MODELLING AND SIMULATION OF A SMART OBSTACLE DETECTION SENSOR FOR A BIKE OR SCOOTER WITH MODEL-BASED DESIGN

This thesis has been developed within the framework of technologies for autonomous vehicles; it is connected, in particular, to the Advanced Driver-Assistance Systems (ADAS), real-time multi-sensor collision avoidance systems field of research. Advanced Driver-Assistance Systems (ADAS) are groups of electronic technologies that assist drivers in driving actions and their aim is to improve vehicle safety during critical driving conditions by measuring external vehicle variables (such as road and traffic environment conditions). Examples of ADAS are Adaptive Cruise Control (ACC) or Lane Keeping Assist (LKA). The main objective of the thesis is to improve the potential of an existent proof of concept (POC) sensor for bike and scooter types of vehicles, able to correctly detect objects or road irregularities and also communicate a possible dangerous situation to the user in real-time. This task can be divided into two different but connected phases: the first one regards the improvements of the measurement system; the second one is about the device’s hardware and software testing, useful to verify the theorized results previously obtained. The measurement campaign demonstrated not only the feasibility of the project but also the potential of the new device’s characteristics, which enable the user to benefit from a more precise and reliable safety system.