DE102020200875A1 - Method for providing sensor data by a sensor system of a vehicle - Google Patents

Abstract

The invention relates to a method (500) for providing sensor data (118, 118 ', 120, 120') by a sensor system (110) of a vehicle (102), the sensor system (110) at least one sensor unit (112, 114) for Detecting the surroundings of the vehicle (102) and the vehicle (102) has an evaluation unit (116) for evaluating the sensor data (118, 118 ', 120, 120'). The method (500) comprises the following steps: generation (510) of sensor data (118, 120) by the at least one sensor unit (112, 114) and sending (510) the sensor data (118, 120) to the evaluation unit (116); Subdividing (520) the sensor data (118, 120) into processing areas (306, 308, 310, 312) each with a processing scheme, a processing scheme specifying how sensor data for the processing area (306, 308, 310, 312) are processed by the at least one Sensor unit (112, 114) are to be provided; Sending (530) the processing areas (306, 308, 310, 312) to the at least one sensor unit (112, 114); Selecting (540) sensor data (118 ', 120') to be transmitted from the generated sensor data (118, 120) for each of the processing areas (306, 308, 310, 312) based on the processing schemes; Transmission (550) of the selected sensor data (118 ', 120') to the evaluation unit (116).

Description

The invention relates to a method, a computer program and a computer-readable medium for providing sensor data by a sensor system of a vehicle. The invention also relates to a vehicle system.

Current ADAS algorithms for automated driving (ADAS = Advanced Driver Assistance Systems) are mostly based on a forward-driven data flow in which data predominantly flows from a sensor system to a data processing electronics. The sensors usually provide all data in the maximum possible resolution and frequency. A large number of case distinctions can be made in the algorithms on the basis of this data. For example, different scenarios that are recognized in an environment of the vehicle can be stored in a general environment model and partially combined with one another there. The validation of the data available in this environment model can be correspondingly complex.

The sensor system can include, for example, a camera that provides images of the surroundings of a vehicle with a fixed resolution and update speed.

It is the object of the invention to improve the provision of sensor data by a sensor system of a vehicle.

This object is achieved by the subject matter of the independent claims. Further embodiments of the invention emerge from the dependent claims and from the following description.

A first aspect of the invention relates to a method for providing sensor data by a sensor system of a vehicle. The sensor system comprises at least one sensor unit for detecting the surroundings of the vehicle. The vehicle has an evaluation unit for evaluating the sensor data. The method comprises the following steps: generating sensor data by the at least one sensor unit and sending the sensor data to the evaluation unit; Dividing the sensor data into processing areas, each with a processing scheme, a processing scheme specifying how sensor data are to be provided for the processing area by the at least one sensor unit; Sending the processing areas to the at least one sensor unit; Selecting sensor data to be transmitted from the generated sensor data for each of the processing areas based on the processing schemes; Transmission of the selected sensor data to the evaluation unit.

The method can be carried out by a vehicle system comprising the evaluation unit and the sensor system. The evaluation unit can be part of an on-board computer of the vehicle, for example. The vehicle system can be designed, for example, to recognize the surroundings of the vehicle and to automatically control the vehicle in accordance with the recognized surroundings, i. H. to steer, accelerate, brake and / or navigate. For this purpose, the vehicle system can include corresponding actuators such as steering or braking actuators or actuators for engine control.

A vehicle can be understood to mean a motor vehicle such as a car, truck, bus or motorcycle.

The sensor system can include several identical and / or different sensor units such as a camera, a radar, lidar or ultrasonic sensor.

A preprocessing module for preprocessing the sensor data in hardware and / or software can be implemented in the sensor unit. The preprocessing can include, for example, the following basic steps: recording a useful signal by the sensor unit and converting the useful signal into an electrical raw signal (signal recording), generating raw data by interpreting the raw signal as a physical measured variable (signal processing), extracting features such as edges, areas or extreme values from the raw data (feature extraction), assignment of the extracted features to object categories (data association). The sensor data to be transmitted can be selected, for example, by the preprocessing module.

A processing area can be understood to mean a section of a detection area of the sensor unit or a section of sensor data depicting the detection area. The detection area can be defined by a range and / or a field of view of the sensor unit. The detection area or the sensor data can be completely or only partially divided into processing areas.

For example, a processing area can represent an image section of a captured image or a frequency range of a captured noise. Accordingly, different processing areas of the sensor data can represent different image details of the captured image or different frequency ranges of the captured noise.

The processing areas can differ from one another, for example, in terms of relevance for the vehicle.

The subdivision of the sensor data into the processing areas can take place based on objects detected in the vicinity of the vehicle. The objects can be recognized using an environment model, as described in more detail below. The processing areas can differ from one another by the relevance of the recognized objects assigned to them. For example, a processing area in which an object located on the edge of the road is recognized may have less relevance for the vehicle than a processing area in which an object located on a roadway of the vehicle is recognized.

The sensor system can for example comprise at least two sensor units with at least partially overlapping detection areas. Sensor data generated by the sensor unit and at least one further sensor unit can be subdivided into processing areas, for example, in such a way that at least one processing area from the sensor data of the sensor unit and at least one processing area from the sensor data of the further sensor unit match one another.

A processing scheme can, for example, specify a spatial and / or temporal resolution with which the surroundings of the vehicle in the relevant processing area are to be recognized, i.e. H. with which the sensor unit is to provide sensor data relating to the processing area in question for the evaluation unit. Different processing areas may have different or the same processing schemes.

Briefly summarized, the sensor unit can be designed to control a data flow from the sensor unit to the evaluation unit, i. H. to either increase or decrease depending on the processing areas determined by the evaluation unit. The sensor unit can, for example, be designed to continuously generate sensor data in a predetermined data quality, for example in the highest possible data quality. From this sensor data, certain data areas to be transmitted to the evaluation unit can then be selected based on the processing schemes. In this way it can be avoided that all the sensor data generated by the sensor unit are always transmitted to the evaluation unit in the specified data quality. In this way, the computational effort when evaluating the sensor data in the evaluation unit can ultimately be reduced.

High-resolution sensors can require a correspondingly complex transmission of sensor data to an evaluation unit that processes the sensor data, unless suitable preprocessing of the sensor data takes place in the sensors themselves. The increasing number of ever higher resolution sensors in modern vehicles is accompanied by an increasing amount of increasingly complex sensor data. It is therefore desirable if the amount and / or complexity of the sensor data is significantly reduced by suitable preprocessing while the recognition quality remains the same, in order to keep the overall costs of an ADAS system as low as possible.

An approach is therefore proposed by which a sensor system of a vehicle can specifically detect individual sections of its detection area, for example controlled by a corresponding algorithm for environment recognition, with less data than other sections, for example with lower resolution and / or lower update speed. In other words, the sensor system can be configured to selectively receive sensor data, i. H. to output to the evaluation unit with regard to individual sections of their detection area, with different resolutions and / or update speeds. As a result, the quantity and / or complexity of the sensor data to be transmitted and processed can be significantly reduced in comparison to solutions without such selective preprocessing by the sensor system.

According to one embodiment, the processing scheme can indicate a desired resolution of the processing area. Sensor data to be transmitted can be selected for the processing area that have the desired resolution. A resolution can be understood to mean, for example, a number of pixels or a measurement frequency. In particular, the desired resolution can be lower than a resolution with which the sensor data were originally generated when the surroundings were recorded. For this purpose, the generated sensor data can be compressed, filtered and / or converted in a suitable manner. Thus, a quantity and / or complexity of the sensor data to be transmitted can be effectively reduced compared to the sensor data generated.

According to one embodiment, the processing scheme can specify a desired contour of the processing area. In this case, sensor data to be transmitted can be selected for the processing area that have the desired contour. In the event that the sensor unit captures images of the surroundings of the vehicle, a contour can be, for example, a rectangle, a circle or a contiguous circle Lines defined form can be understood. In the event that the sensor unit detects noises in the vicinity of the vehicle, a contour can be understood to mean, for example, a characteristic frequency pattern.

According to one embodiment, the processing scheme can specify a desired update frequency with which the processing area is to be updated. In this case, sensor data to be transmitted can be selected for the processing area which have the desired update frequency. An update frequency can generally be understood as a number of measurements per time unit. For example, the update frequency can also be used to specify whether a measurement should be carried out once or repeatedly, i.e. That is, whether sensor data that was generated in a single measurement or sensor data that was generated in several successive measurements with a specific frequency should be selected for the processing area.

According to one embodiment, the processing scheme can specify a desired change in the processing area over a number of time steps. In this case, sensor data to be transmitted can be selected for the processing area which have the desired change in the processing area. In other words, the processing area can vary from time step to time step, for example in shape and / or size. This allows the processing area to be dynamically adapted to changes in the surroundings of the vehicle.

According to one embodiment, the processing scheme can specify a desired change in a position of the processing area within a detection area of the at least one sensor unit over several time steps. In this case, sensor data to be transmitted can be selected for the processing area which have the desired change in the position of the processing area. In the event that the sensor unit captures images of the surroundings of the vehicle, the processing scheme can, for example, indicate a movement of the processing area in an x and / or y direction of a coordinate system fixed to the vehicle. In the event that the sensor unit detects noises in the vicinity of the vehicle, the processing scheme can, for example, indicate a shift in a frequency range to be processed within a frequency range that can be detected by the sensor unit.

According to one embodiment, the processing scheme can specify a desired change in a size of the processing area over a number of time steps. In this case, sensor data to be transmitted can be selected for the processing area which have the desired change in the size of the processing area. In the event that the sensor unit captures images of the surroundings of the vehicle, the processing scheme can, for example, specify a change in a zoom factor for the processing area. In the event that the sensor unit detects noises in the vicinity of the vehicle, the processing scheme can specify, for example, a broadening or narrowing of a frequency range to be processed within a frequency range that can be detected by the sensor unit.

For example, a processing area can be selected in a first time step such that at least a main section of an object in the processing area can be detected by the at least one sensor unit, which can be the case, for example, when a previously undetected object is detected for the first time. In a second time step, the processing area can be correspondingly reduced in size based on the main section of the object recognized in the first time step and on an anticipated change in position and / or location of the object, so that in the reduced processing area, only a new section of the object to be recognized by the at least a sensor unit can be detected. Thus, the amount of data to be processed in the second time step can be significantly reduced compared to the first time step.

According to one embodiment, the method further comprises the following steps: recognizing objects in the vicinity of the vehicle based on the sensor data; Assigning the recognized objects to relevance categories, objects in different relevance categories differing from one another in a relevance for the vehicle. The sensor data can be divided into processing areas in such a way that at least one object of a relevance category can be detected by the at least one sensor unit in each processing area. A processing scheme based on the relevance category can each be assigned to the processing areas.

The detection of the objects can include what is known as track estimation, also called tracking, in which the states of the objects, for example their position and / or location and / or their speed, are estimated. Furthermore, the detection of the objects can include object discrimination in which the objects are detected and / or classified. In the event of a detection, it is decided whether an object is present. When classified, an object becomes a predefined object category, which can also be referred to as a class, assigned, for example an object category “vehicle” or “person”.

The objects can be recognized, for example, using an environment model. This can be understood as a dynamic data structure in which relevant objects in the vicinity of the vehicle, such as other vehicles or infrastructure elements, are realistically represented in a common reference system in place and time. In simple terms, the environment model can be used to model how the vehicle itself moves, which other road users are in the vicinity of the vehicle, how the other road users move and in which traffic area, i.e. H. in which common context, the vehicle and the other road users move. The environment model can be based on a physical model with which a current situation of the vehicle can be evaluated and predicted with a certain probability into the future.

The movement of the vehicle can be determined, for example, by a model of its own movement, in the simplest case for example a kinematic, linear single-track model, and / or by a driver's intention recognition. The traffic area can for example be determined by road marking recognition, recognition of freely passable areas, localization relative to a lane and / or in a digital map and / or recognition of traffic signs and / or traffic signal systems. The objects can be modeled in the environment model, for example, as point models and / or extended two- and / or three-dimensional models. Such an object model can, for example, describe a position, a speed and / or a yaw angle of an object relative to the vehicle and continuously estimate it based on the sensor data of the sensor system. In addition, the object model can describe translational acceleration components and / or a yaw rate of the object. For this purpose, it is useful if the sensor system is designed to measure speeds directly, for example by means of a radar sensor.

The objects can be recognized, for example, based on a fusion of sensor data from several sensor units. In addition, information from, for example, a high-resolution digital map and / or information received outside the vehicle via a Car2X communication network can be used to identify the objects.

To put it simply, this embodiment enables the processing areas to be prioritized, depending on which objects in the processing areas can be detected by the sensor unit. For example, objects with a higher relevance for the vehicle can be tracked with a higher accuracy than objects with a lower relevance for the vehicle by assigning a corresponding processing scheme to the processing area comprising the objects.

According to one embodiment, a larger amount of sensor data to be transmitted can be selected based on a processing scheme that is assigned to a processing area with at least one object of a higher relevance category than based on a processing scheme that is assigned to a processing area with at least one object of a lower relevance category. As a result, a data flow from the sensor unit to the evaluation unit can be controlled depending on the relevance of the objects to be detected by the sensor unit. In other words, the less relevant the objects to be recorded, the lower the data flow. It can also be achieved in this way that, with the data flow remaining the same, a larger amount of data is available for recognizing more relevant objects, in that the amount of data required for recognizing less relevant objects is correspondingly reduced.

According to one embodiment, a processing area with at least one object of a higher relevance category with a higher priority can be sent to the at least one sensor unit than a processing area with at least one object of a lower relevance category.

Additionally or alternatively, a processing area with at least one object of a higher relevance category with a higher priority can be processed by the at least one sensor unit than a processing area with at least one object of a lower relevance category.

The priority can be mapped, for example, by a maximum waiting time between receiving the processing areas in the sensor unit and transmitting the selected sensor data to the evaluation unit.

Further aspects of the invention relate to a computer program which, when it is executed on a processor, carries out the method as described above and below, as well as a computer-readable medium on which such a computer program is stored. A computer-readable medium can be a hard disk, a USB storage device, a RAM, a ROM, an EPROM or a flash memory. On Computer-readable medium can also be a data communication network, such as the Internet, for example, which enables program code to be downloaded. The computer readable medium can be transitory or non-transitory. Features of the method, as described above and below, can also be features of the computer program and / or the computer-readable medium.

Another aspect of the invention relates to a vehicle system that is designed to carry out the method as described above and below. For this purpose, the vehicle system comprises a sensor system with at least one sensor unit for detecting the surroundings of a vehicle and an evaluation unit coupled to the at least one sensor unit. Features of the method, as described above and below, can also be features of the vehicle system and vice versa.

• 1 zeigt schematisch ein Fahrzeugsystem gemäß einem Ausführungsbeispiel der Erfindung.
• 2 zeigt ein Blockschaltbild einer Auswerteeinheit aus 1.
• 3 zeigt schematisch einen Erfassungsbereich einer Sensorik aus 1.
• 4 zeigt ein Blockschaltbild einer Kamera aus 1.
• 5 zeigt ein Ablaufdiagramm eines Verfahrens gemäß einem Ausführungsbeispiel der Erfindung.

In the following, exemplary embodiments of the invention are described in detail with reference to the accompanying figures.

• 1 shows schematically a vehicle system according to an embodiment of the invention.
• 2 shows a block diagram of an evaluation unit from 1 .
• 3 shows schematically a detection area of a sensor system 1 .
• 4th shows a block diagram of a camera 1 .
• 5 shows a flow chart of a method according to an embodiment of the invention.

The reference symbols used in the figures and their meaning are given in summarized form in the list of reference symbols. In principle, identical or similar parts are provided with the same reference symbols.

1 shows schematically a vehicle system 100 that is a vehicle 102 includes. The vehicle is driving as an example 102 on one by two roadsides 104 limited roadway 106 . Next to one of the two edges of the road 104 there is a tree 108 . The vehicle 102 is with a sensor system 110 for detecting an environment of the vehicle 102 equipped here by the roadway 106 and the tree 108 is shown schematically. In this example, the sensor system includes 110 a camera 112 and a radar sensor 114 as sensor units. The vehicle system also includes 100 an evaluation unit 116 , such as an on-board computer, for evaluating by the sensors 110 generated sensor data, here from camera data 118 the camera 112 and from radar data 120 of the radar sensor 114 . The camera data 118 can include two- or three-dimensional images of the environment. The radar data 114 can measure the distances and / or speeds of objects in the vicinity relative to the vehicle 102 include. Part of the vehicle system 100 is also an actuator 122 that have one or more actuators to control the vehicle 102 , for example a steering or braking actuator.

The evaluation unit 116 is running to get from the sensor data 118 , 120 To extract features such as edges, surfaces or points and to assign the extracted features to stored object categories, here for example the object categories "tree" or "roadside" around the tree 108 and the edges of the road 104 as objects in the vicinity of the vehicle 102 recognizable and relative to the vehicle 102 to locate. Based on the detected objects 104 , 106 , 108 generates or updates the evaluation unit 116 a three-dimensional model of the surroundings of the vehicle 102 . On the one hand, the respective positions, locations and object categories of the recognized objects are shown in the environment model 104 , 106 , 108 saved. On the other hand, the expected movements of the objects 104 , 106 , 108 To predict as realistically as possible, the environment model is built up as a physical model. Anticipated changes in positions, locations or speeds of the objects 104 , 106 , 108 are calculated with the help of a physics engine taking into account physical laws. Furthermore, the evaluation unit 116 configured to get from the sensor data 118 , 120 areas in the vicinity of the vehicle using the environment model 102 to determine which are different from each other in terms of relevance to the vehicle 102 distinguish. Depending on its relevance, the evaluation unit 116 Each of these areas, also called processing areas, is assigned a processing scheme that specifies the accuracy with which objects in the relevant area are to be recognized. For example, the evaluation unit determines 116 in the in 1 example shown that the tree 108 with a lower quality, ie for example with a lower resolution, is to be tracked, detected and / or classified than a vehicle 102 oncoming vehicle.

The evaluation unit 116 is also configured to the vehicle 102 automated control. The evaluation unit controls this 116 the actuators 122 according to the surroundings of the vehicle recognized with the environmental model 102 at.

The processing of the sensor data 118 , 120 through the evaluation unit 116 As well as their Provision by the sensors 110 are described in more detail below.

2 shows schematically an exemplary configuration of the evaluation unit 116 out 1 . The evaluation unit 116 includes a preprocessing module 200 with a camera module 202 for preprocessing the camera data 118 and a radar module 204 for preprocessing the radar data 120 . All modules mentioned here can be software components in the evaluation unit 116 be executed computer program.

In the preprocessing module 200 finds, for example, a fusion of the camera data 118 with the radar data 120 instead of the positions, locations and object categories of the objects 104 , 106 , 108 to recognize. An environmental module 206 receives from the preprocessing module 200 Detection data 208 showing the positions, locations and object categories of the detected objects 104 , 106 , 108 contain. Based on the recognition data 208 adds the environment module 206 the detected objects 104 , 106 , 108 into an environment model that shows the surroundings of the vehicle 102 for example object-based in a three-dimensional space. As an alternative or in addition, the representation can also take place on a raster basis. Based on the positions and locations of the objects 104 , 106 , 108 that were determined in earlier time steps are calculated by the environment module 206 a probable object trajectory for each object. To calculate the probable object trajectories, the environment module 206 on a physics module 210 fall back, also called physics engine, in the movements and positions of the detected objects 104 , 106 , 108 can be calculated and checked for plausibility based on physical laws.

The preprocessing module 200 can optionally be designed to include object data 213 to be received wirelessly via a Car2X communication network, for example from other vehicles or infrastructure elements, and evaluated for object recognition. The object data 213 for example, data about objects in the vicinity of the other vehicles and / or about the objects 104 , 106 , 108 around the vehicle 102 if they were recorded by the other vehicles.

In addition, the environmental module divides 206 the recognized and using the physics module 210 objects checked for plausibility 104 , 106 , 108 into relevance categories. With the help of this classification, the objects 104 , 106 , 108 with regard to their respective relevance for the vehicle 102 be distinguished from each other. Depending on the relevance category, the objects 104 , 106 , 108 then in a subsequent time step with different quality from the sensors 110 detected and / or by the preprocessing unit 200 can be detected.

Like the objects 104 , 106 , 108 are to be recorded and / or detected with different relevance, the sensor system 110 or the preprocessing module 200 by one with the environmental module 206 connected feedback module 212 communicated. The feedback module 212 sends corresponding processing information 214 to the sensors 110 or the preprocessing module 200 .

3 illustrates an example of how a detection area 300 the sensors 110 is divided into areas of different relevance. The detection area 300 can be viewed as a total detection area, which is made up of individual detection areas of sensor units of the sensor system 110 , here the camera 112 and the radar sensor 114 , composed.

The detection area 300 covers, for example, an area around the vehicle 102 from where the roadway is 106 with the edges of the road 104 and the tree 108 are located. In the detection area 300 there is also a house 302 and on the vehicle 102 oncoming vehicle in a left lane 304 .

The environmental module 206 divides those in the detection area 300 detected and recognized objects 104 , 106 , 108 , 302 , 304 into two different relevance categories by the roadway 106 , the tree 108 and the house 102 classified as static objects and the oncoming vehicle 304 is classified as a dynamic object. The dynamic objects differ from the static objects in that they are more relevant to the vehicle 102 . Depending on the exemplary embodiment, the objects can also be divided into more than two different relevance categories. For example, the objects can also be based on their relative movement to the vehicle 102 be classified, for example, to recognize whether an object is on the vehicle 102 moved towards or away from it.

The detection area is based on this classification 300 for example divided into four processing areas. The subdivision is based on the positions and locations of the detected objects and the sensor units stored in the environment model 112 , 114 . This includes a first processing area 306 an area to the left of the lane 106 with the house 302 , a second processing area 308 an area to the right of the lane 106 with the tree 108 , a third processing area 310 the left lane with the oncoming vehicle 304 and a fourth Processing area 312 a right lane on which the vehicle is located 102 moved.

The processing areas 306 , 308 , 312 each have the same relevance with regard to the vehicle, for example 102 . The third processing area 310 has due to the oncoming vehicle 104 a higher relevance than the other processing areas 306 , 308 , 312 . Alternatively, the fourth processing area 312 A medium relevance can be assigned, which is between the relevance of the processing areas 306 , 308 and the relevance of the third processing area 310 lies.

The four processing areas 306 , 308 , 310 , 312 are arranged in such a way that objects located therein each through the camera 112 and / or the radar sensor 114 can be captured.

In the 3 Subdivision of the detection area shown 300 in the processing areas 306 , 308 , 310 , 312 is only chosen as an example. Alternatively, the detection area 300 be divided as desired. For example, the subdivision can also take place in such a way that a different relevance category is assigned to each processing area. For example, a detection area of the camera 112 independent of a detection range of the radar sensor 114 divided into processing areas and vice versa.

The environmental module 206 now assigns each processing area 306 , 308 , 310 , 312 a processing scheme that corresponds to its relevance category. This indicates how the sensor data 118 , 120 in the relevant processing area by the sensors 110 provided, so to be preprocessed and / or by the evaluation unit 116 should be processed. For example, the processing scheme specifies a spatial and / or temporal resolution, such as a number of pixels and / or a measurement frequency, which is adapted to the relevance category of the processing area in question. The one from the feedback module 212 generated processing information 214 indicates which processing scheme is assigned to which processing area. As mentioned earlier, the processing information 214 with the processing areas contained therein 306 , 308 , 310 , 312 to the sensors 110 Posted. The provision of sensor data by the sensor system 110 based on the processing information 214 is explained below using 4th using the camera as an example 112 described in more detail.

The environmental module 206 can for example comprise a scene manager, the scenes in the surroundings of the vehicle 102 calculated based on the environment model and also determined which sections of the environment model require an update next. A corresponding request can be made by a sensor manager to suitable sensor units of the sensor system 110 to get redirected. The sensor manager can, for example, be a component of the feedback module 212 be.

For example, in a first step, new, ie previously unknown objects can be inserted into the environment model. For this purpose, the scene manager contains an object detector that executes suitable algorithms for object recognition. If it is recognized during the object detection that a previously requested section does not completely cover an object, the object detector can trigger the request for further sections. The finished object model is made by the physics module 210 checked for plausibility and inserted into the environment model. The now known area is communicated to the scene manager, more precisely to a scene update manager contained therein. In this way, a first complete environment model can be built.

The efficiency when updating the environment model can now be increased by prioritizing the areas to be updated or the objects to be updated in the environment model. A physical model of the surroundings of the vehicle can be used for this purpose 102 can be used in which static and dynamic objects are stored and which is enriched with information from a high-resolution digital map, for example, and with information about traffic rules.

The objects saved in the environment model 104 , 106 , 108 , 302 , 304 can move relative to the vehicle 102 be tracked. An expected movement of the objects 104 , 106 , 108 , 302 , 304 can be predicted and corresponding object areas can be preselected in the environment model. The preselected object areas can now be revalidated more quickly and with less computational effort using known key areas or key points. This has the advantage that the areas to be newly recognized in each cycle are smaller than with a complete new recognition of the objects 104 , 106 , 108 , 302 , 304 . This can reduce the computing power required.

The validation can, for example, depend on a respective relevance category of the recognized objects 104 , 106 , 108 , 302 , 304 respectively. For example, the static objects 108 , 302 be tracked at the roadside with a lower resolution than the dynamic object 304 or an object that is a trajectory of the vehicle 102 likely to cross.

4th shows an exemplary configuration of the camera 112 out 1 . The camera 112 includes a camera sensor 400 to generate the camera data 118 , such as a CCD or CMOS sensor, and a logic module 402 for preprocessing the camera data 118 according to the processing information 214 . The logic module 402 can be a software component of one in the camera 112 be executed computer program. Alternatively, the logic module 402 into the camera sensor 400 be integrated.

The logic module 402 is designed to use the processing information 214 from the from the camera sensor 400 for example continuously generated camera data 118 camera data to be transferred 118 ' to select. This is done for each of the processing areas 306 , 308 , 310 , 312 based on those in the processing information 214 A certain data area is determined, for example by suitable filtering, compressing and / or converting the camera data 118 . The data areas determined in this way, taken together, result in the camera data to be transmitted 118 ' . In particular, the camera data to be transmitted differ 118 ' from those originally from the camera sensor 400 generated camera data 118 through less complexity and / or less data volume. The logic module 402 transfers the selected camera data 118 ' finally for further processing to the evaluation unit 116 . The selected camera data 118 ' can be done analogously to the 2 processing of the camera data described 118 or. 120 are processed. It can thus be avoided that an entire camera data set is always sent cyclically to the evaluation unit via a communication bus 116 is transmitted.

The processing information 214 For example, a desired resolution of a section of the surroundings of the vehicle that is to be recorded 102 , a shape of the section to be recorded (e.g. rectangle, circle, contiguous section defined by several lines), a recording priority (e.g. represented by an expected maximum latency in the provision of the camera data to be transmitted 118 ' ) or information about a measurement method with regard to the section to be recorded (e.g. individual measurement or cyclical measurement). In the case of a cyclical measurement, information can also be included as to whether the section to be recorded should be changed continuously, for example by zooming or moving in an x and / or y direction in a coordinate system fixed to the vehicle.

The in 1 shown radar sensor 114 can be analogous to the camera 112 be configured to based on the processing information 214 from the generated radar data 120 radar data to be transmitted 120 ' and to the evaluation unit 116 to send.

5 shows a flow chart of a method 500 as it is from the in 1 vehicle system shown 100 can be carried out. The following is a possible course of the procedure 500 using the camera as an example 112 described. The procedure 500 however, it can also be used in an analogous manner in connection with the radar sensor described above 114 or with another environment sensor of the vehicle 102 be performed.

This will be the first step 510 the camera data 118 generated and to the evaluation unit 116 Posted.

In a second step 520 will be the camera data 118 in the processing areas 306 , 308 , 310 , 312 divided. Doing so will each of the processing areas 306 , 308 , 310 , 312 a processing scheme is assigned which specifies how camera data for the processing area in question by the camera 112 should be provided.

In a third step 530 becomes the the processing areas 306 , 308 , 310 , 312 descriptive processing information 214 to the camera 112 Posted.

In a fourth step 540 processes the logic module 402 those from the camera sensor 400 generated camera data 118 according to the processing information 214 processing schemes included. The camera data to be transmitted are thereby 118 ' determined.

In a fifth step 550 are the camera data to be transferred 118 ' finally to the evaluation unit 116 Posted.

In addition, it should be noted that “comprehensive” does not exclude any other elements or steps and “one” or “one” does not exclude a large number. It should also be noted that features or steps that have been described with reference to one of the above exemplary embodiments can also be used in combination with other features or steps of other exemplary embodiments described above. Reference signs in the claims are not to be regarded as a restriction.

List of reference symbols

100

Vehicle system

102

vehicle

104

Curb

106

roadway

108

tree

110

Sensors

112

camera

114

Radar sensor

116

Evaluation unit

118

Camera data

118 '

camera data to be transferred

120

Radar data

120 '

radar data to be transmitted

122

Actuators

200

Preprocessing module

202

Camera module

204

Radar module

206

Environmental module

208

Detection data

210

Physics module

212

Feedback module

213

Object data

214

Processing information

300

Detection area

302

House

304

oncoming vehicle

306

first processing area

308

second processing area

310

third processing area

312

fourth processing area

400

Camera sensor

402

Logic module

500

Method for providing sensor data

510

Generation and sending of sensor data

520

Divide the sensor data into processing areas

530

Sending the processing areas

540

Selecting the sensor data to be transmitted

550

Transfer of the selected sensor data

Claims (13)

Method (500) for providing sensor data (118, 118 ', 120, 120') by a sensor system (110) of a vehicle (102), wherein the sensor system (110) has at least one sensor unit (112, 114) for detecting an environment of the Vehicle (102) and the vehicle (102) has an evaluation unit (116) for evaluating the sensor data (118, 118 ', 120, 120'), the method (500) comprising: Generation (510) of sensor data (118, 120) by the at least one sensor unit (112, 114) and transmission (510) of the sensor data (118, 120) to the evaluation unit (116); Subdividing (520) the sensor data (118, 120) into processing areas (306, 308, 310, 312) each with a processing scheme, a processing scheme specifying how sensor data for the processing area (306, 308, 310, 312) are processed by the at least one Sensor unit (112, 114) are to be provided; Sending (530) the processing areas (306, 308, 310, 312) to the at least one sensor unit (112, 114); Selecting (540) sensor data (118 ', 120') to be transmitted from the generated sensor data (118, 120) for each of the processing areas (306, 308, 310, 312) based on the processing schemes; Transmission (550) of the selected sensor data (118 ', 120') to the evaluation unit (116). Method (500) according to Claim 1 wherein the processing scheme indicates a desired resolution of the processing area (306, 308, 310, 312); sensor data (118 ', 120') which are to be transmitted and which have the desired resolution are selected for the processing area (306, 308, 310, 312). Method (500) according to one of the preceding claims, wherein the processing scheme indicates a desired contour of the processing region (306, 308, 310, 312); sensor data (118 ', 120') which are to be transmitted and which have the desired contour are selected for the processing area (306, 308, 310, 312). The method (500) according to any one of the preceding claims, wherein the processing scheme provides a desired update frequency with which the Processing area (306, 308, 310, 312) to be updated; sensor data (118 ', 120') which are to be transmitted and which have the desired update frequency are selected for the processing area (306, 308, 310, 312). Method (500) according to one of the preceding claims, wherein the processing scheme indicates a desired change in the processing area (306, 308, 310, 312) over a plurality of time steps; wherein sensor data (118 ', 120') to be transmitted are selected for the processing area (306, 308, 310, 312) which have the desired change in the processing area (306, 308, 310, 312). Method (500) according to one of the preceding claims, wherein the processing scheme indicates a desired change in a position of the processing area (306, 308, 310, 312) within a detection area (300) of the at least one sensor unit (112, 114) over a plurality of time steps; wherein sensor data (118 ', 120') to be transmitted are selected for the processing area (306, 308, 310, 312) which have the desired change in the position of the processing area (306, 308, 310, 312). Method (500) according to one of the preceding claims, wherein the processing scheme indicates a desired change in a size of the processing area (306, 308, 310, 312) over a plurality of time steps; wherein sensor data (118 ', 120') to be transmitted are selected for the processing area (306, 308, 310, 312) which have the desired change in the size of the processing area (306, 308, 310, 312). The method (500) according to any one of the preceding claims, further comprising: Recognizing objects (104, 106, 108; 302, 304) in the vicinity of the vehicle (102) based on the sensor data (118, 118 ', 120, 120'); Assigning the recognized objects (104, 106, 108; 302, 304) to relevance categories, objects (104, 106, 108; 302, 304) differing in relevance for the vehicle (102) in different relevance categories; wherein the sensor data (118, 120) are subdivided into processing areas (306, 308, 310, 312) such that in each processing area (306, 308, 310, 312) at least one object (104, 106, 108; 302, 304) a relevance category can be detected by the at least one sensor unit (112, 114); wherein the processing areas (306, 308, 310, 312) are each assigned a processing scheme based on the relevance category. Method (500) according to Claim 8 wherein, based on a processing scheme that is assigned to a processing area (306, 308, 310, 312) with at least one object (104, 106, 108; 302, 304) of a higher relevance category, a larger amount of sensor data (118 ', 120 ') is selected as based on a processing scheme that is assigned to a processing area (306, 308, 310, 312) with at least one object (104, 106, 108; 302, 304) of a lower relevance category. Method (500) according to Claim 8 or 9 : wherein a processing area (306, 308, 310, 312) with at least one object (104, 106, 108; 302, 304) of a higher relevance category with a higher priority is sent to the at least one sensor unit (112, 114) than a processing area (306, 308, 310, 312) with at least one object (104, 106, 108; 302, 304) of a lower relevance category; and / or wherein a processing area (306, 308, 310, 312) with at least one object (104, 106, 108; 302, 304) of a higher relevance category is processed by the at least one sensor unit (112, 114) with a higher priority than a processing area (306, 308, 310, 312) with at least one object (104, 106, 108; 302, 304) of a lower relevance category. Computer program which, when executed on a processor, carries out the method (500) according to one of the preceding claims. Computer-readable medium on which a computer program is based Claim 11 is stored. Vehicle system (100), comprising: a sensor system (110) with at least one sensor unit (112, 114) for detecting the surroundings of a vehicle (102); an evaluation unit (116) coupled to the sensor system (110) for evaluating the sensor data (118, 118 ', 120, 120'); wherein the vehicle system (100) is designed to perform the method (500) according to one of Claims 1 to 10 perform.

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