Abstract: There is provided a method for operating a vehicle having an automated driving system (ADS) and a fallback stop feature. The method includes obtaining sensor data and localization data including information about a surrounding environment of the vehicle, and determining a plurality of candidate paths for a prediction time horizon within a drivable area in the surrounding environment of the vehicle based on the sensor data and the localization data. Further, the method includes determining an expected trajectory of a target vehicle located in the surrounding environment of the vehicle for the prediction time horizon based on the obtained sensor data and localization data, and determining, for each candidate path, an overlap cost parameter for an overlap between the target vehicle's expected trajectory and a set of stop positions of the vehicle based on predicted executions of the fallback stop feature within the prediction time horizon.

Abstract: There is provided a method for operating a vehicle having an automated driving system (ADS) and a fallback stop feature. The method includes obtaining sensor data and localization data including information about a surrounding environment of the vehicle, and determining a plurality of candidate paths for a prediction time horizon within a drivable area in the surrounding environment of the vehicle based on the sensor data and the localization data. Further, the method includes determining an expected trajectory of a target vehicle located in the surrounding environment of the vehicle for the prediction time horizon based on the obtained sensor data and localization data, and determining, for each candidate path, an overlap cost parameter for an overlap between the target vehicle's expected trajectory and a set of stop positions of the vehicle based on predicted executions of the fallback stop feature within the prediction time horizon.