This paper outlines a methodology for combining user's preferred driving style and safety margins into an ADAS's module for optimal reference maneuver computation. The module for optimal reference maneuver computation is part of the system decision planning chain, which links scenario interpretation to warning intervention strategies. The module objective is the computation of a reference maneuver and produce a measure of the related risk by solving an optimal control problem. In this case, the optimal control problem consists in finding the control functions that minimize the integral of a given penalty function over a planning distance subject to a set of constraints. The penalty function is the mean to implement the safe maneuver concept, which has to comply with three top-level requirements: safety-margins, user acceptance and mobility. In the present work only the safe-speed functionality is addressed and a new penalty function formulation is proposed in order to include both safety criteria and preferred driving style. In this paper it is shown that each user's personal driving style can be characterized through a small set of parameters from the analysis of car longitudinal and lateral accelerations that can be easily used in optimal control formulation.