DE102016106978A1 - Method for operating a driver assistance system of a motor vehicle, computing device, driver assistance system and motor vehicle - Google Patents

Abstract

The invention relates to a method for operating a driver assistance system (2) of a motor vehicle (1) by detecting an object (O) in first sensor data detected by a vehicle-side sensor device (S) from a surrounding area (3) of the motor vehicle (1) and identifying an object-specific one Feature (M) on the object (O) in the first sensor data; Determining a first pose of the motor vehicle (1) to the object-specific feature (M) on the basis of the object-specific feature (M), recognizing the object (O) in the second sensor data detected by the sensor device (S) on the basis of the object-specific feature (M), determining a second pose of the motor vehicle (1) to the object-specific feature (M) on the basis of the object-specific feature (M); Determining a pose of the motor vehicle (1) resulting from a movement of the motor vehicle (1) between the detection of the first and the second sensor data to the object-specific feature (M) by means of odometry; and detecting an odometry error if a deviation between the resulting pose and the second pose exceeds a predetermined threshold. The invention also relates to a computing device (9), a driver assistance system (2) and a motor vehicle (1).

Description

The invention relates to a method for operating a driver assistance system of a motor vehicle by detecting an object in first sensor data acquired by a vehicle-side sensor device from an environmental region of the motor vehicle, identifying an object-specific feature on the object in the first sensor data and determining a first pose of the motor vehicle to the object-specific Feature based on the object-specific feature. The invention also relates to a computing device, a driver assistance system and a motor vehicle having such a driver assistance system.

A method for operating a driver assistance system of the type mentioned is, for example, from DE 10 2010 056 217 A1 known. In this case, an orientation of a motor vehicle to an adjacent vehicle is determined on the basis of an image taken by a vehicle-side camera of the adjacent vehicle. The image is processed by a computing device and identified at least one object on the adjacent vehicle. The orientation of the motor vehicle is determined based on an image of the identified object. Such an object may be, for example, an official license plate and / or tires of the other vehicle. The information about the orientation of the neighboring vehicle may be used to assist the driver in performing parking operations.

It is an object of the present invention to provide a solution to provide a versatile driver assistance system, by means of which a motor vehicle can be located particularly reliable.

This object is achieved by a method by a computing device, by a driver assistance system and by a motor vehicle with the features according to the respective independent claims. Advantageous embodiments of the invention are subject of the dependent claims, the description and the figures.

In one embodiment of a method according to the invention for operating a driver assistance system, an object can be detected in first sensor data detected by a vehicle-side sensor device from a surrounding area of the motor vehicle, and an object-specific feature can be identified on the object in the first sensor data. In addition, a first pose of the motor vehicle to the object-specific feature can be determined based on the object-specific feature. In addition, the object is detected in second sensor data detected by the sensor device from the surrounding area on the basis of the object-specific feature, and a second pose of the motor vehicle for the object-specific feature is determined on the basis of the object-specific feature. In addition, in particular, a pose of the motor vehicle resulting from a movement of the motor vehicle between the detection of the first and second sensor data to the object-specific feature is determined by means of odometry and the odometry error is detected if a deviation between the resulting pose and the second pose exceeds a predetermined threshold value ,

In a preferred refinement of the method for operating a driver assistance system, an object is detected in first sensor data detected by a vehicle-side sensor device from an environmental region of the motor vehicle, and an object-specific feature is identified on the object in the first sensor data. In addition, a first pose of the motor vehicle is determined to the object-specific feature based on the first sensor data. In addition, the object is detected in the second sensor data detected by the sensor device from the surrounding area on the basis of the object-specific feature, and a second pose of the motor vehicle for the object-specific feature is determined on the basis of the object-specific feature. In addition, a pose of the motor vehicle to the object-specific feature resulting from a movement of the motor vehicle between the detection of the first and the second sensor data is determined by means of odometry and the odometry error is detected if a deviation between the resulting pose and the second pose exceeds a predetermined threshold value.

By means of the method, a driver assistance system can be implemented, which is designed to determine poses with respect to at least one object in the surrounding area of the motor vehicle and also during the pose determination for detecting an odometry error. The pose includes a position or a distance of the motor vehicle relative to the object and an orientation of the motor vehicle to the object. By the determination of the pose, that is to say the determination of a spatial position between the motor vehicle and the object, in particular a so-called SLAM method (Simultaneous Localization and Mapping, Simultaneous Localization and Map Creation) is realized. In the case of the SLAM method, an environmental map describing the surrounding area is created at the same time, for example by a computing device of the driver assistance system, and the pose of the motor vehicle within this environment map is estimated. The In this case, a map of surroundings is in particular a two-dimensional map into which the objects detected by the vehicle-side sensor device can be entered and thus spatial positions of the objects to the motor vehicle are indicated. In this case, the motor vehicle can be located, for example, in an origin of a coordinate system describing the environment map. With knowledge of an absolute position of the motor vehicle, which is indicated for example in GPS coordinates, the absolute position of the object can also be determined on the basis of the specific pose of an object with respect to the motor vehicle.

Such per se known SLAM methods are usually very computationally intensive, since the environment map is usually constructed incrementally and thus objects that were detected, for example, in a first measurement must be recognized particularly reliable and accurate in a second measurement. Particularly in the object recognition of, for example, other vehicles by means of ultrasonic sensors, the positions of the vehicles can be determined only very inaccurate, since the ultrasonic sensors measure depending on the pose of the motor vehicle, ie orientation or angle and distance of the motor vehicle to the other vehicle, different contour points on the other vehicle , In order to obtain more reliable results, the data of several measuring cycles and / or sensors are thus usually fused, whereby the computing power increases significantly.

In the method according to the invention, provision is now made in particular to carry out the pose determination of the motor vehicle on the basis of the object-specific feature which is located on the object. For this purpose, the object is first recognized based on the first sensor data. In particular, a first image of at least one camera of the motor vehicle is detected as the first sensor data, and / or first laser scanner data of at least one laser scanner of the motor vehicle is detected as the first sensor data. Preferably, the first sensor data is a first image of the surrounding area of the motor vehicle captured by the camera. In this first image of the surrounding area, which was acquired at a first measurement time, the object is identified and the at least one object-specific feature is identified on the object. The object-specific feature is in particular a feature of the object, based on which the object can be uniquely identified and recognized. Then, based on the object-specific feature, the first pose of the motor vehicle is determined to the object-specific feature. Based on the object, which is uniquely identifiable, and based on the first pose then the environment map can be created by the motor vehicle and the object are entered into the map and thereby have a predetermined by the first pose spatial position to each other.

Then, second sensor data, for example a second camera image and / or second laser scanner data, are acquired by the sensor device at a second measurement time. In particular, a second camera image of the surrounding area is detected as the second sensor data. In particular, between the detection of the first and the second sensor data, ie between the first and the second measurement time, several minutes or even several hours or days lie. The first and the second sensor data are thus in particular no sensor data, which are recorded directly in chronological succession. The first and the second sensor data can be recorded, for example, when the motor vehicle is on a parking space search and passes several times the same location and thus the same object in the surrounding area. It can also be provided that the first and the second sensor data are detected on a route section, which is covered regularly by the motor vehicle, for example in the daily drive to a workstation and / or to a residence of a driver of the motor vehicle. The second sensor data are searched for the object and can be clearly recognized based on the object-specific feature. As soon as the object has been recognized by the computing device of the driver assistance system on the basis of the object-specific feature, the second pose of the motor vehicle relative to the object is determined on the basis of the object-specific feature.

In addition, the pose of the motor vehicle at the second detection time is additionally determined by means of odometry. By odometry, the motor vehicle can estimate its location based on data of its propulsion system. Such data of the propulsion system, for example, a number of Radumdrehungen and steering angle of the motor vehicle. By odometry can thus be determined by detecting the data of the propulsion system and with knowledge of vehicle-specific geometry data, such as a known wheel diameter, a distance that has covered the motor vehicle from the first pose to the second measurement time. An end point of the distance traveled from the first pose is determined as the pose which the motor vehicle has when detecting the second sensor data. If there is no deviation between the second pose and the pose determined by odometry, it is assumed that there is no odometry error. But if the second pose differs from the pose determined by odometry, it is assumed that a There is an odometry error in the pose determination. The odometry error can result, for example, from certain road conditions, changing or incorrect information about the wheel geometry, etc.

In particular, a stationary object is detected as the object. The invention is based on the finding that the odometry adjustment can only be carried out reliably and correctly if the global position of the object has not changed.

The object-specific feature can be recognized in the images, for example by means of pattern recognition. To determine the first and second pose from the feature, edges of the object-specific feature may be identified and an angle between the edges recognized. The detection of the edges can be done by means of a known edge detection method, according to which in the recorded image for color transitions - for example, from black to white - is searched. Depending on the angle, the orientation of the motor vehicle can then be determined, since the angle represents a measure of an orientation angle of the static object with respect to the motor vehicle.

On the basis of the SLAM method, which performs the determination of poses based on the object-specific features and requires very little data and processing power for the localization of the motor vehicle, in addition an odometry adjustment can be carried out and thus a reliable pose determination by Odoemtrie be provided. This can advantageously be provided a reliable and versatile driver assistance system.

Preferably, in the presence of the odometry error, a correction value for compensating the odometry error is determined based on the second pose. It is therefore assumed that the pose detected on the basis of the second sensor data is the correct current pose of the motor vehicle. The correction value is then determined so that the resulting pose determined by odometry corresponds to the second pose.

As a result of the particularly continuous detection of the object-specific features of objects in the surrounding area and mapping of their positions in the environment map or two-dimensional plane, therefore, the odometry errors can be continuously corrected by means of the SLAM method and thus a particularly reliable driver assistance system can be provided.

In an advantageous embodiment of the invention, after identifying the object-specific feature, the object is assigned an identification number which is stored in a vehicle-side storage device. On the basis of this object-specific identification number or ID, which is uniquely assigned to the object-specific feature, the object can be uniquely identified as soon as the object-specific feature has been re-detected. In this case, the ID is stored together with information about the object-specific feature in the storage device. In particular, the ID and the information are stored at least for so long that the odometry adjustment can also be carried out if, for example, the motor vehicle returns to the global position after several days, in which the object with the object-specific feature is located.

In a development of the invention, the second sensor data for recognizing the object is only searched for the object-specific feature if, on the basis of data of a navigation system of the motor vehicle, it was detected that the surrounding area from which the first sensor data is acquired, and the surrounding area from which the second sensor data has been recorded, at least partially overlapping. To navigate the motor vehicle by means of the navigation system, a global position of the motor vehicle in GPS coordinates can be determined by means of GPS (Global Positioning System). The motor vehicle can thus be localized globally by GPS. This global position of the motor vehicle can be detected by means of the navigation system at the first measurement time. If it has been detected by the navigation system that the motor vehicle is at the second measuring time at least in the vicinity of the global position, which held the motor vehicle at the first measuring time, for example in the same street, the second sensor data for identifying the object after the object-specific feature. Thus, computing time and computing power can advantageously be saved since the sensor data are only searched if recognition of the object is probable.

Particularly preferably, a parked other vehicle is recognized as the object and identified as the object-specific feature is a motor vehicle license plate, in particular at least one alphanumeric character of the motor vehicle license plate. In other words, this means that the license plates or license plates are detected by parked vehicles. These number plates can be detected continuously by means of the camera and their positions can be imaged in the two-dimensional plane or environment map. So it will be used the exact positions of the license plates to correct the continuous odometry errors by the SLAM method. This embodiment takes advantage of the fact that almost every vehicle has such an official license plate, so that it can be used reliably for the identification of the vehicle. These license plates can be identified particularly easily, for example, using pattern recognition. Since these license plates usually have a predetermined orientation on the vehicle, the license plates can be used advantageously for reliable determination of the pose. For this purpose, in particular longitudinal edges of the license plate are recognized, and determines an angle between the longitudinal edges as a measure of the orientation angle of the motor vehicle to the other vehicle. In addition, in particular, the at least one alphanumeric character representing information about the vehicle is identified and the ID assigned to this alphanumeric character, so that the parked vehicle can be uniquely identified.

In particular, based on the first and / or the second pose of the motor vehicle with respect to the parked vehicle and based on predetermined geometric data describing the parked motor vehicle, at least one geometric dimension of a parking space adjacent to the parked vehicle is determined for the motor vehicle. In particular, transverse parking gaps can be detected on the basis of the pose of the motor vehicle with respect to the vehicle registration number. If the longitudinal edges of the license plate, for example, extend parallel to a vehicle longitudinal direction of the motor vehicle, the transverse parking space can be detected in a passing of the motor vehicle to the parked vehicles. On the basis of predetermined geometric data, which in particular describe a length of the parked vehicle, it is thus possible in particular to determine a depth of the parking space as the geometric dimension of the parking space. The particular pose can therefore be used advantageously in many ways by the driver assistance system.

Alternatively or additionally, a milestone may be recognized as the object and a kilometer indication on the milestone may be identified as the object-specific feature. The milestones are usually attached to lane edges of lanes at regular intervals so that they can be used to determine the distance traveled and to determine location. This embodiment is particularly advantageous when the motor vehicle is regularly, for example daily, on a certain road section and thus regularly passes by the same milestone. The odometry data are thus recorded over a particularly long period of time, for example, between passing the milestone on a first day and passing the milestone on the following day. The odometry data are then recorded over the entire period, even if the motor vehicle has been turned off in the meantime.

It proves to be advantageous if in third sensor data a further mileage is recognized and a further mileage is recorded on the further milestone, based on the mileage on the milestones a distance between the milestones is determined by a mileage covered by the mileage by means of distance Odometry is detected and the odometer error is detected if a further deviation between the distance and the distance traveled exceeds a further predetermined threshold. This embodiment is based on the finding that the milestones are usually set up at regular intervals. By the mileage information on the milestones in the form of numbers, the distance between two milestones can be determined. In addition, based on the odometry, in particular on the basis of a number of Radumdrehungen, the distance covered by the motor vehicle between the milestones be determined. If there is no odometry error, the distance covered should correspond to the distance between the milestones. However, if the distance covered by odometry deviates from the distance between the milestones, then the odometry error is also detected. This is particularly advantageous when the motor vehicle passes every milestone only once and thus can not perform the Odometrievgleich the same milestone.

It can also be provided that a house is recognized as the object and a house number plate, in particular at least one number on the house number plate, is identified as the object-specific feature. In particular, in this embodiment, the recognition of the object, that is, here of the house, is linked to the position determination carried out by the navigation system of the motor vehicle. If, for example, it has been detected by the navigation system that the motor vehicle repeatedly enters a certain street, then a specific house number can be recognized on a house in this street, and odometry reconciliation can be performed on the basis of this house number.

The invention also relates to a computing device for a driver assistance system Motor vehicle, which is designed to carry out a method according to the invention. The computing device can be integrated, for example, in a vehicle-side control unit.

A driver assistance system according to the invention comprises a computing device according to the invention and a sensor device for detecting an environmental region of the motor vehicle. The sensor device may comprise, for example, at least one laser scanner and / or at least one camera. The driver assistance system is in particular designed to carry out a position determination of the motor vehicle by means of a SLAM method and by means of odometry and thus to determine an area map of the motor vehicle. On the basis of the map of the surroundings and the corrected odometry data, in particular an at least semi-autonomous maneuvering of the motor vehicle can be made possible. For example, an at least semi-autonomous parking process for the motor vehicle can be carried out by the driver assistance system.

Moreover, the invention relates to a motor vehicle with a driver assistance system according to the invention. The motor vehicle is designed in particular as a passenger car.

The preferred embodiments presented with reference to the method according to the invention and their advantages apply correspondingly to the computing device according to the invention, the driver assistance system according to the invention and to the motor vehicle according to the invention.

Further features of the invention will become apparent from the claims, the figures and the description of the figures. The features and feature combinations mentioned above in the description, as well as the features and combinations of features mentioned below in the description of the figures and / or shown alone in the figures, can be used not only in the respectively specified combination but also in other combinations or in isolation, without the frame to leave the invention. Thus, embodiments of the invention are to be regarded as encompassed and disclosed, which are not explicitly shown and explained in the figures, however, emerge and can be produced by separated combinations of features from the embodiments explained. Embodiments and combinations of features are also to be regarded as disclosed, which thus do not have all the features of an originally formulated independent claim. Moreover, embodiments and combinations of features, in particular by the embodiments set out above, are to be regarded as disclosed, which go beyond or deviate from the combinations of features set out in the back references of the claims.

The invention will now be described with reference to preferred embodiments and with reference to the accompanying drawings.

Showing:

1 a schematic representation of an embodiment of a motor vehicle according to the invention; and

2 a schematic representation of a captured by the motor vehicle camera image for Posenbestimmung.

In the figures, identical and functionally identical elements are provided with the same reference numerals.

1 shows a motor vehicle 1 according to the present invention. The car 1 is designed in particular as a passenger car. The car 1 includes a driver assistance system 2 , which is designed to perform a so-called Simultaneous Localization and Mapping (SLAM) method or a "Simultaneous Localization and Map Generation". This means that the driver assistance system 2 is designed to be a an environment area 3 of the motor vehicle 1 create descriptive map of the environment and at the same time a pose of the motor vehicle 1 in the area map estimate or determine. The driver assistance system 2 has to a sensor device S, which is designed to sensor data from the surrounding area 3 capture. In the present case, the sensor device S at least one camera 4 having. The sensor device S can also have at least one laser scanner. The cameras 4 are designed to be the environment area 3 of the motor vehicle 1 to capture in pictures. The cameras 4 Here form a panoramic camera system or surround-view camera system, with a first camera 4 in a front area 5 of the motor vehicle 1 is arranged, a second camera 4 in a rear area 6 of the motor vehicle 1 is arranged a third camera 4 on a driver's side 7 of the motor vehicle 1 is arranged and a fourth camera 4 on a passenger side 8th of the motor vehicle 1 is arranged. By means of the all-round camera system, in particular, the entire surrounding area 3 to the motor vehicle 1 around in pictures.

The driver assistance system 2 here also includes a computing device 9 , which is designed to detect the pose of the sensor based on the sensor data S detected sensor data motor vehicle 1 , So an orientation and a position of the motor vehicle 1 , with respect to an object O (see 2 ) in the surrounding area 3 of the motor vehicle 1 to determine. In addition, the driver assistance system 2 designed to pose the motor vehicle 1 in the surrounding area 3 to be determined by odometry. This can be done by the driver assistance system 2 Data of a propulsion system of the motor vehicle 1 For example, a number of revolutions of wheels 10 of the motor vehicle 1 and / or steering angle of the motor vehicle 1 to capture. Due to vehicle parameters, for example, due to changing and / or incorrectly given wheel geometries and Fahrwerkgeometrien, it may happen that the pose determination by means of odometry is faulty.

First, the sensor device S first sensor data from the surrounding area 3 of the motor vehicle 1 detected. Such first sensor data are in 2 in the form of a first camera image 11 the one in the front area 5 of the motor vehicle 1 arranged camera 4 shown. The car 1 is on a roadway 12 and detects the first camera image during a trip at a first measurement time 11 , The camera 4 may, for example, have a fisheye lens, resulting in the in 2 shown perspective distortion in the camera image 11 results.

In the first camera picture 11 There are images of objects O, with the objects O in the present case as parked, other vehicles 13 and as a house 14 are formed. The objects O are in particular at least temporarily stationary or immovable objects. The computing device 9 is designed to hold the objects O in the camera 4 captured camera image 11 to identify and identify at least one object-specific feature M at the objects O. The respective object-specific feature can be clearly assigned to an object O, in particular. In the present case, the object-specific feature M of the parked vehicles 13 one license plate each 15 or license plate identified and as the object-specific feature M of the house 14 a house nameplate 16 identified.

To identify the license plate 15 and / or the house number plate 16 can take the picture taken 11 from the computing device 9 a pattern recognition regarding corners and edges of the license plate 15 and / or the house number plate 16 be subjected. It can thus be captured in the picture 11 to search for a rectangle or a trapezoid. This method of detecting one of the license plate 15 and / or the house number plate 16 on the one hand is particularly reliable and on the other hand relatively easy to implement. When recognizing the license plate 15 and / or the house number plate 16 First, its edges can be detected, and then the corners of the license plate can be based on the edges 15 and / or the house number plate 16 be identified. The detection of the edges can be done by means of a known edge detection method, according to which in the recorded image 11 for color transitions - for example, from black to white - is sought. If the edges have been detected, the corners of the license plate also result 15 and / or the house number plate 16 , After recognition of the license plate 15 and / or the house number plate 16 the recognition can be made plausible by giving a length of the image of the license plate 15 and / or the house number plate 16 is compared with its width, and it is checked whether this ratio is within a predetermined value range. Thus, the license plate 15 and / or the house number plate 16 be distinguished from other rectangles, since both the length and the width are fixed in particular for license plates and thus represent a standard size.

In addition, the computing device 9 designed to use the object-specific features M a respective first pose of the motor vehicle 1 to determine the object-specific characteristics M. The first pose corresponds to the pose which the motor vehicle 1 when capturing the first camera image 11 to the object-specific feature M holds. To determine the orientation based on the image of the license plate 15 and / or the house number plate 16 can longitudinal edges of the license plate 15 and / or the house number plate 16 in the picture 11 be identified and an angle between the longitudinal edges are determined. Depending on the angle, the orientation can then be determined, since the angle is a measure of an orientation angle of the neighboring vehicle 13 and / or the house 14 with respect to the motor vehicle 1 represents. Based on the determination of the pose with respect to the object-specific features M, the SLAM method can be carried out by imaging the objects O and the motor vehicle in the especially two-dimensional environment map. In this case, the motor vehicle 1 For example, at the origin of a two-dimensional coordinate system in which the environment map is determined, positions of the objects O in the two-dimensional environment map are determined by the camera image 11 result in a determined poses.

In addition, the computing device 9 every object O based on the Object-specific feature M assign a unique identification number or ID and deposit them in a vehicle-mounted storage device. It may be advantageous, the numbers or numbers and letters of the license plate 15 recognize and on the basis of which a unique identification number or ID matching the parked vehicle 13 is created. If the license plate 15 is detected again and recognized, is provided via this ID the information that it is the same license plate 15 the same vehicle 13 is. This information is especially important if only parts of the number plate were recognized and thus results in a scatter, if the same number plate 15 again and again, but recognized or detected at different positions. This dispersion can thus be contained in order to converge faster with the SLAM. Furthermore, for example, only one digit can be picked out, which is to be detected to calculate the SLAM, whereby fewer detection points are necessary to calculate a SLAM, and thus run time can be saved.

Also, the computing device 9 a number on the house number plate 16 recognize and these, in particular together with a street, in which the house 14 assigned to a specific identification number. The road can, for example, based on a navigation system of the motor vehicle 1 be determined by which the motor vehicle 1 is localized globally.

Then, at a second measurement time, another second camera image is used as the second sensor data of the surrounding area 3 from the camera 4 added. If now the motor vehicle 1 again passes the objects O, for example, because the motor vehicle 1 Searching for a parking space, so are the images of the objects O in the other camera image. The computing device 9 can now search the other second image for the objects O by the computing device 9 the additional image is searched for the object-specific characteristics M. When the computing device 9 the object-specific feature M, for example one of the number plates 15 , in which another image has been detected, so also the object O, so the associated vehicle 13 , clearly recognized and a second pose of the motor vehicle 1 determined to the object O. It can be provided that the computing device 9 the further camera image is only searched for the object-specific features M, if based on the navigation system of the motor vehicle 1 it was recognized that the motor vehicle 1 when recording the second camera image in approximately the same surrounding area 3 is like taking the first camera image 11 ,

This second pose is compared to a pose produced by the computing device 9 determined by odometry. The pose determined by means of odometry results from the route which the motor vehicle 1 since capturing the first image 11 until the acquisition of the further image. In other words, starting from the first pose on the basis of odometry data or data of the propulsion system of the motor vehicle 1 For example, a number of wheel revolutions and / or a steering angle determines the distance traveled and determines the end of the distance as the pose to which the second pose is compared. So it is carried out an odometry adjustment. If there is no odometry error, that is, if the underlying and collected odometry data matches the current, real data, the pose determined by odometry would have to match the second pose. If the two poses do not match, then an odometry error is detected. Based on the magnitude of the deviation, a correction factor can be determined, by means of which the odometry error can be corrected during the position determination of the motor vehicle by means of odometry.

In addition, the computing device 9 here on the basis of the specific pose of the motor vehicle 1 to the license plate 15 one of the vehicles 13 and based on at least one predetermined geometric dimension of the parked vehicle 13 a geometric dimension 17 a parking space 18 of the motor vehicle 1 determine. Based on a length of the vehicle 13 can the computing device 9 as the geometric dimension 17 in particular a depth of the parking space 18 detect. The driver assistance system can be based on the environment map and the corrected odometry data 2 then, for example, an at least semi-autonomous parking process for the motor vehicle 1 in the parking space 18 provide or carry out.

QUOTES INCLUDE IN THE DESCRIPTION

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Cited patent literature

• DE 102010056217 A1 [0002]

Claims (14)

Method for operating a driver assistance system ( 2 ) of a motor vehicle ( 1 ) by - detecting an object (O) in by a vehicle-side sensor device (S) from a surrounding area ( 3 ) of the motor vehicle ( 1 ) detected first sensor data and identifying an object-specific feature (M) on the object (O) in the first sensor data; Determining a first pose of the motor vehicle ( 1 ) to the object-specific feature (M) on the basis of the object-specific feature (M); characterized by - recognizing the object (O) in second sensor data acquired by the sensor device (S) on the basis of the object-specific feature (M); Determining a second pose of the motor vehicle ( 1 ) to the object-specific feature (M) on the basis of the object-specific feature (M); Determining one by a movement of the motor vehicle ( 1 ) between the detection of the first and the second sensor data resulting pose of the motor vehicle ( 1 ) to the object-specific feature (M) by means of odometry; Detecting an odometry error if a deviation between the resulting pose and the second pose exceeds a predetermined threshold. A method according to claim 1, characterized in that in the presence of the odometry error, a correction value for compensating the odometry error is determined based on the second pose. Method according to claim 1 or 2, characterized in that as the first and second sensor data a first and a second image ( 11 ) of at least one camera ( 4 ) of the motor vehicle ( 1 ) and / or as the first and second sensor data first and second laser scanner data from at least one laser scanner of the motor vehicle ( 1 ). Method according to one of the preceding claims, characterized in that a stationary object is detected as the object (O). Method according to one of the preceding claims, characterized in that after identifying the object-specific feature (M) the object (O) an identification number is assigned, which is stored in a vehicle-mounted storage device. Method according to one of the preceding claims, characterized in that the second sensor data for recognizing the object (O) are searched for the object-specific feature (M) only if based on data of a navigation system of the motor vehicle ( 1 ) that the environmental area ( 3 ), from which the first sensor data was acquired, and the surrounding area ( 3 ) from which the second sensor data was acquired; at least partially overlap. Method according to one of the preceding claims, characterized in that as the object (O) a parked other vehicle ( 13 ) is recognized and as the object-specific feature (M) a vehicle license plate ( 15 ), in particular at least one alphanumeric character of the motor vehicle identification ( 15 ) is identified. A method according to claim 7, characterized in that based on the first and / or the second pose of the motor vehicle ( 1 ) with regard to the registration number ( 15 ) and based on predetermined, the parked vehicle ( 13 ) at least one geometric dimension ( 17 ) one to the parked vehicle ( 13 ) adjacent parking space ( 18 ) for the motor vehicle ( 1 ) is determined. Method according to one of the preceding claims, characterized in that a milestone is recognized as the object (O) and identified as the object-specific feature (M) is a kilometer indication on the milestone. A method according to claim 9, characterized in that in third sensor data, another milestone is detected and a further mileage is recorded on the further milestone, based on the mileage on the milestones a distance between the milestones is determined, one between the two milestones of the motor vehicle ( 1 ) distance is detected by means of odometry and the odometer error is detected if a further deviation between the distance and the distance traveled exceeds a further predetermined threshold. Method according to one of the preceding claims, characterized in that as the object (O) a house ( 14 ) is recognized and as the object-specific feature (M) a house number plate ( 16 ), in particular at least one digit on the house number plate ( 16 ) is identified. Computing device ( 9 ) for a driver assistance system ( 2 ) of a motor vehicle ( 1 ) which is adapted to perform a method according to any one of the preceding claims. Driver assistance system ( 2 ) for a motor vehicle ( 1 ) with a sensor device (S) for detecting a surrounding area ( 3 ) of Motor vehicle ( 1 ) and with a computing device ( 9 ) according to claim 12. Motor vehicle ( 1 ) with a driver assistance system ( 2 ) according to claim 13.

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