METHOD FOR SUPPRESSING AMBIGUOUS MEASUREMENT DATA FROM ENVIRONMENTAL SENSORS

Abstract

A method for eliminating sensor errors, in particular ambiguities when detecting dynamic objects, by a control device, is provide. Measurement data are received from at least one first sensor and object hypotheses are formed from the received measurement data. Data of at least one reference object, which is detected based on measurement data from at least one second sensor, are received. The formed object hypotheses are compared with the at least one detected reference object. Object hypotheses that do not match the detected reference object are rejected. A method for eliminating sensor errors, in particular ambiguities when detecting static objects is also provided.

Claims

1-13. (canceled)

14. A method for eliminating sensor errors in the form of ambiguities when detecting dynamic objects, the method comprising: receiving, by a control device, measurement data from at least one first sensor; forming, by the control device, object hypotheses from the received measurement data; receiving, by the control device, data of at least one reference object, which is detected based on measurement data from at least one second sensor; comparing, by the control device, the formed object hypotheses with the measurement data of the at least one detected reference object; and rejecting, by the control device, object hypotheses of the formed object hypotheses that do not match the measurement data of the detected reference object.

15. The method of claim 14, wherein rejected object hypotheses of the formed object hypotheses are marked as erroneous, or positions at which the rejected object hypotheses of the formed object hypotheses are determined and are marked as unreliable.

16. The method of claim 14, wherein the formed object hypotheses are formed as angle hypotheses from measurement data from at least one radar sensor, which is one of the at least one first sensor.

17. The method of claim 14, wherein the at least one detected reference object is determined from measurement data from the at least one second sensor, which is different from the at least one first sensor.

18. A method for eliminating sensor errors in the form of ambiguities when detecting static objects, the method comprising: receiving, by a control device, measurement data from at least one first sensor; forming, by the control device, object hypotheses from the received measurement data; calculating, by the control device, speeds of the formed object hypotheses; checking, by the control device based on the calculated speed, whether at least one object hypothesis represents a static object; and rejecting, by the control device when at least one determined object hypothesis represents the static object, all formed object hypothesis other than the at least one determined object hypothesis.

19. The method of claim 18, wherein the at least one object hypothesis represents a static object when a velocity lower than a limit value is calculated as the speed of the at least one object hypothesis.

20. The method of claim 18, wherein if at least two object hypotheses represent one static object, probabilities for the at least two object hypotheses are calculated, wherein an object hypothesis of the at least two object hypotheses with a lower probability is rejected.

21. The method of claim 18, wherein all of the formed object hypotheses except for at least one object hypothesis representing the static object are rejected if no data of a reference object are received.

22. The method of claim 18, wherein rejected object hypotheses marked as erroneous, or positions at which the rejected object hypotheses are determined are marked as unreliable.

23. The method of claim 18, the formed object hypotheses are formed as angle hypotheses from measurement data from at least one radar sensor, which is one of the at least one first sensor.

24. A non-transitory machine-readable storage medium on which a computer program is stored, wherein when the computer program is executed by a control device of a vehicle, the computer program causes the control device to: receive measurement data from at least one first sensor; form object hypotheses from the received measurement data; receive data of at least one reference object, which is detected based on measurement data from at least one second sensor; compare the formed object hypotheses with the measurement data of the at least one detected reference object; and reject object hypotheses of the formed object hypotheses that do not match the measurement data of the detected reference object.

Description

BRIEF DESCRIPTION OF THE DRAWING FIGURES

[0030] In the following, preferred exemplary embodiments of the invention are explained in more detail with the aid of highly simplified schematic diagrams. In these:

[0031] FIG. 1 shows a schematic traffic situation with a dynamic object to illustrate a method according to an embodiment,

[0032] FIG. 2 shows a schematic traffic situation with static objects to illustrate a method according to a further embodiment, and

[0033] FIG. 3 shows a schematic flow chart illustrating a method.

DETAILED DESCRIPTION

[0034] FIG. 1 shows a schematic traffic situation 1 with a dynamic object 2 to illustrate a method according to an embodiment. The method is used in particular to eliminate sensor errors, such as ambiguities in a detection of dynamic objects 2, by a control device 4.

[0035] The control device 4 is installed in a mobile unit 6, which is embodied as a motor vehicle that can be operated in automated fashion. The mobile unit 6 has a first sensor 8 and a second sensor 10.

[0036] The first sensor 8 is embodied, by way of example, as a radar sensor and the second sensor 10 as a LIDAR sensor. The control device 4 can receive and evaluate measurement data from the sensors 8, 10. For this purpose, the control device 4 is connected to the sensors 8, 10 for data transfer.

[0037] To distinguish between correct object hypotheses 12 and erroneous object hypotheses 14, which are based on measurement data from the first sensor 8, information from the second sensor 10 can be used. For example, a stably determined reference object 11 and in particular a position of the reference object 11 can be used to confirm one of the two object hypotheses 12.

[0038] Other object hypotheses 14, 16 are subsequently rejected. The positions where the rejected object hypotheses 14, 16 are present are marked as an unreliable region U.

[0039] FIG. 2 shows a schematic traffic situation 1 with static objects 3 to illustrate a method according to a further embodiment. The method is used to eliminate sensor errors, in particular ambiguities, when detecting static objects 3.

[0040] Measurement data from the first sensor 8 are evaluated here, and a plurality of object hypotheses 12, 14 are formed. There are no reference objects 11 that can be used by the control device 4.

[0041] If the incorrect object hypothesis 14 or angle hypothesis is selected by the signal processing of the control device 4, the result is an incorrect calculated speed over ground for the corresponding object hypothesis 14. This allows static objects 3 to be identified as dynamic or moving objects 2.

[0042] Moving objects 2 have a high relevance for the driving function, since they are usually other road users.

[0043] Stationary targets 3 classified as moving objects 2 are particularly critical, since both their position and their speed are erroneous. It is therefore advantageous to assume a location as a stationary target or as a static object 3 if one of the object hypotheses 12 or angle hypotheses support this. All other object hypotheses 14 are rejected.

[0044] FIG. 3 shows a schematic flow chart illustrating a method according to a further embodiment.

[0045] Measurement data are received from at least one first sensor 8. The first sensor 8 can be a radar sensor, for example. Angle hypotheses are also formed and transmitted with the measurement data.

[0046] Parallel to this, measurement data from an inertial measurement unit 13 can be received. The measurement data can include, for example, a speed, acceleration values and yaw rates of the vehicle 6.

[0047] Based on the measurement data of the first sensor 8 and the inertial measurement unit 13, a selection 20 of an object hypothesis is made, and thus ambiguities are eliminated.

[0048] The selection 20 of an object hypothesis can be implemented by one of the methods according to the invention, so that only correct object hypotheses 12 are forwarded for further processing, such as object tracking and measurement data fusion 22.

[0049] Measurement data from a second sensor 10, such as a LIDAR sensor 10, are used both for sensor data fusion 22 and for object hypothesis selection 20, for example, to provide reference objects 11.

[0050] The fused measurement data can then be used to implement driving functions 24. Here, the driving function 24 can have direct or indirect access to a vehicle actuator 26, such as braking functions, acceleration functions and steering functions. In addition to the driving function 24, the data determined and forwarded by the selection 20 of the object hypothesis can also be used in a landmark-based localization.

[0051] Although the invention has been illustrated and described in detail by way of preferred embodiments, the invention is not limited by the examples disclosed, and other variations can be derived from these by the person skilled in the art without leaving the scope of the invention. It is therefore clear that there is a plurality of possible variations. It is also clear that embodiments stated by way of example are only really examples that are not to be seen as limiting the scope, application possibilities or configuration of the invention in any way. In fact, the preceding description and the description of the figures enable the person skilled in the art to implement the exemplary embodiments in concrete manner, wherein, with the knowledge of the disclosed inventive concept, the person skilled in the art is able to undertake various changes, for example, with regard to the functioning or arrangement of individual elements stated in an exemplary embodiment without leaving the scope of the invention, which is defined by the claims and their legal equivalents, such as further explanations in the description.