluating the advanced driving assistance system based on at least one of a computational effort, a storage, an interface, a transmission bandwidth, and a cost estimate, generating an evaluation result:
generating an evaluation report according to the evaluation result, and generating iteration parameters of the advanced driving assistance system according to the evaluation report so as to carry out iteration optimization on the advanced driving assistance system until a preset iteration stop condition is met, so as to obtain a final system scheme of the advanced driving assistance system.
3. The method of claim 1, wherein the building a chip and sensor model library comprises:
performing chip modeling according to at least one attribute of the computing power of the central processing unit, the computing power of the artificial intelligence, the random access memory, the storage chip, the interface type and the interface quantity to obtain a chip model;
modeling a sensor according to at least one attribute of the detection distance, the angle of view, the transmission data quantity, the interface type and the interface quantity to obtain a sensor model;
and constructing the chip and sensor model library according to the chip model and the sensor model.
4. The method of claim 1, wherein the key device database includes at least one attribute of functionality, performance, and cost of the advanced driving assistance system.
5. The method of claim 1, wherein the modeling of the overall system scheme of the advanced driving assistance system using devices in the key devices database comprises:
the overall system scheme of the advanced driving assistance system is modeled using hardware architecture and system architecture inside the domain control.
6. An evaluation device of an advanced driving assistance system, characterized by comprising:
the construction module is used for constructing a chip and sensor model library and importing at least one important attribute in the chip and sensor model library into the key device database;
the acquisition module is used for modeling the whole system scheme of the advanced driving assistance system by using the devices in the key device database to obtain a modeled system scheme; and
the evaluation module is used for importing the system scheme and the target function list into a preset evaluation model, evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost estimation, and generating an evaluation result.
7. The apparatus as recited in claim 6, further comprising:
and the optimization module is used for evaluating the advanced driving assistance system according to at least one of calculation force, storage, interface, transmission bandwidth and cost estimation, generating an evaluation result, generating an evaluation report according to the evaluation result, generating iteration parameters of the advanced driving assistance system according to the evaluation report, and carrying out iterative optimization on the advanced driving assistance system until a preset iteration stop condition is met, so as to obtain a final system scheme of the advanced driving assistance system.
8. The apparatus of claim 6, wherein the build module comprises:
the first acquisition unit is used for carrying out chip modeling according to at least one attribute of the computing power of the central processing unit, the computing power of the artificial intelligence, the random access memory, the memory chip, the interface type and the interface quantity to obtain a chip model;
the second acquisition unit is used for carrying out sensor modeling according to at least one attribute of the detection distance, the angle of view, the transmission data quantity, the interface type and the interface quantity to obtain a sensor model;
and the construction unit is used for constructing the chip and sensor model library according to the chip model and the sensor model.
9. A vehicle, characterized by comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method of evaluating an advanced driving assistance system according to any one of claims 1-5.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing the evaluation method of an advanced driving assistance system according to any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311693673.5A CN117688750A (en) | 2023-12-06 | 2023-12-06 | Advanced driving assistance system evaluation method, advanced driving assistance system evaluation device, vehicle and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311693673.5A CN117688750A (en) | 2023-12-06 | 2023-12-06 | Advanced driving assistance system evaluation method, advanced driving assistance system evaluation device, vehicle and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117688750A true CN117688750A (en) | 2024-03-12 |
Family
ID=90127871
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311693673.5A Pending CN117688750A (en) | 2023-12-06 | 2023-12-06 | Advanced driving assistance system evaluation method, advanced driving assistance system evaluation device, vehicle and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117688750A (en) |
-
2023
- 2023-12-06 CN CN202311693673.5A patent/CN117688750A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111125854B (en) | Optimization method and device for vehicle dynamics model, storage medium and terminal equipment | |
| EP3944046A1 (en) | Method for upgrading automatic driving system, automatic driving system and vehicle-mounted device | |
| CN107015550B (en) | Diagnostic test execution control system and method | |
| CN111694917B (en) | Vehicle abnormal track detection and model training method and device | |
| CN110174110B (en) | Map corresponding method and device, electronic equipment and computer readable medium | |
| US11580797B2 (en) | Systems and methods for monitoring specifications over simulation and test data | |
| CN117688750A (en) | Advanced driving assistance system evaluation method, advanced driving assistance system evaluation device, vehicle and storage medium | |
| CN111123730B (en) | Unmanned driving fault simulation method, device, equipment and computer readable medium | |
| CN116560688A (en) | Software updating method for domain controller | |
| CN113872971B (en) | New energy Internet of vehicles communication protocol upgrading method and device and cloud platform | |
| CN114896168A (en) | Rapid debugging system, method and memory for automatic driving algorithm development | |
| CN111143423B (en) | Dynamic scene labeling data mining method and device and terminal | |
| CN113677583B (en) | Graph calculation-based vehicle driving data processing method and device and computer equipment | |
| CN113985844A (en) | ECU parameter configuration method and device, electronic equipment and storage medium | |
| CN112104766B (en) | Diagnostic protocol reconstruction method, device, terminal equipment and storage medium | |
| CN112989352A (en) | Method and apparatus for model-based analysis | |
| CN111177877A (en) | Local simulation method and device based on application container engine and storage medium | |
| CN116819964B (en) | Model optimization method, model optimization device, electronic device, vehicle and medium | |
| CN114217539B (en) | Simulation test method and device for automatic driving function, vehicle and storage medium | |
| CN117456496B (en) | Map lane boundary line processing method and system | |
| CN111831266A (en) | Intelligent driving software integration and tracing system and method | |
| CN116775083B (en) | Brushing method and device of vehicle-mounted controller and electronic equipment | |
| US20230202492A1 (en) | Method and system for determining compatibility of system parameters | |
| WO2023037576A1 (en) | Vehicle control system and vehicle control method | |
| CN117955828A (en) | Controller local area network communication method and device, controller and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |