Method and system for information use
Using sensors of a first and second sensor type first and second sensor data are detected and items of information describing identical objects and/or object attributes are allocated to one another in the first and second sensor data. The first and second sensor data are encumbered by first and second ambiguities. Values of the second encumbering ambiguities are at least as great as values of the first encumbering ambiguities. A comparison of the first and second encumbering ambiguities of items of information describing identical objects and/or object attributes takes place. In the case of values of substantially the same size, the items of information describing identical objects and/or object attributes are allocated to one another in the first and second sensor data. In the case of values which are not of substantially the same size the items of information describing identical objects and/or object attributes are confirmed or discarded.
1. A method for information use within a vehicle, the method comprising:
capturing, by a first vehicle sensor type, first sensor data by detecting distances to objects or capturing images of the objects,
capturing, by a second vehicle sensor type, second sensor data by receiving wireless communication indicating presence of the objects,
comparing, by the processor, a value of a first fuzziness affliction of information items describing an identified object and/or object attributes of the identified object in the first sensor data, with a value of a second fuzziness affliction of information items describing the identified object and/or object attributes of the identified object in the second sensor data,
associating, by the processor, the information items describing the identified object and/or object attributes of the identified object in the first and second sensor data with one another when a difference in a magnitude value between the first and second fuzziness afflictions is less than or equal to a threshold, and
confirming, by the processor, validity of the information items describing the identified object and/or object attributes of the identified object in the first sensor data when the difference in the magnitude values is greater than the threshold.
2. The method as claimed in claim 1 , wherein
the sensors of the first sensor type are ambient sensors and the sensors of the second sensor type are vehicle-to-X communication means.
3. The method as claimed in claim 2 , wherein
the first and second sensor data respectively comprise at least one position information item, and the values of the fuzziness afflictions of the position information items are used for the comparison first of all.
4. The method as claimed in claim 3 , wherein
at least the position information item in the second sensor data has been produced using data from a global navigation satellite system prior to being sent via the vehicle-to-X communication means.
5. The method as claimed in claim 1 , wherein
the association of the sensor data comprises the steps of
object recognition in the currently captured sensor data and/or
object tracking from the previously captured to the currently captured sensor data and/or
equalization of capture cycle differences in the sensors and/or the sensor types.
6. The method as claimed in claim 1 , wherein
threshold values for an object recognition algorithm acting on the first sensor data are reduced by the second sensor data.
7. The method as claimed in claim 1 , wherein
an upper limit value is prescribed for the values of the fuzziness afflictions, and if said upper limit value is exceeded then, regardless of the comparison, the information items describing the identified object and/or object attributes of the identified object in the first and second sensor data are not associated with one another.
8. The method as claimed in claim 7 , wherein
the upper limit value is adjusted on the basis of a captured ambient object density, wherein the upper limit value is decreased when an ambient object density rises and is increased when an ambient object density falls.
9. The method as claimed in claim 1 , wherein
if first sensor data are contradictory and/or first sensor data are implausible then information items describing the identified object and/or object attributes of the identified object in the first and second sensor data are always associated with one another.
10. A system for information use within a vehicle, comprising:
vehicle sensors of a first sensor type for detecting distances to objects or capturing images of the objects;
vehicle sensors of a second sensor type for receiving wireless communication indicating presence of the objects; and
a processor configured to:
receive data captured by the vehicle sensors of the first sensor type and the vehicle sensors of the second sensor type,
compare a value of a first fuzziness affliction of information items describing an identified object and/or object attributes of the identified object in the first sensor data, with a value of a second fuzziness affliction of information items describing the identified object and/or object attributes of the identified object in the second sensor data,
associate the information items describing the identified object and/or object attributes of the identified object in the first and second sensor data with one another when a difference in a magnitude values between the first and second fuzziness afflictions is less than or equal to a threshold, and
confirm validity of the information items describing the identified object and/or object attributes of the identified object in the first sensor data when the difference in the magnitude values is greater than the threshold.
11. The system as claimed in claim 10 , wherein the sensors of the first sensor type are one or more elements selected from the group consisting of
a radar sensor,
an optical camera sensor,
a lidar sensor,
a laser sensor and
an ultrasonic sensor.
12. The system as claimed in claim 10 , wherein
the sensors of the second sensor type are one or more elements selected from the group consisting of
WLAN connecting means, based on IEEE 802.11,
ISM (Industrial, Scientific, Medical band) connecting means,
IEEE 802.15.1 connecting means,
IEEE 802.15.4 connecting means,
UWB (Ultra Wide Band) connecting means,
IEEE 802.16 connecting means,
Infrared connecting means,
mobile radio connecting means and
radar-based communication means.