Abstract: A method for diagnosing a bike, in particular an electric bike, by way of a decision tree includes (i) providing a fault notification or a symptom notification, (ii) determining a diagnostic method step for the bike based on the fault notification or the symptom notification, (iii) actuating the bike based on the diagnostic method step determined, (iv) detecting a diagnostic signal based on the actuated bike, and (v) determining a further diagnostic method step, a fault, or a fault underlying a symptom based on the diagnostic signal detected.

Abstract: A method for diagnosing a bike, in particular an electric bike, by way of a decision tree includes (i) providing a fault notification or a symptom notification, (ii) determining a diagnostic method step for the bike based on the fault notification or the symptom notification, (iii) actuating the bike based on the diagnostic method step determined, (iv) detecting a diagnostic signal based on the actuated bike, and (v) determining a further diagnostic method step, a fault, or a fault underlying a symptom based on the diagnostic signal detected.

Abstract: A method for generating an environment model for a reference vehicle in a driving environment is disclosed. A data record is received from a third-party vehicle via a communication interface. The data record includes absolute position information of the third-party vehicle. The absolute position of the reference vehicle is determined. A relative position of the third-party vehicle is calculated based on absolute position information of the reference vehicle and the third-party vehicle. A relative position of an object in the driving environment is detected with a spatially resolving environment sensor on the reference vehicle. The detected object is correlated with the third-party vehicle when the calculated relative position of the third-party vehicle matches the detected relative position of the object.