KR102576733B1 - Method and system for simulating traffic environment based on vils linked to control platform - Google Patents

Abstract

The present disclosure relates to a method of reproducing a traffic environment based on VILS linked to a control platform, which is performed by at least one processor. A method of reproducing a traffic environment includes generating scenario information for evaluating autonomous vehicles within a specific area, transmitting scenario information to a vehicle to be evaluated, transmitting a plurality of virtual object information to a vehicle to be evaluated, and transmitting information from a vehicle to be evaluated. Receiving actual driving data of a vehicle within a specific area, receiving simulated virtual driving data from a vehicle to be evaluated based on the actual driving data of the vehicle, and based on the actual driving data of the vehicle and the virtual driving data of the vehicle. Thus, it includes the step of visualizing the driving of the evaluation target vehicle within a specific area and outputting it on a display.

Description

VILS-based traffic environment reproduction method and system linked to control platform {METHOD AND SYSTEM FOR SIMULATING TRAFFIC ENVIRONMENT BASED ON VILS LINKED TO CONTROL PLATFORM}

This disclosure relates to a VILS-based traffic environment reproduction method and system linked to a control platform. Specifically, by transmitting autonomous vehicle evaluation scenarios and virtual object information and receiving actual driving data and virtual driving data from the evaluation target vehicle, This relates to a method and device for visualizing and outputting the driving of an evaluation target vehicle.

Recently, as automobile-related technologies such as IT, electricity, and electronic technologies have developed, autonomous driving technology that utilizes all of them has been attracting attention. However, because autonomous driving technology controls the vehicle without driver intervention, it entails many social problems such as safety regulations, and verification through many tests is necessary to solve these problems.

However, it takes a lot of time and money to physically implement an actual traffic environment to evaluate autonomous driving technology, and it is difficult to overcome location constraints. In addition, autonomous driving technology evaluation using only a virtual reality model is not accompanied by actual vehicle operation, so results may be different from reality, and there is a problem that the actual driving process cannot be visually confirmed from the outside.

The present disclosure provides a method for reproducing a traffic environment based on VILS linked to a control platform, a computer program stored in a recording medium, and a system (device) to solve the above problems.

The present disclosure may be implemented in various ways, including as a method, system (device), or computer program stored in a readable storage medium.

According to an embodiment of the present disclosure, a traffic environment reproduction method based on VILS (Vehicle In the Loop Simulation) linked to a control platform, performed by at least one processor, generates autonomous vehicle evaluation scenario information within a specific area. Step, transmitting scenario information to the evaluation target vehicle, transmitting a plurality of virtual object information to the evaluation target vehicle, receiving actual driving data of the vehicle within a specific area from the evaluation target vehicle, evaluation target vehicle Receiving simulated virtual driving data based on the actual driving data of the vehicle from the vehicle, and visualizing the driving of the vehicle to be evaluated within a specific area based on the actual driving data of the vehicle and the virtual driving data of the vehicle and displaying the simulated driving data on the display. Includes an output step.

According to an embodiment of the present disclosure, the evaluation target vehicle is a real vehicle that drives using an autonomous driving algorithm within a specific area based on scenario information and a plurality of virtual object information, and the virtual driving data includes scenario information and a plurality of virtual objects. This is the result data of a vehicle subject to evaluation simulating the driving of an autonomous driving algorithm in a virtual environment corresponding to a specific area based on object information.

According to an embodiment of the present disclosure, the scenario information includes at least one of the departure location, arrival location, or scenario initiation trigger condition of the vehicle to be evaluated.

According to an embodiment of the present disclosure, the plurality of virtual objects include a virtual driving vehicle running around the evaluation target vehicle and a virtual pedestrian moving around the evaluation target vehicle, and the virtual driving vehicle simulates the driving behavior of a real driver. It is a virtual vehicle, and a virtual pedestrian is a virtual pedestrian that mimics the movement behavior of an actual pedestrian.

According to an embodiment of the present disclosure, actual driving data includes the speed, acceleration, steering angle, wheel steering angle, brake pedal signal, and accelerator pedal signal of the vehicle to be evaluated.

According to an embodiment of the present disclosure, virtual driving data includes location information of a vehicle subject to evaluation, location information of a plurality of virtual objects, and signal information within a virtual environment.

According to an embodiment of the present disclosure, the method further includes evaluating an autonomous driving algorithm mounted on a vehicle to be evaluated by analyzing received actual driving data and virtual driving data.

According to an embodiment of the present disclosure, the method further includes receiving data for controlling a virtual driving vehicle from a driving simulator and transmitting data for controlling the virtual driving vehicle to a vehicle to be evaluated.

In order to execute the above-described method according to an embodiment of the present disclosure on a computer, a computer program stored in a computer-readable recording medium is provided.

An information processing system according to an embodiment of the present disclosure includes a communication module, a memory, and at least one processor connected to the memory and configured to execute at least one computer-readable program included in the memory, and at least one program Generates scenario information for autonomous vehicle evaluation within a specific area, transmits the scenario information to the vehicle to be evaluated, transmits a plurality of virtual object information to the vehicle to be evaluated, and transmits information from the vehicle to the evaluation target to the vehicle within the specific area. Receive actual driving data, receive virtual driving data simulated based on the actual driving data of the vehicle from the evaluation target vehicle, and receive a plurality of virtual object information, the actual driving data of the vehicle, and the virtual driving data of the vehicle, It includes commands for visualizing the driving of the evaluation target vehicle within a specific area and outputting it on the display.

According to an embodiment of the present disclosure, the driving within a specific area of the evaluation target vehicle is visualized and output based on actual driving data and virtual driving data at the autonomous driving control center, so that the evaluation target is evaluated without the evaluator directly boarding the vehicle. The driving of the vehicle can be checked and evaluated.

According to an embodiment of the present disclosure, by receiving both actual driving data and simulated virtual driving data within a specific area of the evaluation target vehicle, analyzing and evaluating them, the autonomous driving control center mounted on the evaluation target vehicle Algorithms can be verified in various ways.

According to an embodiment of the present disclosure, by introducing a virtual vehicle reflecting the driving behavior of an actual driver into the test through a driving simulator within the autonomous driving control system, various traffic situations can be reproduced and the autonomous vehicle can be tested based on this. .

The effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be explained by those skilled in the art in the technical field to which this disclosure pertains from the description of the claims (hereinafter referred to as 'the person skilled in the art'). can be clearly understood.

Embodiments of the present disclosure will be described with reference to the accompanying drawings described below, in which like reference numerals indicate like elements, but are not limited thereto.
Figure 1 is a diagram showing an example of reproducing a traffic environment based on VILS (Vehicle In the Loop Simulation) linked to a control platform according to an embodiment of the present disclosure.
Figure 2 is a schematic diagram showing a configuration in which an information processing system according to an embodiment of the present disclosure is connected to communicate with a plurality of evaluation target vehicles.
Figure 3 is a block diagram showing the internal configuration of an autonomous driving control system according to an embodiment of the present disclosure.
Figure 4 is a block diagram showing the internal configuration of a vehicle to be evaluated according to an embodiment of the present disclosure.
FIG. 5 is a diagram illustrating an example of data communication between an autonomous driving control system and an evaluation target vehicle according to an embodiment of the present disclosure.
Figure 6 is a diagram showing an example of V2X (Vehicle to Everything) data transmitted and received by a vehicle to be evaluated according to an embodiment of the present disclosure.
Figure 7 is a diagram showing an example of data transmitted and received by a vehicle to be evaluated, a communication unit, and an autonomous driving control system according to an embodiment of the present disclosure.
Figure 8 is a flowchart showing an example of a method for reproducing a traffic environment based on VILS (Vehicle In the Loop Simulation) linked to a control platform according to an embodiment of the present disclosure.

Hereinafter, specific details for implementing the present disclosure will be described in detail with reference to the attached drawings. However, in the following description, detailed descriptions of well-known functions or configurations will be omitted if there is a risk of unnecessarily obscuring the gist of the present disclosure.

In the accompanying drawings, identical or corresponding components are given the same reference numerals. Additionally, in the description of the following embodiments, overlapping descriptions of identical or corresponding components may be omitted. However, even if descriptions of components are omitted, it is not intended that such components are not included in any embodiment.

Advantages and features of the disclosed embodiments and methods for achieving them will become clear by referring to the embodiments described below in conjunction with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. The present embodiments are merely provided to ensure that the present disclosure is complete and that the present disclosure does not convey the scope of the invention to those skilled in the art. It is provided only for complete information.

Terms used in this specification will be briefly described, and the disclosed embodiments will be described in detail. The terms used in this specification are general terms that are currently widely used as much as possible while considering the function in the present disclosure, but this may vary depending on the intention or precedent of a technician working in the related field, the emergence of new technology, etc. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the relevant invention. Accordingly, the terms used in this disclosure should be defined based on the meaning of the term and the overall content of the present disclosure, rather than simply the name of the term.

In this specification, singular expressions include plural expressions, unless the context clearly specifies the singular. Additionally, plural expressions include singular expressions, unless the context clearly specifies plural expressions. When it is said that a certain part includes a certain element throughout the specification, this does not mean excluding other elements, but may further include other elements, unless specifically stated to the contrary.

Additionally, the term 'module' or 'unit' used in the specification refers to a software or hardware component, and the 'module' or 'unit' performs certain roles. However, 'module' or 'unit' is not limited to software or hardware. A 'module' or 'unit' may be configured to reside on an addressable storage medium and may be configured to run on one or more processors. Thus, as an example, a 'module' or 'part' refers to components such as software components, object-oriented software components, class components and task components, processes, functions and properties. , procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, or variables. Components and 'modules' or 'parts' may be combined into smaller components and 'modules' or 'parts' or further components and 'modules' or 'parts'. Could be further separated.

According to an embodiment of the present disclosure, a 'module' or 'unit' may be implemented with a processor and memory. 'Processor' should be interpreted broadly to include general-purpose processors, central processing units (CPUs), microprocessors, digital signal processors (DSPs), controllers, microcontrollers, state machines, etc. In some contexts, 'processor' may refer to an application-specific integrated circuit (ASIC), programmable logic device (PLD), field programmable gate array (FPGA), etc. 'Processor' refers to a combination of processing devices, for example, a combination of a DSP and a microprocessor, a combination of a plurality of microprocessors, a combination of one or more microprocessors in combination with a DSP core, or any other such combination of configurations. You may. Additionally, 'memory' should be interpreted broadly to include any electronic component capable of storing electronic information. 'Memory' refers to random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), programmable read-only memory (PROM), erasable-programmable read-only memory (EPROM), May also refer to various types of processor-readable media, such as electrically erasable PROM (EEPROM), flash memory, magnetic or optical data storage, registers, etc. A memory is said to be in electronic communication with a processor if the processor can read information from and/or write information to the memory. The memory integrated into the processor is in electronic communication with the processor.

In this disclosure, 'control platform' may refer to a platform that can manage and control the evaluation process of an autonomous vehicle. For example, 'control platform' may refer to a platform that monitors the driving process of an autonomous vehicle in real time and receives actual driving data and virtual driving data. As an example of the 'control platform', an autonomous driving control system, which will be described later, may be included.

In this disclosure, 'VILS (Vehicle In the Loop Simulation)' may refer to a test method that delivers a virtually implemented test scenario to an autonomous vehicle driving on an actual road. In other words, 'VILS' can refer to an autonomous driving simulation device that performs various actual vehicle performance tests in a limited real road area in a virtual simulation environment.

Figure 1 is a diagram showing an example of reproducing a traffic environment based on VILS (Vehicle In the Loop Simulation) linked to a control platform according to an embodiment of the present disclosure. As shown, the autonomous driving control system 110 and the evaluation target vehicle 120 may communicate with each other to reproduce the traffic environment. Specifically, the autonomous driving control system 110 may transmit scenario information 112, virtual object information 114, etc. to the evaluation target vehicle 120. The evaluation target vehicle 120 may transmit actual driving data 122, virtual driving data 124, etc. to the autonomous driving control system 110. The evaluation target vehicle 120 may be an actual vehicle that drives using an autonomous driving algorithm within a specific area based on the scenario information 112 and the virtual object information 114.

According to one embodiment, the autonomous driving control system 110 may generate scenario information 112 and transmit it to the evaluation target vehicle 120. Scenario information 112 may include scenario information for evaluating autonomous vehicles within a specific area. For example, the scenario information 112 may include the starting location, arrival location, scenario initiation trigger condition, etc. of the vehicle to be evaluated.

According to one embodiment, the autonomous driving control system 110 may transmit virtual object information 114 to the evaluation target vehicle 120. Virtual object information 114 may include information about a plurality of virtual objects. For example, the virtual object information 114 may include information about a virtual driving vehicle traveling around the evaluation target vehicle, information about a virtual pedestrian moving around the evaluation target vehicle, etc. Here, the virtual driving vehicle may be a virtual vehicle that simulates the driving behavior of an actual driver, and the virtual pedestrian may be a virtual pedestrian that simulates the moving behavior of an actual pedestrian.

According to one embodiment, the autonomous driving control system 110 may receive actual driving data 122 from the vehicle 120 to be evaluated. Actual driving data 122 may refer to data obtained during the actual driving process of a vehicle in a specific area. For example, the actual driving data 122 may include the speed, acceleration, steering angle, wheel steering angle, brake pedal signal, or accelerator pedal signal of the vehicle 120 to be evaluated. Here, the brake pedal signal may represent a change in brake pedal trajectory/angle, and the accelerator pedal signal may represent a change in accelerator pedal trajectory/angle. In one embodiment, the actual driving data 122 may be generated continuously or in real time at certain time intervals. Additionally, the evaluation target vehicle 120 may transmit the generated actual driving data 122 to the autonomous driving control system 110 in real time.

According to one embodiment, the autonomous driving control system 110 may receive virtual driving data 124 from the vehicle 120 to be evaluated. The virtual driving data 124 may refer to data resulting from simulating the driving of an autonomous driving algorithm by a vehicle subject to evaluation in a virtual environment corresponding to a specific area based on the scenario information 112 and the virtual object information 114. For example, the virtual driving data 124 may include location information of a vehicle subject to evaluation, location information of a plurality of virtual objects, and signal information within the virtual environment. In one embodiment, the virtual driving data 124 may be generated continuously in a certain time unit or in real time. Additionally, the evaluation target vehicle 120 may transmit the generated virtual driving data 124 to the autonomous driving control system 110 in real time.

Although not shown in FIG. 1, based on the actual driving data 122 and the virtual driving data 124 of the evaluation target vehicle 120, the driving within a specific area of the evaluation target vehicle 120 is visualized and displayed on the display. It can be printed to . In this case, the display that visualizes and outputs the driving of the evaluation target vehicle 120 may include the display of the autonomous driving control system 110 and/or a display inside the evaluation target vehicle 120.

Through the configuration described above, the autonomous driving control center visualizes and outputs the driving of the evaluation target vehicle within a specific area based on actual driving data and virtual driving data, so that the evaluation target vehicle is driven without the evaluator directly boarding the vehicle. can be confirmed and evaluated.

Figure 2 is a schematic diagram showing a configuration in which the information processing system 230 according to an embodiment of the present disclosure is connected to communicate with a plurality of evaluation target vehicles 210_1, 210_2, and 210_3. In Figure 2, the evaluation target vehicles (210_1, 210_2, 210_3) are shown as communicating with the information processing system 230 through the network 220, but the scope is not limited to this, and the communication unit mounted on the evaluation target vehicle is the information processing system 230. ) can communicate with. Additionally, the information processing system 230 may include the autonomous driving control system(s) described with reference to FIG. 1 .

In one embodiment, information processing system 230 may include one or more server devices and/or databases capable of storing, providing, and executing computer-executable programs (e.g., downloadable applications) and data related to replicating a traffic environment, or It may include one or more distributed computing devices and/or distributed databases based on cloud computing services. The information processing system 230 may provide information corresponding to a signal input through an application (e.g., an application related to reproducing a traffic environment, etc.) or perform corresponding processing. For example, the information processing system 230 may transmit an autonomous vehicle evaluation scenario within a specific area to a plurality of evaluation target vehicles 210_1, 210_2, and 210_3 through an arbitrary application related to reproducing a traffic environment.

The information processing system 230 may communicate with a plurality of evaluation target vehicles 210_1, 210_2, and 210_3 through the network 220. The network 220 may be configured to enable communication between a plurality of evaluation target vehicles 210_1, 210_2, and 210_3 and the information processing system 230. Depending on the installation environment, the network 220 may be, for example, a wired network such as Ethernet, a wired home network (Power Line Communication), a telephone line communication device, and RS-serial communication, a mobile communication network, a wireless LAN (WLAN), It may consist of wireless networks such as Wi-Fi, Bluetooth, and ZigBee, or a combination thereof. The communication method is not limited, and includes communication methods that utilize communication networks that the network 220 may include (e.g., mobile communication networks, wired Internet, wireless Internet, broadcasting networks, satellite networks, etc.), as well as evaluation target vehicles (210_1, 210_2, 210_3), short-range wireless communication may also be included.

In FIG. 2 , the evaluation target vehicles 210_1, 210_2, and 210_3 may be vehicles equipped with an autonomous driving algorithm. In addition, Figure 2 shows three evaluation target vehicles (210_1, 210_2, 210_3) communicating with the information processing system 230 through the network 220, but is not limited thereto, and any number of evaluation target vehicles It may also be configured to communicate with the information processing system 230 via the network 220.

In one embodiment, the evaluation target vehicles 210_1, 210_2, and 210_3 receive autonomous vehicle evaluation scenario information and a plurality of virtual object information within a specific area from the information processing system 230 through the network 220, Actual driving data and virtual driving data of a vehicle within a specific area can be transmitted to the information processing system 230. The evaluation target vehicles 210_1, 210_2, and 210_3 may drive using an autonomous driving algorithm within a specific area in response to receiving scenario information and virtual object information.

FIG. 3 is a block diagram showing the internal configuration of the autonomous driving control system 110 according to an embodiment of the present disclosure. As shown in FIG. 3 , the autonomous driving control system 110 may include a traffic environment reproduction unit 310, a driving simulator 320, and an autonomous driving verification analyzer 330. In FIG. 3 , each component of the autonomous driving control system 110 shows functionally distinct functional elements, and a plurality of components may be implemented in a form that is integrated with each other in an actual physical environment. Alternatively, each component of the autonomous driving control system 110 may be implemented separately from each other in an actual physical environment. In addition, in FIG. 3, the autonomous driving control system 110 is implemented by dividing into a traffic environment reproduction unit 310, a driving simulator 320, and an autonomous driving verification analyzer 330, but it is not limited to this, and some components are omitted or other configurations are implemented. This can be added.

According to one embodiment, the traffic environment reproduction unit 310 may generate evaluation scenario information for autonomous vehicles within a specific area and transmit it to the evaluation target vehicle. For example, the traffic environment reproduction unit 310 generates information related to the driving course including the starting location and arrival location of the vehicle to be evaluated, scenario information for a specific situation after the scenario initiation trigger and/or the initiation trigger is activated, and the like. It can be transmitted to the vehicle being evaluated. Additionally, the traffic environment reproduction unit 310 may generate a plurality of virtual object information and transmit it to the evaluation target vehicle. For example, the traffic environment reproduction unit 310 may transmit information about virtual driving vehicles and/or virtual pedestrians moving around the evaluation target vehicle to the evaluation target vehicle.

According to one embodiment, the traffic environment reproduction unit 310 may include a display that can check the result of virtualizing the driving of the evaluation target vehicle in a specific area. Additionally, the traffic environment reproduction unit 310 may visualize/virtualize the driving of the evaluation target vehicle within a specific area based on the actual driving data and virtual driving data received from the evaluation target vehicle and output the results on the display. For example, the traffic environment reproduction unit 310 may visualize the location information and status information of the evaluation target vehicle, the course driven by the evaluation target vehicle, etc., and output them on the display.

According to one embodiment, the driving simulator 320 may generate data for controlling a virtual driving vehicle and transmit it to the evaluation target vehicle. For example, the driving simulator 320 controls the direction and speed of the virtual vehicle driving around the evaluation target vehicle in real time, thereby transmitting information about the virtual vehicle that reflects the driving behavior of the actual driver to the evaluation target vehicle. You can. To this end, the driving simulator 320 may be configured to include a display for checking the driving of the virtual driving vehicle, a steering wheel, pedals, a seat, etc. for controlling the virtual driving vehicle. Additionally or alternatively, the driving simulator 320 may include a joystick, joypad, etc. instead of a steering wheel and pedals to control the virtual driving vehicle.

According to one embodiment, the autonomous driving verification analyzer 330 may receive and analyze actual driving data and virtual driving data to evaluate the autonomous driving algorithm mounted on the evaluation target vehicle. For example, the autonomous driving verification analyzer 330 can determine/verify whether the autonomous driving algorithm is operating normally by analyzing actual driving data such as speed and acceleration of the vehicle being evaluated. Additionally, the autonomous driving verification analyzer 330 may determine whether the autonomous driving algorithm is operating normally by analyzing the location information of the target vehicle, the location information of the virtual object, and signal information within the virtual environment. For example, when a virtual object (e.g., a virtual vehicle, a virtual pedestrian, etc.) in a virtual environment suddenly intervenes, the autonomous driving verification analyzer 330 may recognize this and determine whether the object suddenly braked rather than collided.

According to one embodiment, a replay function using actual driving data and/or virtual driving data may be provided through the autonomous driving verification analyzer 330. For example, the autonomous driving verification analyzer 330 may provide the user with a three-dimensional image that reproduces the driving process of the vehicle to be evaluated based on the received location information of the vehicle to be evaluated, virtual object location information, and signal information. there is.

FIG. 4 is a block diagram showing the internal configuration of an evaluation target vehicle 120 according to an embodiment of the present disclosure. The evaluation target vehicle 120 may be an actual vehicle that drives using an autonomous driving algorithm within a specific area based on scenario information and virtual object information. Additionally, as shown in FIG. 4 , the evaluation target vehicle 120 may include a display 410, an autonomous driving control unit 420, a simulation performance unit 430, and a communication unit 440. In FIG. 4 , each component of the vehicle 120 to be evaluated shows functionally distinct functional elements, and some of the plurality of components may be implemented in a form that is integrated with each other in an actual physical environment. In addition, in FIG. 4, the evaluation target vehicle 120 is implemented by dividing into a display 410, an autonomous driving control unit 420, a simulation performance unit 430, and a communication unit 440, but it is not limited to this and some components may be omitted or Other configurations may be added.

According to one embodiment, the display 410 may output data related to the driving of the evaluation target vehicle 120. For example, the display 410 may output, in real time, a driving simulation that reflects virtual objects of the evaluation target vehicle performed by the simulation performance unit 430. As another example, the display 410 may output actual driving data, such as vehicle speed and acceleration, in real time.

According to one embodiment, the autonomous driving control unit 420 may control the evaluation target vehicle 120 based on scenario information received from the autonomous driving control system and a mounted autonomous driving algorithm. For example, the autonomous driving control unit 420 may control the accelerator and brake of the evaluation target vehicle 120 to adjust driving speed and acceleration. Additionally, the autonomous driving control unit 420 may control the driving direction by controlling the steering wheel of the evaluation target vehicle 120.

According to one embodiment, the simulation performance unit 430 may perform a simulation of a vehicle to be evaluated in a virtual environment corresponding to a specific area based on scenario information and a plurality of virtual object information received from the autonomous driving control system. Additionally, the simulation performance unit 430 may generate virtual driving data that is a simulation result of the evaluation target vehicle.

According to one embodiment, the communication unit 440 communicates with the autonomous driving control system and may transmit and receive data related to the vehicle to be evaluated. The communication unit 440 may receive autonomous vehicle evaluation scenario information and a plurality of virtual object information within a specific area from the autonomous driving control system. Additionally, the communication unit 440 may transmit actual driving data of the vehicle within a specific area and virtual driving data simulated based on the actual data of the vehicle to the autonomous driving control system.

FIG. 5 is a diagram illustrating an example of data communication between the autonomous driving control system 110 and the evaluation target vehicle 120 according to an embodiment of the present disclosure. As shown in FIG. 5, the autonomous driving control system 110 and the vehicle to be evaluated 120 may exchange data with each other through a plurality of networks 510 and 520. Additionally, the communication unit 440 may serve as a communication medium between the autonomous driving control system 110 and the evaluation target vehicle 120. In FIG. 5 , the communication unit 440 and the evaluation target vehicle 120 are shown as separate components, but they are not limited thereto, and the communication unit 440 may be included as a part of the evaluation target vehicle 120.

According to one embodiment, the autonomous driving control system 110 and the communication unit 440 may transmit and receive related data through the networks 510 and 520. In one embodiment, the autonomous driving control system 110 may transmit autonomous vehicle evaluation scenario information and a plurality of virtual object information to the communication unit 440 through a separate network. In more detail, the autonomous driving control system 110 may transmit autonomous vehicle evaluation scenario information through the first network 510 and transmit a plurality of virtual object information through the second network 520. In this case, the first network 510 may be a Wireless Access for Vehicle Environment (WAVE) network, and the second network 520 may be an LTE or 5G network.

According to one embodiment, the communication unit 440 and the evaluation target vehicle 120 may transmit and receive related data through a network. For example, the evaluation target vehicle 120 may transmit data generated during the driving process to a communication unit using UDP (User Datagram Protocol) communication and/or CAN (Controller Area Network) communication.

In FIG. 5, the autonomous driving control system 110 and the communication unit 440 are shown to communicate with each other through two networks, but the present invention is not limited to this, and some networks may be omitted or additional networks may exist. Likewise, two networks are shown connected between the communication unit 440 and the evaluation target vehicle 120, but the present invention is not limited to this, and some networks may be omitted or additional networks may exist.

FIG. 6 is a diagram illustrating an example of V2X (Vehicle to Everything) data 600 transmitted and received by a vehicle to be evaluated according to an embodiment of the present disclosure. V2X data 600 may refer to data related to communication technology between vehicles and objects such as other vehicles, mobile devices, and roads through wired and wireless networks, and refers to vehicle-to-vehicle (V2V) communication, vehicle-to-vehicle communication (V2V). It may include data related to vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-mobile device (Vehicle to Nomadic Device).

According to one embodiment, V2X data 600 may be composed of PVD 610, SPat 620, MAP 630, RSA 640, and custom data 650. In one embodiment, PVD 610 may refer to Probe Vehicle Data and may include data associated with driving state information of the vehicle. For example, the PVD 610 may include vehicle speed, vehicle location, brake pedal trajectory/angle value, light system status, etc.

In one embodiment, SPat 620 may refer to signal current operation information (Signal Phase and Timing) and may include current state information of a real-time signal intersection coming from a signal controller. MAP 630 may refer to map data and may include spatial data for the corresponding driving environment. For example, the MAP 630 may include driving lane characteristics, intersection information, lane information, etc.

In one embodiment, RSA 640 may refer to Road Side Alert data and may include information on obstacles in the driving environment. For example, RSA 640 may include information about emergency vehicles and emergency events. Additionally, custom data 650 is data other than the data described above and may refer to data that takes into account the characteristics of the vehicle being evaluated.

In FIG. 6, PVD (610), SPat (620), MAP (630), RSA (640), and custom data (650) are shown as V2X data 600, but it is not limited thereto, and some data is omitted or additional data is included. may exist.

FIG. 7 is a diagram showing an example of data transmitted and received by the evaluation target vehicle 120, the communication unit 440, and the autonomous driving control system 110 according to an embodiment of the present disclosure. The evaluation target vehicle 120, the communication unit 440, and the autonomous driving control system 110 may exchange data shown in FIG. 7 with each other.

According to one embodiment, the evaluation target vehicle 120 includes WSM data, J2735 standard data, vehicle detect data, sensor (CAM, LIDAR, radar, etc.) data, and a vehicle electronic control unit (electronic control unit; ECU)-related data, GPS data, and inertial measurement unit (IMU) data can be received. Additionally, the evaluation target vehicle 120 may transmit vehicle status data, vehicle actual driving data, etc. to the communication unit 440 or the autonomous driving control system 110.

According to one embodiment, the communication unit 440 may receive actual driving data of the vehicle, WSM data, scenario management data, etc. Additionally, the communication unit 440 may transmit J2735 standard data, WSM data, scenario management data, etc. to the evaluation target vehicle 120 or the autonomous driving control system 110.

According to one embodiment, the autonomous driving control system 110 may receive scenario management data and vehicle status data. Additionally, the autonomous driving control system 110 may transmit simulator management data, data related to the vehicle to be evaluated, virtual object information, etc. to the vehicle to be evaluated 120 or the communication unit 440 .

Figure 8 is a flowchart showing an example of a traffic environment reproduction method 800 based on VILS (Vehicle In the Loop Simulation) linked to a control platform according to an embodiment of the present disclosure. In one embodiment, method 800 may be performed by at least one processor of an autonomous driving control system (or a traffic environment reproduction unit or an information processing system). The method 800 may begin with the processor generating autonomous vehicle evaluation scenario information within a specific region (S810). Here, the scenario information may include at least one of the starting location, arrival location, or scenario initiation trigger condition of the evaluation target vehicle.

In one embodiment, the processor may transmit scenario information to the evaluation target vehicle (S820). Here, the evaluation target vehicle may be an actual vehicle that drives using an autonomous driving algorithm within a specific area based on scenario information and a plurality of virtual object information.

In one embodiment, the processor may transmit a plurality of virtual object information to the evaluation target vehicle (S830). Here, the plurality of virtual objects may include a virtual driving vehicle traveling around the evaluation target vehicle and a virtual pedestrian moving around the evaluation target vehicle. A virtual driving vehicle may be a virtual vehicle that simulates the driving behavior of an actual driver, and a virtual pedestrian may be a virtual pedestrian that simulates the moving behavior of an actual pedestrian.

In one embodiment, the processor may receive actual driving data of the vehicle within a specific area from the vehicle to be evaluated (S840). Here, the actual driving data may include at least one of the speed, acceleration, steering angle, wheel steering angle, brake pedal signal, or accelerator pedal signal of the vehicle to be evaluated.

In one embodiment, the processor may receive simulated virtual driving data based on the actual driving data of the vehicle from the vehicle to be evaluated (S850). Here, the virtual driving data may be data obtained by simulating the driving of an autonomous driving algorithm in a virtual environment corresponding to a specific area based on scenario information and a plurality of virtual object information. For example, virtual driving data may include location information of a vehicle subject to evaluation, location information of a plurality of virtual objects, and signal information within a virtual environment.

In one embodiment, the processor may visualize the driving of the evaluation target vehicle within a specific area based on the actual driving data of the vehicle and the virtual driving data of the vehicle and output the visualization on the display (S860).

In one embodiment, a processor (e.g., at least one processor of an autonomous driving control system, an autonomous driving verification analyzer, or an information processing system) analyzes the received actual driving data and virtual driving data to determine the autonomous driving data mounted on the vehicle to be evaluated. Driving algorithms can be evaluated.

In one embodiment, the processor may receive data for controlling the virtual driving vehicle from the driving simulator and transmit the data for controlling the virtual driving vehicle to the evaluation target vehicle.

The flowchart shown in FIG. 8 and the above description are only examples and may be implemented differently in some embodiments. For example, in some embodiments, the order of each step may be changed, some steps may be performed repeatedly, some steps may be omitted, or some steps may be added.

The above-described method may be provided as a computer program stored in a computer-readable recording medium for execution on a computer. The medium may continuously store a computer-executable program, or may temporarily store it for execution or download. In addition, the medium may be a variety of recording or storage means in the form of a single or several pieces of hardware combined. It is not limited to a medium directly connected to a computer system and may be distributed over a network. Examples of media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, And there may be something configured to store program instructions, including ROM, RAM, flash memory, etc. Additionally, examples of other media include recording or storage media managed by app stores that distribute applications, sites or servers that supply or distribute various other software, etc.

The methods, operations, or techniques of this disclosure may be implemented by various means. For example, these techniques may be implemented in hardware, firmware, software, or a combination thereof. Those skilled in the art will understand that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented in electronic hardware, computer software, or combinations of both. To clearly illustrate this interchange of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and design requirements imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementations should not be interpreted as causing a departure from the scope of the present disclosure.

In a hardware implementation, the processing units used to perform the techniques may include one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs). ), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, and other electronic units designed to perform the functions described in this disclosure. , a computer, or a combination thereof.

Accordingly, the various illustrative logical blocks, modules, and circuits described in connection with this disclosure may be general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or It may be implemented or performed as any combination of those designed to perform the functions described in. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, such as a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other configuration.

For firmware and/or software implementations, techniques include random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), and PROM ( on computer-readable media such as programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, compact disc (CD), magnetic or optical data storage devices, etc. It can also be implemented with stored instructions. Instructions may be executable by one or more processors and may cause the processor(s) to perform certain aspects of the functionality described in this disclosure.

Although the above-described embodiments have been described as utilizing aspects of the presently disclosed subject matter in one or more standalone computer systems, the disclosure is not limited thereto and may also be implemented in conjunction with any computing environment, such as a network or distributed computing environment. . Furthermore, aspects of the subject matter of this disclosure may be implemented in multiple processing chips or devices, and storage may be similarly effected across the multiple devices. These devices may include PCs, network servers, and portable devices.

Although the present disclosure has been described in relation to some embodiments in this specification, various modifications and changes may be made without departing from the scope of the present disclosure as can be understood by a person skilled in the art to which the invention pertains. Additionally, such modifications and changes should be considered to fall within the scope of the claims appended hereto.

110: Autonomous driving control system
112: Scenario information
114: Virtual object information
120: Vehicle subject to evaluation
122: Actual driving data
124: Virtual driving data

Claims (10)

In a method of reproducing a traffic environment based on VILS (Vehicle In the Loop Simulation) linked to a control platform, performed by at least one processor,
Generating autonomous vehicle evaluation scenario information within a specific region;
Transmitting the scenario information to an evaluation target vehicle;
Transmitting a plurality of virtual object information to the evaluation target vehicle;
Receiving data for controlling a virtual vehicle running around the evaluation target vehicle from a driving simulator;
transmitting data for controlling the virtual driving vehicle to the evaluation target vehicle;
Receiving actual driving data of the evaluation target vehicle within the specific area from the evaluation target vehicle;
Receiving virtual driving data of the evaluation target vehicle simulated based on actual driving data of the evaluation target vehicle from the evaluation target vehicle; and
Driving within the specific area of the evaluation target vehicle based on actual driving data of the evaluation target vehicle, virtual driving data of the evaluation target vehicle, and data for controlling a virtual driving vehicle running around the evaluation target vehicle. Step of visualizing and outputting on the display
Method for reproducing a traffic environment, including:
According to paragraph 1,
The evaluation target vehicle is an actual vehicle that drives using an autonomous driving algorithm within the specific area based on the scenario information and the plurality of virtual object information,
The virtual driving data is data resulting from the evaluation target vehicle simulating the driving of the autonomous driving algorithm in a virtual environment corresponding to the specific area based on the scenario information and the plurality of virtual object information.
According to claim 1,
The scenario information includes at least one of a departure location, an arrival location, or a scenario initiation trigger condition of the evaluation target vehicle.
According to paragraph 1,
The plurality of virtual objects are,
A virtual driving vehicle running around the evaluation target vehicle; and
Including a virtual pedestrian moving around the evaluation vehicle,
The virtual driving vehicle is a virtual vehicle that simulates the driving behavior of an actual driver,
A method of reproducing a traffic environment, wherein the virtual pedestrian is a virtual pedestrian that simulates the movement behavior of an actual pedestrian.
In clause 2,
The actual driving data includes the speed, acceleration, steering angle, wheel steering angle, brake pedal signal, and accelerator pedal signal of the vehicle to be evaluated.
According to paragraph 2,
The virtual driving data includes location information of the evaluation target vehicle within the virtual environment, location information of the plurality of virtual objects, and signal information.
According to paragraph 2,
Evaluating the autonomous driving algorithm mounted on the evaluation target vehicle by analyzing the received actual driving data and the virtual driving data
A method for reproducing a traffic environment, further comprising:
delete A computer program stored in a computer-readable recording medium for executing the method according to any one of claims 1 to 7 on a computer.
As an information processing system,
communication module;
Memory; and
At least one processor connected to the memory and configured to execute at least one computer-readable program included in the memory
Including,
The at least one program is,
Generate autonomous vehicle evaluation scenario information within a specific region,
Transmit the scenario information to the evaluation vehicle,
Transmitting a plurality of virtual object information to the evaluation target vehicle,
Receiving data from a driving simulator for controlling a virtual driving vehicle driving around the evaluation vehicle,
Transmitting data for controlling the virtual driving vehicle to the evaluation target vehicle,
Receiving actual driving data of the evaluation target vehicle within the specific area from the evaluation target vehicle,
Receiving virtual driving data of the evaluation target vehicle simulated based on actual driving data of the evaluation target vehicle from the evaluation target vehicle,
Driving within the specific area of the evaluation target vehicle based on actual driving data of the evaluation target vehicle, virtual driving data of the evaluation target vehicle, and data for controlling a virtual driving vehicle running around the evaluation target vehicle. An information processing system including instructions for visualizing and outputting on a display.

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