Robert Boschgmbh

Muhammad Sheraz Khan

Carsten Hasberg

Philipp Rasp

Jan-Hendrik Pauls

Ali Alawieh

Danny Hiendriana

Fabian Dominik Reister

Valentin Frommherz

A method is described for verifying a digital map of a higher-level automated vehicle (HAV), in particular a highly automated vehicle, including the steps: S1 providing a digital map, preferably a highly accurate digital map: S2 determining an instantaneous reference position and localizing the reference position in the digital map; S3 establishing at least one actual feature property of a feature in the surroundings of the reference position, the establishment being carried out with the aid of at least one information source; S4 comparing the actual feature property to a setpoint feature property of the feature and ascertaining at least one difference value as the result of the comparison. A corresponding device and a computer program are also described.

Method for verifying a digital map of a higher-level automated vehicle, corresponding device and computer program

A method for operating a higher-level automated vehicle (HAV), in particular a highly automated vehicle, is provided, including: S1 for providing a digital map, which may be a highly accurate digital map, in a driver assistance system of the HAV; S2 for determining an instantaneous vehicle position and localizing the vehicle position in the digital map; S3 for providing an expected setpoint traffic density at the vehicle position; S4 for ascertaining an instantaneous actual traffic density in the surroundings of the HAV; S5 for comparing the actual traffic density to the setpoint traffic density and ascertaining a difference value as the result of the comparison; S6 for checking the vehicle position of the HAV for plausibility at least partially based on the difference value and/or S7 for updating the digital map at least partially based on the difference value. Also described are a corresponding driver assistance system and a computer program.

Method for operating a higher-level automated vehicle (HAV), in particular a highly automated vehicle

A method for ascertaining features in an environment of at least one mobile unit for implementation of a localization and/or mapping by a control unit. In the course of the method, sensor measurement data of the environment are received, the sensor measurement data received are transformed by an alignment algorithm into a cost function and a cost map is generated with the aid of the cost function, a convergence map is generated based on the alignment algorithm. At least one feature is extracted from the cost map and/or the convergence map and stored, the at least one feature being provided in order to optimize a localization and/or mapping. A control unit, a computer program, and a machine-readable storage medium are also described.

Use of cost maps and convergence maps for localization and mapping

A method for predicting a construction-related driving-route change of a driving route for a vehicle includes at least a step of reading in and a step of detecting. In the step of reading in, at least one image signal is read in, which represents an image, recorded by the vehicle, of a construction-site parameter in the environment of the driving route. In the step of detecting, the impending driving-route change is detected using the image signal.

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Heilbronn, Germany

Muhammad Sheraz Khan