A method for verifying the accuracy of virtual sensor models for simulating real-world information databases

Abstract

To provide an accuracy verification method of a virtual sensor model for simulation of reality information database which can be expected of improvement of accuracy, accelerates algorithm development and also enhances stability.SOLUTION: A virtual sensor verification method includes: acquiring the position and status information of an actual vehicle traveling on an actual road, and acquiring sensor data generated by an actual sensor of a vehicle for which reality information is acquired in the actual vehicle; reproducing the actual vehicle on a virtual road by a virtual vehicle from the acquired position and status information, and acquiring virtual sensor data output from a virtual sensor mounted on the vehicle for which the virtual information is acquired, in the virtual vehicle; comparing the acquired actual sensor data with the virtual sensor data, and verifying the virtual sensor; and measuring and verifying accuracy of the virtual sensor data supplied to recognition, determination and control algorithms for autonomous travel, and thus improvement of accuracy for a simulator-based verification result of an autonomous travel algorithm can be expected.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an autonomous driving simulation, and more particularly to a method for verifying the accuracy of a virtual sensor model used to verify an autonomous driving algorithm in a virtual road environment using a simulator. [Background technology]

[0002] For the recognition, judgment, and control operations of an autonomous vehicle, sensors are installed in the vehicle to sense the surroundings and grasp information on objects in all directions. In particular, the autonomous vehicle recognizes the objects around the vehicle, the drivable areas on the road, the traffic signal status, etc. from the sensor data of the camera, lidar, radar, etc. installed in the autonomous vehicle, and determines the direction of movement of the surrounding objects, the current driving possibility, etc., and controls the movement of the vehicle. In order to verify the autonomous driving algorithms installed in the autonomous vehicles, not only real vehicle-based verification but also simulator-based methods are used simultaneously for fast and effective verification. Various sensor data required for the operation of the recognition, judgment and control algorithms installed in the autonomous vehicles are generated by modeling and simulating virtual sensors and supplied to the algorithms. Therefore, for accurate algorithm operation, it is important that the output values ​​of the virtual sensor models used in the autonomous driving simulator are kept accurate. Summary of the Invention [Problem to be solved by the invention]

[0003] Therefore, the present invention has been made in consideration of the above problems, and an object of the present invention is to provide a method for measuring and verifying the accuracy of virtual sensor data supplied to recognition, judgment, and control algorithms for autonomous driving when verifying autonomous driving SW installed in an autonomous driving vehicle on a simulator basis. [Means for solving the problem]

[0004] To achieve the above-mentioned objective, a virtual sensor verification method according to one embodiment of the present invention includes the steps of acquiring position and status information of an actual vehicle traveling on a real road, acquiring actual sensor data generated from an actual sensor of one of the actual vehicles that acquires the real information, reproducing the actual vehicle on a virtual road with a virtual vehicle based on the acquired position and status information, acquiring virtual sensor data output from a virtual sensor attached to one of the virtual vehicles that acquires the virtual information, and comparing the acquired actual sensor data with the virtual sensor data to verify the virtual sensor. The virtual sensor may be a virtual sensor that simulates the type and specifications of an actual sensor.

[0005] The real sensors may include real cameras, real lidars, and real radars, and the virtual sensors may include virtual cameras, virtual lidars, and virtual radars. The position and status information of the real vehicle may be obtained from a GNSS / INS mounted on the real vehicle. The GNSS / INS installed in the actual vehicle may be synchronized based on the GPS time of the GNSS / INS installed in the vehicle acquiring the real information. The difference between the GPS time of the vehicle receiving the real information and the GPS time of the target vehicle is calculated by the following formula:

[0006]

number

[0007] TIFF0007675152000002.tif1927 is GPS time difference, TIFF0007675152000003.tif1827 is the delay time of GPS time data processing in the acquisition equipment of the vehicle acquiring the real information. TIFF0007675152000004.tif1827 is the delay time of GPS time data processing in the acquisition equipment of the target vehicle, TIFF0007675152000005.tif1823 is the delay time of GPS reception in the acquisition equipment of the vehicle acquiring the real information, TIFF0007675152000006.tif2020 may be the delay time of GPS reception at the acquisition equipment of the target vehicle. The actual sensor data of the real acquisition vehicle may be synchronized based on the GPS time of the real acquisition vehicle.

[0008] The virtual road may be a road that simulates an actual road in a virtual space. The simulator may be a tool for testing autonomous driving algorithms through a real-world capture vehicle.

[0009] According to another embodiment of the present invention, there is provided a virtual sensor verification system including: a synchronization module that acquires position and status information of a real vehicle traveling on a real road, and acquires actual sensor data generated from an actual sensor of a vehicle that acquires real information among the real vehicles; a simulation module that reproduces the real vehicle as a virtual vehicle on a virtual road based on the acquired position and status information; and a verification module that acquires virtual sensor data output from a virtual sensor attached to a vehicle that acquires virtual information among the virtual vehicles, compares the acquired actual sensor data with the virtual sensor data, and verifies the virtual sensor.

[0010] According to yet another embodiment of the present invention, there is provided a virtual sensor verification method comprising the steps of: reproducing a real vehicle on a virtual road using a virtual vehicle based on position and status information acquired from a real vehicle running on a real road; acquiring virtual sensor data output from a virtual sensor mounted on one of the virtual vehicles that acquires the virtual information; and comparing the acquired virtual sensor data with actual sensor data acquired from an actual sensor of the real vehicle that acquires the real information, thereby verifying the virtual sensor.

[0011] According to yet another embodiment of the present invention, there is provided a virtual sensor verification system including: a simulation module that reproduces a real vehicle on a virtual road using position and status information acquired from a real vehicle traveling on a real road; and a verification module that acquires virtual sensor data output from a virtual sensor attached to a vehicle among the virtual vehicles that acquires virtual information, compares the acquired virtual sensor data with actual sensor data acquired from an actual sensor of the vehicle among the real vehicles that acquires real information, and verifies the virtual sensor. Effect of the Invention

[0012] As described above, according to an embodiment of the present invention, it is possible to measure and verify the accuracy of virtual sensor data supplied to perception, judgment, and control algorithms for autonomous driving, which is ultimately expected to improve the accuracy of simulator-based verification results of autonomous driving algorithms. Furthermore, according to an embodiment of the present invention, it is possible to verify autonomous driving SW based on scenarios of various environments and conditions, which can speed up algorithm development and further improve the stability of the algorithm. [Brief description of the drawings]

[0013] [Figure 1] FIG. 1 is a diagram showing a configuration of a verification system for a virtual sensor model according to an embodiment of the present invention. [Diagram 2] 11 is a flowchart illustrating a method for verifying a virtual sensor model according to another embodiment of the present invention. [Diagram 3] FIG. 1 illustrates a method for synchronizing data obtained from a real vehicle. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] In the following, the invention will be explained in more detail with reference to the drawings. In an embodiment of the present invention, a method for verifying the accuracy of a virtual sensor model for simulating a real information database is presented. This is a technology for measuring and verifying the accuracy of a virtual sensor model, which is used to verify an autonomous driving algorithm in a virtual road environment using a simulator.

[0015] 1 is a diagram showing a configuration of a virtual sensor model verification system according to an embodiment of the present invention. As shown in the figure, the virtual sensor model verification system according to the embodiment of the present invention includes a sensor data synchronization module 110, an autonomous driving simulation module 120, and a virtual sensor verification module 130. The sensor data synchronization module 110 receives and synchronizes data from real vehicles 10, 10-1, 10-2, ..., 10-n that run on real roads. The real vehicles 10, 10-1, 10-2, ..., 10-n may be divided into acquisition vehicles 10 for real information and target vehicles 10-1, 10-2, ..., 10-n.

[0016] The vehicle 10 acquiring real information corresponds to an ego vehicle as a target for generating actual sensor data, and the target vehicles 10-1, 10-2, . . . , 10-n refer to vehicles running around the vehicle 10 acquiring real information. Acquiring real-world information The data collected from the vehicle 10 includes GNSS / INS data and actual sensor data. On the other hand, only GNSS / INS data is collected from the target vehicles 10-1, 10-2, ..., 10-n.

[0017] The GNSS / INS data includes position and status (such as vehicle position, orientation, speed, etc.) information of the actual vehicles 10, 10-1, 10-2, ..., 10-n. Acquiring Real Information The actual sensors installed on the vehicle 10 may include cameras, lidars, radars, and may further include other types of sensors. Thereby, the sensor data synchronization module 110 receives GNSS / INS data and actual sensor data from the real information acquisition vehicle 10, and receives GNSS / INS data from the target vehicles 10-1, 10-2, ..., 10-n, and synchronizes the received data. The synchronization method by the sensor data synchronization module 110 will be described in detail later with reference to Figure 3.

[0018] The autonomous driving simulation module 120 reproduces the actual vehicles 10, 10-1, 10-2, ..., 10-n as virtual vehicles on a virtual road based on the position and status information of the actual vehicles 10, 10-1, 10-2, ..., 10-n recorded in the GNSS / INS data transmitted via the sensor data synchronization module 110. The autonomous driving simulator is a tool for testing autonomous driving algorithms in a virtual environment through virtual vehicles. A virtual road is a road in a virtual space that is a simulation of a real road.

[0019] Meanwhile, among the virtual vehicles, a virtual information acquisition vehicle, which is a virtual vehicle corresponding to the real information acquisition vehicle 10, is equipped with a virtual sensor model. The virtual sensor model is a virtual sensor that simulates the type and specifications of an actual sensor installed in the real information acquisition vehicle 10 in the same manner.

[0020] The virtual sensor verification module 130 compares the actual sensor data with the virtual sensor data to verify the accuracy of the virtual sensor model installed in the virtual information acquisition vehicle. The actual sensor data is acquired from the real information acquisition vehicle 10 via the sensor data synchronization module 110, and the virtual sensor data is acquired from the autonomous driving simulation module 120.

[0021] FIG. 2 is a flowchart illustrating a method for verifying a virtual sensor model according to another embodiment of the present invention. To verify the virtual sensor model, first, the sensor data synchronization module 110 acquires position and status information of the real vehicles 10, 10-1, 10-2, ..., 10-n driving on the real road (S210), and acquires real sensor data from the real information acquisition vehicle 10 (S220).

[0022] Next, the autonomous driving simulation module 120 reproduces the actual vehicles 10, 10-1, 10-2, . . . , 10-n as virtual vehicles on the virtual road based on the position and status information acquired in step S210 (S230). Then, the virtual sensor verification module 130 acquires virtual sensor data from a virtual sensor model mounted on a virtual information acquisition vehicle corresponding to the real information acquisition vehicle 10 (S240), and compares the acquired virtual sensor data with the actual sensor data acquired in step S220 to verify the accuracy of the virtual sensor model (S250).

[0023] The synchronization method performed by the sensor data synchronization module 110 described above will now be described in detail. In order to realize a virtual environment from the data acquired from the real information acquisition vehicle 10 and the target vehicles 10-1, 10-2, ..., 10-n, it is necessary to synchronize the data. A method for synchronizing the data acquired from different real vehicles is shown in Figure 3.

[0024] It is assumed that the GNSS / INS data of the surrounding target vehicles is acquired as shown in Fig. 3 based on the GPS time of the real information acquiring vehicle 10. There is a high possibility that the acquisition time of the GNSS / INS data acquired from the real information acquiring vehicle 10 and the acquisition time of the GNSS / INS data of the surrounding target vehicles are different from each other. In addition, since the times at which the GNSS / INS data acquisition started are also different from each other, a process of synchronizing the data based on the real information acquiring vehicle 10, which is the own vehicle, is required.

[0025] 3 shows an example of GNSS / INS data acquired from the data acquisition equipment mounted on the real-world information acquisition vehicle 10 and the data acquisition equipment of the surrounding target vehicles. To compare with UTC time, the time information of each data acquisition equipment is acquired, and GPS time data is acquired. To synchronize sensor data acquired from different equipment and extract accurate comparison data The calculation method for TIFF0007675152000007.tif1927 is as follows.

[0026]

number

[0027] In the above formula, the data with the smallest time difference among the GPS data acquired from acquisition equipment #1 [acquisition equipment of the acquisition vehicle 10 of the real information] and acquisition equipment #2 [acquisition equipment of the target vehicles 10-1, 10-2, ..., 10-n] TIFF0007675152000009.tif2124, Extract TIFF0007675152000010.tif1724. TIFF0007675152000011.tif2324 is the delay time required for GPS time data processing at acquisition equipment #1, TIFF0007675152000012.tif2124 is the delay time required for GPS time data processing in acquisition equipment #2.

[0028] In addition, TIFF0007675152000013.tif1823 means the delay time of GPS reception at acquisition equipment #1, TIFF0007675152000014.tif2020 means the delay time of GPS reception at acquisition equipment #2. TIFF0007675152000015.tif2245 TIFF0007675152000016.tif1629, and this value When added to TIFF0007675152000017.tif2024, The value of TIFF0007675152000018.tif2024 can be estimated. Therefore, TIFF0007675152000019.tif1924 means the GPS time difference between acquisition equipment #1 and acquisition equipment #2.

[0029] On the other hand, the actual sensor data of the vehicle 10 acquiring the real information is synchronized based on the GPS time of the vehicle 10 acquiring the real information. So far, the method for verifying the accuracy of a virtual sensor model for simulating a real information database has been described in detail with reference to a preferred embodiment.

[0030] The above embodiment shows a method for measuring and verifying the accuracy of virtual sensor data supplied to the recognition, judgment, and control algorithms for autonomous driving when verifying autonomous driving SW installed in an autonomous driving vehicle on a simulator basis. This is expected to improve the accuracy of simulator-based verification results for autonomous driving algorithms and recognition, judgment, and control algorithms to be installed in autonomous vehicles. It will also enable autonomous driving SW verification based on scenarios for various environments and conditions, accelerating algorithm development and further improving algorithm stability.

[0031] Meanwhile, the technical idea of ​​the present invention may also be applied to a computer readable recording medium incorporating a computer program for performing the functions of the apparatus and method according to the present embodiment. The technical idea of ​​various embodiments of the present invention may be realized in the form of computer readable code recorded on a computer readable recording medium. The computer readable recording medium may be any data storage device that can be read by a computer and can store data. For example, the computer readable recording medium may be a ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical disk, hard disk drive, etc. The computer readable code or program stored on the computer readable recording medium may be transmitted via a network connected between computers.

[0032] Although the preferred embodiment of the present invention has been described in detail above with reference to the accompanying drawings, the present invention is not limited to the above embodiment. It is clear that a person having ordinary knowledge in the technical field to which the present invention pertains can conceive of various modified or altered examples within the scope of the technical intent described in the claims, and it is understood that these also naturally belong to the technical scope of the present invention.

Claims

1. A virtual sensor validation system comprising: A step of acquiring position and status information of a plurality of vehicles including a first vehicle running on an actual road and one or more second vehicles running around the first vehicle from a GNSS / INS mounted on each of the plurality of vehicles; acquiring actual sensor data generated from an actual sensor of the first vehicle of the plurality of vehicles; a step of synchronizing the position and status information acquired for the one or more second vehicles based on a GPS time of a GNSS / INS mounted on the first vehicle, and reproducing each of the plurality of vehicles as a virtual vehicle on a virtual road based on the position and status information of the first vehicle and the synchronized position and status information of the one or more second vehicles; acquiring virtual sensor data output from a virtual sensor mounted on a virtual vehicle corresponding to the first vehicle; comparing the actual sensor data with the virtual sensor data to validate the virtual sensor; A virtual sensor verification method comprising:

2. The virtual sensor is A virtual sensor that simulates the type and specifications of the actual sensor. The method of claim 1 , wherein the virtual sensor is a cascade of sensors.

3. The actual sensor comprises: Including real cameras, real lidar, real radar, The virtual sensor includes: Includes virtual camera, virtual lidar, and virtual radar The method of claim 1 , wherein the virtual sensor is a cascade of sensors.

4. The difference between the GPS time of the first vehicle and the GPS time of the one or more second vehicles is calculated by the following formula: [0010] [0025] is the GPS time difference, [0030] is the delay time of the GPS time data processing in the acquisition device of the first vehicle, [0045] is a delay time of GPS time data processing in the acquisition device of the one or more second vehicles, [0050] is the delay time of GPS reception in the acquisition device of the first vehicle, [006] is the delay time of GPS reception at the acquisition device of the one or more second vehicles. The method of claim 1 , wherein the virtual sensor is a cascade of sensors.

5. The actual sensor data of the first vehicle is Synchronizing with the GPS time of the first vehicle as a reference The method of claim 1 , wherein the virtual sensor is a cascade of sensors.

6. The virtual road is A road that is a virtual space that mimics the actual road. The method of claim 1 , wherein the virtual sensor is a cascade of sensors.

7. The simulator for the reproducing step includes: a tool for testing autonomous driving algorithms via the first vehicle; The method of claim 1 , wherein the virtual sensor is a cascade of sensors.

8. a synchronization module that acquires position and status information of a plurality of vehicles including a first vehicle running on an actual road and one or more second vehicles running around the first vehicle from a GNSS / INS mounted on each of the plurality of vehicles, and acquires actual sensor data generated from an actual sensor of the first vehicle among the plurality of vehicles; a simulation module that synchronizes the acquired position and status information of the one or more second vehicles based on a GPS time of a GNSS / INS mounted on the first vehicle, and reproduces each of the plurality of vehicles as a virtual vehicle on a virtual road based on the position and status information of the first vehicle and the synchronized position and status information of the one or more second vehicles; a verification module for acquiring virtual sensor data output from a virtual sensor mounted on a virtual vehicle corresponding to the first vehicle, and for verifying the virtual sensor by comparing the actual sensor data with the virtual sensor data; A virtual sensor validation system comprising:

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