Granted Patent B2

US 12,534,091 · App. 18/339,257 · Granted Jan 27, 2026

Inventors: Matthias Schreier (Heppenheim, DE); Matthias Komar (Heppenheim, DE); Linda Schubert (Kressbronn, DE)

Assignee: Continental Autonomous Mobility Germany GmbH

B60W50/0205B60W40/02B60W2050/021B60W2050/0215B60W2556/65

Abstract

Claims (19)

1 . A method for determining sensor error, the method comprising:

recording a vehicle environment of an ego vehicle by an environment perception sensor of the ego vehicle;

generating an environment representation based on the recording by the environment perception sensor;

analyzing the environment representation in the ego vehicle by an analysis unit;

determining environment information based on the analysis of the environment representation;

entering the environment information in an environment model, wherein the environment information comprises an absolute position of the ego vehicle;

determining at least one further vehicle in the environment representation from the environment perception sensor of the ego vehicle, wherein the environment information comprises a perceived position of the at least one further vehicle relative to the ego vehicle;

transmitting information from the at least one further vehicle to the ego vehicle by a vehicle-to-vehicle communication unit, wherein the transmitted information comprises a first absolute position of the at least one further vehicle;

comparing (i) a second absolute position of the at least one further vehicle determined from the absolute position of the ego vehicle and the perceived position of the at least one further vehicle with (ii) the first absolute position of the at least one further vehicle;

determining a sensor error based on the result of the comparing; and

deactivating at least one of a driver assistance system and a vehicle autonomous system based on a determination of the sensor error.

2 . The method as claimed in claim 1 , wherein determining the sensor error comprises neural networks and/or probabilistic models and/or fuzzy logic approaches and/or probabilistic logic determining the sensor error.

3 . The method as claimed in claim 1 , wherein determining the sensor error comprises determining whether the sensor error is present in the ego vehicle or in the at least one further vehicle.

4 . The method as claimed in claim 3 , wherein if the determined sensor error is present in the at least one further vehicle the at least one further vehicle is informed of the error by the ego vehicle or a backend server and the at least one further vehicle deactivates at least one of its respective driver assistance system and its respective vehicle autonomous system.

5 . The method as claimed in claim 1 , wherein determining the sensor error comprises transmitting further information from additional vehicles that detect the ego vehicle by at least one environment perception sensor.

6 . The method as claimed in claim 5 , wherein the information from the at least one further vehicle and from the additional vehicles is transferred by means of a CAM and/or a CPM.

7 . The method as claimed in claim 5 , wherein determining the sensor error comprises determining the sensor error based on uncertainties in the position of the further vehicle in the CAM message and/or uncertainties in the position of the further vehicle,

wherein the position of the further vehicle is detected by the ego vehicle and tracked in the environment model.

8 . The method as claimed claim 7 , wherein determining the sensor error comprises determining the sensor error based on driving context knowledge.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (18)