Signal processing device and vehicle display device having the same

Abstract

A signal processing device and a vehicle display device equipped with the same according to one embodiment of the present disclosure include a network interface for receiving sensor data from an area 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. The processor processes a first sensor data among the sensor data and controls the transmission of a second sensor data among the sensor data to a storage device. By doing so, data can be processed efficiently.

Description

Technology Field

[0001] The present disclosure relates to a signal processing device and a vehicle display device equipped with the same, and more specifically, to a signal processing device capable of efficiently processing data and a vehicle display device equipped with the same. Background Technology

[0002] A vehicle is a device that moves the user in the desired direction. A typical example is an automobile.

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

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

[0005] Meanwhile, due to Advanced Driver Assistance Systems (ADAS) and autonomous driving, the types and number of sensors installed in vehicles are exploding, and consequently, the amount of data generated by vehicles is also on the rise.

[0006] Multiple signal processing devices are used for processing such data, and as communication between multiple signal processing devices increases, a load is generated on the communication channels.

[0007] Accordingly, there is a need for a method to efficiently process or share data between signal processing devices. The problem to be solved

[0008] The problem that the present disclosure aims 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 aims to solve is to provide a signal processing device capable of prioritizing the processing of time-critical data among sensor data, and a vehicle display device equipped with the same.

[0010] Another problem that the present disclosure aims 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 equipped with the same. means of solving the problem

[0011] A signal processing device and a vehicle display device equipped with the same according to an embodiment of the present disclosure for solving the above technical problem include a network interface for receiving sensor data from an area 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 a first sensor data among the sensor data and controls the second sensor data among the sensor data to be transmitted to a storage device.

[0012] Meanwhile, the processor can process the time-critical data, which is the first sensor data among the sensor data, and control the transmission of the non-time-critical data, which is the second sensor data among the sensor data, 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 execute a distributed lock manager for controlling the storage interface.

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

[0016] Meanwhile, the processor can receive a second data processing pipeline for transmitting the second sensor data to a storage device.

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

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

[0019] Meanwhile, the processor may allocate 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.

[0020] Meanwhile, the first data processing pipeline may include 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 according to one embodiment of the present disclosure and a vehicle display device equipped with the same may further include a storage device.

[0024] Meanwhile, the processor can control the transmission path of the 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 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 connected to the network interface.

[0026] Meanwhile, the processor controls the second sensor data to be transmitted to a shared namespace within the storage device when processing of the second sensor data is delayed, and when the utilization rate of resources for processing the second sensor data is below a predetermined value, the processor can receive and process the second sensor data from the storage device.

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

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

[0029] Meanwhile, the processor can 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 includes lidar data or radar data, and the second sensor data may include black box data. Effects of the invention

[0031] A signal processing device and a vehicle display device equipped with the same according to one embodiment of the present disclosure include a network interface for receiving sensor data from an area 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. The processor processes first sensor data among the sensor data and controls the transmission of second sensor data among the sensor data to a storage device. Accordingly, data can be processed efficiently.

[0032] Meanwhile, the processor can process the first sensor data, which is time-critical data, among the sensor data, and control the transmission of the second sensor data, which is non-time-critical data, to a storage device. Accordingly, data can be processed efficiently.

[0033] Meanwhile, the storage interface can transmit the second sensor data to the shared namespace of the storage device. Accordingly, data can be processed efficiently.

[0034] Meanwhile, the processor can execute a distributed lock manager for controlling the storage interface. As a result, data can be processed efficiently.

[0035] Meanwhile, the processor can receive a first data processing pipeline for processing the first sensor data. Accordingly, the data can be processed efficiently.

[0036] Meanwhile, the processor can receive a second data processing pipeline for transmitting the second sensor data to a storage device. Accordingly, the data can be processed efficiently.

[0037] Meanwhile, the processor can control the processing of some elements among a plurality of elements in a first data processing pipeline for processing first sensor data, based on the resources of a signal processing device or the resources of another signal processing device, so that other elements among the plurality of elements in the first data processing pipeline are processed by another signal processing device. Accordingly, data can be processed efficiently.

[0038] Meanwhile, the processor may allocate a first data processing pipeline based on the resources of a signal processing device or the resources of another signal processing device. Accordingly, data can be processed efficiently.

[0039] Meanwhile, the processor may allocate 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. Accordingly, data can be processed efficiently.

[0040] Meanwhile, the first data processing pipeline may include a first data processing queue for input and a second data processing queue for output. Accordingly, data can be processed efficiently.

[0041] Meanwhile, the first data processing queue or the second data processing queue can receive or transmit sensor data and metadata through the vehicle network. Accordingly, data can be processed efficiently.

[0042] 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. Accordingly, data can be processed efficiently.

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

[0044] Meanwhile, the processor can control the transmission path of the 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. Accordingly, data can be processed efficiently.

[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 rate of the vehicle network connected to the network interface. Accordingly, data can be processed efficiently.

[0046] Meanwhile, the processor controls the second sensor data to be transmitted to a shared namespace within the storage device when processing of the second sensor data is delayed, and when the utilization rate of resources for processing the second sensor data is below a predetermined value, it can receive and process the second sensor data from the storage device. 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 there is a processing delay in the first data processing pipeline based on the first sensor data. Accordingly, data can be processed efficiently.

[0048] Meanwhile, the processor checks the resource utilization rate at regular intervals after temporarily suspending the processing of the second data processing pipeline based on the second sensor data, and can resume the processing of the second data processing pipeline based on the second sensor data if the resource utilization rate is below a predetermined value. Accordingly, data can be processed efficiently.

[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. Accordingly, data can be processed efficiently.

[0050] Meanwhile, the first sensor data includes lidar data or radar data, and the second sensor data may include black box data. Accordingly, data can be processed efficiently. Brief explanation of the drawing

[0051] Figure 1 is a drawing illustrating an example of the exterior and interior of a vehicle. FIGS. 2a to 2c are drawings illustrating various architectures of a vehicle communication gateway. FIG. 3a is a drawing illustrating an example of the arrangement of a vehicle display device inside a vehicle. FIG. 3b is a drawing illustrating another example of the arrangement of a vehicle display device inside a vehicle. Figure 4 is an example of an internal block diagram of a vehicle display device of Figure 3b. FIGS. 5a to 5d are drawings illustrating various examples of display devices for vehicles. FIG. 6 is an example of a block diagram of a vehicle display device according to an embodiment of the present disclosure. FIG. 7 is another example of a block diagram of a vehicle display device according to an embodiment of the present disclosure. FIG. 8 is an example of an internal block diagram of a signal processing device according to an embodiment of the present disclosure. FIGS. 9a to 19b are drawings referenced in the description of FIG. 8. Specific details for implementing the invention

[0052] The present disclosure will be described in more detail below with reference to the drawings.

[0053] The suffixes "module" and "part" for components used in the following description are assigned solely for the ease of drafting this specification and do not inherently confer any particularly significant meaning or role. Accordingly, the terms "module" and "part" may be used interchangeably.

[0054] Figure 1 is a drawing illustrating an example of the exterior and interior of a vehicle.

[0055] Referring to the drawing, the vehicle (200) is operated by a plurality of wheels (103FR, 103FL, 103RL,...) that rotate by a power source, and a steering wheel (150) for controlling the direction of travel of the vehicle (200).

[0056] Meanwhile, the vehicle (200) may further be equipped with a camera (195), etc., for acquiring an image of the front of the vehicle.

[0057] Meanwhile, the vehicle (200) may be equipped with a plurality of displays (180a, 180b) for displaying images, information, etc. inside.

[0058] In FIG. 1, a cluster display (180a) and an AVN (Audio Video Navigation) display (180b) are exemplified as multiple displays (180a, 180b). Other displays such as a HUD (Head Up Display) are also possible.

[0059] Meanwhile, the AVN (Audio Video Navigation) display (180b) may also be named a Center Information Display.

[0060] Meanwhile, the vehicle (200) described in this specification may be a concept that includes all of the following: 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, an electric vehicle equipped with an electric motor as a power source, etc.

[0061] FIGS. 2a to 2c are drawings illustrating various architectures of a vehicle communication gateway.

[0062] First, FIG. 2a is a diagram illustrating the first architecture of a vehicle communication gateway.

[0063] Referring to the drawing, the first architecture (300a) can correspond to a zone-based architecture.

[0064] Accordingly, sensor devices and processors inside the vehicle may be placed in each of the multiple 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 multiple zones (Z1 to Z4).

[0065] Meanwhile, the signal processing device (170a) may additionally include an autonomous driving control module (ACC), a cockpit control module (CPG), etc., in addition to the vehicle communication gateway (GWDa).

[0066] The vehicle communication gateway (GWDa) within the signal processing device (170a) may be a High Performance Computing (HPC) gateway.

[0067] 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) in a plurality of zones (Z1 to Z4).

[0068] FIG. 2b is a diagram illustrating the second architecture of a vehicle communication gateway.

[0069] Referring to the drawing, the second architecture (300b) can correspond to a domain-integrated architecture.

[0070] 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 a plurality of processors (ECUs) can be electrically connected to each module (BSG, PTG, ADG, CPG).

[0071] Meanwhile, each processor (ECU) can be integrated into and connected to the gateway (GWDb).

[0072] Meanwhile, the signal processing device (170) including the gateway (GWDb) of FIG. 2b operates as a domain-integrated signal processing device.

[0073] FIG. 2c is a diagram illustrating the third architecture of a vehicle communication gateway.

[0074] Referring to the drawing, the third architecture (300c) can correspond to a distributed architecture.

[0075] 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).

[0076] Compared to Fig. 2b, the third architecture differs in that each processor (ECU) is connected directly to the gateway (GWDb) without connecting to other modules.

[0077] Meanwhile, the signal processing device (170) including the gateway (GWDc) of FIG. 2c operates as a distributed signal processing device.

[0078] FIG. 3a is a drawing illustrating an example of the arrangement of a vehicle display device inside a vehicle.

[0079] Referring to the drawing, the vehicle interior may be equipped with a cluster display (180a), an AVN (Audio Video Navigation) display (180b), a rear seat entertainment display (180c, 180d), a rearview mirror display (not shown), etc.

[0080] FIG. 3b is a drawing illustrating another example of the arrangement of a vehicle display device inside a vehicle.

[0081] 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).

[0082] Among the plurality of displays (180a to 180b), the first display (180a) is 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 operation information, navigation map, various entertainment information or video.

[0083] The signal processing device (170) has a processor (175) inside and can execute a first virtualization machine to a third virtualization machine (not shown) on a hypervisor (not shown) within the processor (175).

[0084] A second virtualization machine (not shown) operates for the first display (180a), and a third virtualization machine (not shown) can operate for the second display (180b).

[0085] Meanwhile, the first virtualization machine (not shown) within the processor (175) can be controlled to set up a shared memory (508) based on a hypervisor (505) for the same data transmission to the second virtualization machine (not shown) and the third virtualization machine (not shown). Accordingly, the same information or the same image can be synchronized and displayed on the first display (180a) and the second display (180b) within the vehicle.

[0086] Meanwhile, the first virtualization machine (not shown) within the processor (175) shares at least a portion of the data with the second virtualization machine (not shown) and the third virtualization machine (not shown) for data sharing processing. Accordingly, data can be shared and processed by multiple virtualization machines for multiple displays within the vehicle.

[0087] Meanwhile, the first virtualization machine (not shown) within the processor (175) can receive and process wheel speed sensor data of the vehicle and transmit the processed wheel speed sensor data to at least one of the second virtualization machine (not shown) or the third virtualization machine (not shown). Accordingly, the wheel speed sensor data of the vehicle can be shared with at least one virtualization machine, etc.

[0088] 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.

[0089] The signal processing device (170) can control the RSE display (180c) by running a fourth virtualization machine (not shown) in addition to the first to third virtualization machines (not shown) on a hypervisor (not shown) within the processor (175).

[0090] Accordingly, various displays (180a to 180c) can be controlled using a single signal processing device (170).

[0091] Meanwhile, some of the multiple displays (180a to 180c) operate under a Linux OS, and others can operate under a Web OS.

[0092] A signal processing device (170) according to an embodiment of the present disclosure can control displays (180a to 180c) operating under various operating systems (OS) to synchronize and display the same information or the same image.

[0093] Meanwhile, FIG. 3b illustrates that 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, a vehicle speed indicator (212b), and a vehicle interior temperature indicator (213b) is displayed on a second display (180b), and a second home screen (222b) including a plurality of applications and a vehicle interior temperature indicator (213c) is displayed on a third display (180c).

[0094] Figure 4 is an example of an internal block diagram of a vehicle display device of Figure 3b.

[0095] Referring to the drawings, a vehicle display device (100) according to an embodiment of the present disclosure may comprise an input unit (110), a communication unit (120) for communication with an external device, a plurality of communication modules (EMa~EMd) for internal communication, a memory (140), a signal processing unit (170), a plurality of displays (180a~180c), an audio output unit (185), and a power supply unit (190).

[0096] Multiple communication modules (EMa~EMd) can be placed in each of the multiple zones (Z1~Z4) of FIG. 2a, for example.

[0097] Meanwhile, the signal processing device (170) may have a communication switch (736b) inside for data communication with each communication module (EM1~EM4).

[0098] Each communication module (EM1~EM4) can perform data communication with a plurality of sensor devices (SN), ECU (770), or area signal processing device (170Z).

[0099] Meanwhile, a plurality of sensor devices (SN) may include a camera (195), lidar (196), radar (197), or position sensor (198).

[0100] The input unit (110) may be equipped with physical buttons, pads, etc. for button input, touch input, etc.

[0101] Meanwhile, the input unit (110) may be equipped with a microphone (not shown) for user voice input.

[0102] The communication unit (120) can exchange data wirelessly with a mobile terminal (800) or a server (900).

[0103] In particular, the communication unit (120) can wirelessly exchange data with the vehicle driver's mobile terminal. Various data communication methods are possible as wireless data communication methods, such as Bluetooth, WiFi, WiFi Direct, and APiX.

[0104] The communication unit (120) can receive weather information, road traffic condition 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).

[0105] A plurality of communication modules (EM1~EM4) can receive sensor data, etc. from an ECU (770), a sensor device (SN), or a region signal processing device (170Z), and transmit the received sensor data to the signal processing device (170).

[0106] 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 tilt data, vehicle forward / reverse data, battery data, fuel data, tire data, vehicle lamp data, vehicle interior temperature data, and vehicle interior humidity data.

[0107] Such sensor data can be obtained from a heading sensor, a yaw sensor, a gyro sensor, a position module, a vehicle forward / reverse sensor, a wheel sensor, a vehicle speed sensor, a vehicle body inclination sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor based on steering wheel rotation, a vehicle interior temperature sensor, a vehicle interior humidity sensor, etc.

[0108] Meanwhile, the position module may include a GPS module or a position sensor (198) for receiving GPS information.

[0109] Meanwhile, at least one of the multiple communication modules (EM1 to EM4) can transmit location information data sensed from a GPS module or a location sensor (198) to a signal processing device (170).

[0110] 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, and obstacle distance information around the vehicle from a camera (195), lidar (196), radar (197), etc., and transmit the received information to a signal processing device (170).

[0111] 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).

[0112] For example, memory (140) can store data regarding a hypervisor, a first virtualization machine to a third virtualization machine, for execution within a processor (175).

[0113] The audio output unit (185) converts an electrical signal from the signal processing device (170) into an audio signal and outputs it. To do this, a speaker or the like may be provided.

[0114] The power supply unit (190) can supply power necessary for the operation of each component under the control of the signal processing unit (170). In particular, the power supply unit (190) can receive power from a battery inside the vehicle, etc.

[0115] The signal processing device (170) controls the overall operation of each unit within the vehicle display device (100).

[0116] For example, the signal processing device (170) may include a processor (175) that performs signal processing for a vehicle display (180a, 180b).

[0117] The processor (175) can run a first virtualization machine to a third virtualization machine (not shown) on a hypervisor (not shown) within the processor (175).

[0118] Among the first to third virtual machines (not shown), the first virtual machine (not shown) may be named a Server Virtual Machine, and the second to third virtual machines (not shown) may be named a Guest Virtual Machine.

[0119] For example, a first virtualization machine (not shown) within a processor (175) can receive 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, and process or modify it to output it.

[0120] In this way, by performing most of the data processing in the first virtualization machine (not shown), 1:N data sharing becomes possible.

[0121] As another example, the first virtualization machine (not shown) can directly receive and process CAN data, Ethernet data, audio data, radio data, USB data, and wireless communication data for the second virtualization machine to the third virtualization machine (not shown).

[0122] And, the first virtualization machine (not shown) can transmit the processed data to the second virtualization machine to the third virtualization machine (not shown).

[0123] Accordingly, among the first to third virtualization machines (not shown), only the first virtualization machine (not shown) receives sensor data, communication data, or external input data from a plurality of sensor devices and performs signal processing, thereby reducing the signal processing burden on other virtualization machines and enabling 1:N data communication, which enables synchronization when sharing data.

[0124] Meanwhile, the first virtualization machine (not shown) can control the sharing of the same data with the second virtualization machine (not shown) and the third virtualization machine (not shown) by writing data to the shared memory (508).

[0125] For example, the first virtualization machine (not shown) can record vehicle sensor data, the location information data, the camera image data, or the touch input data in a shared memory (508) and control the sharing of the same data with the second virtualization machine (not shown) and the third virtualization machine (not shown). Accordingly, data sharing in a 1:N manner becomes possible.

[0126] Ultimately, by performing most of the data processing on the first virtualization machine (not shown), 1:N data sharing becomes possible.

[0127] Meanwhile, the first virtualization machine (not shown) within the processor (175) can control the second virtualization machine (not shown) and the third virtualization machine (not shown) to set up a shared memory (508) based on the hypervisor (505) for the same data transmission.

[0128] 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).

[0129] Meanwhile, the signal processing device (170) in the display device (100) of FIG. 4 may be identical to the signal processing device (170, 170a1, 170a2) of the vehicle display device of FIG. 5a and below.

[0130] FIGS. 5a to 5d are drawings illustrating various examples of display devices for vehicles.

[0131] FIG. 5a illustrates an example of a vehicle display device according to an embodiment of the present disclosure.

[0132] 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).

[0133] Meanwhile, in the drawing, two signal processing devices (170a1, 170a2) are exemplified, but this is exemplified for backup purposes, and one is also possible.

[0134] Meanwhile, the signal processing device (170a1, 170a2) may be named as an HPC (High Performance Computing) signal processing device.

[0135] A plurality of area signal processing devices (170Z1~170Z4) are positioned in each area (Z1~Z4) and can transmit sensor data to signal processing devices (170a1, 170a2).

[0136] The signal processing device (170a1, 170a2) receives data via wire from a plurality of area signal processing devices (170Z1~170Z4) or a communication device (120).

[0137] In the drawing, data is exchanged based on wired communication between the signal processing device (170a1, 170a2) and the plurality of area signal processing devices (170Z1~170Z4), and data is exchanged based on wireless communication between the signal processing device (170a1, 170a2) and the server (400), but data can be exchanged based on wireless communication between the communication device (120) and the server (400), and data can be exchanged based on wired communication between the signal processing device (170a1, 170a2) and the communication device (120).

[0138] Meanwhile, the data received by the signal processing device (170a1, 170a2) may include camera data or sensor data.

[0139] For example, sensor data within the 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 tilt data, vehicle forward / reverse data, battery data, fuel data, tire data, vehicle lamp data, vehicle interior temperature data, vehicle interior humidity data, vehicle external radar data, and vehicle external lidar data.

[0140] Meanwhile, camera data may include external vehicle camera data and internal vehicle camera data.

[0141] Meanwhile, the signal processing device (170a1, 170a2) can execute multiple virtualization machines (820, 830, 840) based on safety standards.

[0142] In the drawing, a processor (175) within a signal processing unit (170a) executes a hypervisor (505) and, on the hypervisor (505), executes first to third virtualization machines (820 to 840) according to the Automotive Safety Integrity Level (Automotive SIL; ASIL).

[0143] The first virtualization machine (820) may be a virtualization machine corresponding to Quality Management (QM), which is the lowest safety level and non-mandatory grade in the Automotive Safety Integrity Level (ASIL).

[0144] The first virtualization machine (820) can run an operating system (822), a container runtime (824) on the operating system (822), and containers (827, 829) on the container runtime (824).

[0145] The second virtualization machine (830) may be a virtualization machine corresponding to ASIL A or ASIL B, where the sum of Severity, Exposure, and Contrallability in the Automotive Safety Integrity Level (ASIL) is 7 or 8.

[0146] The second virtualization machine (830) can run an operating system (832), a container runtime (834) on the operating system (832), and containers (837, 839) on the container runtime (834).

[0147] The third virtualization machine (840) may be a virtualization machine corresponding to ASIL C or ASIL D, in which the sum of Severity, Exposure, and Contrallability in the Automotive Safety Integrity Level (ASIL) is 9 or 10.

[0148] Meanwhile, ASIL D can correspond to the grade requiring the highest level of safety.

[0149] The third virtualization machine (840) can run a safety operating system (842) and an application (845) on the operating system (842).

[0150] Meanwhile, the third virtualization machine (840) may also run a safety operating system (842), a container runtime (844) on the safety operating system (842), and a container (847) on the container runtime (844).

[0151] Meanwhile, unlike the drawing, the third virtualization machine (840) may also be executed through a separate core rather than the processor (175). This will be described later with reference to FIG. 5b.

[0152] FIG. 5b illustrates another example of a vehicle display device according to an embodiment of the present disclosure.

[0153] 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).

[0154] 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) differs in some ways from the signal processing device (170a1) of FIG. 5a.

[0155] To describe the difference, the signal processing device (170a1) may be equipped with a processor (175) and a second processor (177).

[0156] A processor (175) within a signal processing unit (170a1) executes a hypervisor (505) and, on the hypervisor (505), executes first and second virtualization machines (820 to 830) according to the Automotive Safety Integrity Level (Automotive SIL; ASIL).

[0157] The first virtualization machine (820) can run an operating system (822), a container runtime (824) on the operating system (822), and containers (827, 829) on the container runtime (824).

[0158] The second virtualization machine (830) can run an operating system (832), a container runtime (834) on the operating system (832), and containers (837, 839) on the container runtime (834).

[0159] Meanwhile, the second processor (177) in the signal processing device (170a1) can execute the third virtualization machine (840).

[0160] The third virtualization machine (840) can run a safety operating system (842), an AUTOSAR (845) on the operating system (842), and an application (845) on the AUTOSAR (845). That is, unlike FIG. 5a, it can further run an AUTOSAR (846) on the operating system (842).

[0161] Meanwhile, the third virtualization machine (840) may run a safety operating system (842), a container runtime (844) on the safety operating system (842), and a container (847) on the container runtime (844), similar to FIG. 5a.

[0162] Meanwhile, the third virtualization machine (840), which requires a high level of safety, is preferably executed on a second processor (177), which is a different core or a different processor, unlike the first and second virtualization machines (820 to 830).

[0163] Meanwhile, in the signal processing devices (170a1, 170a2) of FIG. 5a and 5b, the second signal processing device (170a2) can operate as a backup when the first signal processing device (170a) malfunctions.

[0164] Alternatively, signal processing devices (170a1, 170a2) may operate simultaneously, with the first signal processing device (170a) operating as the main and the second signal processing device (170a2) operating as the sub. This is described with reference to FIG. 5c and FIG. 5d.

[0165] FIG. 5c illustrates another example of a vehicle display device according to an embodiment of the present disclosure.

[0166] 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).

[0167] Meanwhile, in the drawing, two signal processing devices (170a1, 170a2) are exemplified, but this is exemplified for backup purposes, and one is also possible.

[0168] Meanwhile, the signal processing device (170a1, 170a2) may be named as an HPC (High Performance Computing) signal processing device.

[0169] A plurality of area signal processing devices (170Z1~170Z4) are positioned in each area (Z1~Z4) and can transmit sensor data to signal processing devices (170a1, 170a2).

[0170] The signal processing device (170a1, 170a2) receives data via wire from a plurality of area signal processing devices (170Z1~170Z4) or a communication device (120).

[0171] In the drawing, data is exchanged based on wired communication between the signal processing device (170a1, 170a2) and the plurality of area signal processing devices (170Z1~170Z4), and data is exchanged based on wireless communication between the signal processing device (170a1, 170a2) and the server (400), but data can be exchanged based on wireless communication between the communication device (120) and the server (400), and data can be exchanged based on wired communication between the signal processing device (170a1, 170a2) and the communication device (120).

[0172] Meanwhile, the data received by the signal processing device (170a1, 170a2) may include camera data or sensor data.

[0173] Meanwhile, the processor (175) in the first signal processing device (170a1) among the signal processing devices (170a1, 170a2) can execute a hypervisor (505) and, on the hypervisor (505), execute a safety virtualization machine (860) and a non-safety virtualization machine (870), respectively.

[0174] Meanwhile, the processor (17b5) in the second signal processing unit (170a2) among the signal processing units (170a1, 170a2) can execute the hypervisor (505b) and, on the hypervisor (505), execute only the safety virtualization machine (880).

[0175] According to this method, 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.

[0176] Meanwhile, high-speed network communication can be performed between the first signal processing device (170a1) and the second signal processing device (170a2).

[0177] FIG. 5d illustrates another example of a vehicle display device according to an embodiment of the present disclosure.

[0178] 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).

[0179] 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) differs in some ways from the second signal processing device (170a2) of FIG. 5c.

[0180] The processor (17b5) in the second signal processing unit (170a2) of FIG. 5d can execute a hypervisor (505b) and, on the hypervisor (505), execute a safety virtualization machine (880) and a non-safety virtualization machine (890), respectively.

[0181] That is, unlike Fig. 5c, the difference is that the processor (17b5) in the second signal processing unit (170a2) further executes the non-safety virtualization machine (890).

[0182] According to this method, since the processing of safety and non-safety is separated by the first signal processing device (170a1) and the second signal processing device (170a2), it is possible to improve stability and processing speed.

[0183] FIG. 6 is an example of a block diagram of a vehicle display device according to an embodiment of the present disclosure.

[0184] Referring to the drawings, a vehicle display device (900) according to an embodiment of the present disclosure comprises a plurality of area signal processing devices (170Z1 to 170Z4) and a signal processing device (170).

[0185] The signal processing device (170) at this time is a high-performance centralized signal processing and control device having a plurality of central processors (CPU) (175, 178), a neural network processor (NPU) (177), and a graphics processor (GPU) (179), and can be named as a High Performance Computing (HPC) signal processing device or a central signal processing device.

[0186] Multiple area signal processing devices (170Z1~170Z4) and signal processing device (170) are connected by wired cables (CB1~CB4).

[0187] Meanwhile, multiple area signal processing devices (170Z1~170Z4) can be connected to each other by wired cables (CBa~CBd).

[0188] The wired cable (CBa~CBd) at this time may include a CAN communication cable, an Ethernet communication cable, or a PCI Express cable.

[0189] Meanwhile, the 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).

[0190] For example, at least one processor may be a central processor.

[0191] Meanwhile, the signal processing device (170) according to an embodiment of the present disclosure may further include a graphics processor (179) or a neural processor (177).

[0192] Meanwhile, sensor data can 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 can be stored in a storage device (925) within the signal processing device (170).

[0193] The sensor data at this time may include at least one of camera data, lidar data, radar data, vehicle direction data, vehicle position data (GPS data), vehicle angle data, vehicle speed data, vehicle acceleration data, vehicle tilt data, vehicle forward / reverse data, battery data, fuel data, tire data, vehicle lamp data, vehicle interior temperature data, and vehicle interior humidity data.

[0194] In the drawing, 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) and a third area signal processing device (170Z3), etc.

[0195] Meanwhile, since the data reading or writing speed to the storage device (925) is faster than the network speed when sensor data is transmitted from at least one of the multiple area signal processing devices (170Z1~170Z4) to the signal processing device (170), it is desirable to perform multipath routing so that network bottlenecks do not occur.

[0196] To this end, the signal processing device (170) according to an embodiment of the present disclosure can perform multipath routing based on a Software Defined Network (SDN). Accordingly, a stable network environment can be secured when reading or writing data of the storage device (925). Furthermore, since data can be transmitted to the storage device (925) using multiple paths, data can be transmitted by dynamically changing the network configuration.

[0197] Data communication between a plurality of area signal processing devices (170Z1~170Z4) and a signal processing device (170) within 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.

[0198] FIG. 7 is another example of a block diagram of a vehicle display device according to an embodiment of the present disclosure.

[0199] Referring to the drawings, a vehicle display device (900b) according to another embodiment of the present disclosure comprises a plurality of area signal processing devices (170Z1 to 170Z4), a signal processing device (170), and a large capacity storage device (925).

[0200] 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).

[0201] FIG. 8 is an example of an internal block diagram of a signal processing device according to an embodiment of the present disclosure.

[0202] Referring to the drawings, a vehicle display device (900) according to an embodiment of the present disclosure comprises a plurality of signal processing devices (170a to 170c).

[0203] 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.

[0204] As another example, among the plurality of signal processing devices (170a to 170c), the first signal processing device (170a) may be the signal processing device (170a1) of FIGS. 5a to 5d.

[0205] 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.

[0206] 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.

[0207] A first signal processing device (170a) according to one embodiment of the present disclosure includes a network interface (835a) for receiving sensor data from area signal processing devices (170Z1 to 170Z4), a first processor (175a) for processing at least a portion of the sensor data, and a storage interface (816a) for transmitting another portion of the sensor data to a storage device (925).

[0208] Meanwhile, a first processor (175a) according to one embodiment of the present disclosure processes first sensor data among sensor data and controls the second sensor data among sensor data to be transmitted to a storage device (925). Accordingly, data can be processed efficiently.

[0209] Meanwhile, a second signal processing device (170b) according to one embodiment of the present disclosure includes a network interface (835b) for receiving sensor data from area signal processing devices (170Z1 to 170Z4), a second processor (175b) for processing at least a portion of the sensor data, and a storage interface (816b) for transmitting another portion of the sensor data to a storage device (925).

[0210] Meanwhile, a second processor (175b) according to one embodiment of the present disclosure processes third sensor data among sensor data and controls the transmission of fourth sensor data among sensor data to a storage device (925). Accordingly, data can be processed efficiently.

[0211] Meanwhile, a third signal processing device (170c) according to one embodiment of the present disclosure includes a network interface (835c) for receiving sensor data from area signal processing devices (170Z1 to 170Z4), a third processor (175c) for processing at least a portion of the sensor data, and a storage interface (816c) for transmitting another portion of the sensor data to a storage device (925).

[0212] Meanwhile, a 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 a storage device (925). Accordingly, data can be processed efficiently.

[0213] Meanwhile, a plurality of signal processing devices (170a to 170c) according to one embodiment of the present disclosure can each communicate with a vehicle network (850).

[0214] 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 PCIe network (852) or Ethernet communication based on 10G bit Ethernet (854) or Ethernet communication based on 1G bit Ethernet (852) with a vehicle network (850).

[0215] Meanwhile, a plurality of signal processing devices (170a to 170c) according to one embodiment of the present disclosure can perform communication for data sharing with a storage device (925).

[0216] For example, a plurality of signal processing devices (170a to 170c) can transmit data to a shared namespace (810) within a storage device (925).

[0217] To this end, the storage device (925) may each be provided with a shared namespace (810), an interface (812a, 812b, 812c) for communication with each signal processing device (170a~170c), and a controller (814a, 814b, 814c).

[0218] Meanwhile, it is desirable that the communication speed between the signal processing device (170a~170c) and the vehicle network (850) be faster than the communication speed between the signal processing device (170a~170c) and the storage device (925).

[0219] Meanwhile, each processor (175a~175c) within the signal processing device (170a~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.

[0220] 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.

[0221] Meanwhile, each processor (175a~175c) within the signal processing device (170a~170c) can transmit the second sensor data to the shared namespace (810) of the storage device (925) via the storage interface (816a~816c).

[0222] For example, the storage interface (816a) within the first signal processing device (170a) can transmit the second sensor data to the shared namespace (810) of the storage device (925). Accordingly, the data can be processed efficiently.

[0223] Meanwhile, the first sensor data is data that requires real-time processing and may be time-critical data.

[0224] 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.

[0225] Specifically, the first sensor data may be sensor data for autonomous driving (AD) or advanced driver assistance systems (ADAS).

[0226] For example, the first sensor data may include lidar data or radar data.

[0227] Meanwhile, the second sensor data is data that is important to the vehicle system but does not need to be processed in real time, and may be non-time critical data.

[0228] In other words, since the second sensor data does not need to be processed in real time, it is desirable to process it when resources are available.

[0229] Meanwhile, the second sensor data has a large data size to process, so when processed simultaneously with the first sensor data, it is highly likely to occupy a significant amount of bandwidth of the vehicle network (850).

[0230] For example, the second sensor data may include black box data or data to be transmitted to a learning server.

[0231] Meanwhile, each processor (175a~175c) within the signal processing device (170a~170c) can receive a first data processing pipeline (842a~842c) for processing the first sensor data.

[0232] For example, the first processor (175a) within the first signal processing device (170a) can receive the first data processing pipeline (842a) for processing the first sensor data. Accordingly, the data can be processed efficiently.

[0233] Meanwhile, the data processing pipeline may be a unit of data for processing in-vehicle data, such as sensor data.

[0234] 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, which is an example of second image processing, object classification, object check, and video encoding.

[0235] As another example, a data processing pipeline may be a unit of data for processing such as preprocessing, object detection, sensor fusion, and vehicle control.

[0236] As another example, a data processing pipeline can be a unit of data for processing such as preprocessing, video encoding, object checking, and saving.

[0237] Meanwhile, each processor (175a~175c) within the signal processing device (170a~170c) can receive a second data processing pipeline (843a~843c) for transmission to the storage device (925) of the second sensor data.

[0238] For example, the first processor (175a) within the first signal processing device (170a) can receive a second data processing pipeline (843a) for transmission to the storage device (925) of the second sensor data. Accordingly, data can be processed efficiently.

[0239] Meanwhile, the data processing pipeline can be divided into a first data processing pipeline (842a~842c) and a second data processing pipeline (843a~843c) that guarantee real-time processing.

[0240] Meanwhile, the first data processing pipeline (842a to 842c) can process data or input or output it through a path of the high-speed vehicle network (850) when communication between the signal processing devices (170a to 170c) is required.

[0241] Meanwhile, the first data processing pipeline (842a to 842c) can change the transmission path according to the utilization rate of the transmission network path, and accordingly, load balancing of the vehicle network (850) may be possible.

[0242] Meanwhile, the first data processing pipeline (842a~842c) can process data or input or output data through a transmission network path or the sharing of a high-speed storage device (925) when communication between signal processing devices (170a~170c) is required.

[0243] Meanwhile, the second data processing pipeline (842a~842c) may be delayed or processed through a change in the signal processing device (170a~170c) when input / output data is transmitted by sharing of the high-speed storage device (925) or when the utilization rate of the hardware for data processing is high.

[0244] Meanwhile, each processor (175a~175c) within the signal processing device (170a~170c) may execute or be equipped with a resource monitor (825a~825c) that monitors resource information, such as the hardware utilization rate of each signal processing device (170a~170c).

[0245] Meanwhile, the first signal processing device (170a) may be the main signal processing device among the plurality of signal processing devices (170a to 170c).

[0246] 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 other signal processing devices (170b to 170c).

[0247] Meanwhile, the pipeline manager (820a) can create, remove, or control various operations of the data processing pipeline.

[0248] For example, the pipeline manager (820a) can create or remove instances of the data processing pipeline.

[0249] As another example, the pipeline manager (820a) can create or remove a template of a data processing pipeline.

[0250] Meanwhile, the pipeline manager (820a) can change the data transmission method, change or allocate the signal processing device for data processing, or control the execution or termination of data delay processing based on the data scheduling policy from the resource scheduler (830a).

[0251] 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.

[0252] In particular, the resource scheduler (830a) can send a corresponding command to the pipeline manager (820a) based on scheduling.

[0253] Meanwhile, the resource monitor (825a) can convert information such as the hardware utilization rate of signal processing devices (170a to 170c) within the system and transmit it to the resource scheduler (830a).

[0254] For example, the resource scheduler (830a) can request the pipeline manager (820a) to load balance each channel according to the channel utilization rate of the vehicle network (850).

[0255] Meanwhile, the resource scheduler (830a) can control the 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 by another high-priority data processing pipeline is longer than a predetermined time while the data processing pipeline is in a time-critical state.

[0256] Meanwhile, the resource scheduler (830a) can control the suspended data processing pipeline to be moved to another signal processing device and processed if the utilization rate or usage of a specific signal processing device is not reduced for a second predetermined time or longer.

[0257] Figures 9a and 9b are diagrams illustrating the sharing of namespaces.

[0258] First, FIG. 9a illustrates an example of namespace sharing related to the present disclosure.

[0259] Referring to the drawing, the namespace (810) within the storage device (925a) can transmit data to the second host device (912B) via the external first host device (912) through the interface (812) and controller (814).

[0260] 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.

[0261] Accordingly, the present disclosure proposes a method for reducing bottlenecks during data transmission.

[0262] FIG. 9b illustrates an example of namespace sharing according to an embodiment of the present disclosure.

[0263] Referring to the drawing, the namespace (810) within the storage device (925b) can transmit data through interfaces (812a, 812b, 812c) and controllers (814a, 814b, 814c) corresponding to each of the multiple host devices (912a, 912b, 912c).

[0264] However, according to this data transmission method, the impact of network throughput related to bottlenecks during data transmission, such as in Fig. 9a, is reduced.

[0265] In particular, the storage device (925b) according to the embodiment of the present disclosure enables data to be shared at the file level without network transmission through a shared namespace (810).

[0266] FIG. 9c is a drawing referenced in the description of the storage interface of FIG. 8.

[0267] Referring to the drawing, the namespace (810) within the storage device (925c) can transmit data through interfaces (812a, 812b) and controllers (814a, 814b) corresponding to each of the multiple host devices (912a, 912b).

[0268] Meanwhile, a plurality of host devices (912a, 912b) can each receive data from a storage device (925c) through a storage interface (816a, 816b) and transmit the data to an application (922a, 922b) via a distributed lock manager (924a, 924b) for controlling the storage interfaces (816a, 816b).

[0269] At this time, the host device (912a, 912b) can correspond to the signal processing device (170a, 170b) of FIG. 8.

[0270] Meanwhile, the storage interface (816a, 816b) is a global file system interface, and one journal can be executed per file system node.

[0271] 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).

[0272] Meanwhile, with respect to FIG. 8, the first processor (175a) in 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.

[0273] Figure 10 is a diagram referenced in the description of the operation of a vehicle network.

[0274] Referring to the drawing, each signal processing unit (170a, 170b) can perform Ethernet communication or PCIe communication with the vehicle network (950).

[0275] 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 can transmit the received sensor data to an application (922a, 922b) that is executed.

[0276] Data transmission between the signal processing device (170a, 170b) and the vehicle network (950) may be packet-based memory-to-memory based data transmission and may be faster than the storage device (925) with a namespace sharing method.

[0277] Figure 11 is a diagram illustrating a data processing pipeline.

[0278] Referring to the drawing, the data processing pipeline may have multiple elements.

[0279] In the drawing, a first data processing pipeline (842) is illustrated as including a color space conversion (1102), which is an example of first image processing, a chroma region deletion (1104), which is an example of second image processing, and an object classification (1106), and a second data processing pipeline (843) is illustrated as including an object check (1112) and video encoding (1114).

[0280] 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).

[0281] Alternatively, the first processor (175a) in the first signal processing device (170a) can 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.

[0282] Similarly, the first processor (175a) in the first signal processing device (170a) can process some of the elements in the first data processing pipeline (842) for processing the first sensor data, and control other elements in the first data processing pipeline (842) to be processed in other signal processing devices (170b, 170c).

[0283] For example, as some elements among a plurality of elements in the first data processing pipeline (842), color space conversion (1102), which is an example of first image processing, and chroma region deletion (1104), which is an example of second image processing, can be controlled to be processed in the first signal processing device (170a), and object classification (1106), which is another element, can be controlled to be processed in the second signal processing device (170b). Accordingly, data can be processed efficiently.

[0284] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control the transmission of data between elements in the data processing pipeline to be transmitted in the same communication method.

[0285] 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 a color space conversion (1102), which is an example of first image processing, and a chroma region deletion (1104), which is an example of second image processing.

[0286] As another example, the first processor (175a) in the first signal processing device (170a) can control data communication based on a shared namespace to be performed during data communication between a color space conversion (1102), which is an example of first image processing, and a chroma region deletion (1104), which is an example of second image processing.

[0287] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control data transmission through the connection of a plurality of data processing pipelines.

[0288] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control multiple data processing pipelines to overlap.

[0289] Meanwhile, the first processor (175a) in 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.

[0290] Meanwhile, the first processor (175a) in 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.

[0291] Meanwhile, the first processor (175a) in the first signal processing device (170a) can be controlled to dump the data processing context of an element and store the data processing context in a storage device (925) in response to a request from the pipeline manager (820a).

[0292] 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.

[0293] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control the data to be processed in corresponding units by dividing the processing units based on the type of hardware used for data processing.

[0294] Meanwhile, the first processor (175a) in the first signal processing device (170a) can perform classification for storing data processing contexts.

[0295] For example, the first processor (175a) in the first signal processing device (170a) can classify the data processing context to the lowest level, level 1, for copying, partial deletion, etc. of data in the processor.

[0296] As another example, the first processor (175a) in the first signal processing device (170a) can classify the data processing context to level 2 for processing data frames or data compression in the processor.

[0297] As another example, the first processor (175a) in the first signal processing device (170a) can classify the data processing context in the video encoder, 2D graphics engine, etc. into level 3.

[0298] As another example, the first processor (175a) in the first signal processing device (170a) can classify the data processing context in the graphics processor or video decoder, etc., to the highest level, level 4.

[0299] Meanwhile, the first processor (175a) in the first signal processing device (170a) can set a minimum unit for storing the data processing context.

[0300] For example, the first processor (175a) in the first signal processing device (170a) can be set as a reference picture in the case of a video encoder, as a Group Of Picture (GOP) such as an I frame, B, 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 as a minimum unit for storing a data processing context.

[0301] FIGS. 12a to 12c are drawings referenced in the description of a data processing queue.

[0302] FIG. 12a is a diagram illustrating a first data processing pipeline and each data processing queue of the first data processing pipeline.

[0303] Referring to the drawing, the first data processing pipeline (842) may include a first data processing queue (1101) for input and a second data processing queue (1109) for output.

[0304] In the drawing, a first data processing queue (1101) is positioned at the 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 positioned at the output end of a plurality of elements (1102, 1104, 1106).

[0305] 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).

[0306] Meanwhile, data stored in the first data processing queue (1101) or the second data processing queue (1109) can be stored using a memory or storage device (925).

[0307] Meanwhile, the first data processing queue (1101) or the second data processing queue (1109) can receive or transmit sensor data and metadata through the vehicle network (850). Accordingly, data can be processed efficiently.

[0308] Meanwhile, the first data processing queue (1101) or the second data processing queue (1109) can transmit sensor data through namespace sharing and transmit metadata through the vehicle network (850). Accordingly, data can be processed efficiently.

[0309] Meanwhile, the second data processing pipeline (843) may include a third data processing queue (1111) for input and a fourth data processing queue (1119) for output.

[0310] The operation of the third data processing queue (1111) and the fourth data processing queue (1119) can correspond to the first data processing queue (1101) and the second data processing queue (1119), respectively.

[0311] Figure 12b is an example of the internal structure of a data processing queue.

[0312] Referring to the drawing, data from the vehicle network (850) can be stored in internal memory (not shown) within each signal processing unit (170a to 170c).

[0313] That is, the data processing queue (1109a) of the vehicle network (850) can be matched and stored as a data processing queue (1111a) in the internal memory (not shown) within each signal processing device (170a~170c).

[0314] Meanwhile, a queue element within the data processing queue (1109a) may be provided with metadata (1130a) and a pointer (1132a) representing a memory area.

[0315] Meanwhile, metadata (1130a) and pointer (1132a) can be transmitted via the vehicle network (850) to an internal memory (not shown) within each signal processing unit (170a~170c) and matched with metadata (1130b) and pointer (1132b).

[0316] That is, through the vehicle network (850), actual data and metadata (1130a) can be transmitted to an internal memory (not shown) within each signal processing unit (170a~170c).

[0317] Figure 12b is another example of the internal structure of a data processing queue.

[0318] Referring to the drawing, data from each signal processing device (170a to 170c) can be stored in a storage device (925).

[0319] That is, the data processing queue (1109b) of each signal processing device (170a~170c) can be matched and stored as a data processing queue (1111b) within the storage device (925).

[0320] Meanwhile, the queue element within the data processing queue (1109b) can store the name and path of the data.

[0321] 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).

[0322] That is, metadata (1130a) is transmitted to a storage device (925) via a vehicle network (850), and actual data (1134a) can be transmitted via a shared namespace (810) and matched with data (1134b).

[0323] Figure 13 illustrates an example of processing in a data processing pipeline.

[0324] Referring to the drawing, the first data processing pipeline (842a) can be transmitted through the vehicle network (850) to at least some (170a, 170b) of each signal processing device (170a to 170c) and processed.

[0325] In the drawing, a first data processing pipeline (842a) is illustrated as comprising a plurality of elements, a color space conversion (1102) which is an example of first image processing, a chroma region deletion (1104) which is an example of second image processing, and an object classification (1106).

[0326] Meanwhile, the first processor (175a) can process some of the elements among the plurality of elements in 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 of the elements among the plurality of elements in the first data processing pipeline (842a) to be processed by other signal processing devices (170b, 170c).

[0327] In the drawing, color space conversion (1102), which is an example of first image processing, and chroma region deletion (1104), which is an example of second image processing, are examples of some elements within the first data processing pipeline (842a), and are processed in a graphics processor (179a) within the first signal processing unit (170a), and object classification (1106), which is another element, is processed in a neural network processor (177b) within the second signal processing unit (170b).

[0328] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control the result data of the completed object classification (1106) to be stored in a shared namespace (810) in the storage device (925).

[0329] 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).

[0330] Meanwhile, the second data processing pipeline (843a) may include a plurality of elements, an object check (1112), a video encoding (1114), and a data storage (1116).

[0331] For example, object check (1112) may be processed in the first central processor (175c) within the third signal processing unit (170c), video encoding (1114) may be processed in the video encoder (173c) within the third signal processing unit (170c), and data storage (1116) may be processed in the second central processor (178c) within the third signal processing unit (170c).

[0332] Figure 14 illustrates an example of processing in a data processing pipeline.

[0333] Referring to the drawing, the first data processing pipeline (872) can be transmitted through the vehicle network (850) to at least some (170a, 170b) of each signal processing device (170a to 170c) and processed.

[0334] In the drawing, the first data processing pipeline (872) is illustrated as having preprocessing (1202) and object detection (1206) with a plurality of elements.

[0335] Meanwhile, preprocessing (1202), which is a part element within the first data processing pipeline (872a), may be processed in a graphics processor (179a) within the first signal processing device (170a), and object detection (1206), which is another part element, may be processed in a neural network processor (177b) within the second signal processing device (170b).

[0336] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control the transmission of the result data, in which object detection (1206) is completed, to the second data processing pipeline (873).

[0337] Meanwhile, the second data processing pipeline (873) may be equipped with sensor fusion (1208) as an element.

[0338] Meanwhile, sensor fusion (1208) can be processed in a neural network processor (177c) within a third signal processing device (170c).

[0339] Meanwhile, the first processor (175a) in the first signal processing device (170a) can control the transmission of the result data of the sensor fusion (1208) to the third data processing pipeline (874).

[0340] Meanwhile, the third data processing pipeline (874) may be equipped with a vehicle control (1209) as an element.

[0341] Meanwhile, vehicle control (1209) can be processed in a central processor (175c) within a third signal processing unit (170c).

[0342] Meanwhile, the first processor (175a) in 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).

[0343] For example, the first processor (175a) within the first signal processing device (170a) can control the transmission path of the 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, the data can be processed efficiently.

[0344] Meanwhile, the first processor (175a) in the first signal processing device (170a) can vary the processing of elements in 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.

[0345] FIGS. 15a and 15b illustrate an example of processing in a time-critical based data processing pipeline.

[0346] FIG. 15a illustrates an example of the utilization rate of multiple vehicle networks.

[0347] Referring to the drawing, among the multiple vehicle networks, the utilization rate of the first vehicle network (850a) is approximately 90%, and the utilization rate of the second vehicle network (850b) may be approximately 0%.

[0348] 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 each be transmitted to the signal processing devices (170a~170c).

[0349] Meanwhile, preprocessing (1202), which is a part element within the first data processing pipeline (872), may be processed in a graphics processor (179a) within the first signal processing device (170a), and object detection (1206), which is another part element, may be processed in a neural network processor (177b) within the second signal processing device (170b).

[0350] Meanwhile, sensor fusion (1208) in the second data processing pipeline (873) can be processed in a neural network processor (177c) in the third signal processing device (170c).

[0351] Meanwhile, vehicle control (1209) in the third data processing pipeline (874) can be processed in the central processor (175c) in the third signal processing unit (170c).

[0352] FIG. 15b illustrates another example of the utilization rate of multiple vehicle networks.

[0353] Referring to the drawing, among the multiple vehicle networks, the utilization rate of the first vehicle network (850a) may be approximately 50%, and the utilization rate of the second vehicle network (850b) may be approximately 4%.

[0354] 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).

[0355] Meanwhile, preprocessing (1202), which is a part element within the first data processing pipeline (872), may be processed in a graphics processor (179a) within the first signal processing device (170a), and object detection (1206), which is another part element, may be processed in a neural network processor (177b) within the second signal processing device (170b).

[0356] Meanwhile, sensor fusion (1208) in the second data processing pipeline (873) can be processed in a neural network processor (177c) in the third signal processing device (170c).

[0357] Meanwhile, vehicle control (1209) in the third data processing pipeline (874) can be processed in the central processor (175c) in the third signal processing unit (170c).

[0358] FIGS. 16a through 17b illustrate various examples of processing in a non-time critical data processing pipeline.

[0359] First, FIG. 16a illustrates an example of a non-time-critical data processing pipeline.

[0360] Referring to the drawing, the first data processing pipeline (872) and the second data processing pipeline (873) that are not time-critical can be stored in a shared namespace (810) within the storage device (925).

[0361] 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).

[0362] Meanwhile, the result data processed by the graphics processor (179a) in the first signal processing device (170a) is stored in the preprocessing (1202), and the result data processed by the video encoder (173b) in the second signal processing device (170b) can be stored in the video encoding (1203).

[0363] Meanwhile, the result data processed by the central processor (175c) within 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) within the third signal processing device (170c), and the result data processed by the central processor (175c) can be stored in the private namespace (1310).

[0364] Next, Fig. 16b illustrates another example of a non-time-critical data processing pipeline.

[0365] 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~170c) via the vehicle network (850).

[0366] For example, preprocessing (1602), which is some element in the first data processing pipeline (872), may be processed in a graphics processor (179a) in the first signal processing unit (170a), and object detection (1604), which is another element, may be processed in a neural network processor (177b) in the second signal processing unit (170b).

[0367] Meanwhile, sensor fusion (1606) in the second data processing pipeline (873) can be processed in a neural network processor (177c) in the third signal processing device (170c).

[0368] Meanwhile, vehicle control (1608) in the third data processing pipeline (874) can be processed in the central processor (175c) in the third signal processing unit (170c).

[0369] FIG. 16c illustrates an example of storage device operation during the operation of FIG. 16b.

[0370] 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~170c) via the vehicle network (850).

[0371] For example, data for preprocessing (1602), which is a part element within the first data processing pipeline (872), is transmitted to a graphics processor (179a) within the first signal processing device (170a), and the graphics processor (179a) within the first signal processing device (170a) can perform preprocessing (1602).

[0372] Meanwhile, data for object detection (1604), which is another element within the first data processing pipeline (872), can be transmitted to and processed by a neural network processor (177b) within the second signal processing device (170b).

[0373] 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).

[0374] 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 namespace (810) in the storage device (925).

[0375] Meanwhile, the shared namespace (810) can store a data processing pipeline (1613) based on a data processing queue (1612).

[0376] Meanwhile, the neural network processor (177c) in the third signal processing device (170c) can receive the data processing pipeline (1613) stored in the storage device (925) and perform sensor fusion processing.

[0377] And, 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).

[0378] Meanwhile, the vehicle network (850) can transmit data for sensor fusion (1606) in the second data processing pipeline (873) to a shared namespace (810) in the storage device (925).

[0379] Accordingly, the shared namespace (810) within the storage device (925) can store data for sensor fusion (1606).

[0380] Meanwhile, the shared namespace (810) within the storage device (925) can store a data processing pipeline (1617) based on data for sensor fusion (1606) and result data of sensor fusion processing.

[0381] And, the shared namespace (810) in the storage device (925) can transfer data in the data processing pipeline (1617) to the central processor (175c) in the third signal processing device (170c).

[0382] The central processor (175c) in the third signal processing device (170c) can perform sensor data check (1618) processing based on the received data and control the result data to be stored in a shared namespace (810) in the storage device (925).

[0383] FIG. 16d illustrates another example of storage device operation during the operation of FIG. 16b.

[0384] Referring to the drawings, the operation of FIG. 16d is similar to the operation of FIG. 16c, but differs in 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).

[0385] FIGS. 17a and FIGS. 17b are drawings referenced in the operation description of FIG. 16d.

[0386] FIG. 17a illustrates the temporary suspension of the operation of the data processing pipeline within the storage device (925).

[0387] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in a first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0388] 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).

[0389] 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).

[0390] 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 namespace (810) in the storage device (925) (S1702).

[0391] Meanwhile, the shared namespace (810) within the storage device (925) can stop the operation of the data processing pipeline (1613) including internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including sensor data check (1618) (S1704).

[0392] Meanwhile, the first processor (175a) in the first signal processing device (170a) controls the second sensor data to be transmitted to a shared namespace (810) in the storage device (925) when processing of the second sensor data among the sensor data is delayed, and when the utilization rate of resources for processing the second sensor data is below a predetermined value, it can receive and process the second sensor data from the storage device (925). Accordingly, data can be processed efficiently.

[0393] Meanwhile, the first processor (175a) in 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 processing delay in the first data processing pipeline based on the first sensor data. Accordingly, data can be processed efficiently.

[0394] FIG. 17b illustrates the resumption of operation of a data processing pipeline within a storage device (925).

[0395] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in a first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0396] 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).

[0397] 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).

[0398] 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 namespace (810) in the storage device (925) (S1706).

[0399] Meanwhile, if the data stored in the data processing queue (1612) within the shared namespace (810) within the storage device (925) is greater than a predetermined value, the shared namespace (810) within the storage device (925) can resume the operation of the data processing pipeline (1613) including internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including sensor data check (1618) (S1708).

[0400] 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.

[0401] Meanwhile, when the utilization rate of the neural network processor (177b) in the second signal processing device (170b) is below a predetermined value, the shared namespace (810) in the storage device (925) can resume the operation of the data processing pipeline (1613) including internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including sensor data check (1618). Accordingly, data can be processed efficiently.

[0402] That is, the first processor (175a) in the first signal processing device (170a) checks 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, it can resume the processing of the second data processing pipeline (1613, 1617) based on the second sensor data. Accordingly, data can be processed efficiently.

[0403] Figure 18 is a diagram referenced to illustrate dynamic resource mapping.

[0404] Referring to the drawing, among each signal processing device (170a to 170c), the second signal processing device (170b) can process a plurality of data processing pipelines (842b, 843b, 844b).

[0405] Among the plurality of data processing pipelines (842b, 843b, 844b), the first data processing pipeline (842b) includes color space conversion (1102), which is an example of first image processing, and chroma region deletion (1104), which is an example of second image processing; the second data processing pipeline (843b) includes object classification (1106); and the third data processing pipeline (844b) may include object checking (1112) and video encoding (1114).

[0406] FIGS. 19a and FIGS. 19b are drawings referenced in the operation description of FIG. 18.

[0407] FIG. 19a illustrates the temporary suspension of the operation of the data processing pipeline within the storage device (925).

[0408] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in a first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0409] 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).

[0410] 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).

[0411] 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 namespace (810) in the storage device (925) (S1902).

[0412] Meanwhile, the shared namespace (810) within the storage device (925) can stop the operation of the data processing pipeline (1613) including internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including sensor data check (1618) (S1904). Accordingly, data can be processed efficiently.

[0413] FIG. 19b illustrates the resumption of operation of a data processing pipeline within a storage device (925).

[0414] Referring to the drawing, the vehicle network (840) transmits data for preprocessing (1602) to a graphics processor (179a) in a first signal processing device (170a), and the graphics processor (179a) in the first signal processing device (170a) can perform preprocessing (1602).

[0415] 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).

[0416] 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).

[0417] 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 namespace (810) in the storage device (925) (S1906).

[0418] Meanwhile, when the data stored in the data processing queue (1612) within the shared namespace (810) in the storage device (925) is greater than a predetermined value, the shared namespace (810) within the storage device (925) can resume the operation of the data processing pipeline (1613) including internal sensor fusion (1616), the data processing queue (1615), and the data processing pipeline (1617) including sensor data check (1618). Accordingly, data can be processed efficiently.

[0419] Although preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above. Various modifications are possible by those skilled in the art without departing from the essence of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical spirit or perspective of the present disclosure.

Claims

Claim 1 A signal processing device comprising: 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 a first sensor data among the sensor data and controls the second sensor data among the sensor data to be transmitted to the storage device. Claim 2 A signal processing device according to claim 1, wherein the processor processes time-critical data, which is the first sensor data among the sensor data, and controls the transmission of non-time-critical data, which is the second sensor data among the sensor data, to the storage device. Claim 3 In claim 1, the storage interface is a signal processing device that transmits the second sensor data to the shared namespace of the storage device. Claim 4 In claim 1, the processor is a signal processing device that executes a distributed lock manager for controlling the storage interface. Claim 5 In claim 1, the processor is a signal processing device that receives a first data processing pipeline for processing the first sensor data. Claim 6 In claim 1, the processor is a signal processing device that receives a second data processing pipeline for transmitting the second sensor data to the storage device. Claim 7 A signal processing device according to claim 1, wherein the processor 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 by another signal processing device. Claim 8 In paragraph 6, the processor is 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. Claim 9 A signal processing device according to claim 1, wherein the processor 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. Claim 10 In claim 6, the signal processing device wherein the first data processing pipeline comprises a first data processing queue for input and a second data processing queue for output. Claim 11 In paragraph 10, the first data processing queue or the second data processing queue is a signal processing device that transmits sensor data and metadata through a vehicle network. Claim 12 In claim 10, the signal processing device wherein the first data processing queue or the second data processing queue transmits sensor data through namespace sharing and transmits metadata through a vehicle network. Claim 13 A signal processing device according to claim 1, wherein the processor controls the transmission path of the 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. Claim 14 A signal processing device according to claim 1, wherein the processor varies 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 connected to the network interface. Claim 15 A signal processing device according to claim 1, wherein 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 processing delay, and 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. Claim 16 A signal processing device according to claim 1, wherein the processor controls the processing of the second data processing pipeline based on the second sensor data to be temporarily suspended when there is a processing delay of the first data processing pipeline based on the first sensor data. Claim 17 A signal processing device according to claim 1, wherein the processor checks the resource utilization rate at regular intervals after temporarily suspending the processing of the second data processing pipeline based on the second sensor data, and resumes the processing of the second data processing pipeline based on the second sensor data when the resource utilization rate is below a predetermined value. Claim 18 A signal processing device according to claim 1, wherein the processor 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 temporarily suspending the processing of the second data processing pipeline based on the second sensor data. Claim 19 A signal processing device according to claim 1, wherein the first sensor data includes lidar data or radar data, and the second sensor data includes black box data. Claim 20 A vehicle display device comprising: a display; a signal processing device for controlling the display; wherein the signal processing device comprises the signal processing device of claims 1 to 18.

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