Lane Keeping Algorithms and Intersection Management on a scaled mock-up autonomous vehicle

The interest in autonomous driving has grown in the recent years, such that it is starting to be adopted in many applications, like in research, industries or in student works and competitions, as its use will probably spread more in the future if people will not fear letting go of the wheel. The main topic of this thesis is the analysis and implementation of control algorithms for a scale model of a self-driving car that has to deal with specific scenarios: straight roads, crosses, curves and stop lines. The information from the external world will come to the car from a camera, that is needed for the development of lane detection algorithms and to let the vehicle know in which situation it is involved. The images captured by the device are later processed in such a way that lanes are recognized: from this, the vehicle trajectory can be generated and it will be used as a reference for lane keeping controls. Hence, both lane detection and lane keeping instructions will be applied to our 1/10 scale on-road vehicle of the Bosch Future Mobility Challenge (BFMC), already provided with the needed hardware and that will constitute our starting point, from which then we will move away in terms of programming language and tasks, as well as of some electronic components.