Thesis Code: 18006

Thesis type: Master Thesis for Telecommunication Engineering, Computer Engineering or related fields

Research Area: Multi-Layer Wireless Solutions

• Good software programming skills
• Good experience with Python programming language
• Knowledge of deep learning, convolutional neural networks and simulations is a plus
• Some background in wireless communications will be a plus

Motivation: Autonomous driving is one of the most complex and interesting topics in the ICT landscape. One of the main challenges for AD is to collect enough data to test and validate autonomous algorithms. Moreover, many different sensors are involved in data collection to feed these algorithms. The behavior of these sensors should be modelled to simulate the real world perception of an AD car. Wireless communications are one of the most promising sensor that will permit to increase the safety of driving, thanks to low-delay direct communication between vehicles, often called V2V (Vehicle-to-vehicle).

Objective: At the beginning of the thesis, the student should analyze the panorama of open source projects aimed at the simulation, testing and validation of sensors and autonomous driving algorithms. The most promising ones should be carefully analyzed, so to understand their maturity level: the second part of the thesis work will be about some tests on such platforms, in particular, delving into the Deep Learning features. As an optional activity, depending on the effort spent on the main activities mentioned before, the student might develop a module to simulate vehicles communications and integrate it in the chosen platform.

Contact: send a resume with attached the list of exams to specifying the thesis code and title.