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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.

This paper outlines the modeling process in SysML (Systems Modeling Language) in context of MBSE (Model Based Software Engineering) as well as the MBD (Model-Based Design) in Simulink and we compare the models to get useful information into software. For this goal, we propose the use of an RM/SM tool (Requirements Management and Systems Modeling) (3SL Cradle) and Matlab/Simulink to model the system, do the system validations, and finally embed the generated code. For automotive systems, the development process is visualized through the V-Model, which leads to the right choice of components, the integration of the system and the project realization. The first step in V-Model handles the requirements management for the development, i.e., the requirements for a project will be collected in respect to the stakeholder’s needs and system limitations.