Method for operating a more highly automated vehicle (HAF), in particular a highly automated vehicle

A driver assistance system for controlling an automated vehicle (HAF), comprising:

• at least one sensor that detects at least one feature property of a feature in the surroundings of the HAF;
• a storage module that stores a digital map, the storage module being integrated in the HAF or a central server;
• a position module that determines a position of the HAF, the position module including a global positioning system (GPS) module;
• and
• a control unit that exchanges data with the storage module and the position module and localizes the position of the HAF determined by the position module in the digital map;
• wherein the control unit includes a non-transitory computer readable medium having a computer program, which is executable by a processor of the control unit, including a program code arrangement having program code operating an automated vehicle (HAF), by performing the following:
• providing a digital map in a driver assistance system of the HAF;
• determining a current position of the HAF and localizing the position of the HAF in the digital map;
• providing at least one expected feature property of at least one feature in a surroundings of the HAF;
• detecting at least one feature property of the at least one feature in the surroundings of the HAF at least partially based on the at least one expected feature property;
• performing a feature matching operation between the at least one feature property and the at least one expected feature property by comparing the at least one feature property with the at least one expected feature property and ascertaining a feature differential value, based on the comparing, corresponding to a degree of deviation between the at least one feature property with the at least one expected feature property, and wherein when the ascertained feature differential value is the same as or below a feature differential threshold, storing the detected at least one feature property as an actual feature property, and wherein when the ascertained feature differential value exceeds the feature differential threshold, discarding the detected at least one feature property as a false detection;
• and
• determining a plausibility of the at least one feature property at least partially based on the ascertained feature differential value, wherein when the ascertained feature differential value exceeds the feature differential threshold, the at least one feature property is not plausible and a detected feature property is discarded as a false detection;
• wherein the at least one feature includes road markers in the surroundings of the HAF, and wherein the at least one expected feature property includes at least one of a geographical position, dimensions, a color, and/or a relative position of the road markers with respect to the HAF,
• wherein the determining of the plausibility includes discarding a feature property as a false detection when the differential value exceeds the feature differential threshold,
• wherein in the providing of at least one expected feature property, a group of expected feature properties of a group of expected features is provided, and the determining of the plausibility includes discarding the detected at least one feature property as a false detection when the ascertained feature differential value is the same as or below the feature differential threshold when ascertained feature differential values of each of a group of detected features associated with the at least one feature property corresponding to degrees of deviation between each of the group of detected features associated with the at least one feature property exceed the feature differential threshold, and
• wherein the feature differential threshold depends upon the type of the detected feature property, including whether the detected feature is a road marker, or a traffic light, wherein the feature differential threshold corresponding to a detected road marker is lower than the feature differential threshold corresponding to a detected traffic light.

A non-transitory computer readable medium having a computer program, which is executable by a processor, comprising:

• a program code arrangement having program code operating an automated vehicle (HAF), by performing the following:
• providing a digital map in a driver assistance system of the HAF;
• determining a current position of the HAF and localizing the position of the HAF in the digital map;
• providing at least one expected feature property of at least one feature in a surroundings of the HAF;
• detecting at least one feature property of at least one feature in surroundings of the HAF at least partially based on the at least one expected feature property;
• performing a feature matching operation between the at least one feature property and the at least one expected feature property by comparing the at least one feature property with the at least one expected feature property and ascertaining a feature differential value, based on the comparing, corresponding to a degree of deviation between the at least one feature property with the at least one expected feature property, and wherein when the ascertained feature differential value is the same as or below a feature differential threshold, storing the detected at least one feature property as an actual feature property, and wherein when the ascertained feature differential value exceeds the feature differential threshold, discarding the detected at least one feature property as a false detection;
• and
• determining a plausibility of the at least one feature property at least partially based on the ascertained feature differential value, wherein when the ascertained feature differential value exceeds the feature differential threshold, the at least one feature property is not plausible and a detected feature property is discarded as a false detection;
• wherein the at least one feature includes road markers in the surroundings of the HAF, and wherein the at least one expected feature property includes at least one of a geographical position, dimensions, a color, and/or a relative position of the road markers with respect to the HAF,
• wherein the determining of the plausibility includes discarding a feature property as a false detection when the differential value exceeds the feature differential threshold,
• wherein in the providing of at least one expected feature property, a group of expected feature properties of a group of expected features is provided, and the determining of the plausibility includes discarding the detected at least one feature property as a false detection when the ascertained feature differential value is the same as or below the feature differential threshold when ascertained feature differential values of each of a group of detected features associated with the at least one feature property corresponding to degrees of deviation between each of the group of detected features associated with the at least one feature property exceed the feature differential threshold, and
• wherein the feature differential threshold depends upon the type of the detected feature property, including whether the detected feature is a road marker, or a traffic light, wherein the feature differential threshold corresponding to a detected road marker is lower than the feature differential threshold corresponding to a detected traffic light.