Method and system for verifying the correspondence between motor vehicle sensor data information and a motor vehicle sensor data processing module

Abstract

The present application relates to verifying a match between motor vehicle sensor data information and a motor vehicle sensor data processing module. The motor vehicle sensor data information indicates the detection characteristics of the motor vehicle sensor data of a motor vehicle sensor. The motor vehicle sensor data processing module is configured to generate intermediate data based on the motor vehicle sensor data and adapted to the motor vehicle sensor data information. Furthermore, the motor vehicle sensor data processing module is configured to provide the intermediate data to a vehicle control module. The vehicle control module is configured to control a lateral and / or longitudinal movement of a vehicle based on the intermediate data.If the match between the vehicle sensor data information and the vehicle sensor data processing module is verified, the vehicle control module is enabled to control the lateral and / or longitudinal movements of the vehicle.

Description

TECHNICAL FIELD

[0001] The invention relates generally to processing automotive sensor data in a vehicle, and more particularly to verifying whether information relating to data sensed by an automotive sensor corresponds to an automotive module configured to receive and process the data sensed by the automotive sensor. BACKGROUND

[0002] In order to assist a driver of a vehicle and / or to at least partially control the vehicle by controlling longitudinal and / or lateral movement, vehicles contain a plurality of automotive sensors of various types. The data acquired by the plurality of sensors has various acquisition characteristics, such as acquisition errors, that are typical for a given type of automotive sensor and which may collectively be referred to as error statistics. The acquisition characteristics may also be referred to as automotive sensor data information. The automotive sensor data is then processed by automotive sensor data processing modules, which may include, for example, a pose estimator configured to determine a pose of the vehicle based on localization data or an object detection function configured to detect objects in image data.To take the sensing characteristics into account, each motor vehicle processing module is configured to perform its respective function by processing the motor vehicle sensor data in a manner that takes the motor vehicle sensor data information into account. In other words, each motor vehicle sensor data processing module is adapted to the sensing characteristics of the various motor vehicle sensors included in the vehicle whose motor vehicle sensor data it processes. Adapting to the sensing characteristics of the various motor vehicle sensors included in the vehicle is particularly important if a corresponding motor vehicle sensor data processing module relates to at least partial control of the vehicle, because this adaptation enables more precise and therefore safer control of the vehicle.

[0003] Modern vehicles can be updated at a car dealership or over the air, with updates including updates to the automotive sensor data processing modules. Similarly, automotive sensors in a vehicle can be replaced, for example, to upgrade the vehicle's data collection capabilities or to replace a faulty automotive sensor. Both updating the automotive sensor data processing modules and replacing the automotive sensors carry the risk of causing a mismatch between the automotive sensor and the automotive sensor data information.That is, updating the vehicle may update a motor vehicle sensor data processing module to a version of the motor vehicle sensor data processing module configured to process the motor vehicle sensor data based on motor vehicle sensor data information that does not correspond to the motor vehicle sensor data information of the respective motor vehicle sensors included in the vehicle. Likewise, replacing a motor vehicle sensor may result in the vehicle including a motor vehicle sensor having motor vehicle sensor data information that does not correspond to the motor vehicle sensor data information on which the processing of the motor vehicle sensor data processing modules included in the vehicle is based. These situations may cause a reduction in the accuracy of at least partially controlling the vehicle, which may be detrimental to the safety of the at least partially controlling.

[0004] Therefore, it is an object of the present invention to verify within a vehicle a correspondence between the motor vehicle sensor data information of the motor vehicle sensors and a motor vehicle sensor data processing module. SUMMARY OF THE INVENTION

[0005] To achieve this object, the present disclosure provides a method for verifying a match between the motor vehicle sensor data information and a motor vehicle sensor data processing module. The method comprises obtaining the motor vehicle sensor data information. The motor vehicle sensor data information indicates the sensing characteristics of the motor vehicle sensor data of a motor vehicle sensor. The method further comprises obtaining the motor vehicle sensor data processing module. The motor vehicle sensor data processing module is configured to generate intermediate data based on the motor vehicle sensor data and adapted to the motor vehicle sensor data information. The motor vehicle 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 a lateral movement and / or a longitudinal movement of a vehicle based on the intermediate data. The method further includes verifying the match of the vehicle sensor data information with the vehicle sensor data processing module. Finally, the method includes enabling the vehicle control module to control the lateral movement and / or the longitudinal movement of the vehicle if the match is verified.

[0006] The present disclosure further provides a motor vehicle control unit. The motor vehicle control unit comprises at least one processing unit and a data storage 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 obtain the motor vehicle sensor data information. The motor vehicle sensor data information indicates the sensing characteristics of the motor vehicle sensor data of a motor vehicle sensor. The machine-readable instructions further cause the at least one processing unit to obtain the motor vehicle sensor data processing module. The motor vehicle sensor data processing module is configured to generate intermediate data based on the motor vehicle sensor data and adapted to the motor vehicle sensor data information.The motor vehicle 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 a lateral movement and / or a longitudinal movement of a vehicle based on the intermediate data. The machine-readable instructions further cause the at least one processing unit to verify the match of the motor vehicle sensor data information with the motor vehicle sensor data processing module. Finally, the machine-readable instructions further cause the at least one processing unit to enable the vehicle control module to control the lateral movement and / or the longitudinal movement of the vehicle if the match is verified.

[0007] The present disclosure further provides a vehicle including the motor vehicle control unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The examples of the present disclosure are described with reference to the following accompanying drawings, in which like reference numerals refer to like elements. Fig. 1 shows a flowchart of a method for verifying a match between the vehicle sensor data information and a vehicle sensor data processing module according to examples of the present disclosure. Fig. 2 illustrates a vehicle according to examples of the present disclosure. Fig. 3 illustrates a motor vehicle control unit according to examples of the present disclosure.

[0009] It should be appreciated that the drawings identified above are in no way intended to limit the present disclosure. Rather, these drawings are provided to aid in understanding the present disclosure. Those skilled in the art will readily recognize that aspects of the present invention shown in one drawing may be combined with aspects shown in another drawing or omitted without departing from the scope of the present disclosure. DETAILED DESCRIPTION

[0010] A modern vehicle contains multiple automotive sensors to collect automotive sensor data indicative of the vehicle's surroundings. However, the automotive sensor data typically does not provide an accurate indication of the vehicle's surroundings. For example, each automotive sensor may collect the respective automotive sensor data at specific time intervals, causing the automotive sensor data to be accurate only in each detection instance, but to only provide an approximation of the surroundings outside of the detection instances. Furthermore, each automotive sensor may collect data indicative of the surroundings with a specific resolution, causing the automotive sensor data to be accurate only at each detection location, but to only provide an approximation of the surroundings between detection locations.Furthermore, each automotive sensor may collect automotive sensor data with a statistical error, causing the automotive sensor data to generally provide only an approximation of the environment.

[0011] To account for the fact that the automotive sensor data may, at least in part, only indicate an approximation of the vehicle's surroundings, the automotive sensor data in the context of the present disclosure is processed in a manner that takes into account the sensing characteristics of each automotive sensor. To this end, the automotive sensor data in the context of the present disclosure is processed based on the automotive sensor data information, which may include any type of information about the sensing characteristics of the automotive sensor data based on how a corresponding automotive sensor is configured to acquire automotive sensor data, such as sensing time intervals, sensor resolution, and error statistics.

[0012] Automotive sensors may be replaced during the vehicle's lifetime by automotive sensors whose detection characteristics differ from those of the replaced automotive sensors. Furthermore, the automotive sensor data processing modules may be updated with versions that assume the detection characteristics of the vehicle's automotive sensors that differ from the actual detection characteristics of the vehicle. Given that the processing of automotive sensor data in the vehicle must be based on a knowledge of the vehicle's surroundings that is as accurate as possible, the control of the vehicle's lateral and longitudinal movement can only be carried out if the vehicle's automotive sensor data processing modules process the automotive sensor data according to the detection characteristics of the automotive sensor data and, consequently, according to the detection characteristics of the automotive sensors included in the vehicle, i.e.i.e., based on the vehicle sensor data information corresponding to the vehicle sensor data and the respective vehicle sensors. Therefore, in the context of the present disclosure, control of the lateral movement and / or the longitudinal movement of the vehicle is only enabled if a match of the vehicle sensor data information with the vehicle sensor data processing module is verified.

[0013] This general concept is explained with reference to the attached drawings, where Fig. 1 provides a flowchart of a method 100 for verifying a match between the vehicle sensor data information and a vehicle sensor data processing module. Fig. 2 additionally illustrates a vehicle according to the present disclosure, while Fig. 3 illustrates a motor vehicle control unit configured to perform method 100.

[0014] It is recognized that the dashed boxes in Fig. 1 illustrate optional steps of the method 100.

[0015] The method 100 is configured to verify a match between the vehicle sensor data information and a vehicle sensor data processing module in a vehicle configured to enable at least one driver assistance.

[0016] In Fig. 2, the vehicle 200, and more generally the term vehicle in the context of the present disclosure, refers to any type of motor vehicle configured to transport people and / or cargo. The engine of the vehicle 200 may be any type of engine, such as an electric motor or an internal combustion engine. The vehicle 200 may, for example, be a passenger car, as shown in Fig. 2. However, it will be appreciated that the vehicle 200 may also be a bus, a truck, or any other type of vehicle that includes one or more sensors 210 and a vehicle control unit 300 that enables the vehicle 200 to provide at least driver assistance. In other words, the vehicle control unit 300 and one or more sensors 210 are configured to enable one or more vehicle control modules of the vehicle 200 to provide vehicle control functionality capable of at least driver assistance, i.e., Level 1 of the driving automation taxonomy defined in the SAE International J3016 standard.That is, the one or more vehicle control modules may be configured to control the lateral movement and / or the longitudinal movement of the vehicle 200 based on the vehicle sensor data provided by one or more sensors 210 under the supervision of a driver of the vehicle 200.

[0017] It is recognized that Level 1 driving automation is the minimum level of driving automation of which the vehicle 200 is capable. The vehicle 200 may be configured to enable higher levels of driving automation, such as partial driving automation, i.e., Level 2 or higher of the driving automation taxonomy defined in the SAE International J3016 standard. That is, the one or more vehicle control modules may be configured to control both the lateral and longitudinal movement of the vehicle 200 based on automotive sensor data provided by one or more sensors 210, under the supervision of the driver of the vehicle 200.

[0018] In view of the above discussion of the various levels of driving automation, it will be appreciated that the term vehicle control module, in the context of the present disclosure, may refer to any type of control module configured to control lateral and / or longitudinal movement of the vehicle 200 based on the automotive sensor data. The one or more vehicle control modules may, for example, be an advanced cruise control (ACC) function, a Level 3 function for a specific operating environment, such as an automated driving function restricted to controlled access highways and driving speeds of less than 100 km / h, or a function enabling full automation of driving, i.e., Level 5 of the automated driving taxonomy defined in SAE International's J3016 standard, or a sub-function of such a Level 5 function.

[0019] The one or more sensors 210 are configured to collect automotive sensor data indicative of the surroundings of the vehicle 200. Accordingly, the automotive sensor data provides environmental awareness to the one or more vehicle control modules, and thereby to the vehicle 200, to enable at least driver assistance. The automotive sensor data collected by the one or more sensors 210 may, for example, provide the vehicle 200 with information about the position and size of other vehicles, pavement markings, or traffic signs. For this purpose, the one or more sensors 210 may be radar sensors that may be configured to emit radio waves to determine a distance, angle, and speed of objects around the vehicle based on the reflected radio waves.The one or more sensors 210 may be light detection and location (LIDAR) sensors configured to emit laser beams to determine a distance, angle, and speed of objects around the vehicle 200 based on the reflected laser beams. The one or more sensors 210 may be cameras that capture images of the vehicle's surroundings. The one or more sensors 210 may be thermal imaging cameras that capture images of the vehicle's surroundings based on infrared radiation. It is recognized that the LIDAR sensors, radar sensors, or cameras are merely provided as examples of the sensor types of the one or more sensors 210. The one or more sensors 210 may also be ultrasonic sensors, for example.The 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 the vehicle 200. More generally, the one or more sensors 210 may be any type of sensor capable of acquiring automotive sensor data indicative of the surroundings of the vehicle 200. It is further recognized that the one or more sensors 210 may include multiple sensors of different types. Further, the one or more sensors 210 of the same type may have different characteristics, for example, by being configured to acquire automotive sensor data in different ranges, such as a near range, a medium range, and a far range. For example, the vehicle 200 maythree short-range radar sensors each at a front and a rear of the vehicle 200, a mid-to-long-range radar sensor at the rear of the vehicle 200, a LIDAR sensor at the front of the vehicle 100, a rear-facing camera at the rear of the vehicle 200, a forward-facing camera at the front of the vehicle, a forward-facing camera on the rearview mirror, and a rear-facing short-to-mid-range radar sensor in each door-mounted exterior rearview mirror. It is recognized that the vehicle 200 may include more or fewer automotive sensors than shown in FIG. Fig. 2 and have been discussed in the example above.

[0020] As stated above, the automotive sensor data provides environmental awareness to the one or more vehicle control modules. To this end, the automotive sensor data must be processed to extract the environmental information from the automotive sensor data, which may be raw sensor data or sensor data that has been preprocessed by a given automotive sensor, e.g., by applying a filter or some other preprocessing step to the raw sensor data. Raw sensor data refers to the sensor data as acquired by a given automotive sensor. Examples of preprocessing applied by a given automotive sensor may include upsampling, downsampling, or any other type of filtering.Instead of having each vehicle control module individually extract environmental information, thereby causing identical or similar repeated processing of the vehicle sensor data by the one or more vehicle control modules, the extraction of environmental information from the vehicle sensor data is performed by one or more vehicle sensor data processing modules. The one or more vehicle sensor data processing modules are thus configured to generate intermediate data based on the vehicle sensor data and to provide the intermediate data to the one or more vehicle control modules. The intermediate data thus represents the environmental information obtained by processing the vehicle sensor data acquired by the one or more vehicle sensors 210.

[0021] To provide examples of the one or more automotive sensor data processing modules, they may include, for example, an object detection module configured to detect one or more objects within an environment of the vehicle 200. That is, the object detection module may process the automotive sensor data, such as the sensor data acquired by the LIDAR sensors and / or the various cameras, to detect objects in the environment of the vehicle 200 and generate an object list containing the detected objects. The object list may also include other information, including, but not limited to, the type of each object on the object list, such as vulnerable road user (VRU) or vehicle, and the relative distance of each object on the object list with respect to the vehicle 200.According to this example, the intermediate data is the object list generated based on the automotive sensor data indicating the objects in the vicinity of the vehicle 200. The object list may then be used by the one or more vehicle control modules to determine control of the vehicle, such as an autonomous emergency braking module that determines to stop the vehicle 200 to avoid a collision with an object detected in the path of the vehicle 200.

[0022] If the object detection module only provides a list of the detected objects, other vehicle sensor data processing modules may each determine the type of each object and / or the relative distance of the objects from the vehicle 200. To determine this type of information, such vehicle sensor data processing modules may, in addition to or instead of processing the vehicle sensor data, process the intermediate data generated by other vehicle sensor data processing modules. That is, while the vehicle sensor data processing modules are configured to generate the intermediate data based on the vehicle sensor data, they may also generate the intermediate data by processing the intermediate data generated by other vehicle sensor data processing modules.

[0023] The one or more vehicle sensor data processing modules may further include a pose estimation module configured to estimate a position of the vehicle 200. The pose estimation module may receive data from one or more GNSS sensors and / or data from both one or more cellular communication interfaces and other sensors, and may process the data from the one or more sources to determine the position and direction of the vehicle 200. Accordingly, the intermediate data may be position data generated based on the vehicle sensor data indicating the position of the vehicle 200.

[0024] As can be seen from these examples, in the context of the present disclosure, intermediate data is understood to mean any type of data indicative of the environment of the vehicle 200 that has been inferred from the vehicle sensor data collected by the one or more vehicle sensors 210. The intermediate data is then used by the one or more vehicle control modules to control at least the longitudinal and / or lateral movement of the vehicle 200.

[0025] In summary, the one or more vehicle sensors 210 acquire vehicle sensor data indicative of the surroundings of the vehicle 200. The vehicle sensor data, which may be raw sensor data or preprocessed sensor data, is then processed by one or more vehicle sensor data processing modules to generate intermediate data containing information about the surroundings inferred from the vehicle sensor data. Finally, the one or more vehicle control modules control the longitudinal and / or lateral movement of the vehicle 200 based on the information about the surroundings provided by the intermediate data.The motor vehicle sensors 210, the one or more motor vehicle sensor data processing modules, and the one or more vehicle control modules may thus be viewed as a data processing chain configured to process the motor vehicle sensor data and generate the vehicle control data via the intermediate data.

[0026] It is recognized that the one or more motor vehicle sensor data processing modules and the one or more vehicle control modules may each be implemented as software modules executing in the motor vehicle control unit 400, which may be related to Fig. 5, or each can be implemented as individual hardware modules, such as an application-specific integrated circuit (ASIC) or a field-programmable gate array (FPGA).

[0027] As explained above, the motor vehicle sensor data provides environmental awareness. While the motor vehicle sensor data provides a digital representation of the environment of the vehicle 200, the motor vehicle sensor data generally only provides an approximation of the environment of the vehicle 200. The approximation of the environment of the vehicle 200 is based on the sensing characteristics of each motor vehicle sensor 210, i.e., the sensing characteristics of each motor vehicle sensor 210 determine the accuracy of the environmental awareness provided by the motor vehicle sensors 210. In order to take the approximation of the environment of the vehicle 200 into account when processing the motor vehicle sensor data, the one or more motor vehicle sensor data processing modules are configured to process the motor vehicle sensor data information, i.e.to take into account the data indicating the sensing characteristics of the automotive sensor data of a respective automotive sensor 210. The sensing characteristics of the automotive sensor data may include, for example, statistical information about the automotive sensor data of a respective automotive sensor 210, which may include, for example, a 3σ value and a maximum error resilience value. The one or more automotive sensor data processing modules that process the automotive sensor data of the respective automotive sensor 210 take the statistical information into account when generating the intermediate data, i.e., they generate the intermediate data in a manner that compensates for any statistical errors in the automotive sensor data caused by the sensing characteristics of the automotive sensor.According to further examples, the vehicle sensor data information may indicate time intervals or a sensor resolution at which a given vehicle sensor 210 collects the vehicle sensor data.

[0028] More generally, the automotive sensor data information is thus to be understood as any type of data that indicates the sensing characteristics of a given automotive sensor 210 and thus indicates the approximation of the environment of the vehicle 200. Based on the automotive sensor data information, the one or more automotive sensor data processing modules are thus configured to generate the intermediate data in a manner that compensates for the approximation of the environment, thereby causing the intermediate data to provide more accurate environmental awareness to the one or more vehicle control modules. The one or more automotive sensor processing modules thus process the automotive sensor data to generate the intermediate data in a manner adapted to the automotive sensor data information.

[0029] In addition to indicating the sensing characteristics of a given automotive sensor 210, the automotive sensor data information may further indicate how the automotive sensor data provides the automotive sensor data to the one or more automotive sensor data processing modules. That is, the automotive sensor data information may additionally indicate how the approximation of the environment is structured to enable processing of the automotive sensor data by the one or more automotive sensor data processing modules. Further, the automotive sensor data information may indicate the processing parameters that define how the automotive sensor data may be processed by the one or more automotive sensor data processing modules.

[0030] Because the processing of the motor vehicle sensor data by the one or more motor vehicle sensor data processing modules is adapted to the motor vehicle sensor data information of each motor vehicle sensor 210, it must be ensured that the motor vehicle sensor data information to which the one or more motor vehicle sensor data processing modules have been adapted is consistent. For this purpose, the method 100 verifies a match between the motor vehicle sensor data information of the motor vehicle sensors 210 and the one or more motor vehicle sensor data processing modules. In other words, the method 100 checks for each motor vehicle sensor data processing module whether it has been adapted to the motor vehicle sensor data information of each motor vehicle sensor 210 whose motor vehicle sensor data processing module processes the motor vehicle sensor data.The term "match" in the context of the present disclosure is therefore to be understood as referring to the fact that the processing of a given automotive sensor data processing module has been adapted to the sensing characteristics of the one or more automotive sensors whose data it receives. If there is no match, a given automotive sensor data processing module will therefore receive the automotive sensor data from the automotive sensors 210 to whose sensing characteristics its processing has not been adapted. Accordingly, the method 100 ensures that the one or more processing modules only generate intermediate data based on the automotive sensor data of the automotive sensors to whose automotive sensor data information the one or more processing modules have been adapted.

[0031] In step 110, the method 100 obtains the automotive sensor data information. For example, the method 100 may obtain the automotive sensor data whenever the automotive sensor data information of a given automotive sensor 210 changes, e.g., during a firmware update of the given automotive sensor 210. That is, a firmware update of a given automotive sensor 210 may change the sensing characteristics, the structuring of the automotive sensor data, and / or the processing parameters of a given automotive sensor 210. The method 100 may also obtain the automotive sensor data information during the installation or replacement of a given automotive sensor 210. In addition, the method 100 may obtain the automotive sensor data information by retrieving it from a data store of the vehicle 200 during power-up of the vehicle 200.Accordingly, step 110 may include one of steps 111 and 112. In step 111, the method 100 may update the vehicle sensor data information. In step 110, the method 100 may install the vehicle sensor data information upon installation of the vehicle sensor in the vehicle.

[0032] In step 120, the method 100 obtains the vehicle sensor data processing module. Similar to step 110, the method 100 may obtain the vehicle sensor data processing module when the vehicle sensor data processing module is updated, e.g., during an over-the-air (OTA) update, or otherwise provided to the vehicle 200. Additionally, the method 100 may obtain the vehicle sensor data processing module by retrieving it from a data store of the vehicle 200 during power-up of the vehicle 200. Accordingly, step 120 may include a step 121 in which the method 100 updates the vehicle sensor data processing module.

[0033] Steps 110 and 120, and thereby method 100, may be performed whenever the vehicle sensor data information and / or one or more vehicle sensor data processing modules change based on predetermined time intervals or whenever the vehicle 200 is turned on.

[0034] The method 100 may include a step 130 in which the method 100 obtains the verification data of the vehicle sensor data processing module and the verification data of the vehicle sensor data information. In other words, to facilitate verification of the correspondence between the vehicle sensor data information and the one or more vehicle sensor data processing modules, according to some examples of the method 100, the method 100 may obtain data that respectively identify the vehicle sensor data information and the vehicle sensor data processing module. This data may be used during step 142 to verify the correspondence between the vehicle sensor data information and the one or more vehicle sensor data processing modules.The verification data of the vehicle sensor data processing module and the verification data of the vehicle sensor data information may each include at least one of a public key, a verification certificate, and a version number.

[0035] In step 140, the method 100 verifies the consistency of the vehicle sensor data information with the one or more vehicle sensor data processing modules. As discussed above, this step ensures that the one or more vehicle sensor data processing modules generate the intermediate data based on the vehicle sensor data to whose sensing characteristics they have been matched. This further ensures that the one or more vehicle control modules receive the intermediate data that provides accurate environmental awareness, thereby enabling accurate control of the vehicle 100.

[0036] To verify the match in step 140, the one or more vehicle sensor data processing modules may be configured to provide match data indicative of the expected vehicle sensor data information. Accordingly, according to the examples of the present disclosure in which the one or more vehicle sensor data processing modules are configured to provide match data, step 140 may include a step 141 in which the method 100 compares the expected vehicle sensor data information with the vehicle sensor data information.

[0037] According to the examples of the present disclosure in which the method 100 includes step 130, step 140 may further include step 142 in which the method 100 further compares the verification data of the motor vehicle sensor data processing module and the verification data of the motor vehicle sensor data information to verify the correspondence of the motor vehicle sensor data information with the one or more motor vehicle sensor data processing modules.

[0038] Finally, in step 150, the method 100 enables the one or more vehicle control modules to control the lateral and / or longitudinal movement of the vehicle if the match is verified in step 140. That is, only if the intermediate data is generated based on the vehicle sensor data acquired with the sensing characteristics to which the one or more vehicle processing units are adapted, the one or more vehicle control modules are enabled to control the vehicle 100.

[0039] In summary, the method 100 verifies whether one or more vehicle sensor data processing modules receive the vehicle sensor data they are configured to process. Only if so, are the one or more vehicle control modules enabled to control the vehicle 100.

[0040] It is recognized that the method 100 can be used in the vehicle 100 during development, manufacture and / or after delivery of the vehicle 100.

[0041] Fig. 3 shows a motor vehicle control unit 300 configured to perform method 100. The motor vehicle control unit 300 may include a processor 310, a graphics processing unit (GPU) 320, a motor vehicle processing system 330, a data storage 340, a removable storage 350, a memory 360, a cellular interface 370, a global navigation satellite system (GNSS) interface 380, and a communications interface 390.

[0042] Processor 310 may be any type of single-core or multi-core processing unit using a reduced instruction set (RISC) or a complex instruction set (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 may execute instructions that cause vehicle control unit 300 to perform method 100. Processor 310 may be directly coupled to any of the components of vehicle control unit 300 or may be directly coupled to memory 330, GPU 320, and a device bus.

[0043] The GPU 320 may be any type of processing unit optimized for processing graphics-related instructions or, more generally, for parallel processing of instructions. As such, the GPU 320 may be configured to generate a display of information, such as ADAS information or telemetry data, to the driver of the vehicle, e.g., via a head-up display (HUD) or a display located in the driver's view. The GPU 320 may be coupled to the HUD and / or the display via connection 320C. The GPU 320 may further execute at least a portion of the method 100 to enable rapid parallel processing of instructions related to the method 100. It should be noted that, according to some embodiments, the processor 310 may determine that the GPU 320 does not need to execute any instructions related to the method 100.The GPU 320 may be directly coupled to any of the components of the vehicle control unit 300 or may be directly coupled to the processor 310 and the data memory 330. According to some embodiments, the GPU 320 may also be coupled to the device bus.

[0044] The automotive processing system 330 may 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 while driving. The automotive processing system 330 may interface only with the processor 310 or may interface with other devices via the system bus. For example, the automotive processing system 330 may execute the instructions related to the one or more automotive sensor data processing modules and the one or more vehicle control modules.

[0045] Data storage 340 may be any type of fast memory that allows the processor 310, GPU 320, and automotive processing system 330 to both store instructions for rapid retrieval while processing inputs, as well as to cache and buffer data. Data storage 340 may be a unified data storage coupled to the processor 310, GPU 320, and automotive processing system 330 to enable allocation of data storage 340 to the processor 310, GPU 320, and automotive processing system 330 as needed. Alternatively, the processor 310, GPU 320, and automotive processing system 330 may be coupled to a separate processor memory 340a, GPU memory 340b, and automotive processing system memory 340c.

[0046] Removable memory 350 may be a storage device that can be removably coupled to vehicle control unit 300. Examples include a digital versatile disk (DVD), a compact disk (CD), a universal serial bus (USB) storage device such as an external SSD, or a magnetic tape. It should be noted that removable memory 350 may store data such as instructions of method 100, vehicle sensor data, intermediate data, and / or vehicle control data, or may be omitted.

[0047] Memory 360 may be a storage device that enables the storage of program instructions and other data. Memory 360 may be, for example, a hard disk drive (HDD), a solid-state drive (SSD), or any other type of non-volatile memory. Memory 360 may store, for example, the instructions of method 100, vehicle sensor data, intermediate data, and / or vehicle control data.

[0048] Removable storage 350 and memory 360 may be coupled to processor 310 via the system bus. The system bus may be any type of bus system that allows both processor 310 and optionally GPU 420, as well as vehicle processing system 330, to communicate with the other devices of vehicle control unit 300. Bus 340 may be, for example, a Peripheral Component Interconnect Express (PCIe) bus or a Serial Attached Storage (SATA) bus.

[0049] The cellular interface 370 may be any type of interface that allows the vehicle control unit 300 to communicate over a cellular network, such as a 4G network or a 5G network.

[0050] The GNSS interface 380 may be any type of interface that enables the vehicle control unit 300 to receive position data provided by a satellite network, such as the Global Positioning System (GPS), the Global Navigation Satellite System (GLONASS), or Galileo. The position data may be one of the types of vehicle sensor data in the context of the present disclosure.

[0051] The communication interface 390 may enable the vehicle control unit 300 to interface with external devices, either directly or via a network via the connection 380C. The communication interface 380 may, for example, enable the vehicle control unit 300 to be coupled to a wired or wireless network, such as Ethernet, Wi-Fi, a controller area network (CAN) bus, or any other bus system suitable in vehicles. The vehicle control unit 300 may, for example, be coupled to one or more sensors 210 to receive vehicle sensor data, which is then processed by the processing chain if the match between the vehicle sensor data information and the vehicle sensor data processing module is verified by the method 100.

[0052] The motor vehicle control unit 300 can be integrated into the vehicle 200, for example, under the cabin, under the instrument panel or in the trunk of the vehicle 200.

[0053] The invention can be further illustrated by the following examples.

[0054] According to one example, a method for verifying a match between motor vehicle sensor data information and a motor vehicle sensor data processing module comprises obtaining the motor vehicle sensor data information. The motor vehicle sensor data information indicates the sensing characteristics of the motor vehicle sensor data of a motor vehicle sensor. The example method further comprises obtaining the motor vehicle sensor data processing module. The motor vehicle sensor data processing module is configured to generate intermediate data based on the motor vehicle sensor data and adapted to the motor vehicle sensor data information. The motor vehicle 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 a lateral movement and / or a longitudinal movement of a vehicle based on the intermediate data.The exemplary method further includes verifying the match of the vehicle sensor data information with the vehicle sensor data processing module. Finally, the exemplary method includes enabling the vehicle control module to control the lateral and / or longitudinal movement of the vehicle if the match is verified.

[0055] According to the exemplary method, the sensing characteristics of the automotive sensor data may include statistical information of the sensor data of the automotive sensor.

[0056] According to the exemplary method, the statistical information may include at least one of a 3σ value and a maximum error resistance value.

[0057] According to the example method, verifying the match of the motor vehicle sensor data information with the motor vehicle sensor data processing module may include comparing the expected motor vehicle sensor data information with the motor vehicle sensor data information, wherein the motor vehicle sensor data processing module may be configured to provide match data indicative of the expected motor vehicle sensor data information.

[0058] The exemplary method may further comprise obtaining verification data of the motor vehicle sensor data processing module and verification data of the motor vehicle sensor data information, wherein verifying the match of the motor vehicle sensor data information with the motor vehicle sensor data processing module may include comparing the verification data of the motor vehicle sensor data processing module and the verification data of the motor vehicle sensor data information.

[0059] According to the exemplary method, the verification data of the motor vehicle sensor data processing module and the verification data of the motor vehicle sensor data information may each include at least one of a public key, a verification certificate, and a version number.

[0060] According to the example method, maintaining the vehicle sensor data processing module may include updating the vehicle sensor data processing module.

[0061] According to the exemplary method, obtaining the vehicle sensor data information may include at least one of updating the vehicle sensor data information and installing the vehicle sensor data information upon installation of the vehicle sensor in the vehicle.

[0062] According to the exemplary method, the motor vehicle sensor data processing module may be at least one of a pose estimation module configured to estimate a position of the vehicle and an object detection module configured to detect one or more objects in the vicinity of the vehicle.

[0063] According to the exemplary method, the automotive sensor may be at least one of a global navigation satellite system (GNSS) sensor configured to receive position data, an infrared camera, a light detection and positioning (LIDAR) sensor, and a plurality of cameras forming a stereo camera system.

[0064] An exemplary motor vehicle control unit includes at least one processing unit and a data store coupled to the at least one processing unit and configured to store exemplary machine-readable instructions. The exemplary machine-readable instructions cause the at least one processing unit to obtain the motor vehicle sensor data information. The motor vehicle sensor data information indicates the sensing characteristics of the motor vehicle sensor data of a motor vehicle sensor. The exemplary machine-readable instructions further cause the at least one processing unit to obtain the motor vehicle sensor data processing module. The motor vehicle sensor data processing module is configured to generate intermediate data based on the motor vehicle sensor data and adapted to the motor vehicle sensor data information.The motor vehicle 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 a lateral movement and / or a longitudinal movement of a vehicle based on the intermediate data. The example machine-readable instructions further cause the at least one processing unit to verify the match of the motor vehicle sensor data information with the motor vehicle sensor data processing module. The example machine-readable instructions further cause the at least one processing unit to enable the vehicle control module to control the lateral movement and / or the longitudinal movement of the vehicle if the match is verified.

[0065] According to the exemplary motor vehicle control unit, the exemplary machine-readable instructions may further cause the at least one processing unit to perform one of the foregoing exemplary methods.

[0066] An exemplary vehicle includes one of the foregoing exemplary automotive control units.

[0067] The foregoing description has been provided to illustrate the verification of a correspondence between automotive sensor data information and an automotive sensor data processing module. It should be appreciated that the description is in no way intended to limit the scope of the present disclosure to the precise embodiments discussed throughout the description. Rather, those skilled in the art will appreciate that the examples of the present disclosure may be combined, modified, or combined without departing from the scope of the present disclosure as defined by the following claims. List of reference symbols 100 procedures 110-150 process steps 200 vehicles 210 Automotive sensor 220 light 300 vehicle control unit 310 CPU 320 GPU 320c connection 330 Automotive Processing System 340 data storage 350 Removable Storage 360 storage 370 cell interface 380 GNSS interface 390 Communication interface QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited non-patent literature

[0000] Standard J3016

[0018]

Claims

[1] A method (100) for verifying a match between motor vehicle sensor data information and a motor vehicle sensor data processing module, the method comprising: Obtaining (110) the motor vehicle sensor data information, wherein the motor vehicle sensor data information indicates the sensing characteristics of the motor vehicle sensor data of a motor vehicle sensor (210); Receiving (120) the motor vehicle sensor data processing module, wherein the motor vehicle sensor data processing module is configured to generate intermediate data, wherein the generation of the intermediate data is based on the motor vehicle sensor data and is adapted to the motor vehicle sensor data information, and to provide the intermediate data to a vehicle control module, wherein the vehicle control module is configured to control a lateral movement and / or a longitudinal movement of a vehicle (200) based on the intermediate data; Verifying (140) the consistency of the vehicle sensor data information with the vehicle sensor data processing module; and, if the match is verified, enabling (150) the vehicle control module to control the lateral movement and / or the longitudinal movement of the vehicle (200). [2] The method (100) of claim 1, wherein the detection characteristics of the motor vehicle sensor data comprise statistical information of the motor vehicle sensor data of the motor vehicle sensor. [3] The method (100) of claim 2, wherein the statistical information includes at least one of a 3σ value and a maximum error resistance value. [4] Method (100) according to one of the preceding claims, wherein: verifying the conformity of the motor vehicle sensor data information with the motor vehicle sensor data processing module includes comparing the expected motor vehicle sensor data information with the motor vehicle sensor data information, the motor vehicle sensor data processing module is configured to provide matching data indicating the expected motor vehicle sensor data information. [5] Method (100) according to one of the preceding claims, wherein: the method further comprises obtaining (130) verification data of the motor vehicle sensor data processing module and verification data of the motor vehicle sensor data information; verifying (140) the correspondence of the motor vehicle sensor data information with the motor vehicle sensor data processing module includes comparing the verification data of the motor vehicle sensor data processing module and the verification data of the motor vehicle sensor data information. [6] The method (100) of claim 5, wherein the verification data of the motor vehicle sensor data processing module and the verification data of the motor vehicle sensor data information each include at least one of a public key, a verification certificate, and a version number. [7] The method (100) of any preceding claim, wherein obtaining (120) the motor vehicle sensor data processing module includes updating (121) the motor vehicle sensor data processing module. [8] The method (100) of any preceding claim, wherein obtaining (110) the motor vehicle sensor data information includes at least one of updating (111) the motor vehicle sensor data information and installing (112) the motor vehicle sensor data information upon installation of the motor vehicle sensor in the vehicle. [9] The method (100) of any preceding claim, wherein the motor vehicle sensor data processing module is at least one of a position estimation module configured to estimate a position of the vehicle (200) and an object detection module configured to detect one or more objects in the vicinity of the vehicle. [10] Method (100) according to one of the preceding claims, wherein the motor vehicle sensor (210) is at least one of a Global Navigation Satellite System sensor - GNSS sensor - configured to receive position data, an infrared camera, a light detection and location sensor - LIDAR sensor - and a plurality of cameras forming a stereo camera system. [11] Motor vehicle control unit (300) comprising: at least one processing unit (310, 320, 330); and a data memory (340, 350, 360) coupled to 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: obtain the motor vehicle sensor data information, wherein the motor vehicle sensor data information indicates the detection characteristics of the motor vehicle sensor data of a motor vehicle sensor (210); the motor vehicle sensor data processing module, wherein the motor vehicle sensor data processing module is configured to generate intermediate data, wherein the generation of the intermediate data is based on the motor vehicle sensor data and is adapted to the motor vehicle sensor data information, and to provide the intermediate data to a vehicle control module, wherein the vehicle control module is configured to control a lateral movement and / or a longitudinal movement of a vehicle (200) based on the intermediate data; to verify the consistency of the vehicle sensor data information with the vehicle sensor data processing module; if the match is verified, enabling the vehicle control module to control the lateral movement and / or 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 (310, 320, 330) to perform the method of any one of claims 2 to 10. [13] Vehicle (200) comprising the motor vehicle control unit according to one of claims 11 and 12.

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