Thesis Code: 19001
Thesis Type: Master Thesis for Telecommunication Engineering, Computer Engineering or related fields
Research Area: Multi-Layer Wireless Solutions
- Excellent software programming skills
- Strong experience with Python/bash scripting and Linux environment
- Strong experience with C/C++ programming languages
- Basic knowledge of image processing
- Basic knowledge of machine learning
The knowledge of the surrounding environment is crucial for the connected and autonomous vehicles. These vehicles must timely know the position and the trajectories of other road users to perform safe road manoeuvres. If other road users cannot communicate such information, each vehicle has to rely on its own sensors to identify other cars, bicycles and pedestrians and to foresee their trajectories. A significant support can be provided from the road-side infrastructure. In critical places, fixed sensors can continuously sense the surrounding environment to identify vehicles, pedestrians, other road users and obstacles and the infrastructure can communicate the gathered information to the connected vehicles.
The aim of the thesis is to develop a framework for the identification of road users and for the prediction of their trajectories.
The first part of the thesis will be devoted to the analysis of state-of-art objects tracking methods. In the second part of the thesis, the student will develop a real object tracking system exploiting available cutting-edge image processing tool. Final step is the definition of trajectory prediction algorithm exploiting the gathered information.
The student will have the possibility to work with real-data coming from the field in an informal cutting-edge research laboratory using the latest available technologies on these fields.
Contact: send a resume with attached the list of exams to firstname.lastname@example.org specifying the thesis code and title.