METHOD FOR AUTOMATED DEVELOPMENT OF A PATH PLANNING MODULE FOR AN AUTOMATED DRIVING SYSTEM

The present invention relates to a method (100) and apparatus (10) that utilize production vehicles to develop new path planning features for Automated Driving Systems (ADSs) by using federated learning. To achieve this the "under-test" path planning module's output is evaluated in closed-loop in order to produce a cost-function that is subsequently used to update or train a path planning model of the path planning development-module (210). The method comprises obtaining a candidate path from the path planning development-module and determining a risk value for the candidate path. If the determined risk value satisfies at least one risk criterion, the method further comprises: generating, at an output, a first control signal indicative of an instruction for the ADS to execute the candidate path; obtaining at least one quality parameter of the executed candidate path, wherein the at least one quality parameter is indicative of a performance of the candidate path in terms of quality and/or comfort of the executed candidate path.