Signal processing device and vehicle display device comprising same

Abstract

A signal processing device and a vehicle display device comprising same, according to one embodiment of the present disclosure, comprise: a network interface for receiving sensor data from zonal signal processing devices; a processor for processing at least one portion of the sensor data; and a storage interface for transmitting another portion of the sensor data to a storage device, wherein the processor processes first sensor data of the sensor data, and controls that second sensor data of the sensor data is transmitted to the storage device. Therefore, the data can be efficiently processed.

Description

Signal processing device and vehicle display device having the same

[0001] The present disclosure relates to a signal processing device and a vehicle display device having the same, and more particularly, to a signal processing device capable of efficiently processing data and a vehicle display device having the same.

[0002] A vehicle is a device that allows the user to move in the desired direction. A representative example is an automobile.

[0003] Meanwhile, for the convenience of vehicle users, a vehicle signal processing device is installed inside the vehicle.

[0004] The signal processing device inside the vehicle receives and processes sensor data from various sensor devices inside the vehicle.

[0005] Meanwhile, the types and number of sensors installed in vehicles are exploding due to advanced driver assistance systems (ADAS) and autonomous driving, and the amount of data generated from vehicles is also exploding.

[0006] For processing such data, multiple signal processing devices are being used, and as communication between multiple signal processing devices increases, the load on the communication channel is increasing.

[0007] Accordingly, a method for efficiently processing or sharing data between signal processing devices is needed.

[0008] The problem that the present disclosure seeks to solve is to provide a signal processing device capable of efficiently processing data and a vehicle display device equipped with the same.

[0009] Another problem that the present disclosure seeks to solve is to provide a signal processing device capable of prioritizing time-critical data among sensor data and a vehicle display device equipped with the same.

[0010] Another problem that the present disclosure seeks to solve is to provide a signal processing device capable of efficiently processing data according to the resources of a plurality of signal processing devices and a vehicle display device having the same.

[0011] According to one embodiment of the present disclosure for solving the above technical problem, a signal processing device and a vehicle display device including the same include a network interface for receiving sensor data from a region signal processing device, a processor for processing at least a portion of the sensor data, and a storage interface for transmitting another portion of the sensor data to a storage device, wherein the processor processes first sensor data among the sensor data and controls second sensor data among the sensor data to be transmitted to the storage device.

[0012] Meanwhile, the processor can process time-critical data, which is first sensor data among the sensor data, and control non-time-critical data, which is second sensor data among the sensor data, to be transmitted to a storage device.

[0013] Meanwhile, the storage interface can transmit the second sensor data to the shared namespace of the storage device.

[0014] Meanwhile, the processor can run a distributed lock manager for controlling the storage interface.

[0015] Meanwhile, the processor may receive a first data processing pipeline for processing first sensor data.

[0016] Meanwhile, the processor may receive a second data processing pipeline for transmission of the second sensor data to a storage device.

[0017] Meanwhile, the processor may control some of the elements among the plurality of elements in the first data processing pipeline for processing the first sensor data based on the resources of the signal processing device or the resources of another signal processing device to be processed, and other some of the elements among the plurality of elements in the first data processing pipeline to be processed in another signal processing device.

[0018] Meanwhile, the processor may allocate the first data processing pipeline based on the resources of the signal processing device or the resources of another signal processing device.

[0019] Meanwhile, the processor may assign the first data processing pipeline for processing the first sensor data to another signal processing device based on the resources of the signal processing device or the resources of another signal processing device.

[0020] Meanwhile, the first data processing pipeline may have a first data processing queue for input and a second data processing queue for output.

[0021] Meanwhile, the first data processing queue or the second data processing queue can receive or transmit sensor data and metadata through the vehicle network.

[0022] Meanwhile, the first data processing queue or the second data processing queue can transmit sensor data through namespace sharing and transmit metadata through the vehicle network.

[0023] Meanwhile, a signal processing device and a vehicle display device including the same according to one embodiment of the present disclosure may further include a storage device.

[0024] Meanwhile, the processor can control the transmission path of time-critical data, which is the first sensor data among the sensor data, to be variable based on the utilization rate of the vehicle network connected to the network interface.

[0025] Meanwhile, the processor may vary the processing of elements within the first data processing pipeline based on the first sensor data based on the utilization of the vehicle network connected to the network interface.

[0026] Meanwhile, the processor controls the second sensor data among the sensor data to be transmitted to a shared namespace within the storage device when there is a delay in processing the second sensor data, and when the utilization rate of resources for processing the second sensor data is below a predetermined value, the second sensor data can be received from the storage device and processed.

[0027] Meanwhile, the processor can control to temporarily suspend processing of the second data processing pipeline based on the second sensor data when there is a delay in processing of the first data processing pipeline based on the first sensor data.

[0028] Meanwhile, the processor may check resource utilization at regular intervals after pausing processing of the second data processing pipeline based on the second sensor data, and may resume processing of the second data processing pipeline based on the second sensor data if the resource utilization is below a predetermined value.

[0029] Meanwhile, the processor may process the second data processing pipeline based on the second sensor data if the capacity of the data processing queue is greater than or equal to a reference value after temporarily suspending the processing of the second data processing pipeline based on the second sensor data.

[0030] Meanwhile, the first sensor data may include lidar data or radar data, and the second sensor data may include black box data.

[0031] A signal processing device and a vehicle display device including the same according to one embodiment of the present disclosure include a network interface for receiving sensor data from a region signal processing device, a processor for processing at least a portion of the sensor data, and a storage interface for transmitting another portion of the sensor data to a storage device, wherein the processor processes first sensor data among the sensor data and controls second sensor data among the sensor data to be transmitted to the storage device. Accordingly, data can be processed efficiently.

[0032] Meanwhile, the processor can process time-critical data, which is the first sensor data among the sensor data, and control the transmission of non-time-critical data, which is the second sensor data among the sensor data, to a storage device. This enables efficient data processing.

[0033] Meanwhile, the storage interface can transmit secondary sensor data to the storage device's shared namespace, enabling efficient data processing.

[0034] Meanwhile, the processor can run a distributed lock manager to control the storage interface, enabling efficient data processing.

[0035] Meanwhile, the processor can receive a first data processing pipeline for processing the first sensor data. This enables efficient data processing.

[0036] Meanwhile, the processor can receive a second data processing pipeline for transmitting the second sensor data to a storage device, thereby enabling efficient data processing.

[0037] Meanwhile, the processor may control some of the elements within the first data processing pipeline for processing the first sensor data based on the resources of the signal processing device or the resources of another signal processing device, and other elements within the first data processing pipeline to be processed by another signal processing device. Accordingly, data can be efficiently processed.

[0038] Meanwhile, the processor can allocate the first data processing pipeline based on the resources of the signal processing device or other signal processing devices, thereby enabling efficient data processing.

[0039] Meanwhile, the processor can assign the first data processing pipeline for processing the first sensor data to another signal processing device based on the resources of the signal processing device or another signal processing device. This enables efficient data processing.

[0040] Meanwhile, the first data processing pipeline may include a first data processing queue for input and a second data processing queue for output. This allows for efficient data processing.

[0041] Meanwhile, the first data processing queue or the second data processing queue can receive or transmit sensor data and metadata via the vehicle network. This enables efficient data processing.

[0042] Meanwhile, the first data processing queue or the second data processing queue can transmit sensor data through namespace sharing and metadata over the vehicle network. This enables efficient data processing.

[0043] Meanwhile, the signal processing device and vehicle display device including the same according to one embodiment of the present disclosure may further include a storage device. Accordingly, data can be processed efficiently.

[0044] Meanwhile, the processor can control the transmission path of time-critical data, the first sensor data, to vary based on the utilization rate of the vehicle network connected to the network interface. This allows for efficient data processing.

[0045] Meanwhile, the processor can vary the processing of elements within the first data processing pipeline based on the first sensor data based on the utilization of the vehicle network connected to the network interface. This enables efficient data processing.

[0046] Meanwhile, the processor controls the transmission of second sensor data to a shared namespace within the storage device when there is a delay in processing the second sensor data among the sensor data, and if the utilization rate of resources for processing the second sensor data is below a predetermined value, the second sensor data can be received from the storage device and processed. Accordingly, data can be processed efficiently.

[0047] Meanwhile, the processor can control the processing of the second data processing pipeline based on the second sensor data to be temporarily suspended when the processing of the first data processing pipeline based on the first sensor data is delayed. This enables efficient data processing.

[0048] Meanwhile, the processor may, after pausing the processing of the second data processing pipeline based on the second sensor data, check the resource utilization at regular intervals and, if the resource utilization is below a predetermined value, resume the processing of the second data processing pipeline based on the second sensor data. This enables efficient data processing.

[0049] Meanwhile, the processor can process the second data processing pipeline based on the second sensor data if the capacity of the data processing queue exceeds a threshold after temporarily suspending the processing of the second data processing pipeline based on the second sensor data. This enables efficient data processing.

[0050] Meanwhile, the first sensor data may include lidar data or radar data, and the second sensor data may include black box data. This allows for efficient data processing.

[0051] Figure 1 is a drawing showing an example of the exterior and interior of a vehicle.

[0052] Figures 2a to 2c are drawings illustrating various architectures of a vehicle communication gateway.

[0053] Figure 3a is a drawing showing an example of the arrangement of a vehicle display device inside a vehicle.

[0054] Figure 3b is a drawing showing another example of the arrangement of a vehicle display device inside a vehicle.

[0055] Fig. 4 is an example of an internal block diagram of the vehicle display device of Fig. 3b.

[0056] FIGS. 5A to 5D are drawings showing various examples of vehicle display devices.

[0057] FIG. 6 is an example of a block diagram of a vehicle display device according to an embodiment of the present disclosure.

[0058] FIG. 7 is another example of a block diagram of a vehicle display device according to an embodiment of the present disclosure.

[0059] FIG. 8 is an example of an internal block diagram of a signal processing device according to an embodiment of the present disclosure.

[0060] Figures 9a to 19b are drawings referred to in the description of Figure 8.

[0061] Hereinafter, the present disclosure will be described in more detail with reference to the drawings.

[0062] The suffixes "module" and "part" used in the following description are given solely for the convenience of writing this specification and do not impart any particularly significant meaning or role to the components themselves. Therefore, the terms "module" and "part" may be used interchangeably.

[0063] Figure 1 is a drawing showing an example of the exterior and interior of a vehicle.

[0064] Referring to the drawing, the vehicle (200) is operated by a plurality of wheels (103FR, 103FL, 103RL, etc.) that rotate by a power source and a steering wheel (150) for controlling the direction of travel of the vehicle (200).

[0065] Meanwhile, the vehicle (200) may further be equipped with a camera (195) for capturing images of the front of the vehicle.

[0066] Meanwhile, the vehicle (200) may be equipped with multiple displays (180a, 180b) for displaying images, information, etc. inside.

[0067] In Fig. 1, a cluster display (180a) and an AVN (Audio Video Navigation) display (180b) are exemplified as multiple displays (180a, 180b). In addition, a HUD (Head Up Display) is also possible.

[0068] Meanwhile, the AVN (Audio Video Navigation) display (180b) may also be named a center information display.

[0069] Meanwhile, the vehicle (200) described in this specification may be a concept that includes all of a vehicle equipped with an engine as a power source, a hybrid vehicle equipped with an engine and an electric motor as a power source, and an electric vehicle equipped with an electric motor as a power source.

[0070] Figures 2a to 2c are drawings illustrating various architectures of a vehicle communication gateway.

[0071] First, FIG. 2a is a drawing illustrating the first architecture of a vehicle communication gateway.

[0072] Referring to the drawing, the first architecture (300a) can correspond to a zone-based architecture.

[0073] Accordingly, sensor devices and processors inside the vehicle may be placed in each of the plurality of zones (Z1 to Z4), and a signal processing device (170a) including a vehicle communication gateway (GWDa) may be placed in the central area of ​​the plurality of zones (Z1 to Z4).

[0074] Meanwhile, the signal processing device (170a) may further include, in addition to the vehicle communication gateway (GWDa), an autonomous driving control module (ACC), a cockpit control module (CPG), etc.

[0075] The vehicle communication gateway (GWDa) within the signal processing device (170a) may be an HPC (High Performance Computing) gateway.

[0076] That is, the signal processing device (170a) of FIG. 2a is an integrated HPC and can exchange data with an external communication module (not shown) or a processor (not shown) within a plurality of zones (Z1 to Z4).

[0077] FIG. 2b is a diagram illustrating a second architecture of a vehicle communication gateway.

[0078] Referring to the drawing, the second architecture (300b) can correspond to a domain-integrated architecture.

[0079] Accordingly, a body chassis control module (BSG), a power control module (PTG), an ADAS control module (ADG), and a cockpit control module (CPG) are connected in parallel to the gateway (GWDb), and multiple processors (ECUs) can be electrically connected to each module (BSG, PTG, ADG, CPG).

[0080] Meanwhile, each processor (ECU) can be integrated and connected to a gateway (GWDb).

[0081] Meanwhile, the signal processing device (170) including the gateway (GWDb) of FIG. 2b operates as a domain-integrated signal processing device.

[0082] Figure 2c is a diagram illustrating the third architecture of a vehicle communication gateway.

[0083] Referring to the drawing, the third architecture (300c) can correspond to a distributed architecture.

[0084] Accordingly, a body chassis control module (BSG), a power control module (PTG), an ADAS control module (ADG), and a cockpit control module (CPG) are connected in parallel to the gateway (GWDc), and in particular, multiple processors (ECUs) within each control module can be connected in parallel to the gateway (GWDb).

[0085] Compared to Fig. 2b, the third architecture differs in that each processor (ECU) is directly connected to the gateway (GWDb) without being connected to other modules.

[0086] Meanwhile, the signal processing device (170) including the gateway (GWDc) of FIG. 2c operates as a distributed signal processing device.

[0087] Figure 3a is a drawing showing an example of the arrangement of a vehicle display device inside a vehicle.

[0088] Referring to the drawing, the interior of the vehicle may be equipped with a cluster display (180a), an AVN (Audio Video Navigation) display (180b), a rear seat entertainment display (180c, 180d), a room mirror display (not shown), etc.

[0089] Figure 3b is a drawing showing another example of the arrangement of a vehicle display device inside a vehicle.

[0090] A vehicle display device (100) according to an embodiment of the present disclosure may include a plurality of displays (180a to 180b), and a signal processing device (170) that performs signal processing for displaying images, information, etc. on the plurality of displays (180a to 180b).

[0091] Among the plurality of displays (180a to 180b), the first display (180a) may be a cluster display (180a) for displaying driving status, operation information, etc., and the second display (180b) may be an AVN (Audio Video Navigation) display (180b) for displaying vehicle driving information, a navigation map, various entertainment information, or images.

[0092] The signal processing device (170) has a processor (175) therein and can execute a first virtual machine to a third virtual machine (not shown) on a hypervisor (not shown) within the processor (175).

[0093] A second virtual machine (not shown) can operate for the first display (180a), and a third virtual machine (not shown) can operate for the second display (180b).

[0094] Meanwhile, the first virtual machine (not shown) within the processor (175) can control the shared memory (508) based on the hypervisor (505) to be set for the same data transmission to the second virtual machine (not shown) and the third virtual machine (not shown). Accordingly, the same information or the same image can be displayed in synchronization on the first display (180a) and the second display (180b) within the vehicle.

[0095] Meanwhile, the first virtual machine (not shown) within the processor (175) shares at least a portion of data with the second virtual machine (not shown) and the third virtual machine (not shown) for data sharing processing. Accordingly, data can be shared and processed among multiple virtual machines for multiple displays within the vehicle.

[0096] Meanwhile, a first virtual machine (not shown) within a processor (175) may receive and process vehicle wheel speed sensor data, and transmit the processed wheel speed sensor data to at least one of a second virtual machine (not shown) or a third virtual machine (not shown). Accordingly, the vehicle wheel speed sensor data may be shared with at least one virtual machine.

[0097] Meanwhile, the vehicle display device (100) according to the embodiment of the present disclosure may further include a rear seat entertainment display (180c) for displaying driving status information, simple navigation information, various entertainment information, or images.

[0098] The signal processing device (170) can control the RSE display (180c) by executing a fourth virtual machine (not shown) in addition to the first virtual machine to the third virtual machine (not shown) on a hypervisor (not shown) within the processor (175).

[0099] Accordingly, it is possible to control various displays (180a to 180c) using one signal processing device (170).

[0100] Meanwhile, some of the multiple displays (180a~180c) may operate under Linux OS, while others may operate under Web OS.

[0101] The signal processing device (170) according to the embodiment of the present disclosure can control the same information or the same image to be displayed in synchronization on displays (180a to 180c) operating under various operating systems (OS).

[0102] Meanwhile, in FIG. 3b, a vehicle speed indicator (212a) and a vehicle interior temperature indicator (213a) are displayed on a first display (180a), a home screen (222) including a plurality of applications and a vehicle speed indicator (212b) and a vehicle interior temperature indicator (213b) are displayed on a second display (180b), and a second home screen (222b) including a plurality of applications and a vehicle interior temperature indicator (213c) are displayed on a third display (180c).

[0103] Fig. 4 is an example of an internal block diagram of the vehicle display device of Fig. 3b.

[0104] Referring to the drawings, a vehicle display device (100) according to an embodiment of the present disclosure may include an input unit (110), a communication unit (120) for communication with an external device, a plurality of communication modules (EMa to EMd) for internal communication, a memory (140), a signal processing unit (170), a plurality of displays (180a to 180c), an audio output unit (185), and a power supply unit (190).

[0105] A plurality of communication modules (EMa to EMd) can be arranged, for example, in a plurality of zones (Z1 to Z4) of FIG. 2a, respectively.

[0106] Meanwhile, the signal processing device (170) may have a communication switch (736b) for data communication with each communication module (EM1 to EM4) inside.

[0107] Each communication module (EM1 to EM4) can perform data communication with multiple sensor devices (SN) or ECUs (770) or area signal processing devices (170Z).

[0108] Meanwhile, the plurality of sensor devices (SN) may include a camera (195), a lidar (196), a radar (197), or a position sensor (198).

[0109] The input unit (110) may be equipped with physical buttons, pads, etc. for button input, touch input, etc.

[0110] Meanwhile, the input unit (110) may be equipped with a microphone (not shown) for user voice input.

[0111] The communication unit (120) can exchange data wirelessly with a mobile terminal (800) or a server (900).

[0112] In particular, the communication unit (120) can wirelessly exchange data with the vehicle driver's mobile terminal. Various data communication methods are possible, such as Bluetooth, WiFi, WiFi Direct, and APiX.

[0113] The communication unit (120) can receive weather information, road traffic information, for example, TPEG (Transport Protocol Expert Group) information, from a mobile terminal (800) or a server (900). To this end, the communication unit (120) may be equipped with a mobile communication module (not shown).

[0114] A plurality of communication modules (EM1 to EM4) can receive sensor data, etc. from an ECU (770), a sensor device (SN), or an area signal processing device (170Z), and transmit the received sensor data to the signal processing device (170).

[0115] Here, the sensor data may include at least one of vehicle direction data, vehicle location data (GPS data), vehicle angle data, vehicle speed data, vehicle acceleration data, vehicle inclination data, vehicle forward / backward data, battery data, fuel data, tire data, vehicle lamp data, vehicle interior temperature data, and vehicle interior humidity data.

[0116] Such sensor data can be obtained from a heading sensor, a yaw sensor, a gyro sensor, a position module, a vehicle forward / backward sensor, a wheel sensor, a vehicle speed sensor, a body tilt detection sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor by steering wheel rotation, a vehicle interior temperature sensor, a vehicle interior humidity sensor, etc.

[0117] Meanwhile, the position module may include a GPS module or a position sensor (198) for receiving GPS information.

[0118] Meanwhile, at least one of the plurality of communication modules (EM1 to EM4) can transmit location information data sensed by a GPS module or location sensor (198) to a signal processing device (170).

[0119] Meanwhile, at least one of the plurality of communication modules (EM1 to EM4) can receive vehicle front image data, vehicle side image data, vehicle rear image data, vehicle surrounding obstacle distance information, etc. from a camera (195), lidar (196), radar (197), etc., and transmit the received information to a signal processing device (170).

[0120] The memory (140) can store various data for the overall operation of the vehicle display device (100), such as a program for processing or controlling the signal processing device (170).

[0121] For example, the memory (140) may store data regarding a hypervisor, a first virtual machine, a third virtual machine, or the like, for execution within the processor (175).

[0122] The audio output unit (185) converts an electric signal from the signal processing device (170) into an audio signal and outputs it. For this purpose, a speaker or the like may be provided.

[0123] The power supply unit (190) can supply power required for the operation of each component under the control of the signal processing device (170). In particular, the power supply unit (190) can receive power from a battery or the like inside the vehicle.

[0124] The signal processing device (170) controls the overall operation of each unit within the vehicle display device (100).

[0125] For example, the signal processing device (170) may include a processor (175) that performs signal processing for a vehicle display (180a, 180b).

[0126] The processor (175) can execute a first virtual machine to a third virtual machine (not shown) on a hypervisor (not shown) within the processor (175).

[0127] Among the first virtual machine to the third virtual machine (not shown), the first virtual machine (not shown) may be named a server virtual machine (Server Virtual Maschine), and the second virtual machine to the third virtual machine (not shown) may be named a guest virtual machine (Guest Virtual Maschine).

[0128] For example, a first virtual machine (not shown) within a processor (175) may receive, process, or output sensor data from a plurality of sensor devices, such as vehicle sensor data, location information data, camera image data, audio data, or touch input data.

[0129] In this way, by performing most of the data processing in the first virtual machine (not shown), data sharing in a 1:N manner becomes possible.

[0130] As another example, a first virtual machine (not shown) can directly receive and process CAN data, Ethernet data, audio data, radio data, USB data, and wireless communication data for a second virtual machine or a third virtual machine (not shown).

[0131] And, the first virtual machine (not shown) can transmit processed data to the second virtual machine or the third virtual machine (not shown).

[0132] Accordingly, among the first virtual machine to the third virtual machine (not shown), only the first virtual machine (not shown) receives sensor data, communication data, or external input data from multiple sensor devices and performs signal processing, thereby reducing the signal processing burden on other virtual machines, enabling 1:N data communication, and enabling synchronization when sharing data.

[0133] Meanwhile, the first virtual machine (not shown) can control the second virtual machine (not shown) and the third virtual machine (not shown) to share the same data by writing data to the shared memory (508).

[0134] For example, a first virtual machine (not shown) can record vehicle sensor data, the location information data, the camera image data, or the touch input data in shared memory (508) and control the same data to be shared with a second virtual machine (not shown) and a third virtual machine (not shown). Accordingly, data sharing in a 1:N manner becomes possible.

[0135] Ultimately, by performing most of the data processing on the first virtual machine (not shown), data sharing in a 1:N manner becomes possible.

[0136] Meanwhile, the first virtual machine (not shown) within the processor (175) can control the shared memory (508) based on the hypervisor (505) to be set for the same data transmission to the second virtual machine (not shown) and the third virtual machine (not shown).

[0137] Meanwhile, the signal processing device (170) can process various signals such as audio signals, video signals, and data signals. To this end, the signal processing device (170) can be implemented in the form of a system on chip (SOC).

[0138] Meanwhile, the signal processing device (170) in the display device (100) of FIG. 4 may be the same as the signal processing device (170, 170a1, 170a2) of the vehicle display device of FIG. 5a or lower.

[0139] FIGS. 5A to 5D are drawings showing various examples of vehicle display devices.

[0140] FIG. 5A illustrates an example of a vehicle display device according to an embodiment of the present disclosure.

[0141] Referring to the drawings, a vehicle display device (800a) according to an embodiment of the present disclosure includes a signal processing device (170a1, 170a2) and a plurality of area signal processing devices (170Z1 to 170Z4).

[0142] Meanwhile, in the drawing, two signal processing devices (170a1, 170a2) are exemplified, but this is for backup purposes, etc., and one is also possible.

[0143] Meanwhile, the signal processing device (170a1, 170a2) may also be named an HPC (High Performance Computing) signal processing device.

[0144] Multiple area signal processing devices (170Z1 to 170Z4) are arranged in each area (Z1 to Z4) and can transmit sensor data to signal processing devices (170a1, 170a2).

[0145] The signal processing device (170a1, 170a2) receives data via a wire from multiple area signal processing devices (170Z1 to 170Z4) or a communication device (120).

[0146] In the drawing, data is exchanged based on wired communication between a signal processing device (170a1, 170a2) and multiple area signal processing devices (170Z1 to 170Z4), and the signal processing device (170a1, 170a2) and the server (400) exchange data based on wireless communication. However, data may be exchanged based on wireless communication between a communication device (120) and a server (400), and the signal processing device (170a1, 170a2) and the communication device (120) may exchange data based on wired communication.

[0147] Meanwhile, data received by the signal processing device (170a1, 170a2) may include camera data or sensor data.

[0148] For example, sensor data within a vehicle may include at least one of vehicle wheel speed data, vehicle direction data, vehicle location data (GPS data), vehicle angle data, vehicle speed data, vehicle acceleration data, vehicle inclination data, vehicle forward / backward data, battery data, fuel data, tire data, vehicle lamp data, vehicle interior temperature data, vehicle interior humidity data, vehicle exterior radar data, and vehicle exterior lidar data.

[0149] Meanwhile, camera data may include vehicle exterior camera data and vehicle interior camera data.

[0150] Meanwhile, the signal processing device (170a1, 170a2) can execute multiple virtual machines (820, 830, 840) based on safety standards.

[0151] In the drawing, it is illustrated that a processor (175) within a signal processing device (170a) executes a hypervisor (505) and, on the hypervisor (505), executes first to third virtual machines (820 to 840) according to an automotive safety integrity level (Automotive SIL; ASIL).

[0152] The first virtual machine (820) may be a virtual machine corresponding to Quality Management (QM), which is the lowest safety level in the Automotive Safety Integrity Level (ASIL) and is a non-enforceable level.

[0153] The first virtual machine (820) can execute an operating system (822), a container runtime (824) on the operating system (822), and containers (827, 829) on the container runtime (824).

[0154] The second virtual machine (830) may be a virtual machine corresponding to ASIL A or ASIL B, where the sum of severity, exposure, and controllability is 7 or 8 in the automotive safety integrity level (ASIL).

[0155] The second virtual machine (830) can execute an operating system (832), a container runtime (834) on the operating system (832), and containers (837, 839) on the container runtime (834).

[0156] The third virtual machine (840) may be a virtual machine corresponding to ASIL C or ASIL D, in which the sum of severity, exposure, and controllability is 9 or 10 in the automotive safety integrity level (ASIL).

[0157] Meanwhile, ASIL D can correspond to the grade that requires the highest safety level.

[0158] The third virtual machine (840) can run a safety operating system (842) and an application (845) on the operating system (842).

[0159] Meanwhile, the third virtual machine (840) may also execute a safety operating system (842), a container runtime (844) on the safety operating system (842), and a container (847) on the container runtime (844).

[0160] Meanwhile, unlike the drawing, the third virtual machine (840) can also be executed through a separate core rather than the processor (175). This will be described later with reference to FIG. 5b.

[0161] FIG. 5b illustrates another example of a vehicle display device according to an embodiment of the present disclosure.

[0162] Referring to the drawings, a vehicle display device (800b) according to an embodiment of the present disclosure includes a signal processing device (170a1, 170a2) and a plurality of area signal processing devices (170Z1 to 170Z4).

[0163] The vehicle display device (800b) of FIG. 5b is similar to the vehicle display device (800a) of FIG. 5a, but the signal processing device (170a1) has some differences from the signal processing device (170a1) of FIG. 5a.

[0164] To describe the difference, the signal processing device (170a1) may include a processor (175) and a second processor (177).

[0165] The processor (175) within the signal processing unit (170a1) executes a hypervisor (505), and executes first and second virtual machines (820 to 830) on the hypervisor (505) according to the automotive safety integrity level (Automotive SIL; ASIL).

[0166] The first virtual machine (820) can execute an operating system (822), a container runtime (824) on the operating system (822), and containers (827, 829) on the container runtime (824).

[0167] The second virtual machine (830) can execute an operating system (832), a container runtime (834) on the operating system (832), and containers (837, 839) on the container runtime (834).

[0168] Meanwhile, the second processor (177) within the signal processing device (170a1) can execute a third virtual machine (840).

[0169] The third virtual machine (840) can execute a safety operating system (842), an auto-execution (845) on the operating system (842), and an application (845) on the auto-execution (845). That is, unlike FIG. 5A, an auto-execution (846) on the operating system (842) can be executed.

[0170] Meanwhile, the third virtual machine (840) may, similarly to FIG. 5a, execute a safety operating system (842), a container runtime (844) on the safety operating system (842), and a container (847) on the container runtime (844).

[0171] Meanwhile, the third virtual machine (840) requiring a high level of security is preferably executed on a second processor (177), which is a different core or different processor, unlike the first and second virtual machines (820 to 830).

[0172] Meanwhile, in the signal processing devices (170a1, 170a2) of FIGS. 5a and 5b, when the first signal processing device (170a) malfunctions, the second signal processing device (170a2), which is a backup device, can operate.

[0173] Alternatively, it is also possible for the signal processing devices (170a1, 170a2) to operate simultaneously, with the first signal processing device (170a) operating as the main device and the second signal processing device (170a2) operating as the sub device. This will be described with reference to FIGS. 5c and 5d.

[0174] FIG. 5c illustrates another example of a vehicle display device according to an embodiment of the present disclosure.

[0175] Referring to the drawings, a vehicle display device (800c) according to an embodiment of the present disclosure includes a signal processing device (170a1, 170a2) and a plurality of area signal processing devices (170Z1 to 170Z4).

[0176] Meanwhile, in the drawing, two signal processing devices (170a1, 170a2) are exemplified, but this is for backup purposes, etc., and one is also possible.

[0177] Meanwhile, the signal processing device (170a1, 170a2) may also be named an HPC (High Performance Computing) signal processing device.

[0178] Multiple area signal processing devices (170Z1 to 170Z4) are arranged in each area (Z1 to Z4) and can transmit sensor data to signal processing devices (170a1, 170a2).

[0179] The signal processing device (170a1, 170a2) receives data via a wire from multiple area signal processing devices (170Z1 to 170Z4) or a communication device (120).

[0180] In the drawing, data is exchanged based on wired communication between a signal processing device (170a1, 170a2) and multiple area signal processing devices (170Z1 to 170Z4), and the signal processing device (170a1, 170a2) and the server (400) exchange data based on wireless communication. However, data may be exchanged based on wireless communication between a communication device (120) and a server (400), and the signal processing device (170a1, 170a2) and the communication device (120) may exchange data based on wired communication.

[0181] Meanwhile, data received by the signal processing device (170a1, 170a2) may include camera data or sensor data.

[0182] Meanwhile, among the signal processing devices (170a1, 170a2), the processor (175) in the first signal processing device (170a1) executes a hypervisor (505) and can execute a safety virtualization machine (860) and a non-safety virtualization machine (870) on the hypervisor (505), respectively.

[0183] Meanwhile, among the signal processing devices (170a1, 170a2), the processor (17b5) in the second signal processing device (170a2) executes the hypervisor (505b) and can execute only the safety virtualization machine (880) on the hypervisor (505).

[0184] In this way, since the processing for safety is separated between the first signal processing device (170a1) and the second signal processing device (170a2), it is possible to improve stability and processing speed.

[0185] Meanwhile, high-speed network communication can be performed between the first signal processing device (170a1) and the second signal processing device (170a2).

[0186] FIG. 5d illustrates another example of a vehicle display device according to an embodiment of the present disclosure.

[0187] Referring to the drawings, a vehicle display device (800d) according to an embodiment of the present disclosure includes a signal processing device (170a1, 170a2) and a plurality of area signal processing devices (170Z1 to 170Z4).

[0188] The vehicle display device (800d) of FIG. 5d is similar to the vehicle display device (800c) of FIG. 5c, but the second signal processing device (170a2) has some differences from the second signal processing device (170a2) of FIG. 5c.

[0189] The processor (17b5) in the second signal processing device (170a2) of FIG. 5d executes a hypervisor (505b) and can execute a safety virtualization machine (880) and a non-safety virtualization machine (890) on the hypervisor (505).

[0190] That is, unlike FIG. 5c, the difference is that the processor (17b5) within the second signal processing device (170a2) further executes a non-safety virtualization machine (890).

[0191] In this way, since the processing for safety and non-safety is separated into the first signal processing device (170a1) and the second signal processing device (170a2), it is possible to improve stability and processing speed.

[0192] FIG. 6 is an example of a block diagram of a vehicle display device according to an embodiment of the present disclosure.

[0193] Referring to the drawings, a vehicle display device (900) according to an embodiment of the present disclosure includes a plurality of area signal processing devices (170Z1 to 170Z4) and a signal processing device (170).

[0194] The signal processing device (170) at this time is a high-performance centralized signal processing and control device having a plurality of central processors (CPUs) (175, 178), a neural network processor (NPU) (177), and a graphics processor (GPU) (179), and may be called an HPC (High Performance Computing) signal processing device or a central signal processing device.

[0195] A plurality of area signal processing devices (170Z1 to 170Z4) and a signal processing device (170) are connected by wired cables (CB1 to CB4).

[0196] Meanwhile, multiple area signal processing devices (170Z1 to 170Z4) can be connected to each other with wired cables (CBa to CBd).

[0197] The wired cable (CBa~CBd) at this time may include a CAN communication cable, an Ethernet communication cable, or a PCI Express cable.

[0198] Meanwhile, a signal processing device (170) according to an embodiment of the present disclosure comprises at least one processor (175, 177, 178, 179) and a large-capacity storage device (925).

[0199] For example, at least one processor may be a central processor.

[0200] Meanwhile, the signal processing device (170) according to the embodiment of the present disclosure may further include a graphics processor (179) or a neural processor (177).

[0201] Meanwhile, sensor data may be transmitted from at least one of the multiple area signal processing devices (170Z1 to 170Z4) to the signal processing device (170). In particular, the sensor data may be stored in a storage device (925) within the signal processing device (170).

[0202] The sensor data at this time may include at least one of camera data, lidar data, radar data, vehicle direction data, vehicle location data (GPS data), vehicle angle data, vehicle speed data, vehicle acceleration data, vehicle inclination data, vehicle forward / backward data, battery data, fuel data, tire data, vehicle lamp data, vehicle interior temperature data, and vehicle interior humidity data.

[0203] In the drawing, it is exemplified that camera data from a camera (195a) and lidar data from a lidar sensor (196) are input to a first area signal processing device (170Z1), and the camera data and lidar data are transmitted to a signal processing device (170) via a second area signal processing device (170Z2), a third area signal processing device (170Z3), etc.

[0204] Meanwhile, since the data read speed or write speed to the storage device (925) is faster than the network speed when sensor data is transmitted from at least one of the plurality of area signal processing devices (170Z1 to 170Z4) to the signal processing device (170), it is preferable that multi-path routing be performed so that a network bottleneck does not occur.

[0205] To this end, the signal processing device (170) according to the embodiment of the present disclosure can perform multi-path routing based on a Software Defined Network (SDN). Accordingly, a stable network environment can be secured when reading or writing data from the storage device (925). Furthermore, since data can be transmitted to the storage device (925) using multiple paths, the network configuration can be dynamically changed to transmit data.

[0206] Data communication between a plurality of area signal processing devices (170Z1 to 170Z4) and a signal processing device (170) in a vehicle display device (900) according to an embodiment of the present disclosure is preferably Ethernet communication or Peripheral Component Interconnect Express communication for high-bandwidth, low-latency communication.

[0207] FIG. 7 is another example of a block diagram of a vehicle display device according to an embodiment of the present disclosure.

[0208] Referring to the drawings, a vehicle display device (900b) according to another embodiment of the present disclosure includes a plurality of area signal processing devices (170Z1 to 170Z4), a signal processing device (170), and a large-capacity storage device (925).

[0209] That is, unlike the vehicle display device (900) of FIG. 6, the difference is that a large-capacity storage device (925) is provided separately from the signal processing device (170).

[0210] FIG. 8 is an example of an internal block diagram of a signal processing device according to an embodiment of the present disclosure.

[0211] Referring to the drawings, a vehicle display device (900) according to an embodiment of the present disclosure includes a plurality of signal processing devices (170a to 170c).

[0212] For example, among the plurality of signal processing devices (170a to 170c), the first signal processing device (170a) may be the central signal processing device (170) of FIG. 6 or FIG. 7.

[0213] As another example, the first signal processing device (170a) among the plurality of signal processing devices (170a to 170c) may be the signal processing device (170a1) of FIGS. 5a to 5d.

[0214] Meanwhile, among the plurality of signal processing devices (170a to 170c), the second signal processing device (170b) and the third signal processing device (170c) may be any one of the area signal processing devices (170Z1 to 170Z4) of FIG. 6 or FIG. 7.

[0215] Alternatively, among the plurality of signal processing devices (170a to 170c), the second signal processing device (170b) may be the signal processing device (170a2) of FIGS. 5a to 5d, and the third signal processing device (170c) may be any one of the area signal processing devices (170Z1 to 170Z4) of FIG. 6 or FIG. 7.

[0216] A first signal processing device (170a) according to one embodiment of the present disclosure includes a network interface (835a) that receives sensor data from area signal processing devices (170Z1 to 170Z4), a first processor (175a) that processes at least some of the sensor data, and a storage interface (816a) that transmits another part of the sensor data to a storage device (925).

[0217] Meanwhile, the first processor (175a) according to one embodiment of the present disclosure processes first sensor data among sensor data and controls the transmission of second sensor data among sensor data to the storage device (925). Accordingly, data can be processed efficiently.

[0218] Meanwhile, a second signal processing device (170b) according to one embodiment of the present disclosure includes a network interface (835b) that receives sensor data from area signal processing devices (170Z1 to 170Z4), a second processor (175b) that processes at least some of the sensor data, and a storage interface (816b) that transmits another part of the sensor data to a storage device (925).

[0219] Meanwhile, the second processor (175b) according to one embodiment of the present disclosure processes the third sensor data among the sensor data and controls the transmission of the fourth sensor data among the sensor data to the storage device (925). Accordingly, data can be processed efficiently.

[0220] Meanwhile, a third signal processing device (170c) according to one embodiment of the present disclosure includes a network interface (835c) that receives sensor data from area signal processing devices (170Z1 to 170Z4), a third processor (175c) that processes at least some of the sensor data, and a storage interface (816c) that transmits another part of the sensor data to a storage device (925).

[0221] Meanwhile, the third processor (175c) according to one embodiment of the present disclosure processes the fifth sensor data among the sensor data and controls the transmission of the sixth sensor data among the sensor data to the storage device (925). Accordingly, data can be processed efficiently.

[0222] Meanwhile, a plurality of signal processing devices (170a to 170c) according to one embodiment of the present disclosure can each perform communication with a vehicle network (850).

[0223] For example, a plurality of signal processing devices (170a to 170c) according to one embodiment of the present disclosure can perform PCIe communication based on a vehicle network (850), a PCIe network (852), Ethernet communication based on 10G bit Ethernet (854), or Ethernet communication based on 1G bit Ethernet (852).

[0224] Meanwhile, a plurality of signal processing devices (170a to 170c) according to one embodiment of the present disclosure can perform communication for sharing data with a storage device (925).

[0225] For example, multiple signal processing devices (170a to 170c) can transmit data to a shared namespace (810) within a storage device (925).

[0226] To this end, the storage device (925) may be equipped with a shared namespace (810), interfaces (812a, 812b, 812c) for communication with each signal processing device (170a to 170c), and controllers (814a, 814b, 814c).

[0227] Meanwhile, it is desirable that the communication speed between the signal processing devices (170a to 170c) and the vehicle network (850) be faster than the communication speed between the signal processing devices (170a to 170c) and the storage device (925).

[0228] Meanwhile, each processor (175a to 175c) within the signal processing device (170a to 170c) can process time-critical data, which is the first sensor data among the sensor data, and control the transmission of non-time-critical data, which is the second sensor data among the sensor data, to the storage device (925). Accordingly, data can be processed efficiently.

[0229] For example, the first processor (175a) within the first signal processing device (170a) can process time-critical data, which is the first sensor data among the sensor data, and control the transmission of non-time-critical data, which is the second sensor data among the sensor data, to the storage device (925). Accordingly, data can be processed efficiently.

[0230] Meanwhile, each processor (175a to 175c) within the signal processing device (170a to 170c) can transmit second sensor data to the shared namespace (810) of the storage device (925) through the storage interface (816a to 816c).

[0231] For example, the storage interface (816a) within the first signal processing device (170a) can transmit second sensor data to the shared namespace (810) of the storage device (925). Accordingly, data can be processed efficiently.

[0232] Meanwhile, the first sensor data may be time-critical data, as it requires real-time processing.

[0233] That is, since the first sensor data must be processed at a high speed, it is desirable that it be processed without delay during the processing operation.

[0234] Specifically, the first sensor data may be sensor data for autonomous driving (AD) or advanced driver assistance systems (ADAS).

[0235] For example, the first sensor data may include lidar data or radar data.

[0236] Meanwhile, the second sensor data may be non-time critical data, which is important to the vehicle system but does not need to be processed in real time.

[0237] That is, since the second sensor data does not need to be processed in real time, it is desirable to process it when resources are available.

[0238] Meanwhile, since the second sensor data has a large data size to be processed, it is highly likely that it will take up a significant amount of bandwidth of the vehicle network (850) when processed simultaneously with the first sensor data.

[0239] For example, the second sensor data may include black box data or data to be transmitted to a learning server.

[0240] Meanwhile, each processor (175a to 175c) within the signal processing device (170a to 170c) can receive a first data processing pipeline (842a to 842c) for processing the first sensor data.

[0241] For example, the first processor (175a) within the first signal processing device (170a) can receive a first data processing pipeline (842a) for processing first sensor data. Accordingly, data can be efficiently processed.

[0242] Meanwhile, the data processing pipeline may be a data unit for processing in-vehicle data, such as sensor data.

[0243] For example, the data processing pipeline may be a data unit for processing, such as color space conversion, which is an example of first image processing, chroma region deletion, object classification, object check, video encoding, etc., which is an example of second image processing.

[0244] As another example, a data processing pipeline may be a data unit for processing, such as preprocessing, object detection, sensor fusion, or vehicle control.

[0245] As another example, a data processing pipeline may be a data unit for processing, such as preprocessing, video encoding, object check, and saving.

[0246] Meanwhile, each processor (175a to 175c) within the signal processing device (170a to 170c) can receive a second data processing pipeline (843a to 843c) for transmission of second sensor data to a storage device (925).

[0247] For example, the first processor (175a) within the first signal processing device (170a) may receive a second data processing pipeline (843a) for transmission of second sensor data to a storage device (925). Accordingly, data can be efficiently processed.

[0248] Meanwhile, the data processing pipeline can be divided into a first data processing pipeline (842a to 842c) that guarantees real-time processing and a second data processing pipeline (843a to 843c).

[0249] Meanwhile, the first data processing pipeline (842a to 842c) may process, input, or output data through a path of a high-speed vehicle network (850) when communication between signal processing devices (170a to 170c) is required.

[0250] Meanwhile, the first data processing pipeline (842a to 842c) may change the transmission path according to the utilization rate of the transmission network path, thereby enabling load balancing of the vehicle network (850).

[0251] Meanwhile, the first data processing pipeline (842a to 842c) may process or input or output data through sharing of a transmission network path or high-speed storage device (925) when communication between signal processing devices (170a to 170c) is required.

[0252] Meanwhile, the second data processing pipeline (842a to 842c) may be processed with delay or through a change in the signal processing device (170a to 170c) when input / output data is transmitted by sharing a high-speed storage device (925) or when the utilization rate of hardware for data processing is high.

[0253] Meanwhile, each processor (175a to 175c) within the signal processing devices (170a to 170c) may execute or be equipped with a resource monitor (825a to 825c) that monitors resource information such as hardware utilization of each signal processing device (170a to 170c).

[0254] Meanwhile, the first signal processing device (170a) may be the main signal processing device among a plurality of signal processing devices (170a to 170c).

[0255] Accordingly, the first processor (175a) in the first signal processing device (170a) may further include a pipeline manager (820a) and a resource scheduler (830a), unlike the other signal processing devices (170b to 170c).

[0256] Meanwhile, the pipeline manager (820a) can create, remove, or control various operations of a data processing pipeline.

[0257] For example, the pipeline manager (820a) can create or remove an instance of a data processing pipeline.

[0258] As another example, the pipeline manager (820a) can create or remove a template of a data processing pipeline.

[0259] Meanwhile, the pipeline manager (820a) can change the data transmission method, change or allocate a signal processing device that processes data, or control the execution or termination of data delay processing based on a data scheduling policy from the resource scheduler (830a).

[0260] Meanwhile, the resource scheduler (830a) can perform scheduling for data processing tasks based on hardware information received through the resource monitor (825a) and the operation policy of the data processing pipeline.

[0261] In particular, the resource scheduler (830a) can transmit a corresponding command to the pipeline manager (820a) based on scheduling.

[0262] Meanwhile, the resource monitor (825a) can convert information such as hardware utilization of signal processing devices (170a to 170c) within the system and transmit it to the resource scheduler (830a).

[0263] For example, the resource scheduler (830a) may request the pipeline manager (820a) to load balance each channel according to the channel utilization of the vehicle network (850).

[0264] Meanwhile, the resource scheduler (830a), in a time-critical data processing pipeline state, can control the high-priority data processing pipeline to be temporarily suspended and then transmitted to the storage device (925) when the utilization rate or usage of a specific signal processing device is greater than a predetermined time by another high-priority data processing pipeline.

[0265] Meanwhile, the resource scheduler (830a) can control the paused data processing pipeline to be moved to another signal processing device for processing if the utilization rate or usage of a specific signal processing device does not decrease for a second predetermined period of time or longer.

[0266] Figures 9a and 9b are diagrams explaining the sharing of namespaces.

[0267] First, FIG. 9a illustrates an example of sharing a namespace related to the present disclosure.

[0268] Referring to the drawing, a namespace (810) within a storage device (925a) can transmit data to a second host device (912B) via an external first host device (912) through an interface (812) and a controller (814).

[0269] However, according to this sharing method, data is transmitted to the second host device (912B) via the first host device (912), so a bottleneck may occur during data transmission.

[0270] Accordingly, in this disclosure, a method for reducing bottlenecks during data transmission is proposed.

[0271] FIG. 9b illustrates an example of sharing a namespace according to an embodiment of the present disclosure.

[0272] Referring to the drawing, a namespace (810) within a storage device (925b) can transmit data through interfaces (812a, 812b, 812c) and controllers (814a, 814b, 814c) corresponding to a plurality of host devices (912a, 912b, 912c), respectively.

[0273] However, with this data transmission method, the impact of network throughput related to the bottleneck during data transmission, such as in Fig. 9a, is reduced.

[0274] In particular, the storage device (925b) according to the embodiment of the present disclosure can share data at the file level without network transmission through a shared namespace (810).

[0275] Figure 9c is a drawing referenced in the description of the storage interface of Figure 8.

[0276] Referring to the drawing, a namespace (810) within a storage device (925c) can transmit data to a plurality of host devices (912a, 912b) through interfaces (812a, 812b) and controllers (814a, 814b), each corresponding to the host devices.

[0277] Meanwhile, multiple host devices (912a, 912b) can receive data from a storage device (925c) through each storage interface (816a, 816b) and transmit the data to an application (922a, 922b) through a distributed lock manager (924a, 924b) for controlling the storage interface (816a, 816b).

[0278] At this time, the host device (912a, 912b) can correspond to the signal processing device (170a, 170b) of FIG. 8.

[0279] Meanwhile, the storage interface 816a, 816b) is a global file system interface, and one journal can be executed per each file system node.

[0280] Meanwhile, the Distributed Lock Manager (DSM) (924a, 924b) can change or manage lock information of data or files received through the storage interface 816a, 816b).

[0281] Meanwhile, with respect to FIG. 8, the first processor (175a) within the first signal processing device (170a) can execute a distributed lock manager (924a) for controlling the storage interface (816a). Accordingly, data can be processed efficiently.

[0282] Figure 10 is a drawing referenced in the description of the operation of the vehicle network.

[0283] Referring to the drawing, each signal processing device (170a, 170b) can perform Ethernet communication or PCIe communication with the vehicle network (950).

[0284] To this end, each signal processing device (170a, 170b) can receive sensor data, etc. from a vehicle network (950) through a network device (944a, 944b) and a network stack (942a, 942b), and transmit the received sensor data to an executing application (922a, 922b).

[0285] Data transmission between the signal processing device (170a, 170b) and the vehicle network (950) may be packet-based memory-to-memory data transmission, and may be faster than data transmission using a storage device (925) using a namespace sharing method.

[0286] Figure 11 is a diagram illustrating a data processing pipeline.

[0287] Referring to the drawing, the data processing pipeline may have multiple elements.

[0288] In the drawing, the first data processing pipeline (842) includes color space conversion (1102), which is an example of first image processing, chroma area deletion (1104), and object classification (1106), which are examples of second image processing, and the second data processing pipeline (843) includes object checking (1112) and video encoding (1114).

[0289] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control the first data processing pipeline (842) and the second data processing pipeline (843) to be processed in the first signal processing device (170a) based on the resources of the first signal processing device (170a) or the resources of other signal processing devices (170b, 170c).

[0290] Alternatively, the first processor (175a) within the first signal processing device (170a) may control the first data processing pipeline (842) to be processed in the first signal processing device (170a) and the second data processing pipeline (843) to be processed in the second signal processing device (170b) based on the resources of the first signal processing device (170a) or the resources of other signal processing devices (170b, 170c). Accordingly, data can be processed efficiently.

[0291] Similarly, the first processor (175a) in the first signal processing device (170a) can control some of the elements among the plurality of elements in the first data processing pipeline (842) for processing the first sensor data to be processed, and other some of the elements among the plurality of elements in the first data processing pipeline (842) to be processed in other signal processing devices (170b, 170c).

[0292] For example, among the plurality of elements within the first data processing pipeline (842), some elements, such as color space conversion (1102), which is an example of the first image processing, and chroma area deletion (1104), which is an example of the second image processing, can be controlled to be processed by the first signal processing device (170a), and some other elements, such as object classification (1106), can be controlled to be processed by the second signal processing device (170b). Accordingly, data can be processed efficiently.

[0293] Meanwhile, the first processor (175a) within the first signal processing device (170a) can control data transmission between elements within the data processing pipeline to be transmitted using the same communication method.

[0294] For example, the first processor (175a) in the first signal processing device (170a) can control data communication based on vehicle network communication to be performed during data communication between color space conversion (1102), which is an example of the first image processing, and chroma area deletion (1104), which is an example of the second image processing.

[0295] As another example, the first processor (175a) within the first signal processing device (170a) can control data communication based on a shared namespace to be performed during data communication between color space conversion (1102), which is an example of the first image processing, and chroma area deletion (1104), which is an example of the second image processing.

[0296] Meanwhile, the first processor (175a) within the first signal processing device (170a) can control data transmission through connection of multiple data processing pipelines.

[0297] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control multiple data processing pipelines to overlap.

[0298] Meanwhile, the first processor (175a) within the first signal processing device (170a) can allocate the first data processing pipeline (842) based on the resources of the first signal processing device (170a) or the resources of other signal processing devices (170b, 170c). Accordingly, data can be processed efficiently.

[0299] Meanwhile, the first processor (175a) within the first signal processing device (170a) can allocate the first data processing pipeline (842) for processing the first sensor data to the other signal processing devices (170b, 170c) based on the resources of the first signal processing device (170a) or the resources of the other signal processing devices (170b, 170c). Accordingly, data can be processed efficiently.

[0300] Meanwhile, the first processor (175a) within the first signal processing device (170a) can control, at the request of the pipeline manager (820a), to dump the data processing context of the element and store the data processing context in the storage device (925).

[0301] Meanwhile, the first processor (175a) in the first signal processing device (170a) can determine whether to store the data processing context based on the type of hardware used for data processing in the element.

[0302] Meanwhile, the first processor (175a) in the first signal processing device (170a) can divide the processing units based on the type of hardware used for data processing and control data to be processed in the corresponding units.

[0303] Meanwhile, the first processor (175a) within the first signal processing device (170a) can perform classification for storing data processing context.

[0304] For example, the first processor (175a) in the first signal processing device (170a) may classify the data processing context as Level 1, which is the lowest level, for copying, partial deletion, etc. of data in the processor.

[0305] As another example, the first processor (175a) in the first signal processing device (170a) may classify the data processing context as level 2 for processing data frames or compressing data in the processor.

[0306] As another example, the first processor (175a) within the first signal processing device (170a) may classify the data processing context in a video encoder, 2D graphics engine, etc., as level 3.

[0307] As another example, the first processor (175a) in the first signal processing device (170a) can classify the data processing context in a graphics processor or video decoder, etc., as level 4, which is the highest level.

[0308] Meanwhile, the first processor (175a) in the first signal processing device (170a) can set the minimum unit for storing the data processing context.

[0309] For example, the first processor (175a) in the first signal processing device (170a) may set the minimum unit for storing the data processing context as a reference picture in the case of a video encoder, as a GOP (Group Of Picture) such as an I frame, B frame, or P frame in the case of a video decoder, as a Surface frame in the case of a 2D graphics engine, and as a frame in the case of a camera.

[0310] Figures 12a to 12c are drawings for reference in the description of the data processing queue.

[0311] FIG. 12a is a diagram illustrating a first data processing pipeline and each data processing queue of the first data processing pipeline.

[0312] Referring to the drawing, the first data processing pipeline (842) may have a first data processing queue (1101) for input and a second data processing queue (1109) for output.

[0313] In the drawing, a first data processing queue (1101) is arranged at an input end of a plurality of elements (1102, 1104, 1106) within a first data processing pipeline (842), and a second data processing queue (1109) is arranged at an output end of the plurality of elements (1102, 1104, 1106).

[0314] The first data processing queue (1101) can temporarily store data input to the first data processing pipeline (842) and can temporarily store output data processed in the second data processing queue (1109).

[0315] Meanwhile, data stored in the first data processing queue (1101) or the second data processing queue (1109) may be stored using a memory or storage device (925).

[0316] Meanwhile, the first data processing queue (1101) or the second data processing queue (1109) can receive or transmit sensor data and metadata via the vehicle network (850). Accordingly, data can be processed efficiently.

[0317] Meanwhile, the first data processing queue (1101) or the second data processing queue (1109) can transmit sensor data through namespace sharing and metadata through the vehicle network (850). Accordingly, data can be processed efficiently.

[0318] Meanwhile, the second data processing pipeline (843) may be equipped with a third data processing queue (1111) for input and a fourth data processing queue (1119) for output.

[0319] The operations of the third data processing queue (1111) and the fourth data processing queue (1119) may correspond to the first data processing queue (1101) and the second data processing queue (1119), respectively.

[0320] Figure 12b is an example of the internal structure of a data processing queue.

[0321] Referring to the drawing, data from the vehicle network (850) can be stored in internal memory (not shown) within each signal processing device (170a to 170c).

[0322] That is, the data processing queue (1109a) of the vehicle network (850) can be matched and stored in the data processing queue (1111a) in the internal memory (not shown) in each signal processing device (170a to 170c).

[0323] Meanwhile, a queue element within a data processing queue (1109a) may have metadata (1130a) and a pointer (1132a) indicating a memory area.

[0324] Meanwhile, the metadata (1130a) and pointer (1132a) can be transmitted to the internal memory (not shown) in each signal processing device (170a to 170c) via the vehicle network (850) and matched with the metadata (1130b) and pointer (1132b).

[0325] That is, through the vehicle network (850), actual data and metadata (1130a) can be transmitted to the internal memory (not shown) within each signal processing device (170a to 170c).

[0326] Figure 12b is another example of the internal structure of a data processing queue.

[0327] Referring to the drawing, data from each signal processing device (170a to 170c) can be stored in a storage device (925).

[0328] That is, the data processing queue (1109b) of each signal processing device (170a to 170c) can be matched and stored as the data processing queue (1111b) in the storage device (925).

[0329] Meanwhile, the queue element within the data processing queue (1109b) can store the name and path of the data.

[0330] Meanwhile, actual data can be transmitted through a shared namespace (810) within a storage device (925), and metadata can be transmitted through a vehicle network (850).

[0331] That is, metadata (1130a) can be transmitted to a storage device (925) via a vehicle network (850), and actual data (1134a) can be transmitted via a shared namespace (810) to be matched to data (1134b).

[0332] Figure 13 illustrates an example of processing in a data processing pipeline.

[0333] Referring to the drawing, the first data processing pipeline (842a) may be transmitted to at least some (170a, 170b) of the signal processing devices (170a to 170c) via the vehicle network (850) and processed.

[0334] In the drawing, a first data processing pipeline (842a) is illustrated as having a plurality of elements, including color space conversion (1102), which is an example of first image processing, chroma area deletion (1104), which is an example of second image processing, and object classification (1106).

[0335] Meanwhile, the first processor (175a) may process some elements among a plurality of elements within the first data processing pipeline (842a) for processing the first sensor data based on the resources of the first signal processing device (170a) or the resources of other signal processing devices (170b, 170c), and control other elements among the plurality of elements within the first data processing pipeline (842a) to be processed in other signal processing devices (170b, 170c).

[0336] In the drawing, it is illustrated that some elements within the first data processing pipeline (842a), such as color space conversion (1102), an example of first image processing, and chroma area deletion (1104), an example of second image processing, are processed by a graphics processor (179a) within the first signal processing device (170a), and some other elements, such as object classification (1106), are processed by a neural network processor (177b) within the second signal processing device (170b).

[0337] Meanwhile, the first processor (175a) within the first signal processing device (170a) can control the result data of object classification (1106) to be stored in a shared namespace (810) within the storage device (925).

[0338] Meanwhile, the shared namespace (810) within the storage device (925) can store the second data processing pipeline (843a) based on the result data of the object classification (1106).

[0339] Meanwhile, the second data processing pipeline (843a) may include a plurality of elements, including object checking (1112), video encoding (1114), and data storage (1116).

[0340] For example, object check (1112) may be processed in a first central processor (175c) within a third signal processing device (170c), video encoding (1114) may be processed in a video encoder (173c) within a third signal processing device (170c), and data storage (1116) may be processed in a second central processor (178c) within a third signal processing device (170c).

[0341] Figure 14 illustrates an example of processing in a data processing pipeline.

[0342] Referring to the drawing, the first data processing pipeline (872) may be transmitted to at least some (170a, 170b) of the signal processing devices (170a to 170c) via the vehicle network (850) and processed.

[0343] In the drawing, the first data processing pipeline (872) is illustrated as having a plurality of elements, including preprocessing (1202) and object detection (1206).

[0344] Meanwhile, some elements, such as preprocessing (1202) within the first data processing pipeline (872a), may be processed by a graphics processor (179a) within the first signal processing device (170a), and some other elements, such as object detection (1206), may be processed by a neural network processor (177b) within the second signal processing device (170b).

[0345] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control the completion of object detection (1206) to transmit the result data to the second data processing pipeline (873).

[0346] Meanwhile, the second data processing pipeline (873) may include sensor fusion (1208) as an element.

[0347] Meanwhile, sensor fusion (1208) can be processed in a neural network processor (177c) within a third signal processing device (170c).

[0348] Meanwhile, the first processor (175a) within the first signal processing device (170a) can control the sensor fusion (1208) result data to be transmitted to the third data processing pipeline (874).

[0349] Meanwhile, the third data processing pipeline (874) may include a vehicle control (1209) as an element.

[0350] Meanwhile, vehicle control (1209) can be processed in a central processor (175c) within a third signal processing device (170c).

[0351] Meanwhile, the first processor (175a) within the first signal processing device (170a) can control the transmission path of sensor data or a data processing pipeline or an element within the data processing pipeline to be variable based on the utilization rate of the vehicle network (850) connected to the network interface (835a).

[0352] For example, the first processor (175a) within the first signal processing device (170a) can control the transmission path of time-critical data, which is the first sensor data among the sensor data, to be variable based on the utilization rate of the vehicle network (850) connected to the network interface (835a). Accordingly, data can be processed efficiently.

[0353] Meanwhile, the first processor (175a) within the first signal processing device (170a) can vary the processing of elements within the first data processing pipeline based on the first sensor data based on the utilization rate of the vehicle network (850) connected to the network interface (835a). This is described with reference to FIGS. 15a and 15b.

[0354] Figures 15a and 15b illustrate an example of processing of a time-critical based data processing pipeline.

[0355] Figure 15a illustrates an example of utilization of multiple vehicle networks.

[0356] Referring to the drawing, the utilization rate of the first vehicle network (850a) among the multiple vehicle networks may be approximately 90%, and the utilization rate of the second vehicle network (850b) may be approximately 0%.

[0357] That is, through the first vehicle network (850a), the first data processing pipeline (872), the second data processing pipeline (873), and the third data processing pipeline (874) can be transmitted to the signal processing devices (170a to 170c), respectively.

[0358] Meanwhile, some elements, such as preprocessing (1202) within the first data processing pipeline (872), may be processed by a graphics processor (179a) within the first signal processing device (170a), and some other elements, such as object detection (1206), may be processed by a neural network processor (177b) within the second signal processing device (170b).

[0359] Meanwhile, sensor fusion (1208) within the second data processing pipeline (873) can be processed in a neural network processor (177c) within the third signal processing device (170c).

[0360] Meanwhile, the vehicle control (1209) within the third data processing pipeline (874) can be processed in the central processor (175c) within the third signal processing device (170c).

[0361] Figure 15b illustrates another example of utilization of multiple vehicle networks.

[0362] Referring to the drawing, the utilization rate of the first vehicle network (850a) among the multiple vehicle networks may be approximately 50%, and the utilization rate of the second vehicle network (850b) may be approximately 4%.

[0363] That is, through the first vehicle network (850a), the first data processing pipeline (872) can be transmitted to the first signal processing device (170a) and the second signal processing device (170b), and through the second vehicle network (850b), the second data processing pipeline (873) and the third data processing pipeline (874) can be transmitted to the third signal processing device (170c).

[0364] Meanwhile, some elements, such as preprocessing (1202) within the first data processing pipeline (872), may be processed by a graphics processor (179a) within the first signal processing device (170a), and some other elements, such as object detection (1206), may be processed by a neural network processor (177b) within the second signal processing device (170b).

[0365] Meanwhile, sensor fusion (1208) within the second data processing pipeline (873) can be processed in a neural network processor (177c) within the third signal processing device (170c).

[0366] Meanwhile, the vehicle control (1209) within the third data processing pipeline (874) can be processed in the central processor (175c) within the third signal processing device (170c).

[0367] Figures 16a to 17b illustrate various examples of processing in a non-time critical data processing pipeline.

[0368] First, Figure 16a illustrates an example of a non-time-critical data processing pipeline.

[0369] Referring to the drawing, the non-time critical first data processing pipeline (872) and second data processing pipeline (873) may be stored within a shared namespace (810) within the storage device (925).

[0370] The first data processing pipeline (872) may include preprocessing (1202) and video encoding (1203), and the second data processing pipeline (873) may include object checking (1205) and data storage (1209).

[0371] Meanwhile, the result data processed by the graphic processor (179a) in the first signal processing device (170a) may be stored in preprocessing (1202), and the result data processed by the video encoder (173b) in the second signal processing device (170b) may be stored in video encoding (1203).

[0372] Meanwhile, the result data processed by the central processor (175c) in the third signal processing device (170c) is stored in the object check (1205), and the data related to data storage (1209) is processed by the central processor (175c) in the third signal processing device (170c), and the result data processed by the central processor (175c) can be stored in the private namespace (1310).

[0373] Next, Figure 16b illustrates another example of a non-time-critical data processing pipeline.

[0374] Referring to the drawing, the first data processing pipeline (872), the second data processing pipeline (873), and the third data processing pipeline (874), which are not time-critical, can be transmitted to each signal processing device (170a to 170c) via the vehicle network (850).

[0375] For example, some elements, such as preprocessing (1602) within the first data processing pipeline (872), may be processed by a graphics processor (179a) within the first signal processing device (170a), and some other elements, such as object detection (1604), may be processed by a neural network processor (177b) within the second signal processing device (170b).

[0376] Meanwhile, sensor fusion (1606) within the second data processing pipeline (873) can be processed in a neural network processor (177c) within the third signal processing device (170c).

[0377] Meanwhile, the vehicle control (1608) within the third data processing pipeline (874) may be processed in the central processor (175c) within the third signal processing device (170c).

[0378] Figure 16c illustrates an example of the operation of the storage device during the operation of Figure 16b.

[0379] Referring to the drawing, the first data processing pipeline (872), the second data processing pipeline (873), and the third data processing pipeline (874), which are not time-critical, can be transmitted to each signal processing device (170a to 170c) via the vehicle network (850).

[0380] For example, data for preprocessing (1602), which is a part of an element within a first data processing pipeline (872), may be transmitted to a graphics processor (179a) within a first signal processing device (170a), and the graphics processor (179a) within the first signal processing device (170a) may perform preprocessing (1602).

[0381] Meanwhile, data for object detection (1604), which is another element within the first data processing pipeline (872), may be transmitted to a neural network processor (177b) within the second signal processing device (170b) and processed.

[0382] Meanwhile, the result data processed by the neural network processor (177b) in the second signal processing device (170b) can be transmitted to the vehicle network (850).

[0383] Meanwhile, the vehicle network (850) can store the result data processed by the neural network processor (177b) in the second signal processing device (170b) in the data processing queue (1612) in the shared name space (810) in the storage device (925).

[0384] Meanwhile, the shared name space (810) can store a data processing pipeline (1613) based on a data processing queue (1612).

[0385] Meanwhile, the neural network processor (177c) within the third signal processing device (170c) can receive the data processing pipeline (1613) stored within the storage device (925) and perform sensor fusion processing.

[0386] In addition, the neural network processor (177c) in the third signal processing device (170c) can transmit the result data of the sensor fusion processing to the data processing pipeline (1613) in the storage device (925).

[0387] Meanwhile, the vehicle network (850) can transmit data for sensor fusion (1606) within the second data processing pipeline (873) to a shared name space (810) within the storage device (925).

[0388] Accordingly, the shared name space (810) within the storage device (925) can store data for sensor fusion (1606).

[0389] Meanwhile, the shared name space (810) within the storage device (925) can store data for sensor fusion (1606) and a data processing pipeline (1617) based on the result data of the sensor fusion processing.

[0390] Additionally, the shared name space (810) within the storage device (925) can transmit data within the data processing pipeline (1617) to the central processor (175c) within the third signal processing device (170c).

[0391] The central processor (175c) within the third signal processing device (170c) can perform a check (1618) process on sensor data based on the received data and control the result data to be stored in a shared name space (810) within the storage device (925).

[0392] Figure 16d illustrates another example of the operation of the storage device during the operation of Figure 16b.

[0393] Referring to the drawing, the operation of FIG. 16d is similar to the operation of FIG. 16c, but the difference is that the vehicle network (850) does not transmit the second data processing pipeline (873) and the third data processing pipeline (874) to the storage device (925).

[0394] Figures 17a and 17b are drawings referenced in the operation description of Figure 16d.

[0395] Figure 17a illustrates that the operation of the data processing pipeline within the storage device (925) is paused.

[0396] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in the first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0397] Meanwhile, the vehicle network (840) transmits data for object detection (1604) to a neural network processor (177b) in a second signal processing device (170b), and the neural network processor (177b) in the second signal processing device (170b) can perform object detection (1604).

[0398] Meanwhile, the result data processed by the neural network processor (177b) in the second signal processing device (170b) can be transmitted to the vehicle network (850).

[0399] Meanwhile, the vehicle network (850) can store the result data processed by the neural network processor (177b) in the second signal processing device (170b) in the data processing queue (1612) in the shared name space (810) in the storage device (925) (S1702).

[0400] Meanwhile, the shared name space (810) within the storage device (925) can stop the operation of the data processing pipeline (1613) including the internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including the check (1618) of sensor data (S1704).

[0401] Meanwhile, the first processor (175a) within the first signal processing device (170a) controls the transmission of second sensor data among sensor data to the shared namespace (810) within the storage device (925) when there is a delay in processing the second sensor data, and when the utilization rate of resources for processing the second sensor data is below a predetermined value, the second sensor data can be received from the storage device (925) and processed. Accordingly, data can be processed efficiently.

[0402] Meanwhile, the first processor (175a) within the first signal processing device (170a) can control the processing of the second data processing pipeline (1613, 1617) based on the second sensor data to be temporarily suspended when there is a delay in the processing of the first data processing pipeline based on the first sensor data. Accordingly, data can be processed efficiently.

[0403] Figure 17b illustrates the resumption of operation of the data processing pipeline within the storage device (925).

[0404] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in the first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0405] Meanwhile, the vehicle network (840) transmits data for object detection (1604) to a neural network processor (177b) in a second signal processing device (170b), and the neural network processor (177b) in the second signal processing device (170b) can perform object detection (1604).

[0406] Meanwhile, the result data processed by the neural network processor (177b) in the second signal processing device (170b) can be transmitted to the vehicle network (850).

[0407] Meanwhile, the vehicle network (850) can store the result data processed by the neural network processor (177b) in the second signal processing device (170b) in the data processing queue (1612) in the shared name space (810) in the storage device (925) (S1706).

[0408] Meanwhile, if the data stored in the data processing queue (1612) in the shared name space (810) in the storage device (925) is greater than a predetermined value, the shared name space (810) in the storage device (925) can resume the operation of the data processing pipeline (1613) including the internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including the check (1618) of the sensor data (S1708).

[0409] That is, the first processor (175a) within the first signal processing device (170a) can process the second data processing pipeline (1613, 1617) based on the second sensor data when the capacity of the data processing queue (1612) is greater than or equal to a reference value after temporarily suspending the processing of the second data processing pipeline (1613, 1617) based on the second sensor data. Accordingly, data can be processed efficiently.

[0410] Meanwhile, when the utilization rate of the neural network processor (177b) within the second signal processing device (170b) is below a predetermined value, the shared name space (810) within the storage device (925) can resume the operation of the data processing pipeline (1613) including the internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including the sensor data check (1618). Accordingly, data can be processed efficiently.

[0411] That is, the first processor (175a) within the first signal processing device (170a) can check the resource utilization rate at regular intervals after temporarily suspending the processing of the second data processing pipeline (843a) based on the second sensor data, and if the resource utilization rate is below a predetermined value, can resume the processing of the second data processing pipeline (1613, 1617) based on the second sensor data. Accordingly, data can be processed efficiently.

[0412] Figure 18 is a diagram referenced to explain dynamic resource mapping.

[0413] Referring to the drawing, among each signal processing device (170a to 170c), the second signal processing device (170b) can process multiple data processing pipelines (842b, 843b, 844b).

[0414] Among the plurality of data processing pipelines (842b, 843b, 844b), the first data processing pipeline (842b) may include color space conversion (1102), which is an example of first image processing, and chroma area deletion (1104), which is an example of second image processing, the second data processing pipeline (843b) may include object classification (1106), and the third data processing pipeline (844b) may include object check (1112) and video encoding (1114).

[0415] Figures 19a and 19b are drawings referenced in the operation description of Figure 18.

[0416] FIG. 19a illustrates that the operation of the data processing pipeline within the storage device (925) is paused.

[0417] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in the first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0418] Meanwhile, the vehicle network (840) transmits data for object detection (1604) to a neural network processor (177b) in a second signal processing device (170b), and the neural network processor (177b) in the second signal processing device (170b) can perform object detection (1604).

[0419] Meanwhile, the result data processed by the neural network processor (177b) in the second signal processing device (170b) can be transmitted to the vehicle network (850).

[0420] Meanwhile, the vehicle network (850) can store the result data processed by the neural network processor (177b) in the second signal processing device (170b) in the data processing queue (1612) in the shared name space (810) in the storage device (925) (S1902).

[0421] Meanwhile, the shared namespace (810) within the storage device (925) can stop the operation of the data processing pipeline (1613), including the internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617), including the sensor data check (1618) (S1904). Accordingly, data can be processed efficiently.

[0422] Figure 19b illustrates the resumption of operation of the data processing pipeline within the storage device (925).

[0423] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in the first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0424] Meanwhile, the vehicle network (840) transmits data for object detection (1604) to a neural network processor (177b) in a second signal processing device (170b), and the neural network processor (177b) in the second signal processing device (170b) can perform object detection (1604).

[0425] Meanwhile, the result data processed by the neural network processor (177b) in the second signal processing device (170b) can be transmitted to the vehicle network (850).

[0426] Meanwhile, the vehicle network (850) can store the result data processed by the neural network processor (177b) in the second signal processing device (170b) in the data processing queue (1612) in the shared name space (810) in the storage device (925) (S1906).

[0427] Meanwhile, if the data stored in the data processing queue (1612) in the shared name space (810) within the storage device (925) is greater than a predetermined value, the shared name space (810) within the storage device (925) can resume the operation of the data processing pipeline (1613) including the internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including the sensor data check (1618). Accordingly, data can be processed efficiently.

[0428] Although the preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above, and various modifications may be made by a person skilled in the art to which the present invention pertains without departing from the gist of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the present disclosure.

Claims

1. A network interface for receiving sensor data from a domain signal processing device; A processor for processing at least some of the sensor data; a storage interface for transmitting another portion of the above sensor data to a storage device; The above processor, Processing the first sensor data among the above sensor data, A signal processing device that controls the second sensor data among the above sensor data to be transmitted to the storage device.

2. In paragraph 1, The above processor, Processing the time-critical data, which is the first sensor data among the above sensor data, A signal processing device that controls the non-time critical data, which is the second sensor data among the above sensor data, to be transmitted to the storage device.

3. In paragraph 1, The above storage interface is, A signal processing device that transmits the second sensor data to the shared namespace of the storage device.

4. In paragraph 1, The above processor, A signal processing device that runs a distributed lock manager for controlling the above storage interface.

5. In paragraph 1, The above processor, A signal processing device receiving a first data processing pipeline for processing the first sensor data.

6. In paragraph 1, The above processor, A signal processing device receiving a second data processing pipeline for transmission of the second sensor data to the storage device.

7. In paragraph 1, The above processor, A signal processing device that processes some elements among a plurality of elements in a first data processing pipeline for processing the first sensor data based on the resources of the signal processing device or the resources of another signal processing device, and controls other elements among the plurality of elements in the first data processing pipeline to be processed in another signal processing device.

8. In paragraph 6, The above processor, A signal processing device that allocates the first data processing pipeline based on the resources of the signal processing device or the resources of another signal processing device.

9. In paragraph 1, The above processor, A signal processing device that allocates a first data processing pipeline for processing the first sensor data to another signal processing device based on the resources of the signal processing device or the resources of another signal processing device.

10. In paragraph 6, The above first data processing pipeline, A signal processing device having a first data processing queue for input and a second data processing queue for output.

11. In paragraph 10, The first data processing queue or the second data processing queue, A signal processing device that transmits sensor data and metadata through a vehicle network.

12. In paragraph 10, The first data processing queue or the second data processing queue, A signal processing device that transmits sensor data through namespace sharing and metadata through a vehicle network.

13. In paragraph 1, The above processor, A signal processing device that controls the transmission path of time-critical data, which is the first sensor data among the sensor data, to be variable based on the utilization rate of the vehicle network connected to the network interface.

14. In paragraph 1, The above processor, A signal processing device that varies element processing within a first data processing pipeline based on the first sensor data based on the utilization rate of a vehicle network connected to the network interface.

15. In paragraph 1, The above processor, When there is a delay in processing the second sensor data among the above sensor data, control is made to transmit it to a shared namespace within the storage device, A signal processing device that receives and processes the second sensor data from the storage device when the utilization rate of resources for processing the second sensor data is below a predetermined value.

16. In paragraph 1, The above processor, A signal processing device that controls to temporarily suspend the processing of a second data processing pipeline based on the second sensor data when there is a delay in the processing of a first data processing pipeline based on the first sensor data.

17. In paragraph 1, The above processor, A signal processing device that checks resource utilization at regular intervals after temporarily suspending processing of a second data processing pipeline based on the second sensor data, and resumes processing of the second data processing pipeline based on the second sensor data when the resource utilization is below a predetermined value.

18. In paragraph 1, The above processor, A signal processing device that processes the second data processing pipeline based on the second sensor data when the capacity of the data processing queue is greater than or equal to a reference value after the processing of the second data processing pipeline based on the second sensor data is temporarily suspended.

19. In paragraph 1, The above first sensor data includes lidar data or radar data, A signal processing device wherein the second sensor data includes black box data.

20. Display; A signal processing device for controlling the above display; The above signal processing device, A vehicle display device comprising a signal processing device according to any one of claims 1 to 18.

Images