Various methods for managing and/or monitoring new experiences of an Automated Driving System, ADS, of a vehicle are disclosed. In one example, an ADS experience library is used as training data for an autoencoder on-board the vehicle. A data stream representing driving experiences encountered by the vehicle as it is being driven around is suitably segmented and passed through the autoencoder. The output of the autoencoder exaggerates the reconstruction error for any data in a data segment not included in the training data set. This enables anomalous behavioural data indicative of a new experience encountered by a vehicle when it is being driven around to be identified in the data stream passed through the autoencoder, making it possible to send just the anomalous behavioural data to a back-end fleet server configured to monitor and manage a fleet of vehicles in a timely and bandwidth efficient manner.