Method and device for detecting decalibration of a sensor for acquiring vehicle environment

Abstract

The invention relates to a method for detecting a decalibration of at least one environment sensor (2) for acquiring the environment of a vehicle (1), wherein a plurality of objects (3) in the environment are detected by means of the environment sensor (2), the angular velocities (dα / dt) of the detected objects (3) are determined during a driving process of the vehicle (1), a clustering (P) of a plurality (N) of objects (3) in relation to the angular velocity (dα / dt) is determined by means of a histogram evaluation, and when a clustering (P) is detected outside of a zero angular velocity (dα / dt), a decalibration of the environment sensor (2) is inferred due to a deviation of the orientation of the environment sensor (2) relative to a vehicle axis (A) of the vehicle (1) from a normal position. The invention also relates to a device for detecting a decalibration and a vehicle (1) having such a device.

Description

Technical Field

[0001] The invention relates to a method for detecting decalibration of a sensor for acquiring the surroundings of a vehicle according to the preamble of claim 1. The invention also relates to a device for detecting decalibration of a sensor for acquiring the surroundings of a vehicle according to claim 7, and a vehicle according to claim 8. Background Art

[0002] For example, environmental sensors for motor vehicles may be affected by sudden changes in position and / or orientation, which may lead to degradation of sensor performance. In particular, this may lead to erroneous perception data. With regard to highly automated and / or autonomous driving vehicle systems, undetected sudden changes may lead to unnecessary vehicle interventions and / or prevent necessary vehicle interventions.

[0003] Therefore, it is desirable to detect sudden changes in the position and / or orientation of the environmental sensor.

[0004] In the prior art, the orientation of the sensor is determined based on the time average of the sensed data. The algorithmic methods used for this purpose are inherently slow compared to the update rate of the sensed data. In particular, sudden changes in the sensor orientation relative to the vehicle axis cannot be detected immediately due to the large filter constants.

[0005] DE 10 2021 000 360 A1 describes a device for detecting a miscalibration of a camera. An image sensor is attached to a frame by means of at least one suspension. In addition, at least one capacitor is arranged on the frame, which is fully charged when the camera is deactivated. An evaluation unit is provided, which is designed to determine the charge of the capacitor when the camera is activated, to check whether the determined charge corresponds to an expected value, and to infer a miscalibration of the camera when a deviation between the determined charge and the expected value is detected and / or to output corresponding information when a deviation is detected. Summary of the invention

[0006] The object of the present invention is to provide a method and a device for detecting a miscalibration / calibration deviation / misalignment of a sensor for acquiring a vehicle environment, and to provide a vehicle.

[0007] This object is achieved according to the invention by a method having the features of claim 1 , by a device having the features of claim 7 , and by a vehicle having the features of claim 8 .

[0008] Advantageous embodiments of the invention are the subject matter of the dependent claims.

[0009] The invention relates to a method for detecting a decalibration of a sensor for acquiring the surroundings of a vehicle.

[0010] According to the invention, a plurality of objects in an environment are detected using an environmental sensor. The angular velocity of the detected objects is determined during travel of the vehicle, wherein a clustering of a certain number of objects in relation to the angular velocity is determined by means of a histogram evaluation, and wherein a miscalibration of the environmental sensor is inferred when clustering is detected outside an angular velocity of zero, the miscalibration being caused by a deviation of the orientation of the environmental sensor from a normal position towards a vehicle axis of the vehicle.

[0011] The invention allows for the immediate detection of sudden changes in the position and / or orientation of an environmental sensor. The detection time is limited only by the sensor cycle time.

[0012] This brings the following benefits:

[0013] - reduce the detection time of changes in the position and / or orientation of environmental sensors,

[0014] - avoid safety-related erroneous interventions in vehicle control, and

[0015] -Increase detection confidence of changes in the position and / or orientation of environmental sensors.

[0016] In one embodiment, one or more of the yaw rate, the pitch rate and the roll rate are determined as the angular velocity and a histogram evaluation is performed.

[0017] In one embodiment, the angular velocity of the detected object is determined by comparing the vehicle's motion data with data acquired from or derived from environmental sensors.

[0018] In one embodiment, lidar and / or radar and / or camera and / or ultrasonic sensor are used as environmental sensors.

[0019] In one embodiment, one or more of the following list is used as the vehicle motion data: steering angle, yaw angle, roll angle, pitch angle, yaw acceleration, roll acceleration, pitch acceleration, spring travel signal, wheel speed pulse, position data and redundant environmental sensors.

[0020] In one embodiment, lidar and / or radar and / or camera and / or ultrasonic sensor are used as redundant environmental sensors.

[0021] According to one aspect of the present invention, a device for detecting decalibration of at least one environmental sensor for acquiring vehicle environment is provided, the device comprising a data processing unit connected to at least one environmental sensor and configured to execute any one of the above methods.

[0022] According to another aspect of the present invention, a vehicle is provided, comprising the above device and at least one environment sensor for acquiring vehicle environment.

[0023] In one embodiment, lidar and / or radar and / or camera and / or ultrasonic sensor are provided as environmental sensors.

[0024] In one embodiment, in order to obtain the motion data of the vehicle, one or more sensors are provided to obtain one or more data in the following list: steering angle, yaw angle, roll angle, pitch angle, yaw acceleration, roll acceleration, pitch acceleration, spring travel signal, wheel speed pulse, position data and redundant environmental sensors.

[0025] In order to avoid degradation, the invention proposes to directly compare the data of the different sensors, in particular the available vehicle motion data and the detected sensor data. During normal operation, both data sources provide redundantly the same information about the orientation of the vehicle and the sensor, i.e. there is no misalignment between the two orientations. A change in the orientation of the sensor manifests itself as a shift between the two data sources with respect to the extracted orientation. This change can be detected immediately as soon as the input data are available for processing. The sensitivity is limited by the threshold chosen for the allowed shift.

[0026] Possible sensor data are own perception data (eg point clouds from lidar, radar echoes, camera images, ultrasonic echoes) and data derived therefrom.

[0027] Possible sources of vehicle data are:

[0028] -Vehicle's own motion data:

[0029] - steering angle,

[0030] - yaw, roll and pitch angles, including corresponding accelerations,

[0031] - Spring travel signal,

[0032] - wheel speed pulses,

[0033] - location (GPS, GNSS, map data, etc.),

[0034] -Redundant environmental sensors (radar, camera, lidar, ultrasonic). BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Embodiments of the present invention are explained in more detail below with reference to the accompanying drawings.

[0036] in:

[0037] Figure 1shows a schematic diagram of a vehicle in normal operation,

[0038] Figure 2 A schematic diagram showing a vehicle when the orientation of the environmental sensor changes suddenly.

[0039] Figure 3 shows a schematic histogram for representing the distribution of a plurality of detected objects at different angular velocities during normal operation of the vehicle; and

[0040] Figure 4 A schematic histogram is shown for representing the distribution of a plurality of detected objects at different angular velocities upon a sudden change in the orientation of the environmental sensor.

[0041] In all the figures, parts which correspond to one another are provided with the same reference numerals. DETAILED DESCRIPTION

[0042] Figure 1 is a schematic diagram of a vehicle 1 in normal operation. At least one environment sensor 2 is arranged on the vehicle 1 , which is oriented in the direction of or relative to the vehicle axis A. The positions of objects in the environment detected by the environment sensor 2 are correct.

[0043] Figure 2 is a schematic diagram of the vehicle 1 in the event of a sudden change in the orientation of the environmental sensor 2. For example, the orientation of the environmental sensor 2 deviates from the vehicle axis A by an angle, in particular the yaw angle α. Therefore, in the perception of the environmental sensor 2, the object 3 appears in an offset manner at a distinct position 3'. In the reference coordinate system that moves with the vehicle 1, the change in the position of the object 3 is either the result of the object 3's own movement or the result of the change in the orientation of the environmental sensor 2. The sudden change in orientation appears to the environmental sensor 2 as a movement of the entire arrangement of objects 3 in the same direction. The displacement is r*α, where r is the radial distance of the respective object 3 from the environmental sensor 2. All objects move simultaneously with the same angular velocity dα / dt, in particular the azimuth angular velocity. This movement of the entire arrangement can be detected by algorithmic filtering of the angular velocity dα / dt or the sensor position. The same analysis can be applied to the pitch angle and the roll angle, so that sudden changes in orientation can be detected for all possible cases.

[0044] Figure 3 is a schematic histogram showing the distribution of a plurality of N detected objects at different angular velocities dα / dt during normal operation of the vehicle 1 , ie when the environment sensor 2 is correctly oriented in the direction of or relative to the vehicle axis A.

[0045] The angular velocity dα / dt is defined in a reference coordinate system that moves with the vehicle 1. In normal operation, in typical driving scenarios, the distribution is wide and centered around zero. The variance of the distribution is determined by the motion of the object 3 around the vehicle 1.

[0046] Figure 4 is a schematic histogram representing the distribution of a plurality of N detected objects at different angular velocities dα / dt in the event of a sudden change in orientation, i.e. when the environmental sensor 2 is no longer correctly oriented in the direction of or relative to the vehicle axis A. From the perspective of the environmental sensor 2, a shift in the orientation of the environmental sensor 2 appears as a movement of the entire environment of the vehicle 1 around an angle α. Therefore, all perception data show a strong component of the angular velocity dα / dt, which is superimposed on the real movement of the environment of the vehicle 1. This produces a non-zero peak P or cluster P in the distribution, respectively. The faster the displacement occurs, the greater the magnitude of the angular displacement. Detecting such a cluster P in the distribution of the angular velocity dα / dt provides an effective method for identifying sudden changes in the orientation of the environmental sensor 2.

[0047] The angular velocity dα / dt of the detected object 3 can be determined by comparing the motion data of the vehicle 1 with the data acquired by or derived from the environmental sensor 2. For example, a lidar and / or a radar and / or a camera and / or an ultrasonic sensor can be used as the environmental sensor 2. One or more of the following list can be used as the motion data of the vehicle 1: steering angle, yaw angle, roll angle, pitch angle, yaw acceleration, roll acceleration, pitch acceleration, spring travel signal, wheel speed pulse, position data and redundant environmental sensors, such as a lidar and / or a radar and / or a camera and / or an ultrasonic sensor.

[0048] The method may be executed, for example, in a data processing unit 4 which may be arranged in the vehicle 1 .

Claims

1. A method for detecting a decalibration of at least one environment sensor (2) for acquiring an environment of a vehicle (1), wherein: Using environmental sensors (2) to detect multiple objects (3) in the environment, It is characterized in that The angular velocity of a detected object (3) is determined during travel of a vehicle (1), wherein a clustering of the number of objects (3) in relation to the angular velocity is determined by means of a histogram evaluation, wherein, when clustering is detected at an angular velocity that is not zero, a decalibration of the environmental sensor (2) is inferred due to a deviation of the orientation of the environmental sensor (2) from a normal position with respect to a vehicle axis towards the vehicle (1).

2. The method according to claim 1, It is characterized in that One or more of a yaw rate, a pitch rate, and a roll rate are determined as the angular velocity, and a histogram evaluation is performed.

3. The method according to claim 1 or 2, It is characterized in that The angular velocity of the detected object (3) is determined by comparing the movement data of the vehicle (1) with data acquired from or derived from the environmental sensor (2).

4. The method according to claim 1 or 2, It is characterized in that Lidar and / or radar and / or camera and / or ultrasonic sensor are used as environmental sensors (2).

5. The method according to claim 3, It is characterized in that One or more of the following are used as the motion data of the vehicle (1): steering angle, yaw angle, roll angle, pitch angle, yaw acceleration, roll acceleration, pitch acceleration, spring travel signal, wheel speed pulse, position data and data of redundant environmental sensors.

6. The method according to claim 5, It is characterized in that Lidar and / or radar and / or camera and / or ultrasonic sensor are used as redundant environment sensors.

7. A device for detecting a decalibration of at least one environmental sensor (2) for acquiring the environment of a vehicle (1), the device comprising a data processing unit (4) connected to the at least one environmental sensor (2) and configured to perform a method according to any one of claims 1 to 6.

8. A vehicle (1) comprising a device according to claim 7 and at least one environment sensor (2) for acquiring the environment of the vehicle (1).

9. The vehicle (1) according to claim 8, It is characterized in that Lidar and / or radar and / or camera and / or ultrasonic sensor are provided as environment sensors (2).

10. The vehicle (1) according to claim 8 or 9, It is characterized in that In order to obtain the motion data of the vehicle (1), one or more sensors are provided to obtain one or more of the following data: steering angle, yaw angle, roll angle, pitch angle, yaw acceleration, roll acceleration, pitch acceleration, spring travel signal, wheel speed pulse, position data and data of redundant environmental sensors.

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