A method and system for verifying the correspondence between automotive sensor data and automotive sensor data processing modules.

Abstract

This application relates to verifying the correspondence between automotive sensor data information and an automotive sensor data processing module. The automotive sensor data information indicates the capture characteristics of automotive sensor data. The automotive sensor data processing module is configured to generate intermediate data based on the automotive sensor data and adapt it to the automotive sensor data information. Furthermore, the automotive sensor data processing module is configured to provide the intermediate data to a vehicle control module. The vehicle control module is configured to control at least one of the lateral and longitudinal movements of the vehicle based on the intermediate data. If the correspondence between the automotive sensor data information and the automotive sensor data processing module is verified, the vehicle control module is enabled to control at least one of the lateral and longitudinal movements of the vehicle.

Description

Technical Field

[0001] This disclosure generally relates to the processing of automotive sensor data in a vehicle, and more specifically to verifying whether information relating to data captured by automotive sensors corresponds to an automotive module configured to receive and process the data captured by the automotive sensors. Background Technology

[0002] To assist the driver and / or at least partially control the vehicle by controlling one or both longitudinal and lateral movements, the vehicle includes multiple automotive sensors of various sensor types. The data captured by the multiple sensors exhibits various capture characteristics, such as typical capture errors for a given type of automotive sensor, which can be collectively referred to as error statistics. These capture characteristics can also be referred to as automotive sensor data information. The automotive sensor data is then processed by an automotive sensor data processing module, which may include, for example, an attitude estimator or an object detection function. The attitude estimator is configured to determine the vehicle's attitude based on positioning data, and the object detection function is configured to detect objects in the image data. To take into account the capture characteristics, each automotive processing module is configured to perform its respective function by processing the automotive sensor data in a manner that takes into account the automotive sensor data information. In other words, each automotive sensor data processing module is adapted to the capture characteristics of the various automotive sensors included in the vehicle, processing the automotive sensor data from these various sensors. Adaptation to the capture characteristics of the various automotive sensors included in the vehicle is particularly important if the corresponding automotive sensor data processing module is involved in at least partial control of the vehicle, as this adaptation enables more accurate and thus safer control of the vehicle.

[0003] Modern vehicles can be updated at dealerships or over the air, with updates including updates to the vehicle's sensor data processing module. Similarly, vehicle sensors can be replaced, for example, to upgrade the vehicle's data capture capabilities or to replace faulty sensors. Both updating the sensor data processing module and replacing sensors carry the risk of mismatches between the sensors and their data. That is, updating a vehicle may update the sensor data processing module to a version configured to process sensor data based on sensor data that does not correspond to the sensor data of the corresponding sensors included in the vehicle. Likewise, replacing sensors may result in the vehicle including sensors with sensor data that does not correspond to the sensor data on which the processing by the vehicle's sensor data processing module is based. These situations may lead to reduced accuracy in at least some of the vehicle's control, potentially compromising the safety of at least some of the control.

[0004] Therefore, the purpose of this disclosure is to verify the correspondence between automotive sensor data information and automotive sensor data processing module within a vehicle. Summary of the Invention

[0005] To achieve this objective, this disclosure provides a method for verifying the correspondence between automotive sensor data information and an automotive sensor data processing module. The method includes acquiring automotive sensor data information. The automotive sensor data information indicates the capture characteristics of automotive sensor data. The method also includes acquiring the automotive sensor data processing module. The automotive sensor data processing module is configured to generate intermediate data based on the automotive sensor data and adapt it to the automotive sensor data information. The automotive sensor data processing module is further configured to provide the intermediate data to a vehicle control module. The vehicle control module is configured to control at least one of the lateral and longitudinal movements of the vehicle based on the intermediate data. The method further includes verifying the correspondence between the automotive sensor data information and the automotive sensor data processing module. Finally, if the correspondence is verified, the method includes enabling the vehicle control module to control at least one of the lateral and longitudinal movements of the vehicle.

[0006] This disclosure also provides an automotive control unit. The automotive control unit includes at least one processing unit and a memory coupled to the at least one processing unit and configured to store machine-readable instructions. The machine-readable instructions cause the at least one processing unit to acquire automotive sensor data information. The automotive sensor data information indicates the acquisition characteristics of automotive sensor data. The machine-readable instructions also cause the at least one processing unit to acquire an automotive sensor data processing module. The automotive sensor data processing module is configured to generate intermediate data based on the automotive sensor data and adapt it to the automotive sensor data information. The automotive sensor data processing module is also configured to provide the intermediate data to a vehicle control module. The vehicle control module is configured to control at least one of the lateral and longitudinal movements of the vehicle based on the intermediate data. The machine-readable instructions also cause the at least one processing unit to verify the correspondence between the automotive sensor data information and the automotive sensor data processing module. Finally, if the correspondence is verified, the machine-readable instructions further cause the at least one processing unit to enable the vehicle control module to control at least one of the lateral and longitudinal movements of the vehicle.

[0007] This disclosure also provides a vehicle including an automotive control unit. Attached Figure Description

[0008] Examples of this disclosure will be described with reference to the following figures, in which the same reference numerals refer to the same elements.

[0009] Figure 1 A flowchart illustrating a method for verifying the correspondence between vehicle sensor data information and vehicle sensor data processing module, according to an example of this disclosure, is shown.

[0010] Figure 2 The illustration shows an example vehicle according to this disclosure.

[0011] Figure 3 An example of an automotive control unit according to this disclosure is illustrated.

[0012] It should be understood that the accompanying drawings identified above are by no means intended to limit this disclosure. Rather, these drawings are provided to aid in the understanding of this disclosure. Those skilled in the art will readily understand that aspects of this disclosure illustrated in one drawing may be combined with aspects in another drawing, or may be omitted, without departing from the scope of this disclosure. Detailed Implementation

[0013] Modern vehicles include multiple automotive sensors to capture sensor data indicative of the vehicle's environment. However, automotive sensor data typically does not provide an accurate indication of the vehicle's environment. For example, each automotive sensor may capture corresponding sensor data at specific time intervals, resulting in sensor data that is accurate only within each capture instance, but may only provide an approximation of the environment outside of those instances. Furthermore, each automotive sensor may capture data indicative of the environment at a specific resolution, resulting in sensor data that is accurate only at each capture location, but may only provide an approximation of the environment between capture locations. Additionally, each automotive sensor may capture sensor data with statistical errors, resulting in sensor data that typically only provides an approximation of the environment.

[0014] In order to take into account the fact that automotive sensor data may at least partially indicate only an approximation of the vehicle environment, in the context of this disclosure, automotive sensor data is processed in a manner that takes into account the capture characteristics of each automotive sensor. To this end, in the context of this disclosure, automotive sensor data is processed based on automotive sensor data information, which may include any kind of information about the capture characteristics of the automotive sensor data, based on how the respective automotive sensor is configured to capture automotive sensor data, such as capture time intervals, sensor resolution, and error statistics.

[0015] During the vehicle's lifespan, automotive sensors can be replaced with sensors having different capture characteristics than the replaced sensors. Furthermore, the automotive sensor data processing module can be updated to assume that the capture characteristics of the vehicle's sensors differ from the vehicle's actual capture characteristics. Given that the processing of automotive sensor data in the vehicle needs to be based on the most accurate possible perception of the vehicle's environment, control of the vehicle's lateral and longitudinal movements can only be performed when the vehicle's automotive sensor data processing module processes the automotive sensor data according to its capture characteristics and therefore according to the capture characteristics of the automotive sensors included in the vehicle—that is, based on the automotive sensor data and the corresponding automotive sensor data information. Therefore, in the context of this disclosure, control of the vehicle's lateral and / or longitudinal movements is only enabled when the correspondence between the automotive sensor data information and the automotive sensor data processing module is verified.

[0016] This general concept will be explained with reference to the accompanying drawings, in which... Figure 1 A flowchart is provided for a method 100 for verifying the correspondence between automotive sensor data and automotive sensor data processing modules. Furthermore, Figure 2 The illustration shows a vehicle according to this disclosure, and Figure 3 The illustration shows a car controller configured to execute method 100.

[0017] It should be understood that, Figure 1 The dashed box in the diagram illustrates the optional steps of method 100.

[0018] Method 100 is configured to verify the correspondence between vehicle sensor data information and vehicle sensor data processing module in a vehicle configured to at least enable driver assistance.

[0019] Brief Turn Figure 2 In the context of this disclosure, "vehicle 200" and more generally, "vehicle" refers to any kind of motor vehicle configured to transport persons and / or goods. The motor of vehicle 200 can be any kind of motor, such as an electric motor or an internal combustion engine. Vehicle 200 can be, for example, a motor... Figure 2 The passenger vehicle shown is an example. However, it should be understood that vehicle 200 can also be a bus, truck, or any other type of vehicle including one or more sensors 210 and a vehicle control unit 300, which enables vehicle 200 to provide at least assisted driving. In other words, vehicle control unit 300 and one or more sensors 210 are configured to enable one or more vehicle control modules of vehicle 200 to provide vehicle control functions capable of at least assisted driving, i.e., Level 1 of the driving automation classification as defined in SAE International standard J3016. That is, one or more vehicle control modules can be configured to control at least one of the lateral and longitudinal movements of vehicle 200 under the supervision of the driver of vehicle 200, based on vehicle sensor data provided by one or more sensors 210.

[0020] It should be understood that Level 1 driving automation is the lowest level of driving automation that vehicle 200 can perform. Vehicle 200 can be configured to enable higher levels of driving automation, such as partial driving automation, i.e., Level 2 or higher of the driving automation classification defined in SAE International standard J3016. That is, one or more vehicle control modules can be configured to control both the lateral and longitudinal movements of vehicle 200 under the supervision of the driver of vehicle 200, based on vehicle sensor data provided by one or more sensors 210.

[0021] In light of the foregoing discussion of various levels of driving automation, it should be understood that, in the context of this disclosure, the expression "vehicle control module" can refer to any type of control module configured to control at least one of the lateral and longitudinal movements of vehicle 200 based on vehicle sensor data. One or more vehicle control modules can be, for example, an advanced cruise control (ACC) function, a Level 3 function for a specific operating environment, such as an automated driving function limited to closed highways and driving speeds less than 100 kph, or a function enabling full driving automation, i.e., Level 5 of the driving automation classification as defined in SAE International standard J3016, or a sub-function of such a Level 5 function.

[0022] One or more sensors 210 are configured to capture automotive sensor data indicative of the environment of vehicle 200. Therefore, the automotive sensor data provides environmental perception to one or more vehicle control modules and thereby to vehicle 200 to enable at least assisted driving. For example, the automotive sensor data captured by one or more sensors 210 can provide vehicle 200 with information about the position and size of other vehicles, road surface markings, or traffic signs. For this purpose, one or more sensors 210 can be radar sensors, which can be configured to emit radio waves to determine the distance, angle, and speed of objects around the vehicle based on the reflected radio waves. One or more sensors 210 can be light detection and ranging (LIDAR) sensors, which are configured to emit laser beams to determine the distance, angle, and speed of objects around vehicle 200 based on the reflected laser beams. One or more sensors 210 can be cameras, which capture images of the vehicle's environment. One or more sensors 210 can be thermal imaging cameras, which capture images of the vehicle 200's environment based on infrared radiation. It should be understood that the LIDAR sensor, radar sensor, or camera are provided only as examples of sensor types for one or more sensors 210. For example, one or more sensors 210 may also be ultrasonic sensors. One or more sensors 210 may be Global Navigation Satellite System (GNSS) sensors, configured to receive position data, such as satellite signals, to determine the position of vehicle 200. More generally, one or more sensors 210 may be any type of sensor capable of capturing automotive sensor data indicative of the environment of vehicle 200. It should also be understood that one or more sensors 210 may include multiple sensors of various types. Furthermore, one or more sensors 210 of the same type may exhibit different properties, for example, by being configured to capture automotive sensor data at different ranges, such as short-range, medium-range, and long-range. For example, vehicle 200 may include three short-range radar sensors each at the front and rear of vehicle 200; a medium- to long-range radar sensor at the rear of vehicle 200; a LiDAR sensor at the front of vehicle 200; a rear-facing camera at the rear of vehicle 200; a forward-facing camera at the front of vehicle 200; a forward-facing camera at the rearview mirror; and a rear-facing short- to medium-range radar sensor in the exterior rearview mirror mounted in each door. It should be understood that vehicle 200 may include more than... Figure 2 The car sensors shown and discussed in the examples above have more or fewer car sensors.

[0023] As described above, vehicle sensor data provides environmental perception to one or more vehicle control modules. For this purpose, the vehicle sensor data needs to be processed to extract environmental information. The vehicle sensor data can be raw sensor data or sensor data that has already been preprocessed by a given vehicle sensor, for example, by applying a filter or some other preprocessing step to the raw sensor data. Raw sensor data refers to the sensor data captured by a given vehicle sensor. Examples of preprocessing applied to a given vehicle sensor can include upsampling, downsampling, or any other type of filtering. Instead of each vehicle control module extracting environmental information individually, resulting in one or more vehicle control modules performing the same or similar repetitive processing on the vehicle sensor data, the extraction of environmental information from the vehicle sensor data is performed by one or more vehicle sensor data processing modules. Therefore, one or more vehicle sensor data processing modules are configured to generate intermediate data based on the vehicle sensor data and provide the intermediate data to one or more vehicle control modules. Thus, the intermediate data represents the environmental information obtained by processing the vehicle sensor data captured by one or more vehicle sensors 210.

[0024] To provide an example of one or more automotive sensor data processing modules, they may, for example, include an object detection module configured to detect one or more objects near vehicle 200. That is, the object detection module can process automotive sensor data, such as sensor data captured by LiDAR sensors and / or various cameras, to detect objects near vehicle 200 and generate an object list including the detected objects. The object list may also include additional information, including but not limited to the type of each object in the object list, such as a vulnerable road user (VRU) or vehicle, and the relative distance of each object in the object list relative to vehicle 200. In this example, the intermediate data is an object list generated based on automotive sensor data indicating objects near vehicle 200. The object list can then be used by one or more vehicle control modules to determine vehicle control, such as an autonomous emergency braking module determining to stop vehicle 200 to avoid collisions with objects detected in the travel path of vehicle 200.

[0025] If the object detection module only provides a list of detected objects, other automotive sensor data processing modules can determine the type of each object and / or the relative distance of the object to the vehicle 200. To determine this information, such automotive sensor data processing modules can process intermediate data generated by other automotive sensor data processing modules, in addition to processing automotive sensor data or instead of processing automotive sensor data. That is, while configured to generate intermediate data based on automotive sensor data, the automotive sensor data processing module can also generate intermediate data by processing intermediate data generated by other automotive sensor data processing modules.

[0026] One or more vehicle sensor data processing modules may further include an attitude estimation module configured to estimate the position of vehicle 200. The attitude estimation module may receive data from one or more GNSS sensors and / or data from one or more cellular communication interfaces and other sensors, and may process data from one or more sources to determine the position and orientation of vehicle 200. Therefore, intermediate data may be position data generated based on vehicle sensor data indicating the position of vehicle 200.

[0027] As can be seen from these examples, intermediate data in the context of this disclosure should be understood as any kind of data indicating the environment of vehicle 200, which has been inferred from vehicle sensor data captured by one or more vehicle sensors 210. The intermediate data is then used by one or more vehicle control modules to control at least one of the longitudinal and lateral movements of vehicle 200.

[0028] In summary, one or more vehicle sensors 210 capture vehicle sensor data indicating the environment of vehicle 200. This vehicle sensor data can be raw sensor data or pre-processed sensor data, which is then processed by one or more vehicle sensor data processing modules to generate intermediate data, including information about the environment inferred from the vehicle sensor data. Finally, one or more vehicle control modules control at least one of the longitudinal and lateral movements of vehicle 200 based on the environmental information provided by the intermediate data. Therefore, the vehicle sensors 210, one or more vehicle sensor data processing modules, and one or more vehicle control modules can be considered a data processing chain configured to process vehicle sensor data and generate vehicle control data via the intermediate data.

[0029] It should be understood that one or more automotive sensor data processing modules and one or more vehicle control modules may each be implemented as software modules executing on the automotive control unit 400, which will be discussed with reference to Figure 5, or may each be implemented as separate hardware modules, such as application-specific integrated circuits (ASICs) or field-programmable gate arrays (FPGAs).

[0030] As described above, vehicle sensor data provides environmental perception. However, given that vehicle sensor data provides a digital representation of the environment of vehicle 200, it inherently provides only an approximation of the environment of vehicle 200. This approximation of the environment of vehicle 200 is based on the capture characteristics of each vehicle sensor 210; that is, the capture characteristics of each vehicle sensor 210 determine the accuracy of the environmental perception provided by the vehicle sensor 210. To consider the approximation of the environment of vehicle 200 when processing vehicle sensor data, one or more vehicle sensor data processing modules are configured to consider vehicle sensor data information, i.e., data indicating the capture characteristics of the vehicle sensor data of the corresponding vehicle sensor 210. For example, the capture characteristics of the vehicle sensor data may include statistics of the vehicle sensor data of the corresponding vehicle sensor 210, which may include, for example, a 3σ value and a maximum error duration value. The one or more vehicle sensor data processing modules processing the vehicle sensor data of the corresponding vehicle sensor 210 consider the statistics when generating intermediate data; that is, they generate intermediate data in a manner that compensates for any statistical errors in the vehicle sensor data caused by the capture characteristics of the vehicle sensors. In another example, the vehicle sensor data information may indicate the time interval or sensor resolution at which a given vehicle sensor 210 captures vehicle sensor data.

[0031] More generally, automotive sensor data should therefore be understood as any kind of data indicating the capture characteristics of a given automotive sensor 210 and thus an approximation of the environment of the vehicle 200. Based on the automotive sensor data, one or more automotive sensor data processing modules are therefore configured to generate intermediate data in a manner that compensates for the approximation of the environment, thereby providing more accurate environmental perception to one or more vehicle control modules. One or more automotive sensor processing modules therefore process the automotive sensor data to generate intermediate data in a manner adapted to the automotive sensor data information.

[0032] In addition to indicating the capture characteristics of a given vehicle sensor 210, the vehicle sensor data information can also indicate how the vehicle sensor data is provided to one or more vehicle sensor data processing modules. That is, the vehicle sensor data information can additionally indicate how an approximation of the environment is structured to enable one or more vehicle sensor data processing modules to process the vehicle sensor data. Furthermore, the vehicle sensor data information can indicate processing parameters that define how the vehicle sensor data can be processed by one or more vehicle sensor data processing modules.

[0033] Since the processing of vehicle sensor data by one or more vehicle sensor data processing modules is adapted to the vehicle sensor data information of each vehicle sensor 210, it is necessary to ensure that one or more vehicle sensor data processing modules have been adapted to the vehicle sensor data information. To this end, method 100 verifies the correspondence between the vehicle sensor data information of vehicle sensor 210 and one or more vehicle sensor data processing modules. In other words, method 100 checks for each vehicle sensor data processing module whether it has been adapted to the vehicle sensor data information of each vehicle sensor 210 that processes the vehicle sensor data of each vehicle sensor 210. Therefore, the expression of correspondence in the context of this disclosure should be understood to refer to the fact that the processing of a given vehicle sensor data processing module has been adapted to the capture characteristics of one or more vehicle sensors that receive data. If there is no correspondence, then a given vehicle sensor data processing module therefore receives vehicle sensor data from vehicle sensor 210, and the processing of that given vehicle sensor data processing module has not yet been adapted to the capture characteristics of vehicle sensor 210. Therefore, method 100 ensures that one or more processing modules generate intermediate data based solely on the vehicle sensor data of the vehicle sensor, and that one or more processing modules have been adapted to the vehicle sensor data information of the vehicle sensor.

[0034] In step 110, method 100 acquires vehicle sensor data information. Method 100 may acquire the vehicle sensor data, for example, whenever the vehicle sensor data information of a given vehicle sensor 210 changes, such as during a firmware update of the given vehicle sensor 210. That is, a firmware update of the given vehicle sensor 210 may change the capture characteristics, the structuring of the vehicle sensor data, and / or the processing parameters of the given vehicle sensor 210. Method 100 may also acquire the vehicle sensor data information during the installation or replacement of the given vehicle sensor 210. Method 100 may also acquire the vehicle sensor data information by retrieving the vehicle sensor data information from the memory of the vehicle 200 during the activation of the vehicle 200. Therefore, step 110 may include one of steps 111 and 112. In step 111, method 100 may update the vehicle sensor data information. In step 110, method 100 may install the vehicle sensor data information when the vehicle sensor is installed in the vehicle.

[0035] In step 120, method 100 acquires the vehicle sensor data processing module. Similar to step 110, method 100 may acquire the vehicle sensor data processing module when it is updated, such as during an over-the-air (OTA) update, or otherwise provided to vehicle 200. Method 100 may also acquire the vehicle sensor data processing module by retrieving it from the memory of vehicle 200 during vehicle 200's on-time. Therefore, step 120 may include step 121, in which method 100 updates the vehicle sensor data processing module.

[0036] Whenever the vehicle sensor data information and / or one or more vehicle sensor data processing modules change, steps 110 and 120 can be executed based on a predetermined time interval, or whenever the vehicle 200 is turned on, and thus method 100 is executed.

[0037] Method 100 may include step 130, in which method 100 acquires vehicle sensor data processing module verification data and vehicle sensor data information verification data. In other words, to facilitate verification of the correspondence between vehicle sensor data information and one or more vehicle sensor data processing modules, method 100 may acquire data that identifies the vehicle sensor data information and the vehicle sensor data processing modules, respectively, in some examples of method 100. This data may be used during step 142 to verify the correspondence between the vehicle sensor data information and one or more vehicle sensor data processing modules. The vehicle sensor data processing module verification data and the vehicle sensor data information verification data may each include at least one of a public key, a verification certificate, and a version number.

[0038] In step 140, method 100 verifies the correspondence between vehicle sensor data and one or more vehicle sensor data processing modules. As discussed above, this step ensures that one or more vehicle sensor data processing modules generate intermediate data based on the vehicle sensor data, and that the one or more vehicle sensor data processing modules are adapted to the capture characteristics of the vehicle sensor data. This further ensures that one or more vehicle control modules receive intermediate data that provides correct environmental perception, thereby enabling accurate control of vehicle 100.

[0039] To verify the correspondence in step 140, one or more vehicle sensor data processing modules can be configured to provide correspondence data indicating desired vehicle sensor data information. Therefore, in the following example of this disclosure, where one or more vehicle sensor data processing modules are configured to provide correspondence data, step 140 may include step 141, in which method 100 compares the desired vehicle sensor data information with the vehicle sensor data information.

[0040] Furthermore, in the example of this disclosure, method 100 includes step 130, and step 140 may also include step 142, in which method 100 compares vehicle sensor data processing module verification data and vehicle sensor data information verification data to verify the correspondence between vehicle sensor data information and one or more vehicle sensor data processing modules.

[0041] Finally, if the correspondence is verified in step 140, then in step 150, method 100 enables one or more vehicle control modules to control at least one of the lateral and longitudinal movements of the vehicle. That is, one or more vehicle control modules are enabled to control the vehicle 100 only if the intermediate data is generated based on vehicle sensor data captured with capture characteristics adapted to one or more vehicle processing units.

[0042] In summary, method 100 verifies whether one or more vehicle sensor data processing modules receive vehicle sensor data adapted for processing. Only if this is the case is one or more vehicle control modules activated to control vehicle 100.

[0043] It should be understood that method 100 may be deployed in vehicle 100 during the development and manufacturing of vehicle 100 and / or after delivery of vehicle 100.

[0044] Figure 3An automotive control unit 300 configured to perform method 100 is shown. The automotive control unit 300 may include a processor 310, a graphics processing unit (GPU) 320, an automotive processing system 330, a memory 340, a removable storage device 350, a storage device 360, a cellular interface 370, a Global Navigation Satellite System (GNSS) interface 380, and a communication interface 390.

[0045] Processor 310 can be any type of single-core or multi-core processing unit employing Reduced Instruction Set Computing (RISC) or Complex Instruction Set Computing (CISC). Example RISC processing units include ARM-based cores or RISC V-based cores. Example CISC processing units include x86-based cores or x86-64-based cores. Processor 310 can execute instructions that cause vehicle control unit 300 to perform method 100. Processor 310 can be directly coupled to any component of vehicle control unit 300, or it can be directly coupled to memory 330, GPU 320, and device bus.

[0046] GPU 320 can be any kind of processing unit optimized for processing graphics-related instructions or, more generally, for parallel processing of instructions. Thus, GPU 320 can be configured to generate information displays for the vehicle's driver, such as ADAS information or telemetry data, for example via a head-up display (HUD) or a display positioned within the driver's field of vision. GPU 320 can be coupled to the HUD and / or the display via connection 320C. GPU 320 can also execute at least a portion of method 100 to enable rapid parallel processing of instructions related to method 100. It should be noted that in some embodiments, processor 310 can determine that GPU 320 does not need to execute instructions related to method 100. GPU 320 can be directly coupled to any component of the vehicle control unit 300, or it can be directly coupled to processor 310 and memory 330. In some embodiments, GPU 320 can also be coupled to a device bus.

[0047] The automotive processing system 330 can be any type of system-on-a-chip configured to provide trillions of operations per second (TOPS) to enable the automotive control unit 300 to implement one or more ADAS during driving. The automotive processing system 330 may interface only with the processor 310, or it may interface with other devices via a system bus. The automotive processing system 330 can, for example, execute instructions related to one or more automotive sensor data processing modules and one or more vehicle control modules.

[0048] Memory 340 can be any type of high-speed storage device, enabling processor 310, GPU 320, and automotive processing system 330 to store instructions for fast retrieval during instruction processing, as well as cache and buffer data. Memory 340 can be a unified memory coupled to processor 310, GPU 320, and automotive processing system 330 to enable on-demand allocation of memory 340 to processor 310, GPU 320, and automotive processing system 330. Alternatively, processor 310, GPU 320, and automotive processing system 330 can be coupled to separate processor memory 340a, GPU memory 340b, and automotive processing system memory 340c.

[0049] The removable storage device 350 can be a storage device capable of being removably coupled to the vehicle control unit 300. Examples include a digital multifunction disc (DVD), an optical disc (CD), a universal serial bus (USB) storage device such as an external SSD, or a magnetic tape. It should be noted that the removable storage device 350 can store data, such as instructions of method 100, vehicle sensor data, intermediate data, and / or vehicle control data, or may be omitted.

[0050] Storage device 360 ​​can be a storage device that enables the storage of program instructions and other data. For example, storage device 360 ​​can be a hard disk drive (HDD), a solid-state drive (SSD), or some other type of non-volatile memory. For example, storage device 360 ​​can store instructions of method 100, vehicle sensor data, intermediate data, and / or vehicle control data.

[0051] Removable storage devices 350 and 360 can be coupled to processor 310 via a system bus. The system bus can be any kind of bus system that enables processor 310, and optionally GPU 420 and automotive processing system 330, to communicate with other devices of automotive control unit 300. Bus 340 can be, for example, a Peripheral Component Interconnect High Speed ​​(PCIe) bus or a Serial AT Accessory (SATA) bus.

[0052] The cellular interface 370 can be any kind of interface that enables the vehicle control unit 300 to communicate via a cellular network, such as a 4G network or a 5G network.

[0053] The GNSS interface 380 can be any kind of interface that enables the vehicle control unit 300 to receive location data provided by a satellite network, such as Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), or Galileo. The location data can be one of the types of vehicle sensor data in the context of this disclosure.

[0054] Communication interface 390 enables the vehicle control unit 300 to interface with external devices directly or via a network through connection 380C. Communication interface 380 can, for example, enable the vehicle control unit 300 to couple to wired or wireless networks, such as Ethernet, Wi-Fi, Controller Area Network (CAN) bus, or any suitable bus system in the vehicle. For example, the vehicle control unit 300 can couple to one or more sensors 210 to receive vehicle sensor data, which is then processed by the processing chain if the correspondence between the vehicle sensor data information and the vehicle sensor data processing module is verified by method 100.

[0055] The vehicle control unit 300 can be integrated with the vehicle 200, for example, under the passenger compartment, under the dashboard, or in the trunk of the vehicle 200.

[0056] This disclosure can also be illustrated by the following examples.

[0057] In the example, the method for verifying the correspondence between vehicle sensor data information and the vehicle sensor data processing module includes acquiring the vehicle sensor data information. The vehicle sensor data information indicates the capture characteristics of the vehicle sensor data. The example method also includes acquiring the vehicle sensor data processing module. The vehicle sensor data processing module is configured to generate intermediate data based on the vehicle sensor data and adapt it to the vehicle sensor data information. The vehicle sensor data processing module is also configured to provide the intermediate data to a vehicle control module. The vehicle control module is configured to control at least one of the lateral and longitudinal movements of the vehicle based on the intermediate data. The example method also includes verifying the correspondence between the vehicle sensor data information and the vehicle sensor data processing module. Finally, the example method includes enabling the vehicle control module to control at least one of the lateral and longitudinal movements of the vehicle if the correspondence is verified.

[0058] In the example method, the capture characteristics of vehicle sensor data can include statistical information about the sensor data of the vehicle sensors.

[0059] In the example method, the statistics may include at least one of the 3σ value and the maximum error duration value.

[0060] In the example method, verifying the correspondence between vehicle sensor data and the vehicle sensor data processing module may include comparing the desired vehicle sensor data with the vehicle sensor data, and the vehicle sensor data processing module may be configured to provide correspondence data indicating the desired vehicle sensor data.

[0061] The example method may also include obtaining vehicle sensor data processing module verification data and vehicle sensor data information verification data, wherein verifying the correspondence between vehicle sensor data information and vehicle sensor data processing module may include comparing vehicle sensor data processing module verification data and vehicle sensor data information verification data.

[0062] In the example method, the vehicle sensor data processing module verification data and the vehicle sensor data information verification data may each include at least one of the following: public key, verification certificate, and version number.

[0063] In the example method, obtaining the vehicle sensor data processing module may include updating the vehicle sensor data processing module.

[0064] In the example method, obtaining vehicle sensor data information may include at least one of updating vehicle sensor data information and installing vehicle sensor data information when installing vehicle sensors in the vehicle.

[0065] In the example method, the vehicle sensor data processing module can be at least one of an attitude estimation module and an object detection module, wherein the attitude estimation module is configured to estimate the position of the vehicle and the object detection module is configured to detect one or more objects near the vehicle.

[0066] In the example method, the vehicle sensor can be at least one of the following: a Global Navigation Satellite System (GNSS) sensor configured to receive location data, an infrared camera, a Light Detection and Ranging (LIDAR) sensor, and multiple cameras forming a stereo camera system.

[0067] The example vehicle control unit includes at least one processing unit and a memory coupled to the at least one processing unit and configured to store example machine-readable instructions. The example machine-readable instructions cause the at least one processing unit to acquire vehicle sensor data information. The vehicle sensor data information indicates the capture characteristics of vehicle sensor data. The example machine-readable instructions also cause the at least one processing unit to acquire a vehicle sensor data processing module. The vehicle sensor data processing module is configured to generate intermediate data based on the vehicle sensor data and adapt it to the vehicle sensor data information. The vehicle sensor data processing module is also configured to provide the intermediate data to a vehicle control module. The vehicle control module is configured to control at least one of the lateral and longitudinal movements of the vehicle based on the intermediate data. The example machine-readable instructions also cause the at least one processing unit to verify the correspondence between the vehicle sensor data information and the vehicle sensor data processing module. If the correspondence is verified, the example machine-readable instructions further cause the at least one processing unit to enable the vehicle control module to control at least one of the lateral and longitudinal movements of the vehicle.

[0068] In the example vehicle control unit, the example machine-readable instructions can also cause at least one processing unit to perform any of the aforementioned example methods.

[0069] The example vehicle includes any of the aforementioned example vehicle control units.

[0070] The foregoing is provided to illustrate the verification of the correspondence between automotive sensor data information and the automotive sensor data processing module. It should be understood that this description is in no way intended to limit the scope of this disclosure to the precise embodiments discussed throughout. Rather, those skilled in the art will recognize that examples of this disclosure can be combined, modified, or reduced without departing from the scope of this disclosure as defined by the appended claims. List of reference numerals 100 Method 110-150 Method Steps 200 Vehicle 210 Vehicle Sensors 220 Lights 300 Vehicle Control Unit 310 CPU 320 GPU 320c Connection 330 Vehicle Processing System 340 Memory 350 Removable Storage Device 360 ​​Storage Device 370 Cellular Interface 380 GNSS Interface 390 Communication Interface

Claims

1. A method (100) for verifying the correspondence between vehicle sensor data and vehicle sensor data processing module, comprising: Acquire (110) the vehicle sensor data information, which indicates the vehicle sensor data capture characteristics of the vehicle sensor (210); The vehicle sensor data processing module (120) is configured to generate intermediate data based on and adapted to the vehicle sensor data information, and to provide the intermediate data to a vehicle control module, which is configured to control at least one of the lateral and longitudinal movements of the vehicle (200) based on the intermediate data. Verify (140) the correspondence between the vehicle sensor data information and the vehicle sensor data processing module; as well as If the correspondence is verified, the vehicle control module (150) is enabled to control at least one of the lateral movement and the longitudinal movement of the vehicle (200).

2. The method (100) according to claim 1, wherein the capture characteristics of the vehicle sensor data include statistical information of the vehicle sensor data.

3. The method (100) according to claim 2, wherein the statistical information includes at least one of the 3σ value and the maximum error duration value.

4. The method (100) according to any one of the preceding claims, wherein: Verifying the correspondence between the vehicle sensor data information and the vehicle sensor data processing module includes: comparing the desired vehicle sensor data information with the vehicle sensor data information. The vehicle sensor data processing module is configured to provide correspondence data indicating the desired vehicle sensor data information.

5. The method (100) according to any one of the preceding claims, wherein: The method further includes: acquiring (130) vehicle sensor data processing module verification data and vehicle sensor data information verification data; Verifying the correspondence between the vehicle sensor data information and the vehicle sensor data processing module (140) includes comparing the verification data of the vehicle sensor data processing module and the verification data of the vehicle sensor data information.

6. The method (100) according to claim 5, wherein the vehicle sensor data processing module verification data and the vehicle sensor data information verification data each include at least one of the following: public key, verification certificate and version number.

7. The method (100) according to any one of the preceding claims, wherein acquiring (120) the vehicle sensor data processing module comprises: Update (121) the vehicle sensor data processing module.

8. The method (100) according to any one of the preceding claims, wherein obtaining (110) the vehicle sensor data information includes at least one of the following: updating (111) the vehicle sensor data information and installing (112) the vehicle sensor data information when installing the vehicle sensor in the vehicle.

9. The method (100) according to any one of the preceding claims, wherein, The vehicle sensor data processing module is at least one of an attitude estimation module and an object detection module, the attitude estimation module being configured to estimate the position of the vehicle (200), and the object detection module being configured to detect one or more objects near the vehicle.

10. The method (100) according to any one of the preceding claims, wherein, The vehicle sensor (210) is at least one of the following: a Global Navigation Satellite System (GNSS) sensor, an infrared camera, a Light Detection and Ranging (LIDAR) sensor, and a plurality of cameras forming a stereo camera system, wherein the GNSS sensor is configured to receive position data.

11. A vehicle control unit (300), comprising: At least one processing unit (310, 320, 330); as well as Memory (340, 350, 360), said memory coupled to said at least one processing unit (310, 320, 330) and configured to store machine-readable instructions, Wherein, the machine-readable instructions cause the at least one processing unit to: Acquire vehicle sensor data information, wherein the vehicle sensor data information indicates the vehicle sensor data capture characteristics of the vehicle sensor (210); The vehicle sensor data processing module is configured to generate intermediate data based on and adapted to the vehicle sensor data information, and to provide the intermediate data to a vehicle control module, which is configured to control at least one of the lateral and longitudinal movements of the vehicle (200) based on the intermediate data. Verify the correspondence between the vehicle sensor data and the vehicle sensor data processing module; If the correspondence is verified, the vehicle control module is enabled to control at least one of the lateral movement and the longitudinal movement of the vehicle (200).

12. The vehicle control unit (300) of claim 11, wherein the machine-readable instructions further cause the at least one processing unit (310, 320, 330) to perform the method according to any one of claims 2 to 10.

13. A vehicle (200) comprising a vehicle control unit according to any one of claims 11 and 12.

Images