Method and device for performing wireless communication

Abstract

In one embodiment, a method performed by a first device is provided. For example, the first device may acquire a message including information about a blocking area related to at least one candidate blocking object. For example, on the basis of the information about the blocking area related to the at least one candidate blocking object and a first area pertaining to a first time, the first device may generate first information related to a first blocking object and second information related to a filling area pertaining to the first blocking object. For example, the first device may detect at least one moving object in a second area pertaining to a second time. For example, on the basis of the first information related to the first blocking object in the blocking area and the second information related to the filling area pertaining to the first blocking object, the detection pertaining to the at least one moving object may be performed in a second area in which a first blocking area related to the first blocking object in the second area pertaining to the second time is replaced with the filling area.

Description

Method and device for performing wireless communication

[0001] The present disclosure relates to a wireless communication system.

[0002] 5G NR, the successor to LTE (long-term evolution), is a new clean-slate mobile communications system characterized by high performance, low latency, and high availability. 5G NR can utilize all available spectrum resources, from low-frequency bands below 1 GHz, mid-frequency bands between 1 GHz and 10 GHz, and high-frequency (millimeter wave) bands above 24 GHz.

[0003] The 6G (wireless communication) system aims to achieve (i) very high data rates per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) low energy consumption for battery-free Internet of Things (IoT) devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capabilities. The vision of the 6G system can be divided into four aspects: intelligent connectivity, deep connectivity, holographic connectivity, and ubiquitous connectivity, and the 6G system can satisfy the requirements as shown in Table 1 below. For example, Table 1 can represent an example of the requirements of a 6G system.

[0004] Maximum data rate per device: 1 Tbps, E2E latency: 1 ms, Maximum spectral efficiency: 100 bps / Hz, Mobility support: Up to 1000 km / hr, Satellite integration: Fully AI, Fully autonomous driving, Fully XR, Fully haptic communication

[0005] In one embodiment, a method is provided that is performed by a first device. For example, the first device may obtain a message including information regarding a blocking region associated with at least one candidate blocking object. For example, the first device may generate first information regarding a first blocking object and second information regarding a filling region associated with the first blocking object based on the information regarding the blocking region associated with the at least one candidate blocking object and a first region associated with a first time. For example, the first device may perform detection of at least one moving object within the second region associated with a second time. For example, the detection of the at least one moving object may be performed within a second area in which the first blocking area related to the first blocking object is replaced with the filling area among the second areas with respect to the second time, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

[0006] FIG. 1 illustrates a communication structure that can be provided in a 6G system according to one embodiment of the present disclosure.

[0007] FIG. 2 illustrates an example of a communication scenario based on a 6G system according to an embodiment of the present disclosure.

[0008] FIG. 3 illustrates an example of a sensing operation according to one embodiment of the present disclosure.

[0009] FIG. 4 is a diagram for comparing and explaining V2X communication based on RAT prior to NR and V2X communication based on NR according to one embodiment of the present disclosure.

[0010] FIG. 5 is a diagram illustrating results before and after performing operations related to object detection / perception or object tracking according to one embodiment of the present disclosure.

[0011] FIG. 6 is a diagram for explaining a result before performing an operation related to object detection / perception or object tracking according to one embodiment of the present disclosure.

[0012] FIG. 7 is a diagram illustrating a result after performing an operation related to object detection / perception or object tracking according to one embodiment of the present disclosure.

[0013] FIG. 8 illustrates area information related to a method for performing wireless communication according to one embodiment of the present disclosure.

[0014] FIG. 9 illustrates a result before performing an operation related to object detection / perception or object tracking according to one embodiment of the present disclosure.

[0015] FIG. 10 illustrates a method for performing wireless communication according to one embodiment of the present disclosure.

[0016] FIG. 11 illustrates a method for performing wireless communication according to an embodiment of the present disclosure.

[0017] FIG. 12 illustrates a result after performing an operation related to object detection / perception or object tracking according to one embodiment of the present disclosure.

[0018] FIG. 13 illustrates a method performed by a first device according to one embodiment of the present disclosure.

[0019] FIG. 14 illustrates a method performed by a second device according to one embodiment of the present disclosure.

[0020] FIG. 15 illustrates a communication system (1) according to one embodiment of the present disclosure.

[0021] FIG. 16 illustrates a wireless device according to one embodiment of the present disclosure.

[0022] FIG. 17 illustrates a signal processing circuit for a transmission signal according to one embodiment of the present disclosure.

[0023] FIG. 18 illustrates a wireless device according to one embodiment of the present disclosure.

[0024] FIG. 19 illustrates a mobile device according to one embodiment of the present disclosure.

[0025] FIG. 20 illustrates a vehicle or autonomous vehicle according to one embodiment of the present disclosure.

[0026] As used herein, "A or B" can mean "only A," "only B," or "both A and B." In other words, as used herein, "A or B" can be interpreted as "A and / or B." For example, as used herein, "A, B or C" can mean "only A," "only B," "only C," or "any combination of A, B and C."

[0027] As used herein, a slash ( / ) or a comma can mean "and / or." For example, "A / B" can mean "A and / or B." Accordingly, "A / B" can mean "only A," "only B," or "both A and B." For example, "A, B, C" can mean "A, B, or C."

[0028] In this specification, "at least one of A and B" may mean "only A", "only B" or "both A and B". Additionally, in this specification, the expressions "at least one of A or B" or "at least one of A and / or B" may be interpreted identically to "at least one of A and B".

[0029] Additionally, in this specification, “at least one of A, B and C” can mean “only A,” “only B,” “only C,” or “any combination of A, B and C.” Additionally, “at least one of A, B or C” or “at least one of A, B and / or C” can mean “at least one of A, B and C.”

[0030] Additionally, parentheses used herein may mean "for example." Specifically, when indicated as "control information (PDCCH)", "PDCCH" may be proposed as an example of "control information." In other words, "control information" in this specification is not limited to "PDCCH," and "PDCCH" may be proposed as an example of "control information." Furthermore, even when indicated as "control information (i.e., PDCCH)", "PDCCH" may be proposed as an example of "control information."

[0031] In the following explanation, ‘when, if, in case of’ can be replaced with ‘based on’.

[0032] Technical features individually described in a single drawing in this specification may be implemented individually or simultaneously.

[0033] In this specification, higher layer parameters may be parameters that are set for the terminal, preset, or predefined. For example, a base station or network may transmit higher layer parameters to the terminal. For example, higher layer parameters may be transmitted via radio resource control (RRC) signaling or medium access control (MAC) signaling.

[0034] In this specification, "configured or defined" may be interpreted as being configured or preset to a device through predefined signaling (e.g., SIB, MAC, RRC) from a base station or network. In this specification, "configured or defined" may be interpreted as being preset to a device.

[0035] The technology proposed in this specification can be used in various wireless communication systems such as CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), and SC-FDMA (single carrier frequency division multiple access). CDMA can be implemented with wireless technologies such as UTRA (universal terrestrial radio access) or CDMA2000. TDMA can be implemented with wireless technologies such as GSM (global system for mobile communications) / GPRS (general packet radio service) / EDGE (enhanced data rates for GSM evolution). OFDMA can be implemented with wireless technologies such as IEEE (Institute of Electrical and Electronics Engineers) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802-20, E-UTRA (evolved UTRA), LTE (long term evolution), and 5G NR.

[0036] The technology proposed in this specification can be implemented with 6G wireless technology and applied to various 6G systems. For example, 6G systems can have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine-type communication (mMTC), artificial intelligence (AI) integrated communication, tactile internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion, and enhanced data security.

[0037] FIG. 1 illustrates a communication structure that can be provided in a 6G system according to one embodiment of the present disclosure. The embodiment of FIG. 1 can be combined with various embodiments of the present disclosure.

[0038] As core implementation technologies of the 6G system, technologies such as artificial intelligence (AI), THz (terahertz) communication, optical wireless technology, free-space optical transmission (FSO) backhaul networks, massive MIMO (multiple input multiple output) technology, blockchain, 3D networking, quantum communication, unmanned aerial vehicles, cell-free communication, wireless information and energy transfer (WIET), integration of sensing and communication, integration of access backhaul networks, holographic beamforming, big data analysis, and large intelligent surface (LIS) can be adopted.

[0039] - Artificial Intelligence: Incorporating AI into communications can streamline and improve real-time data transmission. AI can use numerous analytics to determine how complex target tasks should be performed. For example, AI can increase efficiency and reduce processing delays. Time-consuming tasks such as handovers, network selection, and resource scheduling can be performed instantly using AI. AI can also play a crucial role in machine-to-machine (M2M), machine-to-human, and human-to-machine communications. AI can also facilitate rapid communication in brain-computer interfaces (BCIs). AI-based communication systems can be supported by metamaterials, intelligent structures, intelligent networks, intelligent devices, intelligent cognitive radios, self-sustaining wireless networks, and machine learning.

[0040] - THz communication (terahertz communication): Data rates can be increased by increasing the bandwidth. This can be achieved by using sub-THz communication with wide bandwidths and applying advanced massive MIMO technology. THz waves, also known as sub-millimeter waves, typically refer to the frequency range between 0.1 THz and 10 THz, with corresponding wavelengths ranging from 0.03 mm to 3 mm. The 100 GHz to 300 GHz band (sub-THz band) is considered a key part of the THz spectrum for cellular communications. Adding the sub-THz band to the mmWave band will increase the capacity of 6G cellular communications. Among the defined THz bands, 300 GHz to 3 THz lies in the far infrared (IR) frequency band. While part of the optical band, the 300 GHz to 3 THz band lies at the boundary of the optical band, immediately following the RF band. Therefore, this 300 GHz to 3 THz band exhibits similarities to RF. Key characteristics of THz communications include (i) the widely available bandwidth to support very high data rates and (ii) the high path loss that occurs at high frequencies (requiring highly directional antennas). The narrow beamwidths generated by highly directional antennas reduce interference. The small wavelength of THz signals allows for a significantly larger number of antenna elements to be integrated into devices and base stations operating in this band. This enables the use of advanced adaptive array technologies to overcome range limitations.

[0041] - Large-scale MIMO technology

[0042] - Hologram beamforming (HBF)

[0043] - Optical wireless technology

[0044] - Free-space optical transmission backhaul network (FSO backhaul network)

[0045] - Quantum communication

[0046] - Cell-free communication

[0047] - Integration of wireless information and power transmission

[0048] - Integration of wireless communication and sensing

[0049] - Integrated access and backhaul network

[0050] - Big data analysis

[0051] - Reconfigurable intelligent surface

[0052] - metaverse

[0053] - Block chain

[0054] Advanced Air Mobility (AAM): AAM can be a broad concept encompassing urban air mobility (UAM), regional air mobility (RAM), and uncrewed aerial systems (UAS). For example, AAM can include UAM, RAM, UAS, and uncrewed aerial vehicles (UAVs).

[0055] - Autonomous driving (self-driving): V2X (vehicle to everything), a key element in building autonomous driving infrastructure, can be a technology that allows cars to communicate and share with various elements on the road for autonomous driving, such as vehicle to vehicle (V2V) wireless communication and vehicle to infrastructure (V2I) wireless communication.

[0056] Non-terrestrial network (NTN): NTN can refer to a network or network segment that utilizes radio frequency (RF) resources mounted on satellites (or UAS platforms). NTN services may be considered to secure wider coverage or provide wireless communication services in locations where the installation of wireless communication base stations is difficult.

[0057] - Integrated sensing and communication (ISAC): Wireless sensing is a technology that uses radio frequencies to determine the instantaneous linear velocity, angle, distance (range), etc. of an object, thereby obtaining information about the characteristics of the environment and / or objects within the environment.

[0058] - Reconfigurable intelligent surface (RIS): RIS can be used to manipulate and enhance signal propagation in wireless communication environments. For example, a RIS can be composed of many small antennas, or metasurfaces, arranged on a surface, each of which can actively control the phase, amplitude, polarization, etc. of the reflected signal. For example, a RIS can improve signal reception by controlling the path, phase, and / or intensity of the propagating signal. For example, in the case of a RIS, power consumption can be very low because power is consumed only for controlling the phase and amplitude of the small antennas. For example, because a RIS can be reconfigured to suit different environments, it can meet diverse communication requirements and operate effectively in dynamic network environments.

[0059] FIG. 2 illustrates an example of a communication scenario based on a 6G system, according to an embodiment of the present disclosure. The embodiment of FIG. 2 may be combined with various embodiments of the present disclosure.

[0060] Referring to FIG. 2, NTN communication can be performed based on satellite networks, high-altitude platform stations (HAPS) as international mobile telecommunications (IMT) base stations (BS), terminals capable of aerial communication (e.g., AAM), etc. For example, to improve coverage, etc., devices such as satellite networks, HIBS, terminals capable of aerial communication (e.g., AAM), etc. can act as relays. For example, AAMs can communicate with base stations, satellite networks, etc., and / or AAMs can communicate directly with terminals, other AAMs, etc.

[0061] Below, the integrated sensing and communication (ISAC) mentioned above is described in detail.

[0062] Integrated Sensing and Communications (ISAC) is a technology that uses radio frequencies to determine the instantaneous linear velocity, angle, distance (range), etc. of an object, thereby obtaining information about the environment and / or the characteristics of objects within the environment. Because radio frequency sensing does not require a device to connect to the object through a network, it can provide services for object positioning without a device. The ability to obtain range, velocity, and angle information from radio frequency signals can enable a wide range of new capabilities, such as various object detection, object recognition (e.g., vehicles, humans, animals, UAVs), and high-precision localization, tracking, and activity recognition. Wireless sensing services can provide information to a variety of industries (e.g., unmanned aerial vehicles, smart homes, V2X, factories, railways, public safety, etc.), enabling applications such as intruder detection, assisted vehicle steering and navigation, trajectory tracking, collision avoidance, traffic management, and health and traffic management. In some cases, wireless sensing can utilize non-3GPP type sensors (e.g., radar, cameras) to further support 3GPP-based sensing. For example, the operation of a wireless sensing service, e.g., a sensing operation, may depend on the transmission, reflection, and scattering of wireless sensing signals. Therefore, wireless sensing may provide an opportunity to enhance existing communication systems from a communication network to a wireless communication and sensing network. FIG. 3 illustrates an example of a sensing operation according to an embodiment of the present disclosure. The embodiment of FIG. 3 may be combined with various embodiments of the present disclosure. Specifically, FIG. 3 (a) illustrates an example of sensing using a sensing receiver and a sensing transmitter located at the same location (e.g., monostatic sensing), and FIG. 3 (b) illustrates an example of sensing using a separated sensing receiver and a sensing transmitter (e.g., bistatic sensing).

[0063] FIG. 4 is a diagram for explaining and comparing V2X communication based on RAT prior to NR and V2X communication based on NR according to one embodiment of the present disclosure. The embodiment of FIG. 4 can be combined with various embodiments of the present disclosure.

[0064] In relation to V2X communication, in RATs prior to NR, methods for providing safety services based on V2X messages such as Basic Safety Message (BSM), Cooperative Awareness Message (CAM), and Decentralized Environmental Notification Message (DENM) were mainly discussed. V2X messages may include location information, dynamic information, attribute information, etc. For example, a terminal may transmit a CAM of a periodic message type and / or a DENM of an event triggered message type to another terminal.

[0065] For example, a CAM may include basic vehicle information such as dynamic vehicle status information, such as direction and speed, static vehicle data, such as dimensions, external lighting conditions, and route history. For example, a terminal may broadcast a CAM, and the latency of the CAM may be less than 100 ms. For example, in the event of an emergency, such as a vehicle breakdown or accident, a terminal may generate a DENM and transmit it to other terminals. For example, all vehicles within the transmission range of the terminal may receive the CAM and / or DENM. In this case, the DENM may have a higher priority than the CAM.

[0066] Since then, various V2X scenarios have been proposed in NR in relation to V2X communications. For example, various V2X scenarios may include vehicle platooning, advanced driving, extended sensors, and remote driving.

[0067] For example, based on vehicle platooning, vehicles can dynamically form groups and move together. For example, to perform platoon operations based on vehicle platooning, vehicles in the group can receive periodic data from the lead vehicle. For example, vehicles in the group can use this periodic data to narrow or widen the gap between vehicles.

[0068] For example, based on improved driving, vehicles can become semi-autonomous or fully automated. For example, each vehicle can adjust its trajectories or maneuvers based on data acquired from local sensors of nearby vehicles and / or nearby logical entities. Furthermore, for example, each vehicle can share driving intentions with nearby vehicles.

[0069] For example, based on extended sensors, raw data, processed data, or live video data acquired through local sensors can be exchanged between vehicles, logical entities, pedestrian terminals, and / or V2X application servers. Thus, for example, a vehicle can perceive its environment better than it can perceive using its own sensors.

[0070] For example, based on remote driving, a remote driver or V2X application can operate or control the remote vehicle for people who cannot drive or for remote vehicles located in hazardous environments. For example, in cases where the route is predictable, such as public transportation, cloud computing-based driving can be utilized to operate or control the remote vehicle. Additionally, access to a cloud-based back-end service platform, for example, can be considered for remote driving.

[0071] Meanwhile, a method to specify service requirements for various V2X scenarios, such as vehicle platooning, enhanced driving, expanded sensors, and remote driving, is being discussed in NR-based V2X communication.

[0072] According to one embodiment of the present disclosure, for example, an object detection / perception system and / or tracking system for general vision information and / or an artificial intelligence system for object recognition / tracking may have a problem in that the object recognition or tracking performance and accuracy are reduced when an obstacle such as a fixed structure constituting a road marking such as a crosswalk or lane or a traffic light or a sign overlaps (occludes) a first device (e.g., a vehicle) or a pedestrian.

[0073] FIG. 5 is a diagram for explaining the results before and after performing an operation related to object detection / perception or object tracking according to an embodiment of the present disclosure. The embodiment of FIG. 5 can be combined with various embodiments of the present disclosure. FIG. 6 is a diagram for explaining the results before performing an operation related to object detection / perception or object tracking according to an embodiment of the present disclosure. The embodiment of FIG. 6 can be combined with various embodiments of the present disclosure.

[0074] <Figure 5> can show an As-Is case where object recognition and tracking performance is poor when a pedestrian runs on a crosswalk, and a To-Be case where motion blur / background removal is performed through an embodiment of the present disclosure to improve object recognition and tracking performance.

[0075] <Figure 6> may represent an As-Is case in which a first device (e.g., a vehicle) is not recognized or tracked by a structure forming a traffic light or sign.

[0076] Referring to the left side of FIG. 5 and / or FIG. 6, according to an embodiment of the present disclosure, for example, to solve the problems of these cases, a high-definition or high-performance camera may be installed, or other sensor devices such as LiDAR (light detection and ranging) and radar may be additionally installed, and there may be a method of performing sensor fusion, but these may be expensive and cumbersome. Alternatively, for example, an area of ​​interest (ROI) to be overlapped or supplemented may be manually designated to solve the problem through artificial intelligence, and / or a method of solving it through additional learning may be proposed, but this may also be inefficient in terms of cost, and for example, a method of changing the properties (parameters) of the tracker or changing the characteristics may be proposed, which may deteriorate the overall performance of the object tracking system.

[0077] According to one embodiment of the present disclosure, in order to implement a simpler service, a method of estimating and notifying the risk of collision between road users by using the object detection results or POI (point of interest) information at, for example, a road side unit (RSU) or a server may be proposed. For example, fixed areas such as crosswalks and school zones may have RSUs (road side units) installed, and / or these may be initially set and stored and used for V2X services, etc. In this case, for example, the RSU (road side unit) or the server may estimate the probability of collision for all combinations of pedestrians and all first devices (e.g., vehicles) within the detection area, or at least the probability of collision for all combinations of pedestrians and first devices (e.g., vehicles) that satisfy a specific condition (e.g., expected time to collision (i.e., TTC, Time To Collision)).

[0078] In the present disclosure, a technology for automatically designating a region of interest (ROI) that needs to improve object recognition and tracking performance through external data reinforcement such as a high-precision map and / or a method and device for supplementing the recognition and tracking performance of an object located within a designated region of interest may be proposed.

[0079] The present disclosure proposes a method and device for supplementing object recognition and tracking through data augmentation by acquiring POI (point of interest) information on key areas secured as data from high-definition maps or digital twins, such as fixed structures, obstacles, and crosswalks, such as traffic lights or signs. For example, an object recognition and tracking system can be supplemented by utilizing high-definition map or digital twin data without the need to install high-performance sensor equipment or add additional sensor equipment. In addition, the cumbersome process of manually designating an area of ​​interest (ROI) to be overlapped or supplemented can be omitted and automated. Furthermore, for example, by supplementing the problems and performance of an object recognition and tracking system, traffic safety and efficiency can be enhanced.

[0080] To explain the detailed application method of the present disclosure, a case of utilizing vector data corresponding to the segmentation layer among the various data layers that constitute a high-precision map or digital twin can be explained as an application example. For example, for a first device (e.g., a vehicle) moving at a high speed, it may be more efficient to utilize simplified vector data compared to a large amount of point cloud data. However, if, for example, high-performance resources of edge computing equipment can be utilized, point cloud data can be utilized directly for accuracy or can be utilized by merging (data fusion) with vision data.

[0081] FIG. 7 is a diagram illustrating a result obtained after performing an operation related to object detection / perception or object tracking according to an embodiment of the present disclosure. The embodiment of FIG. 7 may be combined with various embodiments of the present disclosure.

[0082] <Fig. 7> can represent an example of utilizing data on crosswalk markings of a high-precision map (e.g., diagrammed in green ((Fig. 7))) to solve the problem of poor object recognition and tracking performance when a pedestrian runs on a crosswalk (of <Fig. 5>). For example, since a high-precision map can secure absolute coordinate values ​​for each point that constitutes the geometry of a crosswalk marking feature, a crosswalk marking area with poor object recognition and tracking performance can be automatically designated as a region of interest (ROI).

[0083] According to one embodiment of the present disclosure, a background subtraction (e.g., background subtraction) technique may be applied to exclude a fixed area (e.g., a crosswalk marking shape) from the background to improve object recognition performance within a fixed area (e.g., a crosswalk marking area). In addition, for example, to improve object tracking performance within a fixed area (e.g., a crosswalk marking shape), the system may be designed to enable precise tracking of objects that are intermittently detected, even if the displacement is large, (among them) objects having the same characteristics.

[0084] According to one embodiment of the present disclosure, a possibility of collision between a pedestrian and a first device (e.g., a vehicle) may be estimated by a road side unit (RSU) or a server, and in this case, when the pedestrian may be stationary (e.g., the pedestrian may be waiting for a pedestrian signal in front of a crosswalk) or the pedestrian is moving quickly but is not detected by a road side unit (e.g., a camera), etc., the possibility of collision may be predicted to be non-existent or the possibility of collision may not be estimated.

[0085] Accordingly, according to one embodiment of the present disclosure, in case a pedestrian is not accurately detected, whether or not the RSU (road side unit) or the server estimates the possibility of a collision, key information about the road situation can be transmitted to first devices (e.g., vehicles) entering the road, and / or the first devices (e.g., vehicles) can separately estimate the possibility of a collision or the risk of a collision based on the key information.

[0086] The operation(s) according to one embodiment of the present disclosure may be performed by receiving information about an area preceding the area, rather than information about an area into which the first device has already entered, when the first device (e.g., a vehicle) enters a specific area (e.g., a specific location or a specific zone).

[0087] Referring to FIG. 7, according to one embodiment of the present disclosure, more specifically, when a first device (e.g., a vehicle) enters a specific intersection, an estimation of the risk of collision at the intersection, etc. may already be performed, and / or performing the operation(s) according to one embodiment of the present disclosure at or after the time when the first device (e.g., the vehicle) enters may cause a delay as a prior warning and may result in the generation of invalid information. In this case, for example, the information estimated and transmitted by the RSU (road side unit) / server, etc. may be specific POI (point of interest) information such as fixed area information (e.g., crosswalk area information) (<FIG. 7>) and / or information on detected objects.

[0088] FIG. 8 illustrates area information related to a method for performing wireless communication according to an embodiment of the present disclosure. The embodiment of FIG. 8 may be combined with various embodiments of the present disclosure.

[0089] Referring to FIG. 8, according to one embodiment of the present disclosure, for example, information on key points for a corresponding area may be transmitted as n points of information so as to be mapped in the form of a polygon. For example, when the value of n is 1, the information may indicate a specific point, or may indicate representative values ​​such as the center point, center of gravity point, and average point of a specific area in order to minimize the amount of information to be transmitted. For example, or when the value of n is 2, the information may indicate a specific linear area, or may indicate values ​​for two points, the start point and the end point, which are indicated by a diagonal line among four points of a rectangular area. For example, when n is 3 or more, the information may be expressed in a simplified form of a polygon for a specific area. For example, if the information is transmitted via a message that transmits sensor data (e.g., CPM (Collective Perception Message), SDSM (Sensor Data Sharing Message), etc.), a field indicating the total number of points may exist in a specific part of the message (e.g., the front part (header)) as in <Fig. 8>, and since the number of points of a polygon may not be infinitely large, if the value of n can be limited to a maximum value (e.g., 7), the size of the field indicating the number of points expressing information indicating the detection area can be configured with an appropriate number of bits (e.g., 3 bits if n is 7).

[0090] According to one embodiment of the present disclosure, there may also be n fields that are mapped to the values ​​of each point for the information of the main points for the corresponding area, and for example, the coordinates of GPS (e.g., x, y, z coordinates) may be configured to the same extent as the V2X message (e.g., 80 bits), or may be further abbreviated, or may be expressed in the form of relative coordinates based on a specific point (e.g., 40 bits).

[0091] FIG. 9 illustrates a result prior to performing an operation related to object detection / perception or object tracking according to an embodiment of the present disclosure. The embodiment of FIG. 9 may be combined with various embodiments of the present disclosure.

[0092] According to one embodiment of the present disclosure, in a directly performed experiment, it was detected that object detection or tracking sometimes fails when a road situation is blocked by structures such as road signs, traffic lights, or signal / speed detection equipment, as shown in <Fig. 9>. In order to prevent such cases, as one embodiment of the present disclosure, information (e.g., region of interest (ROI), bounding box, vector map, segmentation map, etc.) of a static area (e.g., road signs or structures) can be received, and for example, when the size of the area exceeds a certain ratio or threshold value with respect to the size of the entire image area or a certain area (e.g., road lane), and / or when a road user (RU) is located in the area, object detection and / or tracking-related parameters can be changed and applied only to the area in comparison with the previous frame information so that detection and tracking is not missed, or, for example, operations such as a Kalman filter or Intersection over Union (IoU) are supplemented, so that detection and / or tracking can continue without a problem.

[0093] FIG. 10 illustrates a method for performing wireless communication according to an embodiment of the present disclosure. The embodiment of FIG. 10 may be combined with various embodiments of the present disclosure.

[0094] Referring to FIG. 10, according to one embodiment of the present disclosure, for example, according to a self-performance experiment of an object detector, the detection and tracking performance was lower on a crosswalk marked with a yellow marking pattern than on a crosswalk with a white marking pattern. For example, in order to prevent this performance degradation, in the embodiment of FIG. 10, the presence of a fixed area (e.g., a crosswalk) that obscures a first device (e.g., a vehicle) or a pedestrian or other road user among fixed areas can be confirmed from a snapshot or an image, and, for example, if the color (e.g., R / G / B) of the fixed area (e.g., a crosswalk marking pattern) that obscures a first device (e.g., a vehicle) or a pedestrian or other road user among fixed areas is higher than a certain value (e.g., yellow), the corresponding marking pattern is removed and then a blurring removal step is performed, thereby preventing blurring due to high-speed movement or an object not being detected due to the marking pattern.

[0095] According to one embodiment of the present disclosure, for example, referring to FIG. 10, region of interest (ROI) information of a fixed area (e.g., a sign or a structure) that obscures a first device (e.g., a vehicle) or a road user such as a pedestrian among fixed areas can be received from a snapshot or an image, and when an occupancy ratio (e.g., length / width) of the image or a certain area (e.g., a road lane) of the received area is greater than a threshold value To, and / or when some or all of the first device (e.g., a vehicle) or a road user such as a person is located in the area, an enhanced or special detection or tracking algorithm can be applied, and / or even when occlusion occurs between the fixed area (e.g., a sign or a structure) that obscures a first device (e.g., a vehicle) or a road user such as a pedestrian among fixed areas and the road user, the object can be continuously detected and tracked.

[0096] FIG. 11 illustrates a method for performing wireless communication according to an embodiment of the present disclosure. The embodiment of FIG. 11 may be combined with various embodiments of the present disclosure.

[0097] In another embodiment of the present disclosure, instead of performing the fixed area removal / deblurring operation by comparing the color of the fixed area (e.g., marking pattern) that obscures a road user such as a first device (e.g., vehicle) or a pedestrian among fixed areas with a designated color or comparing the value of the color, the fixed area (e.g., surrounding background) may be removed when the accuracy / precision or confidence / score of object recognition becomes below a threshold value. In addition, for example, as a more general embodiment, instead of the designated color, various threshold comparison conditions such as hue-saturation, hue-brightness, grayscale (brightness), hue-saturation-brightness, etc. of the fixed area (e.g., marking area) that obscures a road user such as a first device (e.g., vehicle) or a pedestrian among fixed areas may be configured, which may be integrated with the above embodiment(s) of the present disclosure and may be expressed, for example, in a flowchart such as <Fig. 11>.

[0098] Information of the detection and / or tracking technique proposed in the present disclosure may be provided by utilizing new protocols / messages and / or standard messages (e.g., Decentralized Environmental Notification Message (DENM), Collective Perception Message (CPM), Sensor Data Sharing Message (SDSM), etc.) and / or as a combination of standard messages, a combination of new messages, or a combination of standard messages and new messages. The new or additional messages or data frames (DF) / data elements (DE) / containers proposed in the present disclosure may be defined as in and at least one of the following.

[0099] Descriptive Name ROIPosition ASN.1 Representation ROIPosition ::= SEQUENCE { latitude LatitudeOffset, longitude LongitudeOffset, altitude AltitudeOffset} Definition It defines the geographical position / offset of a position or of an ITS-S. It represents a geographical point position. Each offset value can be presented by either degree or meter. Unit -

[0100] According to one embodiment of the present disclosure, the event position, relevance distance / relevance traffic direction fields existing in the management container of the DENM (Decentralized Environmental Notification Message) among standard messages may be utilized without adding new fields, and the reference position (DF_ReferencePosition) field may also be utilized. For example, new fields such as those in may be added to the DENM (Decentralized Environmental Notification Message).

[0101] According to one embodiment of the present disclosure, a new field may not be added, and a Perceived Objects field of a Perceived Object Container existing in a Perception Data Container of a Collective Perception Message (CPM) among standard messages may be utilized. Alternatively, for example, a new field such as may be added to a Collective Perception Message (CPM).

[0102] According to one embodiment of the present disclosure, for example, when information on a detected object, for example, a pedestrian, is transmitted, at least one of detection time, location, speed, direction information, etc. may be transmitted by default, and in the case of a stopped pedestrian, speed, direction information, etc. may not be displayed, may be expressed as 0, or (in the case of direction) an arbitrary value may be expressed, or a previous value may be expressed.

[0103] According to one embodiment of the present disclosure, if a stopped pedestrian is no longer tracked, it may mean that he or she has physically or image-wise (in terms of detection) disappeared.

[0104] According to one embodiment of the present disclosure, being visually lost may mean being out of the range of the image or may mean being undetectable within the image.

[0105] According to one embodiment of the present disclosure, if it is determined that the pedestrian has gone out of the range of the image through tracking of the pedestrian and estimation of the expected path, the occurrence of a handover between cameras (or sensors) may be notified to a surrounding road side unit (RSU) / server, etc., and the RSU (road side unit) may no longer perform tracking and management.

[0106] According to one embodiment of the present disclosure, in the case where an object exists within the range of an image but is not detected, the time of final detection and the speed and direction information at that time may be the most up-to-date information, and the risk of collision, etc. may be estimated using this information.

[0107] According to one embodiment of the present disclosure, for example, when a specific (stationary or moving) pedestrian is between several set areas or crosswalks, it can be determined whether the pedestrian is currently in an area associated with the RSU (road side unit) (i.e., a target for estimating collision risk, etc.) or moving toward a crosswalk or moving toward an unrelated area or crosswalk, and / or estimated information about the pedestrian can be generated and / or transmitted.

[0108] According to one embodiment of the present disclosure, for example, in the case of a stopped pedestrian, it may be estimated which area or crosswalk to use based on direction information before stopping, and if the direction information does not exist or is invalid (for example, if the pedestrian continues to spin in place), the area or crosswalk at the point that is the shortest distance from the pedestrian may be selected.

[0109] According to one embodiment of the present disclosure, the RSU (road side unit) or server may transmit information about the final location and time of discovery or the expected location and related time of the pedestrian expected to be moving in the associated area or crosswalk.

[0110] According to one embodiment of the present disclosure, based on the information on the set area and the detected / tracked pedestrian, the risk of collision, etc. may be simply estimated by the RSU (road side unit) or server. For example, or in order to more accurately determine the possibility of collision, etc., and / or in order to reduce the computational load on the RSU (road side unit) / server, the risk of collision may be directly estimated by a first device (e.g., a vehicle) approaching the specific area or crosswalk based on the information on the set area and the detected / tracked pedestrian received (or already known) as described above.

[0111] According to one embodiment of the present disclosure, for example, the speed of a pedestrian who is thought to be moving from a previous detection point due to the non-detection may be the last detected speed or may be determined by some other representative value (e.g., the average walking speed or running speed of the pedestrian).

[0112] FIG. 12 illustrates a result after performing an operation related to object detection / perception or object tracking, according to an embodiment of the present disclosure. The embodiment of FIG. 12 may be combined with various embodiments of the present disclosure.

[0113] Referring to FIG. 12, according to one embodiment of the present disclosure, for example, when a first device (e.g., a vehicle) or a road user such as a pedestrian is not recognized or tracked by a fixed area (e.g., a structure forming a traffic light or sign in FIG. 6) that obscures the first device (e.g., a vehicle) or a road user among fixed areas, a region of interest (ROI) can be automatically designated around the area by utilizing traffic light vector data of a high-precision map. For example, for an object approaching and entering or exiting the region of interest (ROI), recognition or tracking information can be compared with data at a time point prior to entry / exit so that the recognition or tracking information can be maintained. For example, techniques such as a Kalman Filter and a Hungarian Method can be utilized for object tracking at a previous time point and a subsequent time point.

[0114] In the present disclosure, signs / structures (traffic lights) / crosswalks (markings) are only one example of composing ground / underground / air transportation / mobility infrastructure, and transportation / mobility infrastructure that controls / controls / notifies (indicates) / communicates the situation regarding the movement / traffic of at least one first device (mobile object) within a certain area may be included.

[0115] In the present disclosure, a pedestrian / vehicle (first device) is only one example of an object that can move on the ground / underground / in the air (see FIG. 15 and the description thereon below), and any vehicle that can move within a certain area may be included.

[0116] According to one embodiment of the present disclosure, a first image (first frame, first time) and / or a reference image may be acquired. For example, features (points) / regions of interest related to an object / non-object background may be extracted from the first image and / or the reference image. For example, a bounding box for an object may be acquired based on the extracted features (points) / regions of interest.

[0117] For example, the reference image may be a region of interest (ROI), a bounding box, a vector map, a segmentation map, or a representative value representing a region / box (represented by points, vectors, segmentation, etc.) of a specific object (e.g., a sign / structure (traffic light) / crosswalk (marking)) that is distinguishable from other objects / backgrounds as the entire image or a part of the entire image (e.g., a center position of an overlapping zone among at least one zone divided by latitude / longitude and a certain unit length, a center of gravity point of the region, a center of mass point of the region, etc.).

[0118] For example, among the first images, images identical / similar to the reference image can be automatically detected as areas that interfere with object detection. For example, the reference image can include a feature (filter) map regarding at least one object (e.g., a sign / structure (traffic light) / crosswalk (marking)), and the feature (filter) map can include a feature map regarding low-level features such as edges, lines, and corners of the object, and a feature map regarding high-level features such as the shape, texture, and components (parts) of the object. For example, the feature map can be extracted through learning from a feature layer (e.g., a convolution layer) that is learned on its own based on input data based on a learning model (e.g., a CNN, a reinforcement learning model, etc.), or can be set through a feature filter bank.

[0119] For example, the image (frame) or reference image may be preprocessed prior to the acquisition / extraction / recognition. For example, the resolution (size) of the image (frame) may be converted. For example, the image (frame) may be converted to grayscale / R / G / B, etc. For example, the image (frame) may be subjected to noise removal through an erosion operation to remove noise in dark areas, a dilation operation to remove noise in bright areas, a dilation operation after an erosion operation, an erosion operation after a dilation operation, etc.

[0120] For example, by comparing the features (points) or bounding boxes (boundary points) of moving / static objects / backgrounds with the features (points) or bounding boxes (boundary points) and the (self-)trained model through (self-)supervised learning / unsupervised learning (e.g., if the difference between the two is less than a threshold), it can be recognized what object the feature (point) or bounding box (boundary point) is.

[0121] For example, based on the difference between an image containing a static object / background and the current image (the object / background within the region of interest (ROI) (automatically) detected through the reference image within the image), it can be extracted whether the object is a moving object or a static object / static background. For example, a region where the result of the difference (e.g., brightness difference in grayscale) is greater than a threshold value can be distinguished / recognized as a moving object. For example, a region where the result of the difference (e.g., brightness difference in grayscale) is less than a threshold value can be distinguished / recognized as a static object / static background.

[0122] For example, points with similar differences between an image containing static objects / backgrounds and the current image (objects / backgrounds within a region of interest (ROI) detected (automatically) through a reference image within it) can be grouped / clustered. For example, among points with similar differences between an image containing static objects / backgrounds and the current image (objects / backgrounds within a region of interest (ROI) detected (automatically) through a reference image within it), areas with differences greater than a threshold can be grouped / clustered into their respective moving objects. For example, among points with similar differences between an image containing static objects / backgrounds and the current image (objects / backgrounds within a region of interest (ROI) detected (automatically) through a reference image within it)), areas with differences less than a threshold can be grouped / clustered into their respective static objects / static backgrounds. For example, clustering can be classified based on the (mean) velocity / displacement of the points. For example, high-velocity / high-displacement point clusters can be clustered into their respective moving objects, and no-velocity / no-displacement clusters can be clustered into their respective static backgrounds / objects.

[0123] For example, based on optical flow, it can be distinguished / converted whether the object is a moving object or a static object / static background, or the area where the moving object overlaps the static object / static background can be extracted. For example, the path along which at least one of a feature (point) or a bounding box (a boundary point) moves over time (frame) can be tracked. For example, it can be distinguished / converted whether the object is a moving object or not based on the position (change) / velocity (change) / acceleration (change) / angular velocity (change) of at least one of a feature (point) or a bounding box (a boundary point). For example, the change over time of a feature (point) or a bounding box (a boundary point) can be expressed as a motion vector. For example, by estimating / tracking the motion vector, it can be detected / recognized whether the object is a moving object or not, and if so, which moving object it is. For example, a point (pixel) without the motion vector can be detected / recognized as a static background.

[0124] However, for example, if the movement path of the tracked moving object in the image is very short, or if the speed of the tracked moving object in the image is too fast, or if the object in the image is a moving object but the feature points / bounding box (points within) are obscured by a stationary object / background, or if the size of the object in the image is too small (e.g., a distant object), the performance of object detection / recognition may be reduced due to blurring or feature (point) loss.

[0125] Therefore, according to one embodiment of the present disclosure, a method or a data augmentation method can be proposed for distinguishing whether a stationary object / background is a stationary object / background that obscures a moving object, and selectively and conditionally removing only the distinguished occluding object / background.

[0126] For example, in a case where a moving object (clustered point cloud, representative motion vector, boundary point box, etc.) having a motion vector overlaps with the static object / background (e.g., sign / structure (traffic light) / crosswalk (marking), etc.) within the region of interest (automatically) detected through the reference image) (e.g., the ratio of moving objects (clustered point cloud, representative motion vector, boundary point box, etc.) having a motion vector among the static objects / background within the region of interest (automatically) detected through the reference image is greater than or equal to a threshold value), a removal operation for the static object / background (mask) overlapping with the moving object (having a motion vector) among the static objects / background within the region of interest (automatically) detected through the reference image) and / or a restoration / filling operation for the dynamic object (mask) may be performed. For example, if there is no change (pixel, voxel) over time in the area where the (static) object / background and the moving object with motion vector overlap within the region of interest (automatically) detected through the reference image (e.g., when the change value is below a threshold value), the moving object may be determined to be occluded by the static object / background, or a removal operation may be performed on the static object / background that overlaps with the moving object (with motion vector) among the static objects / background within the region of interest (automatically) detected through the reference image, and / or a restoration / filling operation may be performed on the dynamic object.

[0127] For example, a restoration / filling operation for the overlapping static / background into a dynamic object can be performed based on images (frames) of the previous time in which the dynamic object / background moved. For example, after the restoration / filling operation for the overlapping static / background into a dynamic object, a pixel (voxel) removal operation for the static object / background overlapping on the restored / filled dynamic object can be performed.

[0128] For example, the operation(s) according to one embodiment of the present disclosure (e.g., a motion blur removal operation, a removal operation for a static object / background overlapping a moving object (having a motion vector) among the static objects / backgrounds within the region of interest (automatically) detected through the reference image, and / or a restoration / peeling operation for the dynamic object) may be performed when a quality parameter for the detection of the dynamic object (e.g., precision, recall, F1 score, confidence score, IoU (intersection over union) between the image frame (bounding box) of the object predicted through the (learning) model and the image frame (bounding box) of the actual object, etc.)) is below a threshold value (which may vary for each parameter). Through this, traffic accidents due to slow collision risk judgment due to overload and computational processing caused by unconditionally performing the removal / restoration operation for the static object / background overlapping on the movement line of the dynamic object can be reduced.

[0129] For example, the operation(s) according to one embodiment of the present disclosure (e.g., a removal operation for a static object / background overlapping with a moving object (having a motion vector) among the static objects / backgrounds within the region of interest (automatically) detected through the reference image and / or a restoration / filling operation for the dynamic object) is performed when the value of each color constituting the static object / background (or a part thereof) overlapping with a moving object (having a motion vector) among the static objects / backgrounds within the region of interest (automatically) detected through the reference image is greater than or equal to a threshold value (e.g., when at least one value of grayscale (brightness) / R / G / B among the colors of (feature points) of a crosswalk and an asphalt road overlapping with a pedestrian is greater than or equal to a threshold value), and / or a quality parameter for the detection of the dynamic object (e.g., precision, recall, F1 score, confidence score, image frame (bounding box) of an object predicted through a (learning) model and image frame (boundary box) of an actual object This can be performed when the IoU (intersection over union) between the boxes is below a threshold value (which may vary depending on the parameter). Through this, traffic accidents caused by slow collision risk assessment due to overload and computational processing caused by unconditional removal / restoration operations on static objects / backgrounds overlapping the movement path of dynamic objects can be reduced.

[0130] For example, the operation(s) according to one embodiment of the present disclosure (e.g., a motion blur removal operation, a removal operation for a static object / background overlapping a moving object (having a motion vector) among the static objects / backgrounds within the region of interest (automatically) detected through the reference image, and / or a restoration / filling operation for the dynamic object) may be performed when the value (brightness in the case of grayscale, saturation of each color in the case of colors such as RGB) for each point (pixel, voxel) constituting the detected dynamic object is greater than or equal to a threshold value (which may vary by parameter). Through this, traffic accidents caused by slow collision risk judgment due to overload and computational processing caused by unconditionally performing a removal / restoration operation on static objects / backgrounds overlapping on the movement line of dynamic objects can be reduced.

[0131] For example, the operation(s) according to one embodiment of the present disclosure (e.g., a motion blur removal operation, a removal operation for a static object / background overlapping with a moving object (having a motion vector) among static objects / backgrounds (clustered point clouds, representative motion vectors, boundary point boxes, etc.) within the region of interest (automatically) detected through the reference image, and / or a restoration / filling operation for the dynamic object) may be performed based on the ratio of moving objects (clustered point clouds, representative motion vectors, boundary point boxes, etc.) having motion vectors among static objects / backgrounds (clustered point clouds, representative motion vectors, boundary point boxes, etc.) having no or few motion vectors being greater than a threshold value, and / or a removal operation for a static object / background (mask) overlapping with a moving object (having a motion vector) among static objects / backgrounds (clustered point clouds, representative motion vectors, boundary point boxes, etc.) within the region of interest (automatically) detected through the reference image, and / or a restoration / filling operation for the dynamic object (mask) may be performed. For example, if there is no change (pixel, voxel) over time in the overlapping area of ​​a static object / background without a motion vector (clustered point cloud, representative motion vector, boundary point box, etc.) and a moving object with a motion vector (e.g., when the change value is below a threshold value), a removal operation for the static object / background (mask) overlapping with the moving object (with a motion vector) among the static objects / backgrounds within the region of interest (automatically) detected through the reference image and / or a restoration / filling operation for the dynamic object (mask) can be performed. Through this, traffic accidents caused by slow collision risk judgment due to overload and computational processing caused by unconditionally performing a removal / restoration operation on the static object / background overlapping on the movement line of the dynamic object can be reduced.

[0132] For example, the operation(s) according to one embodiment of the present disclosure (e.g., motion blur removal operation, removal operation for static objects / backgrounds overlapping with moving objects (having motion vectors) among static objects / backgrounds within the region of interest (automatically) detected through the reference image, and / or restoration / peeling operation for the dynamic objects) can be performed within a specific time region. For example, the specific time region can be obtained based on traffic information (e.g., operation / blinking time of red / yellow / green traffic lights). For example, the specific time region can be obtained based on a value obtained by adding or subtracting a correction value to the passable time of a moving object calculated through traffic information. Through this, traffic accidents caused by overload and slow collision risk judgment due to computational processing that are unconditionally performed to remove / restore static objects / backgrounds overlapping on the path of a dynamic object can be reduced.

[0133] For example, the specific time region can be obtained based on the (predicted / measured / defined) speed information (e.g., average speed, maximum speed, etc.) of the corresponding dynamic object and the length information of the (occluding) static object / background (e.g., the length of the horizontal line / vertical line / diagonal line / center line (connecting line from the center to the vertex) of the bounding box, and which length among the horizontal line / vertical line / diagonal line / center line length can be used can be determined based on how much the direction of the movement path of the dynamic object and the direction of the horizontal line / vertical line / diagonal / center line match each other (e.g., whether the difference between the directions (angles) is less than or equal to a threshold value)). For example, the length of the specific time region can be a value obtained by dividing the length obtained through the length information of the corresponding static object by the speed obtained through the speed information of the corresponding dynamic object. For example, the start time of the specific time region can be the time when the moving speed of the corresponding dynamic object becomes less than or equal to a threshold value. For example, the start time of the specific time region can be the time when the position of the corresponding dynamic object is within a specific position range. Through this, traffic accidents caused by slow collision risk judgment due to overload and computational processing caused by unconditional removal / restoration operations performed on static objects / backgrounds overlapping the movement line of dynamic objects can be reduced.

[0134] According to one embodiment of the present disclosure, for example, in an image / video containing a moving dynamic object and a fixed static background area, the detection performance of the dynamic object can be improved by determining the static background area corresponding to the area mainly occupied by the dynamic object as an obstacle and deleting / replacing it. For example, by conditionally performing the removal (replacement) / motion blur removal (replacement) operation of the fixed background area overlapping the moving area (orbit) / stationary area of ​​the mobile object, both the performance of object detection and the speed of object detection can be harmonized.

[0135] FIG. 13 illustrates a method performed by a first device according to one embodiment of the present disclosure. The embodiment of FIG. 13 may be combined with various embodiments of the present disclosure.

[0136] Referring to FIG. 13, according to an embodiment of the present disclosure, in step S1310, for example, the first device may obtain a message including information regarding a blocking area associated with at least one candidate blocking object. In step S1320, for example, the first device may generate first information regarding a first blocking object and second information regarding a filling area associated with the first blocking object based on the information regarding the blocking area associated with the at least one candidate blocking object and the first area associated with a first time. In step S1330, for example, the first device may perform detection regarding at least one moving object within the second area associated with a second time. For example, the detection of the at least one moving object may be performed within a second area in which the first blocking area related to the first blocking object is replaced with the filling area among the second areas with respect to the second time, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

[0137] Additionally or alternatively, the message may include a collective perception message (CPM).

[0138] Additionally or alternatively, the information about the blocking area may include information relating to the position of at least one point representing the blocking area.

[0139] Additionally or alternatively, the at least one point representing the blocking area may include at least one of a center point of a zone corresponding to the blocking area, a center point of gravity of a bounding box for the blocking area, or a center point of mass of the blocking area.

[0140] Additionally or alternatively, the information about the blocking region associated with the at least one candidate blocking object may include at least one of information related to a region of interest, information related to a bounding box, information related to a vector map, and information related to a segmentation map.

[0141] Additionally or alternatively, the first information related to the first blocking object may be generated based on a difference between a first value processed with a scale for the first color for the first region and a reference value processed with a scale for the first color for a reference region.

[0142] Additionally or alternatively, the first information related to the blocking object may be generated based on the fact that the proportion of the area of ​​the first static object included in the first area among the areas of the first moving object included in the first area is greater than or equal to a threshold value.

[0143] Additionally or alternatively, the second information related to the filling area for the blocking object may be generated based on a movement area of ​​the second moving object included in the first area or a background area around the blocking area.

[0144] Additionally or alternatively, (i) based on a parameter value relating to a quality of detection of said at least one moving object being less than or equal to a threshold value, and (ii) based on said first information and said second information, said detection of said at least one moving object may be performed within a second area in which a first blocking area related to said first blocking object among said second areas relating to said second time is replaced with the filling area.

[0145] Additionally or alternatively, (i) based on a scale value of color or brightness constituting the blocking object being greater than or equal to a threshold value, and (ii) based on the first information and the second information, the detection of the at least one moving object may be performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area.

[0146] Additionally or alternatively, (i) based on the fact that the proportion of the first blocking area among the areas of the second moving object included in the second area is greater than or equal to a threshold value, and (ii) based on the first information and the second information, the detection of the at least one moving object may be performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area.

[0147] Additionally or alternatively, at least one candidate blocking object comprises infrastructure including at least one of a traffic sign, a traffic sign, or a road marking, and infrastructure users may be excluded.

[0148] The proposed method can be applied to devices according to various embodiments of the present disclosure. First, the memory (104) of the first device (100) may have instructions recorded thereon that cause the first device (e.g., the processor (102), the transceiver (106)) to perform operations based on being executed by the processor (102). For example, the operations may include: obtaining a message including information about a blocking region associated with at least one candidate blocking object; generating first information about a first blocking object and second information about a filling region associated with the first blocking object based on the information about the blocking region associated with the at least one candidate blocking object and a first region associated with a first time; and / or performing detection of at least one moving object within the second region associated with a second time; , wherein the detection of the at least one moving object may be performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

[0149] In one embodiment, a first device for performing wireless communication is provided. The first device may include at least one transceiver; at least one processor; and at least one memory executably connected to the at least one processor and storing instructions that cause the first device to perform operations based on being executed by the at least one processor. For example, the operations may include: obtaining a message including information regarding a blocking region associated with at least one candidate blocking object; generating first information regarding a first blocking object and second information regarding a filling region associated with the first blocking object based on the information regarding the blocking region associated with the at least one candidate blocking object and a first region associated with a first time; and / or performing detection of at least one moving object within the second region associated with a second time; , wherein the detection of the at least one moving object may be performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

[0150] In one embodiment, a processing device adapted to control a first device is provided. The processing device may include at least one processor; and at least one memory executable to the at least one processor and having instructions recorded thereon, the instructions being executed by the at least one processor to cause the first device to perform operations. For example, the operations may include: obtaining a message including information regarding a blocking region associated with at least one candidate blocking object; generating first information regarding a first blocking object and second information regarding a filling region associated with the first blocking object based on the information regarding the blocking region associated with the at least one candidate blocking object and a first region associated with a first time; and / or performing detection of at least one moving object within the second region associated with a second time. , wherein the detection of the at least one moving object may be performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

[0151] In one embodiment, a non-transitory computer-readable storage medium having instructions recorded thereon is provided. The instructions, when executed, may cause a first device to perform operations. For example, the operations may include: obtaining a message including information regarding a blocking region associated with at least one candidate blocking object; generating first information regarding a first blocking object and second information regarding a filling region associated with the first blocking object based on the information regarding the blocking region associated with the at least one candidate blocking object and a first region associated with a first time; and / or performing detection of at least one moving object within the second region associated with a second time. , wherein the detection of the at least one moving object may be performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

[0152] FIG. 14 illustrates a method performed by a second device according to an embodiment of the present disclosure. The embodiment of FIG. 14 may be combined with various embodiments of the present disclosure.

[0153] Referring to FIG. 14, in step S1410, for example, the second device may receive an object recognition message related to at least one detected moving object. In step S1420, for example, the second device may generate information regarding an estimation of a collision risk related to the at least one detected moving object based on the object recognition message. For example, a message including information regarding a blocking region related to at least one candidate blocking object may be obtained. For example, based on the information regarding the blocking region related to the at least one candidate blocking object and a first region related to a first time, first information regarding the first blocking object and second information regarding a filling region related to the first blocking object may be generated. For example, detection of the at least one moving object may be performed within the second region related to a second time. For example, the detection of the at least one moving object may be performed within a second area in which the first blocking area related to the first blocking object is replaced with the filling area among the second areas with respect to the second time, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

[0154] Additionally or alternatively, the message may include a collective perception message (CPM).

[0155] Additionally or alternatively, the information about the blocking area may include information relating to the position of at least one point representing the blocking area.

[0156] Additionally or alternatively, the at least one point representing the blocking area may include at least one of a center point of a zone corresponding to the blocking area, a center point of gravity of a bounding box for the blocking area, or a center point of mass of the blocking area.

[0157] Additionally or alternatively, the information about the blocking region associated with the at least one candidate blocking object may include at least one of information related to a region of interest, information related to a bounding box, information related to a vector map, and information related to a segmentation map.

[0158] Additionally or alternatively, the first information related to the first blocking object may be generated based on a difference between a first value processed with a scale for the first color for the first region and a reference value processed with a scale for the first color for a reference region.

[0159] Additionally or alternatively, the first information related to the blocking object may be generated based on the fact that the proportion of the area of ​​the first static object included in the first area among the areas of the first moving object included in the first area is greater than or equal to a threshold value.

[0160] Additionally or alternatively, the second information related to the filling area for the blocking object may be generated based on a movement area of ​​the second moving object included in the first area or a background area around the blocking area.

[0161] Additionally or alternatively, (i) based on a parameter value relating to a quality of detection of said at least one moving object being less than or equal to a threshold value, and (ii) based on said first information and said second information, said detection of said at least one moving object may be performed within a second area in which a first blocking area related to said first blocking object among said second areas relating to said second time is replaced with the filling area.

[0162] Additionally or alternatively, (i) based on a scale value of color or brightness constituting the blocking object being greater than or equal to a threshold value, and (ii) based on the first information and the second information, the detection of the at least one moving object may be performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area.

[0163] Additionally or alternatively, (i) based on the fact that the proportion of the first blocking area among the areas of the second moving object included in the second area is greater than or equal to a threshold value, and (ii) based on the first information and the second information, the detection of the at least one moving object may be performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area.

[0164] Additionally or alternatively, at least one candidate blocking object comprises infrastructure including at least one of a traffic sign, a traffic sign, or a road marking, and infrastructure users may be excluded.

[0165] The proposed method can be applied to devices according to various embodiments of the present disclosure. First, the memory (204) of the second device (200) may have instructions recorded therein that cause the second device (e.g., the processor (202), the transceiver (206)) to perform operations based on being executed by the processor (202). For example, the operations may include: the step of the second device (e.g., the processor (202), the transceiver (206)): receiving an object recognition message related to at least one detected moving object; And / or a step of generating information about prediction of collision risk related to the detected one moving object based on the object recognition message; wherein a message including information about a blocking area related to at least one candidate blocking object can be obtained, and based on the information about the blocking area related to the at least one candidate blocking object and the first area for a first time, first information about a first blocking object and second information about a filling area related to the first blocking object can be generated, and detection about the at least one moving object can be performed within the second area for a second time, and the detection about the at least one moving object can include: detecting, based on the first information about the first blocking object within the blocking area and the second information about the filling area related to the first blocking object, a first blocking object among the second area for a second time related to the first blocking object. The blocking area can be performed within a second area where the filling area is replaced.

[0166] In one embodiment, a second device is provided. The second device may include at least one transceiver; at least one processor; and at least one memory executably connected to the at least one processor and storing instructions that cause the second device to perform operations based on execution by the at least one processor. For example, the operations may include: receiving an object recognition message associated with at least one detected moving object; And / or a step of generating information about prediction of collision risk related to the detected one moving object based on the object recognition message; wherein a message including information about a blocking area related to at least one candidate blocking object can be obtained, and based on the information about the blocking area related to the at least one candidate blocking object and the first area for a first time, first information about a first blocking object and second information about a filling area related to the first blocking object can be generated, and detection about the at least one moving object can be performed within the second area for a second time, and the detection about the at least one moving object can include: detecting, based on the first information about the first blocking object within the blocking area and the second information about the filling area related to the first blocking object, a first blocking object among the second area for a second time related to the first blocking object. The blocking area can be performed within a second area where the filling area is replaced.

[0167] In one embodiment, a processing apparatus configured to control a second device is provided. The apparatus may include at least one processor; and at least one memory executable to the at least one processor, the memory having instructions recorded thereon, the instructions causing the second device to perform operations based on the instructions being executed by the at least one processor. For example, the operations may include: receiving an object recognition message associated with at least one detected moving object; And / or a step of generating information about prediction of collision risk related to the detected one moving object based on the object recognition message; wherein a message including information about a blocking area related to at least one candidate blocking object can be obtained, and based on the information about the blocking area related to the at least one candidate blocking object and the first area for a first time, first information about a first blocking object and second information about a filling area related to the first blocking object can be generated, and detection about the at least one moving object can be performed within the second area for a second time, and the detection about the at least one moving object can include: detecting, based on the first information about the first blocking object within the blocking area and the second information about the filling area related to the first blocking object, a first blocking object among the second area for a second time related to the first blocking object. The blocking area can be performed within a second area where the filling area is replaced.

[0168] In one embodiment, a non-transitory computer-readable storage medium having instructions recorded thereon is proposed. The instructions, when executed by at least one processor, cause a second device to perform operations. For example, the operations may include: receiving an object recognition message associated with at least one detected moving object; And / or a step of generating information about prediction of collision risk related to the detected one moving object based on the object recognition message; wherein a message including information about a blocking area related to at least one candidate blocking object can be obtained, and based on the information about the blocking area related to the at least one candidate blocking object and the first area for a first time, first information about a first blocking object and second information about a filling area related to the first blocking object can be generated, and detection about the at least one moving object can be performed within the second area for a second time, and the detection about the at least one moving object can include: detecting, based on the first information about the first blocking object within the blocking area and the second information about the filling area related to the first blocking object, a first blocking object among the second area for a second time related to the first blocking object. The blocking area can be performed within a second area where the filling area is replaced.

[0169] The various embodiments of the present disclosure may be combined with each other.

[0170] Below, a description is given of devices to which various embodiments of the present disclosure can be applied.

[0171] Although not limited thereto, the various descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed in this document may be applied to various fields requiring wireless communication / connectivity (e.g., 5G) between devices.

[0172] Hereinafter, more specific examples will be provided with reference to the drawings. In the drawings / descriptions below, the same drawing reference numerals may represent identical or corresponding hardware blocks, software blocks, or functional blocks, unless otherwise described.

[0173] FIG. 15 illustrates a communication system (1) according to one embodiment of the present disclosure. The embodiment of FIG. 15 can be combined with various embodiments of the present disclosure.

[0174] Referring to FIG. 15, a communication system (1) to which various embodiments of the present disclosure are applied includes a wireless device, a base station, and a network. Here, the wireless device refers to a device that performs communication using a wireless access technology (e.g., 5G NR (New RAT), LTE (Long Term Evolution)) and may be referred to as a communication / wireless / 5G device. Although not limited thereto, the wireless device may include a robot (100a), a vehicle (100b-1, 100b-2), an XR (eXtended Reality) device (100c), a hand-held device (100d), a home appliance (100e), an IoT (Internet of Things) device (100f), and an AI device / server (400). For example, the vehicle may include a vehicle equipped with a wireless communication function, an autonomous vehicle, a vehicle capable of performing vehicle-to-vehicle communication, etc. Here, the vehicle may include an Unmanned Aerial Vehicle (UAV) (e.g., a drone) and / or an Aerial Vehicle (AV) (e.g., an Advanced Air Mobility (AAM)). The XR device may include an Augmented Reality (AR) / Virtual Reality (VR) / Mixed Reality (MR) device, and may be implemented in the form of a Head-Mounted Device (HMD), a Head-Up Display (HUD) equipped in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance, a digital signage, a vehicle, a robot, etc. The portable device may include a smartphone, a smart pad, a wearable device (e.g., a smart watch, smart glasses), a computer (e.g., a laptop, etc.), etc. The home appliance may include a TV, a refrigerator, a washing machine, etc. The IoT device may include a sensor, a smart meter, etc. For example, a base station and a network may also be implemented as a wireless device, and a specific wireless device (200a) may operate as a base station / network node to other wireless devices.

[0175] Here, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification may include not only LTE, NR, and 6G, but also Narrowband Internet of Things for low-power communication. At this time, for example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology, and may be implemented with standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification may perform communication based on LTE-M technology. At this time, for example, LTE-M technology may be an example of LPWAN technology, and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology can be implemented by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the above-described names. Additionally or alternatively, the wireless communication technology implemented in the wireless devices (100a to 100f) of the present specification can include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN) considering low-power communication, and is not limited to the above-described names. For example, ZigBee technology can create personal area networks (PAN) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and can be called by various names.

[0176] Wireless devices (100a to 100f) can be connected to a network (300) via a base station (200). Artificial Intelligence (AI) technology can be applied to the wireless devices (100a to 100f), and the wireless devices (100a to 100f) can be connected to an AI server (400) via the network (300). The network (300) can be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, etc. The wireless devices (100a to 100f) can communicate with each other via the base station (200) / network (300), but can also communicate directly (e.g., sidelink communication) without going through the base station / network. For example, vehicles (100b-1, 100b-2) can communicate directly (e.g., V2V (Vehicle to Vehicle) / V2X (Vehicle to Everything) communication). In addition, IoT devices (e.g., sensors) can communicate directly with other IoT devices (e.g., sensors) or other wireless devices (100a to 100f).

[0177] Wireless communication / connection (150a, 150b, 150c) can be established between wireless devices (100a~100f) / base stations (200), and base stations (200) / base stations (200). Here, wireless communication / connection can be achieved through various wireless access technologies (e.g., 5G NR) such as uplink / downlink communication (150a), sidelink communication (150b) (or, D2D communication), and communication between base stations (150c) (e.g., relay, IAB (Integrated Access Backhaul). Through wireless communication / connection (150a, 150b, 150c), wireless devices and base stations / wireless devices, and base stations and base stations can transmit / receive wireless signals to each other. For example, wireless communication / connection (150a, 150b, 150c) can transmit / receive signals through various physical channels. To this end, at least some of various configuration information setting processes for transmitting / receiving wireless signals, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, resource mapping / demapping, etc.), and resource allocation processes can be performed based on various proposals of the present disclosure.

[0178] FIG. 16 illustrates a wireless device according to an embodiment of the present disclosure. The embodiment of FIG. 16 may be combined with various embodiments of the present disclosure.

[0179] Referring to FIG. 16, the first wireless device (100) and the second wireless device (200) can transmit and receive wireless signals via various wireless access technologies (e.g., LTE, NR). Here, {the first wireless device (100), the second wireless device (200)} can correspond to {the wireless device (100x), the base station (200)} and / or {the wireless device (100x), the wireless device (100x)} of FIG. 15.

[0180] A first wireless device (100) includes one or more processors (102) and one or more memories (104), and may further include one or more transceivers (106) and / or one or more antennas (108). The processor (102) controls the memories (104) and / or the transceivers (106), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (102) may process information in the memory (104) to generate first information / signal, and then transmit a wireless signal including the first information / signal via the transceiver (106). Furthermore, the processor (102) may receive a wireless signal including second information / signal via the transceiver (106), and then store information obtained from signal processing of the second information / signal in the memory (104). The memory (104) may be connected to the processor (102) and may store various information related to the operation of the processor (102). For example, the memory (104) may perform some or all of the processes controlled by the processor (102), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. Here, the processor (102) and the memory (104) may be part of a communication modem / circuit / chip designed to implement a wireless communication technology (e.g., LTE, NR). The transceiver (106) may be connected to the processor (102) and may transmit and / or receive wireless signals via one or more antennas (108). The transceiver (106) may include a transmitter and / or a receiver. The transceiver (106) may be used interchangeably with an RF (Radio Frequency) unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0181] A second wireless device (200) includes one or more processors (202), one or more memories (204), and may further include one or more transceivers (206) and / or one or more antennas (208). The processor (202) controls the memories (204) and / or the transceivers (206), and may be configured to implement the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document. For example, the processor (202) may process information in the memory (204) to generate third information / signals, and then transmit a wireless signal including the third information / signals via the transceivers (206). In addition, the processor (202) may receive a wireless signal including fourth information / signals via the transceivers (206), and then store information obtained from signal processing of the fourth information / signals in the memory (204). The memory (204) may be connected to the processor (202) and may store various information related to the operation of the processor (202). For example, the memory (204) may perform some or all of the processes controlled by the processor (202), or may store software code including commands for performing the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. Here, the processor (202) and the memory (204) may be part of a communication modem / circuit / chip designed to implement wireless communication technology (e.g., LTE, NR). The transceiver (206) may be connected to the processor (202) and may transmit and / or receive wireless signals via one or more antennas (208). The transceiver (206) may include a transmitter and / or a receiver. The transceiver (206) may be used interchangeably with an RF unit. In the present disclosure, a wireless device may also mean a communication modem / circuit / chip.

[0182] Hereinafter, the hardware elements of the wireless device (100, 200) will be described in more detail. Although not limited thereto, one or more protocol layers may be implemented by one or more processors (102, 202). For example, one or more processors (102, 202) may implement one or more layers (e.g., functional layers such as PHY, MAC, RLC, PDCP, RRC, SDAP). One or more processors (102, 202) may generate one or more Protocol Data Units (PDUs) and / or one or more Service Data Units (SDUs) according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. One or more processors (102, 202) may generate messages, control information, data, or information according to the descriptions, functions, procedures, proposals, methods, and / or operation flowcharts disclosed in this document. One or more processors (102, 202) can generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data or information according to the functions, procedures, proposals and / or methods disclosed herein, and provide the signals to one or more transceivers (106, 206). One or more processors (102, 202) can receive signals (e.g., baseband signals) from one or more transceivers (106, 206) and obtain PDUs, SDUs, messages, control information, data or information according to the descriptions, functions, procedures, proposals, methods and / or operational flowcharts disclosed herein.

[0183] One or more processors (102, 202) may be referred to as a controller, a microcontroller, a microprocessor, or a microcomputer. One or more processors (102, 202) may be implemented by hardware, firmware, software, or a combination thereof. For example, one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), one or more Digital Signal Processing Devices (DSPDs), one or more Programmable Logic Devices (PLDs), or one or more Field Programmable Gate Arrays (FPGAs) may be included in one or more processors (102, 202). The descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed in this document may be implemented using firmware or software, and the firmware or software may be implemented to include modules, procedures, functions, etc. The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software configured to perform one or more processors (102, 202) or stored in one or more memories (104, 204) and executed by one or more processors (102, 202). The descriptions, functions, procedures, suggestions, methods and / or operation flowcharts disclosed in this document may be implemented using firmware or software in the form of codes, instructions and / or sets of instructions.

[0184] One or more memories (104, 204) may be coupled to one or more processors (102, 202) and may store various forms of data, signals, messages, information, programs, codes, instructions, and / or commands. The one or more memories (104, 204) may be configured as ROM, RAM, EPROM, flash memory, hard drives, registers, cache memory, computer-readable storage media, and / or combinations thereof. The one or more memories (104, 204) may be located internally and / or externally to the one or more processors (102, 202). Additionally, the one or more memories (104, 204) may be coupled to the one or more processors (102, 202) via various technologies, such as wired or wireless connections.

[0185] One or more transceivers (106, 206) can transmit user data, control information, wireless signals / channels, etc., as mentioned in the methods and / or flowcharts of this document, to one or more other devices. One or more transceivers (106, 206) can receive user data, control information, wireless signals / channels, etc., as mentioned in the descriptions, functions, procedures, proposals, methods and / or flowcharts of this document, from one or more other devices. For example, one or more transceivers (106, 206) can be connected to one or more processors (102, 202) and can transmit and receive wireless signals. For example, one or more processors (102, 202) can control one or more transceivers (106, 206) to transmit user data, control information, or wireless signals to one or more other devices. Additionally, one or more processors (102, 202) may control one or more transceivers (106, 206) to receive user data, control information, or wireless signals from one or more other devices. Additionally, one or more transceivers (106, 206) may be coupled to one or more antennas (108, 208), and one or more transceivers (106, 206) may be configured to transmit and receive user data, control information, wireless signals / channels, or the like, as referred to in the descriptions, functions, procedures, proposals, methods, and / or operational flowcharts disclosed herein, via one or more antennas (108, 208). In this document, one or more antennas may be multiple physical antennas or multiple logical antennas (e.g., antenna ports). One or more transceivers (106, 206) can convert received user data, control information, wireless signals / channels, etc. from RF band signals to baseband signals in order to process the received user data, control information, wireless signals / channels, etc. using one or more processors (102, 202).One or more transceivers (106, 206) may convert user data, control information, wireless signals / channels, etc. processed by one or more processors (102, 202) from baseband signals to RF band signals. For this purpose, one or more transceivers (106, 206) may include an (analog) oscillator and / or filter.

[0186] FIG. 17 illustrates a signal processing circuit for a transmission signal according to an embodiment of the present disclosure. The embodiment of FIG. 17 can be combined with various embodiments of the present disclosure.

[0187] Referring to FIG. 17, the signal processing circuit (1000) may include a scrambler (1010), a modulator (1020), a layer mapper (1030), a precoder (1040), a resource mapper (1050), and a signal generator (1060). Although not limited thereto, the operations / functions of FIG. 17 may be performed in the processor (102, 202) and / or the transceiver (106, 206) of FIG. 16. The hardware elements of FIG. 17 may be implemented in the processor (102, 202) and / or the transceiver (106, 206) of FIG. 16. For example, blocks 1010 to 1060 may be implemented in the processor (102, 202) of FIG. 16. Additionally, blocks 1010 to 1050 may be implemented in the processor (102, 202) of FIG. 16, and block 1060 may be implemented in the transceiver (106, 206) of FIG. 16.

[0188] The codeword can be converted into a wireless signal through the signal processing circuit (1000) of FIG. 17. Here, the codeword is an encoded bit sequence of an information block. The information block can include a transport block (e.g., an UL-SCH transport block, a DL-SCH transport block). The wireless signal can be transmitted through various physical channels (e.g., a PUSCH or a PDSCH).

[0189] Specifically, the codeword can be converted into a bit sequence scrambled by a scrambler (1010). The scramble sequence used for scrambling is generated based on an initialization value, and the initialization value may include ID information of the wireless device, etc. The scrambled bit sequence can be modulated into a modulation symbol sequence by a modulator (1020). The modulation method may include pi / 2-BPSK (pi / 2-Binary Phase Shift Keying), m-PSK (m-Phase Shift Keying), m-QAM (m-Quadrature Amplitude Modulation), etc. The complex modulation symbol sequence can be mapped to one or more transmission layers by a layer mapper (1030). The modulation symbols of each transmission layer can be mapped to the corresponding antenna port(s) by a precoder (1040) (precoding). The output z of the precoder (1040) can be obtained by multiplying the output y of the layer mapper (1030) by a precoding matrix W of N*M. Here, N is the number of antenna ports, and M is the number of transmission layers. Here, the precoder (1040) can perform precoding after performing transform precoding (e.g., DFT transform) on complex modulation symbols. In addition, the precoder (1040) can perform precoding without performing transform precoding.

[0190] The resource mapper (1050) can map modulation symbols of each antenna port to time-frequency resources. The time-frequency resources can include multiple symbols (e.g., CP-OFDMA symbols, DFT-s-OFDMA symbols) in the time domain and multiple subcarriers in the frequency domain. The signal generator (1060) generates a wireless signal from the mapped modulation symbols, and the generated wireless signal can be transmitted to another device through each antenna. To this end, the signal generator (1060) can include an Inverse Fast Fourier Transform (IFFT) module, a Cyclic Prefix (CP) inserter, a Digital-to-Analog Converter (DAC), a frequency uplink converter, etc.

[0191] The signal processing process for receiving signals in a wireless device can be configured in reverse order of the signal processing process (1010 to 1060) of FIG. 17. For example, a wireless device (e.g., 100, 200 of FIG. 16) can receive wireless signals from the outside through an antenna port / transceiver. The received wireless signals can be converted into baseband signals through a signal restorer. For this purpose, the signal restorer can include a frequency downlink converter, an analog-to-digital converter (ADC), a CP remover, and a fast Fourier transform (FFT) module. Thereafter, the baseband signal can be restored to a codeword through a resource demapper process, a postcoding process, a demodulation process, and a descrambling process. The codewords can be restored to the original information blocks through decoding. Accordingly, a signal processing circuit (not shown) for a received signal may include a signal restorer, a resource de-mapper, a postcoder, a demodulator, a de-scrambler, and a decoder.

[0192] Figure 18 illustrates a wireless device according to an embodiment of the present disclosure. The wireless device may be implemented in various forms depending on the use case / service (see Figure 15). The embodiment of Figure 18 may be combined with various embodiments of the present disclosure.

[0193] Referring to FIG. 18, the wireless device (100, 200) corresponds to the wireless device (100, 200) of FIG. 16 and may be composed of various elements, components, units / units, and / or modules. For example, the wireless device (100, 200) may include a communication unit (110), a control unit (120), a memory unit (130), and additional elements (140). The communication unit may include a communication circuit (112) and a transceiver(s) (114). For example, the communication circuit (112) may include one or more processors (102, 202) and / or one or more memories (104, 204) of FIG. 16. For example, the transceiver(s) (114) may include one or more transceivers (106, 206) and / or one or more antennas (108, 208) of FIG. 16. The control unit (120) is electrically connected to the communication unit (110), the memory unit (130), and the additional elements (140) and controls the overall operation of the wireless device. For example, the control unit (120) may control the electrical / mechanical operation of the wireless device based on the program / code / command / information stored in the memory unit (130). In addition, the control unit (120) may transmit information stored in the memory unit (130) to an external device (e.g., another communication device) via a wireless / wired interface through the communication unit (110), or store information received from an external device (e.g., another communication device) via a wireless / wired interface in the memory unit (130).

[0194] The additional element (140) may be configured in various ways depending on the type of the wireless device. For example, the additional element (140) may include at least one of a power unit / battery, an input / output unit (I / O unit), a driving unit, and a computing unit. Although not limited thereto, the wireless device may be implemented in the form of a robot (Fig. 15, 100a), a vehicle (Fig. 15, 100b-1, 100b-2), an XR device (Fig. 15, 100c), a portable device (Fig. 15, 100d), a home appliance (Fig. 15, 100e), an IoT device (Fig. 15, 100f), a digital broadcasting terminal, a hologram device, a public safety device, an MTC device, a medical device, a fintech device (or a financial device), a security device, a climate / environmental device, an AI server / device (Fig. 15, 400), a base station (Fig. 15, 200), a network node, etc. Wireless devices may be mobile or stationary depending on the use / service.

[0195] In FIG. 18, various elements, components, units / parts, and / or modules within the wireless device (100, 200) may be interconnected entirely via a wired interface, or at least some may be wirelessly connected via a communication unit (110). For example, within the wireless device (100, 200), the control unit (120) and the communication unit (110) may be wired, and the control unit (120) and the first unit (e.g., 130, 140) may be wirelessly connected via the communication unit (110). In addition, each element, component, unit / part, and / or module within the wireless device (100, 200) may further include one or more elements. For example, the control unit (120) may be composed of one or more processor sets. For example, the control unit (120) may be composed of a set of a communication control processor, an application processor, an electronic control unit (ECU), a graphics processing processor, a memory control processor, etc. As another example, the memory unit (130) may be composed of a random access memory (RAM), a dynamic RAM (DRAM), a read only memory (ROM), a flash memory, a volatile memory, a non-volatile memory, and / or a combination thereof.

[0196] Below, the implementation example of Fig. 18 is described in more detail with reference to the drawings.

[0197] FIG. 19 illustrates a mobile device according to an embodiment of the present disclosure. The mobile device may include a smartphone, a smart pad, a wearable device (e.g., a smartwatch, smartglasses), or a portable computer (e.g., a laptop, etc.). The mobile device may be referred to as a Mobile Station (MS), a User Terminal (UT), a Mobile Subscriber Station (MSS), a Subscriber Station (SS), an Advanced Mobile Station (AMS), or a Wireless Terminal (WT). The embodiment of FIG. 19 may be combined with various embodiments of the present disclosure.

[0198] Referring to FIG. 19, the portable device (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a memory unit (130), a power supply unit (140a), an interface unit (140b), and an input / output unit (140c). The antenna unit (108) may be configured as a part of the communication unit (110). Blocks 110 to 130 / 140a to 140c correspond to blocks 110 to 130 / 140 of FIG. 18, respectively.

[0199] The communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with other wireless devices and base stations. The control unit (120) can control components of the mobile device (100) to perform various operations. The control unit (120) can include an AP (Application Processor). The memory unit (130) can store data / parameters / programs / codes / commands required for operating the mobile device (100). In addition, the memory unit (130) can store input / output data / information, etc. The power supply unit (140a) supplies power to the mobile device (100) and can include a wired / wireless charging circuit, a battery, etc. The interface unit (140b) can support connection between the mobile device (100) and other external devices. The interface unit (140b) can include various ports (e.g., audio input / output ports, video input / output ports) for connection with external devices. The input / output unit (140c) can input or output video information / signals, audio information / signals, data, and / or information input from a user. The input / output unit (140c) may include a camera, a microphone, a user input unit, a display unit (140d), a speaker, and / or a haptic module.

[0200] For example, in the case of data communication, the input / output unit (140c) obtains information / signals (e.g., touch, text, voice, image, video) input by the user, and the obtained information / signals can be stored in the memory unit (130). The communication unit (110) converts the information / signals stored in the memory into wireless signals, and can directly transmit the converted wireless signals to other wireless devices or to a base station. In addition, the communication unit (110) can receive wireless signals from other wireless devices or base stations, and then restore the received wireless signals to the original information / signals. The restored information / signals can be stored in the memory unit (130) and then output in various forms (e.g., text, voice, image, video, haptic) through the input / output unit (140c).

[0201] FIG. 20 illustrates a vehicle or autonomous vehicle according to one embodiment of the present disclosure. The vehicle or autonomous vehicle may be implemented as a mobile robot, a car, a train, a manned or unmanned aerial vehicle (AV), a ship, or the like. The embodiment of FIG. 20 may be combined with various embodiments of the present disclosure.

[0202] Referring to FIG. 20, a vehicle or autonomous vehicle (100) may include an antenna unit (108), a communication unit (110), a control unit (120), a driving unit (140a), a power supply unit (140b), a sensor unit (140c), and an autonomous driving unit (140d). The antenna unit (108) may be configured as a part of the communication unit (110). Blocks 110 / 130 / 140a to 140d correspond to blocks 110 / 130 / 140 of FIG. 18, respectively.

[0203] The communication unit (110) can transmit and receive signals (e.g., data, control signals, etc.) with external devices such as other vehicles, base stations (e.g., base stations, road side units, etc.), and servers. The control unit (120) can control elements of the vehicle or autonomous vehicle (100) to perform various operations. The control unit (120) can include an ECU (Electronic Control Unit). The drive unit (140a) can drive the vehicle or autonomous vehicle (100) on the ground. The drive unit (140a) can include an engine, a motor, a power train, wheels, brakes, a steering device, etc. The power supply unit (140b) supplies power to the vehicle or autonomous vehicle (100) and can include a wired / wireless charging circuit, a battery, etc. The sensor unit (140c) can obtain vehicle status, surrounding environment information, user information, etc. The sensor unit (140c) may include an IMU (inertial measurement unit) sensor, a collision sensor, a wheel sensor, a speed sensor, an incline sensor, a weight detection sensor, a heading sensor, a position module, a vehicle forward / backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor, a temperature sensor, a humidity sensor, an ultrasonic sensor, an illuminance sensor, a pedal position sensor, etc. The autonomous driving unit (140d) may implement a technology for maintaining a driving lane, a technology for automatically controlling speed such as adaptive cruise control, a technology for automatically driving along a set path, a technology for automatically setting a path and driving when a destination is set, etc.

[0204] For example, the communication unit (110) can receive map data, traffic information data, etc. from an external server. The autonomous driving unit (140d) can generate an autonomous driving route and driving plan based on the acquired data. The control unit (120) can control the drive unit (140a) so that the vehicle or autonomous vehicle (100) moves along the autonomous driving route according to the driving plan (e.g., speed / direction control). During autonomous driving, the communication unit (110) can irregularly / periodically acquire the latest traffic information data from an external server and can acquire surrounding traffic information data from surrounding vehicles. In addition, during autonomous driving, the sensor unit (140c) can acquire vehicle status and surrounding environment information. The autonomous driving unit (140d) can update the autonomous driving route and driving plan based on newly acquired data / information. The communication unit (110) can transmit information regarding the vehicle location, autonomous driving route, driving plan, etc. to the external server. External servers can predict traffic information data in advance using AI technology or other technologies based on information collected from vehicles or autonomous vehicles, and provide the predicted traffic information data to the vehicles or autonomous vehicles.

[0205] The claims set forth in this specification may be combined in various ways. For example, the technical features of the method claims of this specification may be combined and implemented as a device, and the technical features of the device claims of this specification may be combined and implemented as a method. Furthermore, the technical features of the method claims and the technical features of the device claims of this specification may be combined and implemented as a device, and the technical features of the method claims and the technical features of the device claims of this specification may be combined and implemented as a method.

Claims

1. In the method, Obtaining a message containing information about a blocking region associated with at least one candidate blocking object; A step of generating first information related to a first blocking object and second information related to a filling area related to the first blocking object based on the information about the blocking area related to the at least one candidate blocking object and the first area related to the first time; and A step of performing detection of at least one moving object within a second region with respect to a second time; comprising: A method wherein the detection of the at least one moving object is performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

2. In paragraph 1, A method wherein the above message includes a collective perception message (CPM).

3. In paragraph 1, A method wherein the information about the blocking area includes information related to the location of at least one point representing the blocking area.

4. In paragraph 3, A method wherein the at least one point representing the blocking area includes at least one of the center point of a zone corresponding to the blocking area, the center of gravity point of a bounding box for the blocking area, or the center of mass point of the blocking area.

5. In paragraph 1, A method according to claim 1, wherein the information about the blocking region associated with the at least one candidate blocking object comprises at least one of information related to a region of interest, information related to a bounding box, information related to a vector map, and information related to a segmentation map.

6. In paragraph 1, A method wherein the first information related to the first blocking object is generated based on the difference between a first value processed with a scale for the first color for the first region and a reference value processed with a scale for the first color for the reference region.

7. In paragraph 1, A method in which the first information related to the blocking object is generated based on the fact that, among the areas of the first moving object included in the first area, the area occupied by the first static object included in the first area is greater than or equal to a threshold value.

8. In paragraph 7, A method in which the second information related to the filling area for the blocking object is generated based on a movement area of ​​the second moving object included in the first area or a background area around the blocking area.

9. In paragraph 1, (i) based on a parameter value relating to a quality of detection of said at least one moving object being less than or equal to a threshold value, and (ii) based on said first information and said second information, said detection of said at least one moving object is performed within a second area in which a first blocking area related to said first blocking object among said second areas relating to said second time is replaced with the filling area.

10. In paragraph 1, (i) based on a scale value of color or brightness constituting the blocking object being greater than or equal to a threshold value, and (ii) based on the first information and the second information, the detection of the at least one moving object is performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area.

11. In paragraph 1, (i) a method wherein, based on the fact that a proportion of the first blocking area among the areas of the second moving object included in the second area is greater than or equal to a threshold value, and (ii) based on the first information and the second information, the detection of the at least one moving object is performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area.

12. In paragraph 1, A method wherein at least one candidate blocking object comprises infrastructure including at least one of a traffic sign, a traffic sign, or a road marking, and wherein infrastructure users are excluded.

13. In the first device, At least one transmitter / receiver; at least one processor; and At least one memory executable connected to said at least one processor and having instructions recorded thereon that cause said first device to perform operations based on being executed by said at least one processor, said operations comprising: Obtaining a message containing information about a blocking region associated with at least one candidate blocking object; A step of generating first information related to a first blocking object and second information related to a filling area related to the first blocking object based on the information about the blocking area related to the at least one candidate blocking object and the first area related to the first time; and A step of performing detection of at least one moving object within a second region with respect to a second time; comprising: A first device, wherein the detection of the at least one moving object is performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

14. In a processing device adapted to control a first device, The above processing device, at least one processor; and At least one memory executable connected to said at least one processor and having instructions recorded thereon that cause said first device to perform operations based on being executed by said at least one processor, said operations comprising: Obtaining a message containing information about a blocking region associated with at least one candidate blocking object; A step of generating first information related to a first blocking object and second information related to a filling area related to the first blocking object based on the information about the blocking area related to the at least one candidate blocking object and the first area related to the first time; and A step of performing detection of at least one moving object within a second region with respect to a second time; comprising: A processing device, wherein the detection of the at least one moving object is performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

15. A non-transitory computer-readable storage medium that records commands, The above instructions, when executed, cause the first device to perform actions, wherein the actions are: Obtaining a message containing information about a blocking region associated with at least one candidate blocking object; A step of generating first information related to a first blocking object and second information related to a filling area related to the first blocking object based on the information about the blocking area related to the at least one candidate blocking object and the first area related to the first time; and A step of performing detection of at least one moving object within a second region with respect to a second time; comprising: A non-transitory computer-readable storage medium, wherein the detection of the at least one moving object is performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

16. In a method performed by a second device, receiving an object recognition message associated with at least one detected moving object; and A step of generating information regarding prediction of collision risk related to the detected moving object based on the object recognition message; including; A message containing information about a blocking region associated with at least one candidate blocking object is obtained, Based on the information about the blocking area associated with the at least one candidate blocking object and the first area associated with the first time, first information associated with the first blocking object and second information associated with the filling area associated with the first blocking object are generated, and Detection of at least one moving object is performed within a second region regarding a second time, and A method wherein the detection of the at least one moving object is performed within a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

17. In the second device, At least one transmitter / receiver; at least one processor; and At least one memory executable connected to said at least one processor and having instructions recorded thereon that cause said second device to perform operations based on being executed by said at least one processor, said operations comprising: receiving an object recognition message associated with at least one detected moving object; and A step of generating information regarding prediction of collision risk related to the detected moving object based on the object recognition message; including; A message containing information about a blocking region associated with at least one candidate blocking object is obtained, Based on the information about the blocking area associated with the at least one candidate blocking object and the first area associated with the first time, first information associated with the first blocking object and second information associated with the filling area associated with the first blocking object are generated, and Detection of at least one moving object is performed within a second region regarding a second time, and A second device, wherein the detection of the at least one moving object is performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

18. In a processing apparatus adapted to control a second device, the processing apparatus comprises: at least one processor; and At least one memory executable connected to said at least one processor and having instructions recorded thereon that cause said second device to perform operations based on being executed by said at least one processor, said operations comprising: receiving an object recognition message associated with at least one detected moving object; and A step of generating information regarding prediction of collision risk related to the detected moving object based on the object recognition message; including; A message containing information about a blocking region associated with at least one candidate blocking object is obtained, Based on the information about the blocking area associated with the at least one candidate blocking object and the first area associated with the first time, first information associated with the first blocking object and second information associated with the filling area associated with the first blocking object are generated, and Detection of at least one moving object is performed within a second region regarding a second time, and A processing device, wherein the detection of the at least one moving object is performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

19. A non-transitory computer-readable storage medium that records commands, The above instructions, when executed, cause the second device to perform actions, wherein the actions are: receiving an object recognition message associated with at least one detected moving object; and A step of generating information regarding prediction of collision risk related to the detected moving object based on the object recognition message; including; A message containing information about a blocking region associated with at least one candidate blocking object is obtained, Based on the information about the blocking area associated with the at least one candidate blocking object and the first area associated with the first time, first information associated with the first blocking object and second information associated with the filling area associated with the first blocking object are generated, and Detection of at least one moving object is performed within a second region regarding a second time, and A non-transitory computer-readable storage medium, wherein the detection of the at least one moving object is performed in a second area in which the first blocking area related to the first blocking object among the second areas with respect to the second time is replaced with the filling area, based on first information related to the first blocking object within the blocking area and second information related to the filling area related to the first blocking object.

Images