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The continuous growth of market for Advanced Driver Assistance Systems based on image processing features leads to the advance of the applied techniques, increasing thus the driving safety. Mostly of the edge detection algorithms are traditional approaches, and to achieve improvements it is necessary to combine different methods. The purpose of this work is to implement a strategy for road lanes detection using the traditional Canny operator. Oriented filters are used to remove unnecessary information and vehicle’s yaw rate signal is used to adaptively correct the filter orientation according to the lane boundaries directions. In sequence, morphological filters using dilation and analysis of connected components are applied in order to remove the noise components of the edge detection stage.

Automotive industry is looking for new design and product development practices to become more competitive. Challenges in current global market have often included sustainable development, environmental regulation and innovative solution to reach customer needs. Today, carmakers are striving to take competitive advantages over global marketplace. Model-Based-Design (MBD) seems to be a feasible answer to improve software development practices in automotive industry. Furthermore, it has been reported as a novel development approach to develop advanced driver assistance systems (ADAS). Among ADAS technologies often required to reduce driver fatigue is Electric Power Assisted Steering (EPAS). By using an auxiliary servomotor, it can reduce significantly driver effort in parking maneuvers. In this scenario, this paper aims to describe how MBD can be used to design EPAS control system.