CN114610647A - Parallel simulation test method and system for automatic driving automobile - Google Patents
Parallel simulation test method and system for automatic driving automobile Download PDFInfo
- Publication number
- CN114610647A CN114610647A CN202210399040.2A CN202210399040A CN114610647A CN 114610647 A CN114610647 A CN 114610647A CN 202210399040 A CN202210399040 A CN 202210399040A CN 114610647 A CN114610647 A CN 114610647A
- Authority
- CN
- China
- Prior art keywords
- test
- simulation
- module
- library
- interface
- 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
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3688—Test management for test execution, e.g. scheduling of test suites
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3664—Environments for testing or debugging software
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3684—Test management for test design, e.g. generating new test cases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3692—Test management for test results analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/12—Geometric CAD characterised by design entry means specially adapted for CAD, e.g. graphical user interfaces [GUI] specially adapted for CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Geometry (AREA)
- Quality & Reliability (AREA)
- Evolutionary Computation (AREA)
- Architecture (AREA)
- Human Computer Interaction (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a parallel simulation test method and a system for an automatic driving automobile, wherein the method is established by configuring a simulation resource pool and a measurement purpose pool, multiple test tasks are formulated according to the measurement purpose, multi-node parallel simulation tasks are executed, and evaluation analysis such as passing judgment, data analysis and visual display is obtained through simulation data results. The parallel simulation testing system platform comprises a cloud end, a client end and a background management end, the interaction form of the client end and the interaction form of the client end and the cloud end are established, the automatic driving multi-task parallel simulation testing and the unified management, scheduling and use of data resources are realized, the simulation requirements of different clients are met, and the simulation testing efficiency is improved by the operation of the system platform.
Description
Technical Field
The invention relates to the technical field of simulation testing of an automatic driving automobile, in particular to a parallel simulation testing method and system of the automatic driving automobile.
Background
With the rapid development of the automatic driving technology to the high-grade automatic driving technology, the safety and reliability of the automatic driving technology become more and more important. In the prior art, the simulation test of the automatic driving system is mainly realized by a single machine test mode. Specifically, for a mechanism for researching an automatic driving system, a software and hardware environment for an automatic driving simulation test needs to be built by the mechanism, and if a more comprehensive simulation test needs to be performed on the automatic driving system, more types of simulation test software, scene conditions and the like need to be configured.
In addition, the development of automatic driving needs massive road test mileage data, and from early development and verification of an algorithm to later test, the traditional test method cannot meet the development and verification of an automatic driving algorithm. At present, the automatic driving virtual test platform can partially replace road tests, is complementary with the road tests, can greatly shorten the test period and reduce the test cost, and protects the life safety of testers. However, with the improvement of the performance of computing hardware devices, software algorithms for automatic driving become more complex, and a more efficient method is needed, so that the whole testing efficiency is improved by combining a parallel processing technology and a containerization processing technology on the basis of a virtual simulation technology.
Disclosure of Invention
Therefore, the invention provides a parallel simulation test method and a system for an automatic driving automobile, which aim to solve the problems proposed in the background art, construct a simulation test method by configuring a simulation test resource pool and a target pool, establish a simulation test system platform according to the test method, and realize the requirement of a customer on the simulation test of the automatic driving automobile through the interaction between the customer and the system platform, thereby realizing the multi-node and multi-task management and scheduling of the simulation test of the automatic driving, and solving the problems of low efficiency and limited computing capacity of the simulation test of the automatic driving.
The technical scheme adopted by the invention is as follows: a parallel simulation test method for an automatic driving automobile comprises the following steps:
firstly, establishing a simulation test resource pool and a target pool;
secondly, configuring multiple testing tasks based on testing purposes;
thirdly, respectively configuring test resources and an evaluation model based on multiple test tasks;
thirdly, executing a multi-node parallel simulation task based on the multi-test task;
and finally, evaluating and analyzing the test data after the simulation task is executed, and outputting a simulation test result of the automatic driving system.
Further, the simulation test resource pool at least comprises simulation software, a dynamic model, a sensor model, an algorithm, an IO interface and a test case.
The simulation test resource pool comprises at least one simulation software, at least one dynamic model, at least one sensor model and at least one test case;
the configuration of the test case is to establish a simulation test environment through the selection of the test scene.
Further, the test target pool is formulated based on the evaluation index;
the evaluation indexes comprise compliance indexes, safety indexes, trafficability indexes and comfort indexes, and are not limited to four;
the multi-test task is formulated according to the achieved evaluation index.
Further, in multi-test tasks, the same test resources are shared.
Further, the simulation test result of the automatic driving system comprises test passing judgment, test data analysis and visual display;
the test passing judgment is determined according to a test passing standard, and the test passing comprises a test passing and a test failing.
The invention also provides a parallel simulation test system of the automatic driving automobile, which comprises a client, a cloud and a background management end;
the client comprises a personal center, a project interface, a task interface and a function interface;
the cloud end comprises a library management module, a functional module, a resource management module, a computing service module and a data management module;
the background management end comprises client management, system maintenance and node resource management.
Further, the project interface of the client comprises a project generation module, a project name module and a project description module;
the task interface of the client comprises a task generation module, a task name module and a task belonging module;
the functional interface of the client comprises a simulation platform screening module, a dynamics editing module, a sensor editing module, a test case editing module, a condition editing module, an algorithm uploading module, an IO interface editing module and a simulation data result display module;
the cloud function module comprises simulation platform selection, dynamic parameter selection, sensor parameter selection, test case generation, condition selection, algorithm uploading, IO interface matching, data analysis and visualization;
the cloud library management module comprises a simulation test software library, a dynamic model library, a sensor model library, a test scene library, a test evaluation library, an algorithm library and a simulation analysis library;
the cloud resource management comprises the management of simulation software, a dynamic model, a sensor model, test scene resources and simulation nodes;
the cloud data management comprises the step of managing all data;
and the cloud computing service comprises all computing power provided for simulation test.
Furthermore, the simulation platform selection module of the cloud terminal calls simulation software required by the simulation test software library through the requirement information of the simulation platform screening module of the client terminal to complete the selection operation of the simulation platform;
the cloud dynamics parameter selection module calls dynamics parameters required by a dynamics model library through the demand information of the dynamics editing module of the client to complete dynamics parameter selection operation;
the sensor parameter selection module of the cloud terminal calls sensor parameters required by the sensor model library through the demand information of the sensor editing module of the client terminal to complete sensor parameter selection operation;
the test case generation module of the cloud terminal calls test case parameters required by the test scene library through the requirement information of the test case editing module of the client terminal to complete test case generation operation;
the passing condition selection module of the cloud end calls evaluation indexes required by the test evaluation library through the requirement information of the passing condition editing module of the client end to complete passing condition option operation;
the algorithm uploading and IO interface matching module of the cloud terminal uploads the demand information of the IO interface editing module through the algorithm of the client terminal, calls parameters required by the algorithm library, and completes the algorithm uploading and IO interface matching operation.
Furthermore, the data analysis and visualization module of the cloud retrieves information of the simulation analysis library by executing a multi-node parallel simulation task, and presents a simulation data result on a simulation data result display interface of the client.
Further, the simulation platform selection operation, the dynamics parameter selection operation, the sensor parameter selection operation, the test case generation operation, the condition selection operation, the algorithm uploading and the IO interface matching operation are performed, and the multi-node parallel simulation operation is performed through the test system.
Compared with the prior art, the invention has the following remarkable beneficial effects:
(1) compared with the prior art, the simulation test resource pool and the target pool are established, different tests are realized by configuring different resources during specific test tasks, actual road tests are replaced, the test period is shortened, and the test cost is reduced.
(2) Compared with the prior art, the invention deploys the whole test environment in a containerization mode, reduces the storage space and reduces the resource consumption.
(3) The invention adopts a multi-node parallel simulation mode, and the test quantity and the operation efficiency are improved by increasing the quantity of nodes so as to adapt to the simulation requirements of different customers.
(4) The invention provides a parallel simulation test system platform, which realizes the automatic operation of the whole set of test, greatly reduces manual operation and improves the simulation test efficiency.
Drawings
FIG. 1 is a schematic diagram of a parallel simulation test method for an autonomous vehicle according to the present invention;
FIG. 2 is a flow chart of a parallel simulation test method for an autonomous vehicle according to the present invention;
fig. 3 is an architecture diagram of a parallel simulation test system for an autonomous vehicle according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and examples.
The invention provides a parallel simulation test method of an automatic driving automobile, which comprises the steps of establishing a test resource pool by modules such as simulation software, a dynamic model, a sensor model, an algorithm uploading module, an IO interface, a test case and the like of an automatic driving system, establishing a test target pool aiming at different evaluation indexes based on a test target, wherein the evaluation indexes comprise but are not limited to compliance indexes, safety indexes and trafficability indexes, and the like, as shown in figure 1; and then according to different test purposes, different test tasks are established based on evaluation indexes, different simulation software, dynamic models, sensor models, algorithms, IO interfaces and test cases are configured from a resource pool according to the different test tasks, under the multi-test tasks, containerization-based multi-node parallel simulation tasks are executed through the established multi-group resource configuration, and meanwhile, a plurality of groups of test results are output, so that the method for the parallel simulation test and evaluation of the multi-test tasks of the automatic driving automobile is realized.
The test method comprises the following specific steps:
1. establishing simulation test resource pool and target pool
(1) One or more simulation software is stored for executing simulation test tasks of different requirements.
(2) One or more dynamics models are stored for selection of vehicle types and dynamics related parameters.
(3) One or more sensor models are stored for use in sensing information required for relevant simulation tests, including environment, vehicle, target objects, etc.
(4) And providing an algorithm uploading and IO interface, a standard interface document, a communication mode and the like for helping a user to input a required algorithm into the test system in a connecting manner.
(5) And establishing a test case pool, storing a certain number of test scenes, and providing the test scenes for multi-node and parallel simulation tasks.
The purpose of the above 5 items is to provide the necessary test resources for parallel simulation.
(6) Aiming at different evaluation indexes such as safety indexes, compliance indexes, trafficability indexes and the like, a test target pool is established.
2. Configuring multiple test tasks
(1) Different testing tasks are established for different testing purposes. (2) And respectively configuring simulation software, a dynamic model, a sensor model and a test case of the test resource pool based on different test tasks.
(3) And configuring a test target pool based on different test tasks, and determining evaluation indexes corresponding to the test tasks.
(4) And establishing an evaluation model aiming at different evaluation purposes. In a test system, multiple test tasks can be established at the same time, namely parallel simulation, in one test task, only one evaluation index can be aimed at, and multiple evaluation indexes can be aimed at the same time, namely multi-node simulation; for example, the task one is evaluation of safety of automatic driving, the task two is evaluation of comfort of automatic driving, and the task three is evaluation of compliance and passability of automatic driving. For different test tasks, different test resources are respectively configured, for example, a resource group configured by the task one is a, a resource group configured by the task two is B, a resource group configured by the task three is C, the three resource groups are configured to cooperate with the three test tasks to execute resource calling, and simulation software, vehicle types, dynamic parameters, perception information, algorithms and interfaces, and test scenario information included in each resource group may be different. Different evaluation models are set for different test purposes.
In the configuration of the test case, the key point is the selection of the test scene, and the selection of the test scene directly influences whether the test achieves the same effect as the actual test and is consistent with the configuration of the actual scene, thereby playing an important role in improving the test result of the simulation test.
3. Executing containerization-based multi-node parallel simulation tasks
As shown in fig. 2, after the multi-test task is configured, the parallel simulation task is executed according to the requirement of the customer.
The execution of the multipoint type parallel simulation task deploys the whole test environment in a containerized form, the same resources are shared in each test task, repeated configuration is not needed, and the purpose is to reduce the storage space of the memory and the consumption of the resources. And performing parallel simulation on all the test tasks, and outputting a plurality of groups of test data.
4. The passing judgment is carried out on the test result
As shown in fig. 2, a customer edits an evaluation model according to actual needs, executes a plurality of parallel simulation tasks to obtain a series of test data, and then obtains a test result according to a test passing judgment standard guided by the evaluation model, the test result is output with pass or fail as a result, and evaluation analysis of the automatic driving system is performed based on a previously established test purpose.
Based on the above purpose, the invention provides a test system for automatic driving parallel simulation, as shown in fig. 3, the test system includes three platform systems, namely a client, a cloud and a background management end.
Client terminal
The client comprises a personal center, a project interface, a task interface, a function interface and other plates.
The personal center is used for user registration, login and personal information maintenance.
The project interface comprises modules of project generation, project name, project description and the like.
The task interface comprises modules such as task generation, task names and task belongings.
The functional interface comprises modules of simulation platform screening, dynamics editing, sensor editing, test case editing, condition editing, algorithm uploading, IO interface editing, simulation data result displaying and the like.
The customer maintains the user information through the personal center, establishes the belonged project and task through the project interface and the task interface, and then carries out the operation of corresponding related simulation parameter configuration on the functional interface module.
Cloud
The cloud comprises boards for library management, function modules, resource management, computing service, data management and the like.
The library management comprises a simulation test software library, a dynamic model library, a sensor model library, a test scene library, a test evaluation library, an algorithm library and a simulation analysis library.
The functional modules correspond to functional interfaces of the client one to one and comprise modules of simulation platform selection, dynamic parameter selection, sensor parameter selection, test case selection, condition selection, algorithm uploading, IO interface matching, data analysis, visualization and the like.
The cloud end inputs the resources according to the requirements of the functional interface of the client end, and allocates and executes the functions.
The resource management is used for managing simulation software, a dynamic model, a sensor model, test scene resources and simulation nodes.
The data management is to manage all data.
The computing service provides necessary computing power for the simulation test.
Background management terminal
The background management end comprises plates for client management, system maintenance, node resource management and the like, and manages and maintains cloud computing resources and clients.
The customer management comprises customer account management and management aiming at an administrator and users with different authority levels.
The system maintenance comprises the necessary modification and improvement aiming at the system in the running process of software and hardware.
The node resource management comprises scheduling and managing a plurality of nodes.
The interaction conditions of the test system between the client and between the client and the cloud are described as follows:
the client is presented by a web end.
First, the customer performs user registration, login and personal information maintenance through a personal center.
And then, establishing the belonged project through a project interface, wherein the belonged project comprises editing operations such as project generation, project naming, project description and the like.
And establishing various tasks under the belonged project through a task interface, wherein the task interface comprises editing operations such as test task generation, task name, task belonged project selection and the like.
The interaction condition of the functional interface of the client, the functional module of the cloud and library management is as follows:
screening the simulation platform of the client: after the customer selects the needed simulation platform through the simulation platform screening interface in the functional interface and edits, the system returns the information to the simulation platform selection module of the cloud functional module. The simulation platform selection module has the functions of: and calling a simulation test software library in library management, selecting simulation software conforming to the requirements of customers for matching, carrying out an operation instruction on the matched simulation test software, and executing a functional task screened by the simulation platform.
Dynamic editing of the client: after a client edits required dynamics types and dynamics parameters through a dynamics editing interface in a functional interface, a system returns information to a dynamics parameter selection module in a cloud functional module, and the dynamics parameter selection module has the functions of: and calling a dynamics model library in library management, selecting a dynamics type and dynamics related parameters which are consistent with customer requirements for matching, carrying out an operation instruction on the matched dynamics type and dynamics related parameters, and executing a function task of dynamics parameter selection.
Sensor editing of the client: after a client edits required sensor parameters through a sensor editing interface in a functional interface, a system returns information to a sensor parameter selection module in a cloud functional module, and the sensor parameter selection module has the functions of: and calling a sensor model library in library management, selecting sensor related parameters conforming to customer requirements for matching, carrying out an operation instruction on the matched sensor related parameters, and executing a function task of sensor parameter selection.
Editing the test cases of the client: after the client edits the required test case through the test case editing interface in the functional interface, the system returns the information to the test case generating module in the cloud functional module. The function of the test case generation module is as follows: and calling a test scene library in cloud library management, selecting relevant parameters of the test case which are in line with the requirements of the client for matching, carrying out an operation instruction on the matched relevant parameters of the test case, and executing a function task generated by the test case.
And editing through conditions of the client: after the client edits the required passing condition through the passing condition editing interface in the functional interface, the system returns the information to the passing condition selection module in the cloud functional module, and the passing condition selection module has the functions of: and calling a measurement and control evaluation library in cloud library management, selecting relevant evaluation indexes conforming to the requirements of customers for matching, carrying out an operation instruction on the matched evaluation indexes selected through the conditions, and executing relevant function tasks passing through the condition options.
And (3) algorithm uploading and IO interface editing of the client: after the client uploads the required algorithm and edits the IO interface through the algorithm uploading and IO interface editing interface in the functional interface, the system returns the information to the algorithm uploading and IO interface matching module in the cloud functional module, and the function of the algorithm uploading and IO interface matching module is as follows: and calling an algorithm library in cloud library management, selecting an algorithm upload and IO interface which is in accordance with customer requirements for matching, carrying out an operation instruction on a file related to the matched algorithm upload and IO interface module, and executing the function tasks of the algorithm upload and the IO interface.
And displaying the simulation data result of the client: firstly, after a client edits through a simulation platform screening, dynamics editing, sensor editing, test case editing, condition editing, algorithm uploading and IO interface editing related module interfaces in a functional interface of the client, the client's requirements are converted into corresponding related functional modules in the functional modules of the cloud, and the corresponding steps are as follows: the method comprises the steps of simulation platform selection, dynamics parameter selection, sensor parameter selection, test case generation, condition selection, algorithm uploading and IO interface matching. Then, the functional module of high in the clouds corresponds to the corresponding module storehouse in the storehouse management, corresponding respectively is: the method comprises the steps of matching corresponding library parameters with a simulation test software library, a dynamic model library, a sensor model library, a test scene library, a test evaluation library and an algorithm library, calling a simulation analysis library in cloud library management, executing relevant function tasks, and then generating test results such as analysis data and a visual curve graph.
And finally, displaying parameter data required by the client, a passing judgment result and the like in a simulation data result display module of the client.
The data analysis and visualization functions comprise data analysis and visualization of all test cases of a single task, process data analysis and visualization of a single test case, multi-task overall data statistics, and display interfaces such as test case downloading and the like after completion.
Claims (10)
1. A parallel simulation test method for an automatic driving automobile is characterized by comprising the following steps:
firstly, establishing a simulation test resource pool and a target pool;
secondly, configuring multiple testing tasks based on the testing purpose;
thirdly, respectively configuring test resources and an evaluation model based on the multi-test task;
thirdly, executing a multi-node parallel simulation task based on the multi-test task;
and finally, evaluating and analyzing the test data after the simulation task is executed, and outputting a simulation test result of the automatic driving system.
2. The automated guided vehicle parallel simulation test method of claim 1, wherein:
the simulation test resource pool at least comprises simulation software, a dynamic model, a sensor model, an algorithm, an IO interface and a test case.
3. The automated guided vehicle parallel simulation test method according to claim 1 or 2, characterized in that:
the simulation test resource pool comprises at least one simulation software, at least one dynamic model, at least one sensor model and at least one test case;
the configuration of the test case is to establish a simulation test environment through the selection of the test scene.
4. The automated guided vehicle parallel simulation test method of claim 1, wherein:
the test target pool is formulated based on the evaluation index;
the evaluation indexes comprise a compliance index, a safety index, a trafficability index and a comfort index;
the multi-test task is formulated according to the achieved evaluation index.
5. The autopilot vehicle parallel simulation test method of claim 1 wherein:
in a multi-test task, the same test resources are shared.
6. The automated guided vehicle parallel simulation test method of claim 1, wherein:
the automatic driving system simulation test result comprises test passing judgment, test data analysis and visual display;
the test passing judgment is determined according to a test passing standard, and the test passing comprises a test passing and a test failing.
7. The utility model provides an automatic drive car parallel simulation test system which characterized in that:
the test system comprises a client, a cloud and a background management end;
the client comprises a personal center, a project interface, a task interface and a function interface;
the cloud end comprises a library management module, a functional module, a resource management module, a computing service module and a data management module;
the background management end comprises client management, system maintenance and node resource management.
8. The automated guided vehicle parallel simulation test system of claim 7, wherein:
the project interface of the client comprises a project generation module, a project name module and a project description module;
the task interface of the client comprises a task generation module, a task name module and a task belonging module;
the functional interface of the client comprises a simulation platform screening module, a dynamics editing module, a sensor editing module, a test case editing module, a condition editing module, an algorithm uploading module, an IO interface editing module and a simulation data result display module;
the cloud functional module comprises simulation platform selection, dynamic parameter selection, sensor parameter selection, test case generation, condition selection, algorithm uploading, IO interface matching, data analysis and visualization;
the cloud library management module comprises a simulation test software library, a dynamic model library, a sensor model library, a test scene library, a test evaluation library, an algorithm library and a simulation analysis library;
the cloud resource management comprises the management of simulation software, a dynamic model, a sensor model, test scene resources and simulation nodes;
the cloud data management comprises the step of managing all data;
and the cloud computing service comprises all computing power provided for simulation test.
9. The automated guided vehicle parallel simulation test system of claim 8, wherein:
the simulation platform selection module of the cloud terminal calls simulation software required by the simulation test software library through the requirement information of the simulation platform screening module of the client terminal to complete the selection operation of the simulation platform;
the cloud dynamics parameter selection module calls dynamics parameters required by a dynamics model library through the demand information of the dynamics editing module of the client to complete dynamics parameter selection operation;
the sensor parameter selection module of the cloud terminal calls sensor parameters required by the sensor model library through the demand information of the sensor editing module of the client terminal to complete sensor parameter selection operation;
the test case generation module of the cloud terminal calls test case parameters required by the test scene library through the requirement information of the test case editing module of the client terminal to complete test case generation operation;
the passing condition selection module of the cloud end calls evaluation indexes required by the test evaluation library through the requirement information of the passing condition editing module of the client end to complete passing condition option operation;
the algorithm uploading and IO interface matching module of the cloud terminal uploads the demand information of the IO interface editing module through the algorithm of the client terminal, calls parameters required by the algorithm library, and completes the algorithm uploading and IO interface matching operation.
And the data analysis and visualization module of the cloud side calls information of the simulation analysis library by executing the multi-node parallel simulation task and displays a simulation data result on a simulation data result display interface of the client side.
10. The automated guided vehicle parallel simulation test system of claim 7, wherein:
the simulation system comprises a simulation platform, a dynamic parameter selection operation, a sensor parameter selection operation, a test case generation operation, a condition selection operation, an algorithm uploading and an IO interface matching operation, and a multi-node parallel simulation operation is executed through the test system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210399040.2A CN114610647A (en) | 2022-04-16 | 2022-04-16 | Parallel simulation test method and system for automatic driving automobile |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210399040.2A CN114610647A (en) | 2022-04-16 | 2022-04-16 | Parallel simulation test method and system for automatic driving automobile |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114610647A true CN114610647A (en) | 2022-06-10 |
Family
ID=81868796
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210399040.2A Pending CN114610647A (en) | 2022-04-16 | 2022-04-16 | Parallel simulation test method and system for automatic driving automobile |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114610647A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117473798A (en) * | 2023-12-26 | 2024-01-30 | 国家超级计算天津中心 | Simulation project management method, device, equipment and storage medium |
-
2022
- 2022-04-16 CN CN202210399040.2A patent/CN114610647A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117473798A (en) * | 2023-12-26 | 2024-01-30 | 国家超级计算天津中心 | Simulation project management method, device, equipment and storage medium |
| CN117473798B (en) * | 2023-12-26 | 2024-05-14 | 国家超级计算天津中心 | Simulation project management method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112052608B (en) | Integrated method for war deduction simulation and efficiency evaluation | |
| CN111338973A (en) | Scene-based automatic driving simulation test evaluation service cloud platform and application method | |
| US11481309B2 (en) | Capability test method based on joint test support platform | |
| CN111400186B (en) | Performance test method and system | |
| CN102523030B (en) | Communication satellite effective load test system simulation platform | |
| CN111401722B (en) | Intelligent decision method and intelligent decision system | |
| CN110740079B (en) | Full link benchmark test system for distributed scheduling system | |
| CN107733710A (en) | Construction method, device, computer equipment and the storage medium of link call relation | |
| CN107203464B (en) | Method and device for positioning service problem | |
| CN111753034A (en) | One-stop type geographical big data platform | |
| CN114610647A (en) | Parallel simulation test method and system for automatic driving automobile | |
| CN111860853A (en) | Online prediction system, online prediction equipment, online prediction method and electronic equipment | |
| CN111324635A (en) | Industrial big data cloud platform data processing method and system | |
| CN111046519A (en) | Application analysis method of artificial intelligence technology in electric energy meter error diagnosis | |
| CN114896108A (en) | Test verification system | |
| CN107741909A (en) | A kind of automated testing method and system for distributed block storage | |
| CN105700987B (en) | Energy consumption system energy consumption simulation and energy-saving diagnosis method and platform based on cloud technology | |
| CN105205545A (en) | Method for optimizing logistics system by applying simulation experiment | |
| CN102546235B (en) | Performance diagnosis method and system of web-oriented application under cloud computing environment | |
| von Bülow et al. | Fleet Management Approach for Manufacturers displayed at the Use Case of Battery Electric Vehicles | |
| Liu et al. | An implementation of industrial IoT: a case study in lithium-ion battery pack and assembly | |
| CN110597728A (en) | Method, device and system for constructing test data | |
| CN116737351A (en) | Image processing system operation management method and device, storage medium and electronic equipment | |
| CN108897608A (en) | A kind of intelligent universal task scheduling system that data-driven is expansible | |
| Liu et al. | Agent-based online quality measurement approach in cloud computing environment |
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 |