CN116933561A - Simulation scene construction method, device, equipment and medium - Google Patents

Abstract

The embodiment of the invention discloses a simulation scene construction method, a device, equipment and a medium, wherein the method comprises the following steps: acquiring road parameter information acquired by a target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information; extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle; and constructing a simulation scene based on the road characteristic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs. According to the technical scheme provided by the embodiment of the invention, the simulation scene of the actual road can be constructed.

Description

Simulation scene construction method, device, equipment and medium

Technical Field

The embodiment of the invention relates to a computer technology, in particular to a simulation scene construction method, a simulation scene construction device, simulation scene construction equipment and a simulation scene construction medium.

Background

With the development of technology, automobiles are becoming more and more intelligent. The intelligent driving vehicle can reduce the occurrence rate of traffic accidents caused by human factors. Before intelligent driving of a vehicle in mass production, a large number of tests are required to ensure the safety and reliability of the vehicle.

At present, an intelligent driving test is usually performed by adopting a real vehicle test mode. However, this approach to real vehicle testing is time consuming and laborious and also fails to test in all classical, extreme or ideal scenarios. It can be seen that a way to construct a simulation scenario is currently needed to perform a simulation test on an intelligent driving vehicle in the simulation scenario.

Disclosure of Invention

The embodiment of the invention provides a simulation scene construction method, device, equipment and medium, which are used for constructing a simulation scene of an actual road.

In a first aspect, an embodiment of the present invention provides a method for constructing a simulation scenario, including:

acquiring road parameter information acquired by a target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information;

extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle;

and constructing a simulation scene based on the road characteristic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

In a second aspect, an embodiment of the present invention provides a simulation scene construction apparatus, including:

the road parameter information acquisition module is used for acquiring road parameter information acquired by the target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information;

the road characteristic information determining module is used for extracting characteristics of the road parameter information and determining road characteristic information corresponding to the target vehicle;

and the target simulation scene construction module is used for constructing a simulation scene based on the road characteristic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

In a third aspect, an embodiment of the present invention provides an electronic device, including:

one or more processors;

a memory for storing one or more programs;

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the simulation scenario construction method as provided by any embodiment of the present invention.

In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for constructing a simulation scenario as provided in any embodiment of the present invention.

According to the technical scheme, road parameter information acquired by the target vehicle is acquired; the road parameter information includes: road grade information, altitude information, and lane curvature information; extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle; and constructing a simulation scene based on the road characteristic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs, so that various road characteristics in the actual road can be determined based on various road parameter information acquired on the actual road, the simulation scene of the actual road can be restored by utilizing all the road characteristics, various road characteristics can be regulated, and more diversified simulation scenes can be constructed by utilizing the regulated road characteristics, so that the intelligent driving vehicle can perform simulation test in the more real and diversified simulation scenes.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flowchart of a simulation scenario construction method according to a first embodiment of the present invention;

FIG. 2 is an exemplary diagram of a simulation scenario construction system according to a first embodiment of the present invention;

FIG. 3 is a flowchart of a simulation scenario construction method according to a second embodiment of the present invention;

fig. 4 is a schematic structural diagram of a simulation scene construction apparatus according to a third embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device implementing a simulation scenario construction method according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of a simulation scenario construction method according to an embodiment of the present invention, where the method is applicable to a case of implementing a simulation scenario construction based on an actual scenario, and is particularly applicable to a case of implementing a simulation scenario construction for performing a simulation test on an intelligent driving vehicle, and the method may be performed by a simulation scenario construction device, which may be implemented in a form of hardware and/or software, and the simulation scenario construction device may be configured in an electronic device. As shown in fig. 1, the method includes:

s110, acquiring road parameter information acquired by a target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information.

Wherein the target vehicle may be used to collect road parameter information for the road being traveled. For example, the target vehicle may be, but is not limited to, a real vehicle that is driven by a person or a real vehicle that is controlled by a person to turn on an autonomous driving mode. The road parameter information is a relevant parameter that can be used to represent the characteristics of the road. The road parameter information may include road grade information, altitude information, and lane curvature information.

In this embodiment, after the target vehicle runs a section of road for testing, the collected road parameter information may be uploaded to the data storage server through the wireless network. The data storage server can be used for storing road parameter information uploaded by a plurality of target vehicles, so that the automatic driving scene simulation software can acquire the road parameter information acquired by the target vehicles from the data storage server. For example, the road parameter information may include road grade information, altitude information, and lane curvature information.

In this embodiment, a plurality of vehicles collecting data also have unique vehicle identifiers, and upload the unique vehicle identifiers and the collected road parameter information to the data storage server together, so as to perform targeted downloading, that is, only download and generate a first simulation scene by using the road parameter information collected by the first vehicle, and perform a simulation test on the first intelligent driving vehicle in the first simulation scene.

And S120, extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle.

The road characteristic information may include, but is not limited to, road grade characteristics, elevation characteristics, and lane curvature characteristics, among others. Specifically, the road parameter information is subjected to feature extraction, the extracted feature information is subjected to data processing, and a table or a polynomial is generated to represent road gradient features, altitude features, lane curvature features and the like.

S130, constructing a simulation scene based on the road characteristic information, and obtaining a target simulation scene corresponding to the road on which the target vehicle runs.

The target simulation scene may refer to a simulation scene corresponding to an actual road on which the target vehicle travels. Specifically, a road model can be built by importing a table for representing all road characteristics or writing polynomial coefficients for representing all road characteristics according to a mode of building the road model in scene simulation software, and environment parameters are adjusted to obtain a target simulation scene corresponding to a road on which a target vehicle runs, so that characteristics such as continuous road fluctuation of a specified road section are restored, and the reality of building the simulation scene is improved.

In this embodiment, road parameter information corresponding to at least two sections of roads may be downloaded, feature extraction may be performed, and simulation scenes may be respectively constructed based on the extracted road feature information, so as to obtain a plurality of simulation scenes, and then edges of two simulation scenes to be spliced may be adjusted, so as to perform a round and reasonable simulation scene splicing.

According to the technical scheme, road parameter information acquired by the target vehicle is acquired; the road parameter information includes: road grade information, altitude information, and lane curvature information; extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle; the simulation scene construction is carried out based on the road feature information to obtain a target simulation scene corresponding to the road on which the target vehicle runs, so that various road features in the actual road can be determined based on various road parameter information acquired on the actual road, the simulation scene of the actual road can be restored by utilizing all the road features, various road features can be adjusted, and more diversified simulation scenes can be constructed by utilizing the adjusted road features, so that the intelligent driving vehicle can carry out simulation test in the more real and diversified simulation scenes.

Based on the above technical solution, S110 may include: the acceleration sensor on the control target vehicle collects acceleration of six degrees of freedom and determines road gradient information based on each acceleration; a positioning sensor on a control target vehicle collects altitude information; the intelligent camera on the control target vehicle acquires lane curvature information; the TBOX device on the control target vehicle uploads road gradient information, altitude information, and lane curvature information.

The acceleration sensor can be used for acquiring acceleration of six degrees of freedom. Six degrees of freedom may refer to a degree of freedom of movement in the directions of three orthogonal coordinate axes x, y, z and a degree of freedom of rotation about the three coordinate axes. The rectangular coordinate system is a coordinate system constructed by taking a target vehicle as an origin, taking a horizontal plane as a plane formed by an x-axis and a y-axis, and taking a road direction as an x-axis positive direction. The positioning sensor may be used to collect position information and altitude information. The altitude information is altitude information with the sea level as an original plane. The lane curvature information may be used to represent the degree of tortuosity of the road.

Specifically, an acceleration sensor on a control target vehicle collects acceleration of six degrees of freedom, determines road gradient information based on the acceleration, and determines a time stamp corresponding to each road gradient information; a positioning sensor on a control target vehicle collects altitude information and a time stamp corresponding to each altitude information; the intelligent camera on the control target vehicle acquires lane curvature information and a time stamp corresponding to each lane curvature information; the TBOX device on the control target vehicle uploads road grade information, altitude information, lane curvature information, and their corresponding time stamps in the presence of a wireless network. If the road section for collecting the road parameter information does not cover the wireless network, the collected road parameter information is temporarily stored in the storage device of the target vehicle, and the data uploading is completed under the condition that the network connection can be realized.

In addition, through sensors such as acceleration sensor and the location sensor of vehicle, can acquire road characteristic information such as road slope, road curvature, compare and carry out scene acquisition through the professional scene acquisition equipment of many cameras, radar that generally adopts, can reduce cost and the complexity of autopilot emulation test scene construction. And the road characteristic related information can be obtained without depending on a high-precision map and used for constructing an automatic driving simulation scene, so that the cost is reduced to a certain extent and the efficiency is improved.

By way of example, fig. 2 shows a schematic structural diagram of an autopilot simulation scenario construction system. As shown in fig. 2, the automatic driving simulation scene construction system includes: vehicle end equipment, a data storage server and a simulation system. Wherein the vehicle end comprises a sensor module and a TBOX; the simulation system comprises a simulation scene construction module and a simulation test module; the sensor module comprises an acceleration sensor, a positioning sensor and an intelligent camera. Specifically, a sensor module on the vehicle end controls an acceleration sensor to collect acceleration with six degrees of freedom, determines road gradient information, controls a positioning sensor to collect altitude information, and controls an intelligent camera to collect lane curvature information. And uploading the acquired road parameter information to a data storage server through the TBOX. And downloading the road parameter information from the data storage server, extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle. And constructing a simulation scene based on the road characteristic information in the simulation scene construction module to obtain a target simulation scene corresponding to the road on which the target vehicle runs. And testing the virtual vehicle which is built in advance by utilizing the simulation test module and the target simulation scene, and outputting a test result.

On the basis of the technical scheme, after the target simulation scene is obtained, the method further comprises the following steps: and performing automatic driving simulation test on each virtual vehicle to be tested based on the target simulation scene, obtaining test data corresponding to each virtual vehicle, and determining a test result corresponding to each virtual vehicle based on the test data.

The virtual vehicle to be tested may refer to a vehicle model constructed by various parameters of the intelligent driving vehicle. The test data may include, but is not limited to, number of vehicle collisions, vehicle energy consumption, etc. The test results can be classified into several classes. The test results are results that may indicate performance of the vehicle, such as safety or energy consumption.

Specifically, after the target simulation scene is obtained, the virtual vehicles to be tested can be constructed according to various parameters corresponding to the real vehicles to be tested, automatic driving simulation tests are carried out on the virtual vehicles to be tested based on the target simulation scene, test data corresponding to the virtual vehicles are obtained after the virtual vehicles run out of roads in the target simulation scene, performance indexes of the virtual vehicles in a certain aspect are determined according to each test data, and then the overall test result of the virtual vehicles is comprehensively determined according to various performance indexes.

In this embodiment, test data corresponding to the virtual vehicle may also be obtained when the virtual vehicle runs continuously through the target simulation scene for the preset number of times. The target simulation scene can be adjusted by adding road gradient characteristics, so that the influence of sensor identification range change caused by road gradient on the safety of the automatic driving system and the vehicle oil consumption condition can be tested, and the performance of the automatic driving system in mountain areas can be further evaluated.

Example two

Fig. 3 is a flowchart of a simulation scene construction method according to a second embodiment of the present invention, where, based on the above embodiment, a process of constructing a simulation scene based on road feature information to obtain a simulation scene corresponding to a road on which a target vehicle is traveling is described in detail. Wherein the explanation of the same or corresponding terms as those of the above embodiments is not repeated herein. As shown in fig. 3, the method includes:

s210, acquiring road parameter information acquired by a target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information.

S220, extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle.

S230, constructing a static simulation scene based on the road characteristic information, and obtaining a static simulation scene corresponding to the road on which the target vehicle runs.

Wherein, the static simulation scene can comprise a simulation road. Specifically, the road model can be built by importing a table for representing all road characteristics or writing polynomial coefficients for representing all road characteristics according to a way of building the road model in scene simulation software, so as to realize static simulation scene construction based on road characteristic information and obtain a static simulation scene composed of a road on which a target vehicle runs.

S240, constructing a dynamic scene based on the static simulation scene and preset dynamic information, and obtaining a target simulation scene corresponding to a road on which the target vehicle runs.

The preset dynamic information may be parameter information corresponding to an object to be moved in a preset simulation scene. For example, the preset dynamic information may be, but is not limited to, a driving parameter, a weather variation parameter, or an illumination intensity parameter of other vehicles in the road, etc. In this embodiment, running parameters of other vehicles can be added to simulate the traffic flow in real running, weather variation parameters can be adjusted to simulate the weather, illumination intensity parameters can be adjusted to simulate scenes such as daytime, dusk and night, so that simulation of scenes except roads is realized on the basis of static simulation scenes, a target simulation scene corresponding to the road on which the target vehicle runs is obtained, and then the target simulation scene of a certain section of simulation road under any condition can be determined according to adjustment of preset dynamic information, and further, not only the actual road but also all classical scenes, extreme scenes or ideal scenes can be simulated, and further, the simulation can be realized by adjusting various road features and dynamic features except roads, so that more diversified simulation scenes can be constructed, and intelligent driving vehicles can be subjected to simulation test in more real and more diversified simulation scenes.

According to the technical scheme, static simulation scene construction is carried out based on road characteristic information, and a static simulation scene corresponding to a road on which a target vehicle runs is obtained; the method comprises the steps of constructing a dynamic scene based on a static simulation scene and preset dynamic information to obtain a target simulation scene corresponding to a road on which a target vehicle runs, so that simulation of the scene except the road is realized on the basis of the static simulation scene, the target simulation scene corresponding to the road on which the target vehicle runs is obtained, and then the target simulation scene of a certain section of simulation road under any condition can be determined according to adjustment of the preset dynamic information, and further, not only can an actual road be simulated, but also all classical scenes, extreme scenes or ideal scenes can be simulated, and further, various road features and dynamic features except the road can be adjusted to construct more diversified simulation scenes, so that the intelligent driving vehicle can be subjected to simulation test in the more real and diversified simulation scenes.

Based on the above technical solution, S240 may include: constructing a dynamic scene based on the static simulation scene and preset traffic flow information, and obtaining a dynamic simulation scene corresponding to a road on which a target vehicle runs; the dynamic simulation scene comprises a static simulation scene and a accompany vehicle; and constructing an environment scene based on the dynamic simulation scene and preset environment information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

The preset traffic flow information may refer to a density of traffic flow. The preset traffic flow information may represent traffic flows of different densities. A companion vehicle may refer to other vehicles than a virtual vehicle. The preset environmental information may refer to information other than vehicles and roads. For example, the preset environmental information may include, but is not limited to, weather and light intensity.

In this embodiment, traffic flows with different densities may be defined according to the test requirements, or a complex traffic flow simulation may be implemented by combining specialized traffic flow simulation software (such as SUMO, etc.), and weather (such as rain, snow, fog, etc.) information and illumination (such as daytime, dusk, night, etc.) information may be added, so as to perfect environmental elements in the dynamic simulation scene, further increase diversity of the simulation test scene, and satisfy different test requirements.

Based on the above technical solution, S240 may include: carrying out dynamic scene construction based on the static simulation scene and a preset accompanying driver model to obtain a dynamic simulation scene corresponding to a road on which a target vehicle runs; the dynamic simulation scene comprises a static simulation scene, a running accompanying vehicle and a running accompanying driver; and constructing an environment scene based on the dynamic simulation scene and preset environment information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

The driver for accompanying may refer to a driver for driving the accompanying vehicle, which is constructed according to parameters corresponding to driving habits of various drivers counted in advance. For example, a running driver model can be given to the running accompanying vehicle on the basis of the static simulation scene so as to set specific behaviors (such as acceleration, deceleration, parking, cutting in and cutting out and the like) of the running accompanying driver, so that the running accompanying vehicle can have more various running modes and obtain a dynamic simulation scene corresponding to a road on which the target vehicle runs; and constructing an environment scene based on the dynamic simulation scene and preset environment information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

Based on the above technical solution, S230 may include: and adjusting static parameters in the initial simulation scene based on the road characteristic information to obtain a static simulation scene corresponding to the road on which the target vehicle runs.

The initial simulation scene may refer to a simulation scene when each parameter in the simulation scene is a historical average value. Static parameters may refer to all parameters involved in generating a link. Specifically, the road model can be built by introducing a table for representing all road characteristics or writing polynomial coefficients for representing all road characteristics according to a mode of building the road model in scene simulation software, so as to obtain a static simulation scene corresponding to a road on which a target vehicle runs, thereby quickly adjusting the static parameters on the basis of the initial simulation scene and improving the efficiency of building the simulation scene.

The following is an embodiment of a simulation scene construction apparatus provided by the embodiment of the present invention, which belongs to the same inventive concept as the simulation scene construction method of the above embodiments, and details of the embodiment of the simulation scene construction apparatus, which are not described in detail, may refer to the embodiment of the above simulation scene construction method.

Example III

Fig. 4 is a schematic structural diagram of a simulation scene construction apparatus according to a third embodiment of the present invention. As shown in fig. 4, the apparatus includes: the system comprises a road parameter information acquisition module 310, a road characteristic information determination module 320 and a target simulation scene construction module 330.

The road parameter information acquisition module 310 is configured to acquire road parameter information acquired by the target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information; the road feature information determining module 320 is configured to perform feature extraction on the road parameter information, and determine road feature information corresponding to the target vehicle; the target simulation scene construction module 330 is configured to perform simulation scene construction based on the road feature information, and obtain a target simulation scene corresponding to a road on which the target vehicle is traveling.

According to the technical scheme, road parameter information acquired by the target vehicle is acquired; the road parameter information includes: road grade information, altitude information, and lane curvature information; extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle; the simulation scene construction is carried out based on the road feature information to obtain a target simulation scene corresponding to the road on which the target vehicle runs, so that various road features in the actual road can be determined based on various road parameter information acquired on the actual road, the simulation scene of the actual road can be restored by utilizing all the road features, various road features can be adjusted, and more diversified simulation scenes can be constructed by utilizing the adjusted road features, so that the intelligent driving vehicle can carry out simulation test in the more real and diversified simulation scenes.

Optionally, the target simulation scene construction module 330 may include:

the static simulation scene construction sub-module is used for carrying out static simulation scene construction based on the road characteristic information to obtain a static simulation scene corresponding to a road on which the target vehicle runs;

and the target simulation scene construction sub-module is used for carrying out dynamic scene construction based on the static simulation scene and preset dynamic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

Optionally, the target simulation scene building submodule is specifically configured to: constructing a dynamic scene based on the static simulation scene and preset traffic flow information, and obtaining a dynamic simulation scene corresponding to a road on which a target vehicle runs; the dynamic simulation scene comprises a static simulation scene and a accompany vehicle; and constructing an environment scene based on the dynamic simulation scene and preset environment information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

Optionally, the target simulation scene construction sub-module is further configured to: carrying out dynamic scene construction based on the static simulation scene and a preset accompanying driver model to obtain a dynamic simulation scene corresponding to a road on which a target vehicle runs; the dynamic simulation scene comprises a static simulation scene, a running accompanying vehicle and a running accompanying driver; and constructing an environment scene based on the dynamic simulation scene and preset environment information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

Optionally, the static simulation scene construction submodule is specifically configured to: and adjusting static parameters in the initial simulation scene based on the road characteristic information to obtain a static simulation scene corresponding to the road on which the target vehicle runs.

Optionally, the apparatus further comprises:

and the test result determining module is used for carrying out automatic driving simulation test on each virtual vehicle to be tested based on the target simulation scene after the target simulation scene is obtained, obtaining test data corresponding to each virtual vehicle, and determining a test result corresponding to each virtual vehicle based on the test data.

Optionally, the road parameter information obtaining module 310 is specifically configured to: the acceleration sensor on the control target vehicle collects acceleration of six degrees of freedom and determines road gradient information based on each acceleration; a positioning sensor on a control target vehicle collects altitude information; the intelligent camera on the control target vehicle acquires lane curvature information; the TBOX device on the control target vehicle uploads road gradient information, altitude information, and lane curvature information.

The simulation scene construction device provided by the embodiment of the invention can execute the simulation scene construction method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the simulation scene construction method.

It should be noted that, in the embodiment of the simulation scene construction apparatus, each unit and module included are only divided according to the functional logic, but not limited to the above division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.

Example IV

Fig. 5 shows a schematic diagram of the structure of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the simulation scenario construction method.

In some embodiments, the simulation scenario construction method may be implemented as a computer program, which is tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the simulation scenario construction method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the simulation scenario construction method in any other suitable way (e.g. by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims (10)

1. The simulation scene construction method is characterized by comprising the following steps of:

acquiring road parameter information acquired by a target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information;

extracting the characteristics of the road parameter information, and determining the road characteristic information corresponding to the target vehicle;

and constructing a simulation scene based on the road characteristic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

2. The method according to claim 1, wherein the performing the simulation scene construction based on the road feature information to obtain a target simulation scene corresponding to a road on which the target vehicle travels includes:

constructing a static simulation scene based on the road characteristic information to obtain a static simulation scene corresponding to a road on which the target vehicle runs;

and carrying out dynamic scene construction based on the static simulation scene and preset dynamic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

3. The method according to claim 2, wherein the performing the dynamic scene construction based on the static simulation scene and the preset dynamic information to obtain the target simulation scene corresponding to the road on which the target vehicle is traveling includes:

carrying out dynamic scene construction based on the static simulation scene and preset traffic flow information to obtain a dynamic simulation scene corresponding to a road on which the target vehicle runs; the dynamic simulation scene comprises a static simulation scene and a accompany vehicle;

and constructing an environment scene based on the dynamic simulation scene and preset environment information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

4. The method according to claim 2, wherein the performing the dynamic scene construction based on the static simulation scene and the preset dynamic information to obtain the target simulation scene corresponding to the road on which the target vehicle is traveling includes:

performing dynamic scene construction based on the static simulation scene and a preset accompanying driver model to obtain a dynamic simulation scene corresponding to a road on which the target vehicle runs; the dynamic simulation scene comprises a static simulation scene, a accompanying vehicle and an accompanying driver;

and constructing an environment scene based on the dynamic simulation scene and preset environment information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

5. The method according to claim 2, wherein the performing static simulation scene construction based on the road feature information to obtain a static simulation scene corresponding to a road on which the target vehicle is traveling includes:

and adjusting static parameters in the initial simulation scene based on the road characteristic information to obtain a static simulation scene corresponding to the road on which the target vehicle runs.

6. The method of claim 1, wherein after obtaining the target simulation scenario, the method further comprises:

and carrying out automatic driving simulation test on each virtual vehicle to be tested based on the target simulation scene, obtaining test data corresponding to each virtual vehicle, and determining a test result corresponding to each virtual vehicle based on the test data.

7. The method of claim 1, wherein the obtaining road parameter information collected by the target vehicle comprises:

an acceleration sensor on a control target vehicle collects acceleration of six degrees of freedom, and road gradient information is determined based on each acceleration;

controlling a positioning sensor on the target vehicle to acquire altitude information;

controlling an intelligent camera on the target vehicle to acquire lane curvature information;

controlling a TBOX device on the target vehicle to upload the road grade information, the altitude information, and the lane curvature information.

8. A simulation scene construction apparatus, comprising:

the road parameter information acquisition module is used for acquiring road parameter information acquired by the target vehicle; the road parameter information includes: road grade information, altitude information, and lane curvature information;

the road characteristic information determining module is used for extracting characteristics of the road parameter information and determining road characteristic information corresponding to the target vehicle;

and the target simulation scene construction module is used for constructing a simulation scene based on the road characteristic information to obtain a target simulation scene corresponding to the road on which the target vehicle runs.

9. An electronic device, the electronic device comprising:

one or more processors;

a memory for storing one or more programs;

the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the simulation scenario construction method of any one of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the simulation scene construction method according to any one of claims 1 to 7.