Abstract: Computer-implemented methods and related aspects for planning a driving task for an automated driving system of a vehicle. The method includes obtaining perception data regarding the surrounding environment, obtaining the host vehicle's current state (including pose and velocity), predicting how both the vehicle and its surroundings will evolve over time based on a selected driving policy, determining a threshold velocity for the upcoming driving manoeuvre, verifying the validity of dynamic assumptions used in the predictions (assigning scores to each assumption), and controlling the vehicle to execute a driving task in accordance with a selected driving policy that is selected in view of the current velocity and the verified assumptions.

Abstract: The present invention relates to methods and systems for safety and/or performance monitoring of an Automated Driving System (ADS). The method comprises obtaining a plurality of Performance Indicators (PIs) generated by each of a plurality of ADS-equipped vehicles based one or more driving sessions, wherein the plurality of PIs are of at least one PI-type. The method further comprises modelling each PI-type of the obtained PIs based on an Extreme Value Theory (EVT) model, wherein each modelled PI-type is indicative of a probability for exceeding a PI-value for that PI-type, and evaluating each modelled PI-type against a corresponding predefined requirement. Then, if the evaluation fails, determining that the ADS has violated one or more safety or quality requirements, and transmitting a first signal indicative of the violated one or more safety or quality requirements to an ADS management system and/or a second signal to the plurality of ADS-equipped vehicles.