This master thesis presents research targeting a driver assistance system where it is possible to understand the environment and prepare a safe path for overtaking when necessary. Overtaking is known as one of the most dangerous driving phases; therefore, creating systems aimed at reducing errors made by drivers and unambiguity in their actions is essential. This work is positioned within the rapidly evolving domain of vehicle automation that from the end of the year 2023 has allowed a SAE level higher than level 2. Furthermore, advanced simulation models are used to replicate realistic and challenging driving scenarios, testing the response of the system in critical situations such as overtaking with oncoming vehicles.