A simulation scene database construction method and system

Abstract

The application provides a simulation scene database construction method and system, the method comprises the following steps: receiving road image data collected by crowdsourcing; identifying the image data by an intelligent camera, and outputting road perception information and traffic flow perception information; constructing OpenDrive roads and Openscenario traffic flows according to the road perception information and the traffic flow perception information; obtaining target motion state description information in the Openscenario traffic flow, classifying and summarizing target motion scenes, and forming a simulation scene database. Through the scheme, the simulation scene database can be quickly constructed, the simulation data acquisition cost is reduced, and the amount of collected data is ensured.

Description

Technical Field

[0001] This invention belongs to the field of autonomous driving simulation testing, and in particular relates to a method and system for constructing a simulation scenario database. Background Technology

[0002] Autonomous driving simulation testing technology can accelerate the development process and significantly reduce development costs in the overall vehicle development workflow. Its high reproducibility and editable scenarios make it increasingly important in autonomous driving development. As one of the main methods for testing intelligent connected vehicle products, simulation testing complements real-vehicle testing and is gradually gaining attention. Establishing a systematic simulation scenario database has become a crucial prerequisite for autonomous driving research and development.

[0003] Currently, the construction of simulation scenario databases requires the use of data collection vehicles to collect scenario data on-site. This method can ensure the reliability of simulation data, but the collection cost is high and the amount of data collected is limited, making it difficult to construct complex and diverse traffic flow scenarios. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method and system for constructing a simulation scene database to solve the problems of high cost and limited data volume in simulation data acquisition.

[0005] In a first aspect of the present invention, a method for constructing a simulation scene database is provided, comprising:

[0006] Receive road image data collected through crowdsourcing;

[0007] The image data is identified by intelligent cameras, and road perception information and traffic flow perception information are output.

[0008] Based on road perception information and traffic flow perception information, construct OpenDrive roads and Openscenario traffic flows;

[0009] Obtain descriptions of target motion states in OpenScenario traffic flow, classify and summarize target motion scenarios, and form a simulation scenario database.

[0010] In a second aspect of the present invention, a simulation scenario database construction system is provided, comprising:

[0011] The data receiving module is used to receive road image data collected through crowdsourcing.

[0012] The image recognition module is used to recognize image data through a smart camera and output road perception information and traffic flow perception information.

[0013] The scenario building module is used to construct OpenDrive roads and Openscenario traffic flows based on road perception information and traffic flow perception information;

[0014] The classification and summarization module is used to obtain the target motion state description information in OpenScenario traffic flow, classify and summarize the target motion scenarios, and form a simulation scenario database.

[0015] In a third aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect of the present invention.

[0016] In a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present invention.

[0017] In this embodiment of the invention, road image data is collected through crowdsourcing, and intelligent cameras are used to identify roads and traffic flow in the images to construct simulation scenarios. By identifying target behaviors, the data is classified and summarized to form a scenario database. This not only ensures the amount of simulation scenario data collected, but also effectively reduces the collection cost, achieving low-cost and diversified collection and processing of simulation scenario data. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a method for constructing a simulation scene database according to an embodiment of the present invention;

[0020] Figure 2 This is a schematic diagram of image data perception and recognition provided in one embodiment of the present invention;

[0021] Figure 3 This is a schematic diagram of the structure of a simulation scene database construction system provided in one embodiment of the present invention;

[0022] Figure 4 This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0024] It should be understood that the terms "comprising" and other similar expressions in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, or apparatus that includes a series of steps or units and is not limited to the listed steps or units. Furthermore, "first" and "second" are used to distinguish different objects and are not intended to describe a specific order.

[0025] Please see Figure 1 The present invention provides a flowchart illustrating a method for constructing a simulation scenario database, comprising:

[0026] S101, Receive road image data collected through crowdsourcing;

[0027] The simulation scene data collection is subcontracted. Crowdsourced vehicles collect real-scene image data through onboard cameras and upload the image data to the server. The server provides a user data upload interface.

[0028] The road image data refers to the view image near the rearview mirror of the car, that is, the vehicle camera is located near the rearview mirror of the vehicle and can collect perception information of the road in front and the sides of the vehicle.

[0029] The road image data refers to road images collected by vehicle-mounted cameras. Road perception information and traffic flow perception information can be extracted based on the road images.

[0030] S102. The image data is identified by the intelligent camera, and road perception information and traffic flow perception information are output.

[0031] The crowdsourced video data is played back, and the smart camera is used to perceive and recognize the video data to obtain the corresponding perception information.

[0032] In one embodiment, such as Figure 2 As shown, the screen, teleconverter, and smart camera are all placed in a dark box. The image data is played on the screen, and the teleconverter is set between the smart camera and the screen at the same horizontal line. The smart camera recognizes the image scene on the screen.

[0033] The intelligent camera is used to output road and traffic flow information based on optical image data and computer vision perception, including the identification of lane line positions and distances, and the identification of the relative distance and speed of target vehicles.

[0034] The road perception information includes lane line position, lane line distance, number of lanes, road length, road width, curvature, slope, and orientation; the traffic flow perception information includes target vehicle speed, trigger time, relative speed, relative distance, and vehicle position.

[0035] S103. Construct OpenDrive roads and Openscenario traffic flows based on road perception information and traffic flow perception information;

[0036] OpenDrive describes the static road traffic network required for autonomous driving simulation applications and provides a standard exchange format specification document. This standard mainly describes roads and objects on the roads. OpenScenario is one of the standards developed by ASAM, specifically for dynamic scene planning in the field of scene simulation. It is used to establish standards between maps, scenes, tools and test functions to achieve standardized description of dynamic scenes for intelligent driving. It includes three fields: RoadNetwork, Entity and Storyboard, which are used to describe scene roads, scene participant parameters and participant behaviors, respectively.

[0037] Specifically, the information of each frame sensed by the camera is stored as a dictionary, the dictionary is converted into an XML structure using a built-in Python package, and then modified into a file of a predetermined format;

[0038] Create a dictionary and set two fields in the dictionary: Entities and Storyboard. The Entities field is used to write the description information of the vehicle and the target object, and the Storyboard field is used to write the initial state information of the vehicle and the target object, as well as the state information of the vehicle and the target object after they move.

[0039] Traffic flow scenario files are generated based on the Entities and Storyboard fields.

[0040] In OpenDrive road construction, each frame of information captured by the camera is stored as a dictionary. If a field is looped multiple times, multiple dictionaries are added to the list. The dictionary is then converted into an XML structure using a Python built-in package, with the suffix changed to .xodr. This completes the OpenDrive road construction.

[0041] In the OpenScenario traffic flow construction, an empty dictionary is created, and two fields, Entities and Storyboard, are written into the dictionary. The Entities field mainly describes the basic information of the vehicle and the target object, including the target object's length, width, height, name, weight, etc. The Storyboard field contains two fields, Init and Story. Init mainly describes the initial state of the vehicle and the target object, including the initial position and speed information. Story mainly describes the state of the vehicle and the target object after movement, including movement time, current position, speed, lane change time and direction, etc.

[0042] S104. Obtain the target motion state description information in the OpenScenario traffic flow, classify and summarize the target motion scenarios, and form a simulation scenario database.

[0043] Extract descriptive information from each field in the OpenScenario traffic flow, mainly including target motion state description information, and classify and summarize the scenarios to form a scenario database.

[0044] In this embodiment, not only can crowdsourced data be collected, ensuring the amount of simulation data collected, but the collection cost can also be reduced, thereby enabling the simple and quick establishment of a traffic scenario simulation database.

[0045] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0046] Figure 3 This is a schematic diagram of a simulation scene database construction system provided in an embodiment of the present invention. The system includes:

[0047] Data receiving module 310 is used to receive road image data collected through crowdsourcing;

[0048] The road image data refers to the view image near the rearview mirror of the car.

[0049] The image recognition module 320 is used to recognize image data through a smart camera and output road perception information and traffic flow perception information.

[0050] Optionally, the screen, teleconverter, and smart camera are all placed in a dark box, the image data is played on the screen, and the teleconverter is set between the smart camera and the screen at the same horizontal line, so that the smart camera can recognize the image scene on the screen.

[0051] The scenario building module 330 is used to build OpenDrive roads and Openscenario traffic flows based on road perception information and traffic flow perception information;

[0052] Specifically, the information of each frame sensed by the camera is stored as a dictionary, the dictionary is converted into an XML structure using a built-in Python package, and then modified into a file of a predetermined format;

[0053] Create a dictionary and set two fields in the dictionary: Entities and Storyboard. The Entities field is used to write the description information of the vehicle and the target object, and the Storyboard field is used to write the initial state information of the vehicle and the target object, as well as the state information of the vehicle and the target object after they move.

[0054] Traffic flow scenario files are generated based on the Entities and Storyboard fields.

[0055] The classification and summarization module 340 is used to obtain the target motion state description information in Openscenario traffic flow, classify and summarize the target motion scenes, and form a simulation scene database.

[0056] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the systems and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0057] Figure 4 This is a schematic diagram of an electronic device according to an embodiment of the present invention. The electronic device is used for constructing a simulation scene database. Figure 4 As shown, the electronic device 4 in this embodiment includes a memory 410, a processor 420, and a system bus 430. The memory 410 includes an executable program 4101 stored thereon. As those skilled in the art will understand, Figure 4 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0058] The following is combined Figure 4 A detailed introduction to each component of the electronic device:

[0059] The memory 410 can be used to store software programs and modules. The processor 420 executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory 410. The memory 410 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device (such as cached data), etc. In addition, the memory 410 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0060] The memory 410 contains an executable program 4101 for a network request method. This executable program 4101 can be divided into one or more modules / units, which are stored in the memory 410 and executed by the processor 420 to perform video frame extraction, etc. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, describing the execution process of the computer program 4101 in the electronic device 4. For example, the computer program 4101 can be divided into functional modules such as a data receiving module, an image recognition module, a scene construction module, and a classification and summarization module.

[0061] Processor 420 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in memory 410, and by calling data stored in memory 410, it performs various functions and processes data, thereby monitoring the overall status of the electronic device. Optionally, processor 420 may include one or more processing units; preferably, processor 420 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, application programs, etc., and the modem processor mainly handles wireless communication. It is understood that the aforementioned modem processor may not be integrated into processor 420.

[0062] The system bus 430 is used to connect various functional components inside the computer, transmitting data, address, and control information. Its type can be, for example, a PCI bus, an ISA bus, or a CAN bus. Instructions from the processor 420 are transmitted to the memory 410 via the bus, and the memory 410 sends data back to the processor 420. The system bus 430 is responsible for data and instruction exchange between the processor 420 and the memory 410. Of course, the system bus 430 can also connect to other devices, such as network interfaces and display devices.

[0063] In this embodiment of the invention, the executable program executed by the processing 420 of the electronic device includes:

[0064] Receive road image data collected through crowdsourcing;

[0065] The image data is identified by intelligent cameras, and road perception information and traffic flow perception information are output.

[0066] Based on road perception information and traffic flow perception information, construct OpenDrive roads and Openscenario traffic flows;

[0067] Obtain descriptions of target motion states in OpenScenario traffic flow, classify and summarize target motion scenarios, and form a simulation scenario database.

[0068] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0069] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0070] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing a simulation scene database, characterized in that, include: Receive road image data collected through crowdsourcing; The image data is identified by intelligent cameras, and road perception information and traffic flow perception information are output. The process involves playing video data on a screen and placing a teleconverter between the smart camera and the screen at the same horizontal level. The smart camera then identifies the scene on the screen. The screen, teleconverter, and smart camera are all placed in a dark box. Based on road perception information and traffic flow perception information, construct OpenDrive roads and Openscenario traffic flows; Obtain descriptions of target motion states in OpenScenario traffic flow, classify and summarize target motion scenarios, and form a simulation scenario database.

2. The method according to claim 1, characterized in that, The road image data is a view from the area near the rearview mirror of a car.

3. The method according to claim 1, characterized in that, The construction of OpenDrive roads and Openscenario traffic flows based on road perception information and traffic flow perception information includes: Each frame of information sensed by the camera is stored as a dictionary, the dictionary is converted into an XML structure using a built-in Python package, and then modified into a file of a predetermined format. Create a dictionary and set two fields in the dictionary: Entities and Storyboard. The Entities field is used to write the description information of the vehicle and the target object, and the Storyboard field is used to write the initial state information of the vehicle and the target object, as well as the state information of the vehicle and the target object after they move. Traffic flow scenario files are generated based on the Entities and Storyboard fields.

4. A simulation scene database construction system, characterized in that, At least include: The data receiving module is used to receive road image data collected through crowdsourcing. The image recognition module is used to recognize image data through a smart camera and output road perception information and traffic flow perception information. The process involves playing video data on a screen and placing a teleconverter between the smart camera and the screen at the same horizontal level. The smart camera then identifies the scene on the screen. The screen, teleconverter, and smart camera are all placed in a dark box. The scenario building module is used to construct OpenDrive roads and Openscenario traffic flows based on road perception information and traffic flow perception information; The classification and summarization module is used to obtain the target motion state description information in OpenScenario traffic flow, classify and summarize the target motion scenarios, and form a simulation scenario database.

5. The system according to claim 4, characterized in that, The road image data is a view from the area near the rearview mirror of a car.

6. The system according to claim 4, characterized in that, The construction of OpenDrive roads and Openscenario traffic flows based on road perception information and traffic flow perception information includes: Each frame of information sensed by the camera is stored as a dictionary, the dictionary is converted into an XML structure using a built-in Python package, and then modified into a file of a predetermined format. Create a dictionary and set two fields in the dictionary: Entities and Storyboard. The Entities field is used to write the description information of the vehicle and the target object, and the Storyboard field is used to write the initial state information of the vehicle and the target object, as well as the state information of the vehicle and the target object after they move. Traffic flow scenario files are generated based on the Entities and Storyboard fields.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of a simulation scene database construction method as described in any one of claims 1 to 3.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed, it implements the steps of a simulation scene database construction method as described in any one of claims 1 to 3.

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