Method and system for verifying correspondence between automotive sensor data information and an automotive sensor data processing module

Abstract

The present application relates to a verifying a correspondence between automotive sensor data information and an automotive sensor data processing module. The automotive sensor data information are indicative of capturing characteristics of automotive sensor data of an automotive sensor. The automotive sensor data processing module is configured to generate intermediate data based on the automotive sensor data and adapted to the automotive sensor data information. Further, 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 a lateral and a longitudinal motion of a 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 the longitudinal motion of the vehicle.

Description

Method and System for Verifying Correspondence between Automotive Sensor Data Information and an Automotive Sensor Data Processing ModuleTECHNICAL FIELD

[0001] The invention generally relates to processing of automotive sensor data in a vehicle and more precisely to verifying whether information relating to data captured by an automotive sensor correspond to an automotive module configured to receive and to process the data captured by the automotive sensor.BACKGROUND

[0002] To assist a driver of a vehicle and / or to at least partially control the vehicle by controlling one or both of the longitudinal movement and the lateral movement, vehicles include a plurality of automotive sensors of various sensor types. The data captured by the plurality of sensors exhibit various capturing characteristics, such as capture errors typical for a given type of automotive sensor, which may be collectively referred to as error statistics. The capturing 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 e.g. include 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 account for the capturing characteristics, each automotive processing module is configured to perform its respective function by processing the automotive sensor data in a manner which considers the automotive sensor data information. In other words, each automotive sensor data processing module is adapted to the capturing characteristics of the various automotive sensors included in the vehicle of which it processes automotive sensor data. The adaption to the capturing characteristics of the various automotive sensors included in the vehicle is particularly important if a respective automotive sensor data processing module relates to an at least partial control of the vehicle since this adaptation enables more accurate and thereby safer control of the vehicle.

[0003] Modern vehicles may be updated at a car dealer or over the air, with the updates including updates of the automotive sensor data processing modules. Likewise, automotive sensors in a vehicle may be replaced, e.g. in order to upgrade the data capturing capability of the vehicle or to replace a faulty automotive sensor. Both updating the automotive sensor data processing modules and replacing the automotive sensors carries the risk of causing a mismatch between the automotive sensor and the automotive sensor data information. That is, updating the vehicle may update an automotive sensor data processing module to a version of the automotive sensor data processing module which is configured to process automotive sensor data based on automotive sensor data information which does not correspond to the automotive sensor data information of the respective automotive sensors included in the vehicle. Likewise, replacing an automotive sensor may lead to the vehicle including an automotive sensor having automotive sensor data information which do not correspond to the automotive sensor data information on which the processing of the automotive sensor data processing modules included in the vehicle is based. These situations may cause a reduction in accuracy in the at least partial control of the vehicle, which may be detrimental to the safety of the at least partial control.

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

[0005] To achieve this objective, the present disclosure a method for verifying a correspondence between automotive sensor data information and an automotive sensor data processing module. The method comprises obtaining the automotive sensor data information. The automotive sensor data information is indicative of capturing characteristics of automotive sensor data of an automotive sensor. The method further comprises obtaining 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 adapted 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 a lateral motion and a longitudinal motion of a vehiclebased on the intermediated data. The method further comprises verifying the correspondence of the automotive sensor data information with the automotive sensor data processing module. Finally, the method comprises enabling the vehicle control module to control at least one of the lateral motion and the longitudinal motion of the vehicle if the correspondence is verified.

[0006] The present disclosure further provides an automotive control unit. The automotive control unit comprises 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 obtaining the automotive sensor data information. The automotive sensor data information is indicative of capturing characteristics of automotive sensor data of an automotive sensor. The machine-readable instructions further cause the at least one processing unit to obtain 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 adapted 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 a lateral motion and a longitudinal motion of a vehicle based on the intermediated data. The machine-readable instructions further cause the at least one processing unit to verify the correspondence of the automotive sensor data information with the automotive 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 at least one of the lateral motion and the longitudinal motion of the vehicle if the correspondence is verified.

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

[0008] Examples of the present disclosure will be described with reference to the following appended drawings, in which like reference signs refer to like elements.

[0009] FIG. 1 shows a flowchart of a method for verifying a correspondence between automotive sensor data information and an automotive sensor data processing module according to examples of the present disclosure.

[0010] FIG. 2 illustrates a vehicle according to examples of the present disclosure.

[0011] Fig. 3 illustrates an automotive control unit according to examples of the present disclosure.

[0012] It should be understood that the above-identified drawings are in no way meant to limit the present disclosure. Rather, these drawings are provided to assist in understanding the present disclosure. The person skilled in the art will readily understand that aspects of the present invention shown in one drawing may be combined with aspects in another drawing or may be omitted without departing from the scope of the present disclosure.DETAILED DESCRIPTION

[0013] A modern vehicle includes a plurality of automotive sensors to capture automotive sensor data indicative of the environment of the vehicle. However, the automotive sensor data typically do not provide an exact indication of the environment of the vehicle. For example, each automotive sensor may capture the respective automotive sensor data at specific times intervals, which causes the automotive sensor data to only be exact in each capturing instance but may only provide an approximation of the environment outside of the capturing instances. Further, each automotive sensor may capture data indicative of the environment with a specific resolution, which causes the automotive sensor data to only be exact at each capturing position but may only provide an approximation of the environment between capturing positions. Further each automotive sensor may capture automotive sensor data with a statistical error, which causes the automotive sensor data to generally only provide an approximation of the environment.

[0014] To account for the fact that the automotive sensor data may at least partially be indicative of only an approximation of the environment of the vehicle, the automotive sensor data inthe context of the present disclosure is processed in a manner considering capturing characteristics of each automotive sensor. To this end, automotive sensor data is processed in the context of the present disclosure based on automotive sensor data information, which may include any kind of information of capturing characteristics of the automotive sensor data, which are based on how a respective automotive sensor is configured to capture automotive sensor data, such as capturing time intervals, sensor resolution and error statistics.

[0015] Automotive sensors may be replaced during the lifetime of the vehicle with automotive sensors having capturing characteristics different from the ones of the replaced automotive sensors. Further, automotive sensor data processing modules may be updated with versions assuming capturing characteristics of the automotive sensors of the vehicle which are different from the actual capturing characteristics of the vehicle. Given that the processing of the automotive sensor data in the vehicle needs to be based on an awareness of the environment of the vehicle which is as accurate as possible, control of lateral motion and longitudinal motion of the vehicle may only be performed if the automotive sensor data processing modules of the vehicle process the automotive sensor data in accordance with the capturing characteristics of the automotive sensor data and thus in accordance with the capturing characteristics of the automotive sensors included in the vehicle, i.e. based on automotive sensor data information corresponding to the automotive sensor data and the respective automotive sensors. Therefore, in the context of the present disclosure control of the lateral motion and / or the longitudinal motion of the vehicle is only enabled if a correspondence of the automotive sensor data information with the automotive sensor data processing module is verified.

[0016] This general concept will be explained with reference to the appended drawings, with Fig. 1 providing a flowchart of a method 100 for verifying a correspondence between automotive sensor data information and an automotive sensor data processing module. In addition, Fig. 2 illustrates a vehicle according to the present disclosure and Fig. 3 illustrates an automotive controller configured to perform method 100.

[0017] It will be understood that dashed boxes in Fig. 1 illustrate optional steps of method 100.

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

[0019] Turning briefly to Fig. 2, vehicle 200 and more generally the expression vehicle in the context of the present disclosure refers to any kind of motor vehicle configured to transport people and / or freight. The motor of vehicle 200 may be any kind of motor, such as an electric motor or an internal combustion engine. Vehicle 200 may e.g. be a passenger vehicle as shown in Fig. 2. It will however be understood that vehicle 200 may also be a bus, a truck or any other kind of vehicle including one or more sensors 210 and an automotive control unit 300 enabling vehicle 200 to provide at least driver assistance. In other words, automotive 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 functionality capable of at least driver assistance, i.e. level 1 of the driving automation taxonomy defined in standard J3016 of SAE International. That is, the one or more vehicle control modules may be configured to control at least one of the lateral motion and the longitudinal motion of vehicle 200 based on automotive sensor data provided by one or more sensors 210 under the supervision of a driver of vehicle 200.

[0020] It will be understood that level 1 driving automation is the minimum level of driving automation of which vehicle 200 is capable. 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 standard J3016 of SAE International. That is, the one or more vehicle control modules may be configured to control both the lateral motion and the longitudinal motion of vehicle 200 based on automotive sensor data provided by one or more sensors 210 under the supervision of the driver of vehicle 200.

[0021] In view of the above discussion of the various levels of driving automation, it will be understood that the expression vehicle control module in the context of the present disclosure may refer to any kind of control module configured to control at least one of a lateral motion and a longitudinal motion of vehicle 200 based on 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 automation driving function limitedto controlled-access highways and to driving speeds of less than 100 kph, or a function enabling full driving automation, i.e. level 5 of the driving automation taxonomy defined in standard J3016 of SAE International, or a subfunction of such a level 5 function.

[0022] The one or more sensors 210 are configured to capture automotive sensor data indicative of the environment of vehicle 200. Accordingly, the automotive sensor data provide environmental awareness to the one or more vehicle control modules and thereby to vehicle 200 in order to enable at least driver assistance. For example, the automotive sensor data captured by the one or more sensors 210 may provide vehicle 200 with information on the position and size of other vehicles, road surface markings or traffic signs. To this end, the one or more sensors 210 may be radar sensors, which may be configured to emit radio waves in order to determine a distance, an angle and a velocity of objects around the vehicle based on the reflected radio waves. The one or more sensors 210 may be light detection and ranging (LIDAR) sensors, which are configured to emit laser beams in order to determine a distance, an angle and a velocity of objects around vehicle 200 based on the reflected laser beams. The one or more sensors 210 may be cameras, which capture images of the environment of the vehicle. The one or more sensors 210 may be thermographic cameras, which capture images of the environment of vehicle 200 based on infrared radiation. It will be understood that LIDAR sensors, radar sensors or cameras are merely provided as examples of sensor types of the one or more sensors 210. For example, the one or more sensors 210 may also be ultrasonic sensors. The one or more sensors 210 may be global navigation satellite system (GNSS) sensors configured to receive positional data, such as satellite signals, for determining the position of vehicle 200. More generally, the 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 will further be understood that the one or more sensors 210 may include multiple sensors of various types of sensors. Further, the one or more sensors 210 of the same type may exhibit different properties, e.g. by being configured to capture automotive sensor data at different ranges, such as a close range, a middle range and a far range. For example, vehicle 200 may include three close range radar sensors each at a front and a back of vehicle 200, a middle range to far range radar sensor at the back of vehicle 200, a LIDAR sensor at the front of vehicle 100, a rear-facing camera at the back of vehicle 200, a front-facing camera at the front of the vehicle, a front-facing camera at the rear-view mirror and a rear-facing close range to middle range radar sensor in each door-mounted outer rearview mirror. It will be understood that vehicle 200 may include more or fewer automotive sensors than shown in Fig. 2 and discussed in the above example.

[0023] As stated above, the automotive sensor data provide environmental awareness to the one or more vehicle control modules. To this end, the automotive sensor data need to be processed in order to extract environmental information form the automotive sensor data, which may be raw sensor data or sensor data which has been pre-processed by a given automotive sensor, e.g. by applying a filter or some other pre-processing step on the raw sensor data. Raw sensor data refers to sensor data as captured by a given automotive sensor. Examples of preprocessing applied by a given automotive sensor may include upsampling, downsampling or any other type of filtering. Rather than having each vehicle control module extract environmental information individually and thereby causing identical or similar repeated processing of the automotive sensor data by the one or more vehicle control modules, the extraction of environmental information from the automotive sensor data is performed by one or more automotive sensor data processing modules. The one or more automotive sensor data processing modules are thus configured to generate intermediate data based on the automotive sensor data and to provide the intermediate data to the one or more vehicle control modules. The intermediate data thus represents environmental information obtained by processing the automotive sensor data captured by the one or more automotive sensors 210.

[0024] To provide examples of the one or more automotive sensor data processing modules, they may e.g. include an object detection module configured to detect one or more objects within a vicinity of vehicle 200. That is, the object detection module may process the automotive sensor data, such as sensor data captured by LIDAR sensors and / or various cameras, in order to detect objects in the vicinity of vehicle 200 and to generate an object list including the detected objects. The object list may also include further 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 relative to vehicle 200. In this example, the intermediate data is the object list generated based on automotive sensor data indicative of objects in the vicinity of 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 emergencybraking module determining to stop vehicle 200 in order to avoid a collision with an object detected in the path of travel of vehicle 200.

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

[0026] The one or more automotive sensor data processing modules may further include a pose estimation module configured to estimate a position of vehicle 200. The pose estimation module may receive data from one or more GNSS sensors and / or data from one or more cellular communication interfaces as well as other sensors and may process the data from the one or more sources to determine the position and the direction of vehicle 200. Accordingly, the intermediate data may be positional data generated based on automotive sensor data indicative of the position of vehicle 200.

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

[0028] To summarize, the one or more automotive sensors 210 capture automotive sensor data, which is indicative of the environment of vehicle 200. The automotive sensor data, which may be raw sensor data or pre-processed sensor data, is then processed by one or more automotive sensor data processing modules in order to generate intermediate data, which includesinformation about the environment inferred from the automotive sensor data. Finally, the one or more automotive control modules control at least one of the longitudinal motion and the lateral motion of vehicle 200 based on the information about the environment provided by the intermediate data. The automotive sensors 210, the one or more automotive sensor data processing modules and the one or more vehicle control modules may thus be considered a data processing chain, which is configured to process automotive sensor data and to generate vehicle control data via intermediate data.

[0029] It will be understood that the one or more automotive sensor data processing modules and the one or more vehicle control modules may each be implemented as software modules executed on automotive control unit 400, which will be discussed with reference to Fig. 5, or may each be implemented as individual hardware modules, such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

[0030] As stated above, the automotive sensor data provide environmental awareness. However, given that the automotive sensor data provide a digital representation of the environment of vehicle 200, the automotive sensor data inherently provide only an approximation of the environment of vehicle 200. The approximation of the environment of vehicle 200 is based on the capturing characteristics of each automotive sensor 210, i.e. the capturing characteristics of each automotive sensor 210 determine the accuracy of the environmental awareness provided by the automotive sensors 210. To take the approximation of the environment of vehicle 200 into account when processing the automotive sensor data, the one or more automotive sensor data processing modules are configured to take into account automotive sensor data information, i.e. data indicative of capturing characteristics of the automotive sensor data of a respective automotive sensor 210. For example, the capturing characteristics of the automotive sensor data may comprise statistical information of the automotive sensor data of a respective automotive sensor 210, which may for example include a 3o-value and a maximum error persistence value. The one or more automotive sensor data processing modules processing 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 compensating any statistical errors in the automotive sensor data caused by the capturing characteristics of the automotive sensor. In further examples, the au-tomotive sensor data information may indicate time intervals or a sensor resolution at which a given automotive sensor 210 captures automotive sensor data.

[0031] More generally, the automotive sensor data information is thus to be understood as any kind of data indicative of the capturing characteristics of a given automotive sensor 210 and thus indicative of the approximation of the environment of 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 compensating 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.

[0032] In addition to being indicative of the capturing characteristics of a given automotive sensor 210, the automotive sensor data information may further be indicative of how the automotive sensor data provide 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 in order 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 be indicative of processing parameters defining how the automotive sensor data may be processed by the one or more automotive sensor data processing modules.

[0033] Since the processing of the automotive sensor data by the one or more automotive sensor data processing modules is adapted to the automotive sensor data information of each automotive sensor 210, it needs to be ensured that the automotive sensor data information to which the one or more automotive sensor data processing modules have been adapted to. To this end, method 100 verifies a correspondence between the automotive sensor data information of the automotive sensors 210 and the one or more automotive sensor data processing modules. In other words, method 100 checks for each automotive sensor data processing module whether it has been adapted to the automotive sensor data information of each automotive sensor 210 of which the automotive sensor data processing module processes the automotivesensor data. The expression correspondence in the context of the present disclosure is thus to be understood as referring to the fact that the processing of a given automotive sensor data processing module has been adapted to the capturing characteristics of the one or more automotive sensors which data it receives. If there is no correspondence, a given automotive sensor data processing module consequently receives automotive sensor data from automotive sensors 210 to the capturing characteristics of which its processing has not been adapted to. Accordingly, method 100 ensures that the one or more processing modules only generate intermediate data based on automotive sensor data of automotive sensors to whose automotive sensor data information the one or more processing modules have been adapted to.

[0034] In step 110, method 100 obtains the automotive sensor data information. Method 100 may for example obtain the automotive sensor data whenever the automotive sensor data information of a given automotive sensor 210 change, 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 capturing characteristics, the structuring of the automotive sensor data and / or processing parameters of a given automotive sensor 210. Method 100 may also obtain the automotive sensor data information during installation or replacement of a given automotive sensor 210. Method 100 may also obtain the automotive sensor data information by retrieving them from a memory of vehicle 200 during turn-on of vehicle 200. Accordingly, step 110 may include one of steps 111 and 112. In step 111, method 100 may update the automotive sensor data information. In Step 110, method 100 may install the automotive sensor data information upon installation of the automotive sensor in the vehicle.

[0035] In step 120, method 100 obtains the automotive sensor data processing module. Similarly to step 110, method 100 may obtain the automotive sensor data processing module when the automotive sensor data processing module is updated, e.g. during an over-the-air (OTA) update, or otherwise provided to vehicle 200. Method 100 may also obtain the automotive sensor data processing module by retrieving it from a memory of vehicle 200 during turn-on of vehicle 200. Accordingly, step 120 may include a step 121, in which method 100 updates the automotive sensor data processing module.

[0036] Steps 110 and 120 and thereby method 100 may be performed whenever automotive sensor data information and / or one or more automotive sensor data processing modules change, based on pre-determined time-intervals or whenever vehicle 200 is turned on.

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

[0038] In step 140, method 100 verifies the correspondence of the automotive sensor data information with the one or more automotive sensor data processing module. As discussed above, this step ensures that the one or more automotive sensor data processing modules generate the intermediate data based on automotive sensor data to the capturing characteristics of which it has been adapted to. This further ensures that the one or more vehicle control modules receive intermediate data providing correct environmental awareness, thereby enabling accurate control of vehicle 100.

[0039] To verify the correspondence in step 140, the one or more automotive sensor data processing module may be configured to provide correspondence data indicative of the expected automotive sensor data information. Accordingly, in examples of the present disclosure in which the one or more automotive sensor data processing modules are configured to provide correspondence data, step 140 may include a step 141, in which method 100 compares expected automotive sensor data information with the automotive sensor data information.

[0040] Further, in examples of the present disclosure, in which method 100 includes step 130, step 140 may further include step 142, in which method 100 compares the automotive sensor data processing module verification data and the automotive sensor data information verification data in order to verify the correspondence of the automotive sensor data information with the one or more automotive sensor data processing module.

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

[0042] In summary, method 100 verifies whether one or more automotive sensor data processing modules receive automotive sensor data to the processing of which they are adapted to. Only if this is the case are the one or more vehicle control modules enabled to control vehicle 100.

[0043] It will be understood that method 100 may be deployed both in vehicle 100 during development, manufacture and / or after delivery of vehicle 100.

[0044] Fig. 3 shows automotive control unit 300 configured to perform method 100. automotive control unit 300 may include a processor 310, a graphics processing unit (GPU) 320, automotive processing system 330, a memory 340, a removable storage 350, a storage 360, a cellular interface 370, a global navigation satellite system (GNSS) interface 380 and a communication interface 390.

[0045] Processor 310 may be any kind of single-core or multi-core processing unit employing a reduced instruction set (RISC) or a complex instruction set (CISC). Exemplary RISC processing units include ARM based cores or RISC V based cores. Exemplary CISC processing units include x86 based cores or x86-64 based cores. Processor 310 may perform instructions causing automotive control unit 300 to perform method 100. Processor 310 may be directly coupled to anyof the components of automotive control unit 300 or may be directly coupled to memory 330, GPU 320 and a device bus.

[0046] GPU 320 may be any kind of processing unit optimized for processing graphics related instructions or more generally for parallel processing of instructions. As such, GPU 320 may be configured to generate a display of information, such as ADAS information or telemetry data, to a driver of the vehicle, e.g. via a head-up display (HUD) or a display arranged within the view of the driver. GPU 320 may be coupled to the HUD and / or the display via connection 320C. GPU 320 may further perform at least a part of method 100 to enable fast parallel processing of instructions relating to method 100. It should be noted that in some embodiments, processor 310 may determine that GPU 320 need not perform instructions relating to method 100. GPU 320 may be directly coupled to any of the components of automotive control unit 300 or may be directly coupled to processor 310 and memory 330. In some embodiments, GPU 320 may also be coupled to the device bus.

[0047] Automotive processing system 330 may be any kind of system-on chip configured to provide trillions of operations per second (TOPS) in order to enable automotive control unit 300 to implement one or more ADAS while driving. Automotive processing system 330 may interface only with processor 310 or may interface with other devices via the system bus. Automotive processing system 330 may for example perform the instructions related to the one or more automotive sensor data processing modules and to the one or more vehicle control modules.

[0048] Memory 340 may be any kind of fast storage enabling processor 310, GPU 320 and automotive processing system 330 to store instructions for fast retrieval during processing of instructions as well as to cache and buffer data. Memory 340 may be a unified memory coupled to processor 310 and GPU 320 and automotive processing system 330 in order to enable allocation of memory 340 to processor 310, GPU 320 and automotive processing system 330 as needed. Alternatively, processor 410, GPU 320 and automotive processing system 330 may be coupled to separate processor memory 340a, GPU memory 340b and automotive processing system memory 340c.

[0049] Removable storage 350 may be a storage device which can be removably coupled with automotive control unit 300. Examples include a digital versatile disc (DVD), a compact disc (CD), a Universal Serial Bus (USB) storage device, such as an external SSD, or a magnetic tape. It should be noted that removable storage 350 may store data, such as instructions of method 100, automotive sensor data, intermediate data and / or vehicle control data or may be omitted.

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

[0051] Removable Storage 350 and storage 360 may be coupled to processor 310 via the system bus. The system bus may be any kind of bus system enabling processor 310 and optionally GPU 420 as well as automotive processing system 330 to communicate with the other devices of automotive control unit 300. Bus 340 may for example be a Peripheral Component Interconnect express (PCIe) bus or a Serial AT Attachment (SATA) bus.

[0052] Cellular interface 370 may be any kind of interface enabling automotive control unit 300 to communicate via a cellular network, such as a 4G network or a 5G network.

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

[0054] Communications interface 390 may enable automotive control unit 300 to interface with external devices, either directly or via network, via connection 380C. Communications interface 380 may for example enable automotive control unit 300 to couple to a wired or wireless network, such as Ethernet, Wifi, a Controller Area Network (CAN) bus or any bus system appropriate in vehicles. For example, automotive control unit 300 may be coupled to the one or more sensors 210 to receive automotive sensor data, which is then processed by the processingchain if the correspondence between the automotive sensor data information with the automotive sensor data processing module is verified by method 100.

[0055] Automotive control unit 300 may be integrated with vehicle 200, e.g. beneath the cabin, under the dashboard or in the trunk of vehicle 200.

[0056] The invention may further be illustrated by the following examples.

[0057] In an example, a method for verifying a correspondence between automotive sensor data information and an automotive sensor data processing module comprises obtaining the automotive sensor data information. The automotive sensor data information is indicative of capturing characteristics of automotive sensor data of an automotive sensor. The exemplary method further comprises obtaining 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 adapted 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 a lateral motion and a longitudinal motion of a vehicle based on the intermediated data. The exemplary method further comprises verifying the correspondence of the automotive sensor data information with the automotive sensor data processing module. Finally, the exemplary method comprises enabling the vehicle control module to control at least one of the lateral motion and the longitudinal motion of the vehicle if the correspondence is verified.

[0058] In the exemplary method, the capturing characteristics of the automotive sensor data may comprise statistical information of the sensor data of the automotive sensor.

[0059] In the exemplary method, the statistical information may include at least one of a Bo- value and a maximum error persistence value.

[0060] In the exemplary method, the verifying the correspondence of the automotive sensor data information with the automotive sensor data processing module may include comparing expected automotive sensor data information with the automotive sensor data information,the automotive sensor data processing module may be configured to provide correspondence data indicative of the expected automotive sensor data information.

[0061] The exemplary method may further comprise obtaining automotive sensor data processing module verification data and automotive sensor data information verification data, wherein the verifying the correspondence of the automotive sensor data information with the automotive sensor data processing module may include comparing the automotive sensor data processing module verification data and the automotive sensor data information verification data.

[0062] In the exemplary method, the automotive sensor data processing module verification data and the automotive sensor data information verification data may respectively include at least one of a public key, a verification certificate and a version number.

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

[0064] In the exemplary method, the obtaining the automotive sensor data information may include at least one of updating the automotive sensor data information and installing the automotive sensor data information upon installation of the automotive sensor in the vehicle.

[0065] In the exemplary method, the automotive 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 within a vicinity of the vehicle.

[0066] In the exemplary method, the automotive sensor may be at least one of a global navigation satellite system (GNSS) sensor configured to receive positional data, an infrared camera, a light detection and ranging (LIDAR) sensor and a plurality of cameras forming a stereo camera system.

[0067] An exemplary automotive control unit comprises at least one processing unit and a memory 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 automotive sensor data information. The automotive sensor data information is indicative of capturing characteristics of automotive sensor data of an automotive sensor. The exemplary machine-readable instructions further cause the at least one processing unit to obtain 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 adapted 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 a lateral motion and a longitudinal motion of a vehicle based on the intermediate data. The exemplary machine-readable instructions further cause the at least one processing unit to verify the correspondence of the automotive sensor data information with the automotive sensor data processing module. The exemplary 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 motion and the longitudinal motion of the vehicle, if the correspondence is verified

[0068] In the exemplary automotive control unit, the exemplary machine-readable instructions may further cause the at least one processing unit to perform any one of the preceding exemplary methods.

[0069] An exemplary vehicle comprises any one of the preceding exemplary automotive control units.

[0070] The preceding 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 understood that the description is in no way meant to limit the scope of the present disclosure to the precise embodiments discussed throughout the description. Rather, the person skilled in the art will be aware that the examples of the present disclosure may be combined, modified or condensed without departing from the scope of the present disclosure as defined by the following claims.List of Reference Signs100 method110-150 method steps 200 vehicle210 automotive sensor220 light300 automotive control unit310 CPU 320 GPU320c connection330 automotive processing system340 memory350 removable storage 360 storage370 cellular interface380 GNSS interface390 communications interface

Claims

Claims1. Method (100) for verifying a correspondence between automotive sensor data information and an automotive sensor data processing module, comprising: obtaining (110) the automotive sensor data information, the automotive sensor data information being indicative of capturing characteristics of automotive sensor data of an automotive sensor (210); obtaining (120) the automotive sensor data processing module, the automotive sensor data processing module being configured to generate intermediate data, the generation of the intermediate data being based on the automotive sensor data and being adapted to the automotive sensor data information, and to provide the intermediate data to a vehicle control module, the vehicle control module being configured to control at least one of a lateral motion and a longitudinal motion of a vehicle (200) based on the intermediate data; verifying (140) the correspondence of the automotive sensor data information with the automotive sensor data processing module; and if the correspondence is verified, enabling (150) the vehicle control module to control at least one of the lateral motion and the longitudinal motion of the vehicle (200).

2. The method (100) of claim 1, wherein the capturing characteristics of the automotive sensor data comprise statistical information of the automotive sensor data of the automotive sensor.

3. The method (100) of claim 2, wherein the statistical information includes at least one of a 3o-value and a maximum error persistence value.

4. The method (100) of any one of the preceding claims, wherein: the verifying the correspondence of the automotive sensor data information with the automotive sensor data processing module includes comparing expected automotive sensor data information with the automotive sensor data information, the automotive sensor data processing module is configured to provide correspondence data indicative of the expected automotive sensor data information.

5. The method (100) of any one of the preceding claims, wherein: the method further comprises obtaining (130) automotive sensor data processing module verification data and automotive sensor data information verification data; the verifying (140) the correspondence of the automotive sensor data information with the automotive sensor data processing module includes comparing the automotive sensor data processing module verification data and the automotive sensor data information verification data.

6. The method (100) of claim 5, wherein the automotive sensor data processing module verification data and the automotive sensor data information verification data respectively include at least one of a public key, a verification certificate and a version number.

7. The method (100) of any one of the preceding claims, wherein the obtaining (120) the automotive sensor data processing module includes updating (121) the automotive sensor data processing module.

8. The method (100) of any one of the preceding claims, wherein the obtaining (110) the automotive sensor data information includes at least one of updating (111) the automotive sensor data information and installing (112) the automotive sensor data information upon installation of the automotive sensor in the vehicle.

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

10. The method (100) of any one of the preceding claims, wherein the automotive sensor (210) is at least one of a global navigation satellite system - GNSS - sensor configured to receive positional data, an infrared camera, a light detection and ranging - LIDAR - sensor and a plurality of cameras forming a stereo camera system.

11. An automotive control unit (300), comprising:at least one processing unit (310, 320, 330); and a memory coupled (340, 350, 360) to the 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 automotive sensor data information, the automotive sensor data information being indicative of capturing characteristics of automotive sensor data of an automotive sensor (210); obtain the automotive sensor data processing module, the automotive sensor data processing module being configured to generate intermediate data, the generation of the intermediate data being based on the automotive sensor data and being adapted to the automotive sensor data information, and to provide the intermediate data to a vehicle control module, the vehicle control module being configured to control at least one of a lateral motion and a longitudinal motion of a vehicle (200) based on the intermediate data; verify the correspondence of the automotive sensor data information with the automotive sensor data processing module; if the correspondence is verified, enable the vehicle control module to control at least one of the lateral motion and the longitudinal motion of the vehicle (200).

12. The automotive 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 of any one of claims 2 to 10.

13. A vehicle (200) comprising the automotive control unit of any one of claims 11 and 12.

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