A method of adapting tuning parameter settings of a system functionality for road vehicle speed adjustment control starting from initially selected tuning parameter settings, in order to arrive at adapted tuning parameters by learning from manual driving training data, the method comprising: applying to one or more data processing arrangements of the system a training set of manual driving training data consisting of speed adjustment profiles obtained from manually negotiated road segments and road segment data for these manually negotiated road segments, the method being characterized in that for each of the manually negotiated road segments, it further comprises the steps of: - calculating a simulated speed adjustment profile using the selected tuning parameter settings and the road segment data; - comparing the manual and the simulated speed adjustment profiles to obtain a residual; - calculating a norm of the residual; and for all of the manually negotiated road segments of the training set: - calculating a norm of the norms of the residuals; - performing at least one of optimization, regression analysis or machine-learning to minimize the norm of the norms of the residuals by selecting different tuning parameter settings and iterating the above steps; and selecting, for the road vehicle speed adjustment control functionality, tuning parameter settings rendering a minimal training set norm. applying to one or more data processing arrangements of the system a training set of manual driving training data consisting of speed adjustment profiles obtained from manually negotiated road segments and road segment data for these manually negotiated road segments, the method being characterized in that for each of the manually negotiated road segments, it further comprises the steps of: - calculating a simulated speed adjustment profile using the selected tuning parameter settings and the road segment data; - comparing the manual and the simulated speed adjustment profiles to obtain a residual; - calculating a norm of the residual; and for all of the manually negotiated road segments of the training set: - calculating a norm of the norms of the residuals; - performing at least one of optimization, regression analysis or machine-learning to minimize the norm of the norms of the residuals by selecting different tuning parameter settings and iterating the above steps; and selecting, for the road vehicle speed adjustment control functionality, tuning parameter settings rendering a minimal training set norm. - calculating a simulated speed adjustment profile using the selected tuning parameter settings and the road segment data; - comparing the manual and the simulated speed adjustment profiles to obtain a residual; - calculating a norm of the residual; and for all of the manually negotiated road segments of the training set: - calculating a norm of the norms of the residuals; - performing at least one of optimization, regression analysis or machine-learning to minimize the norm of the norms of the residuals by selecting different tuning parameter settings and iterating the above steps; and selecting, for the road vehicle speed adjustment control functionality, tuning parameter settings rendering a minimal training set norm.