Thesis Code: 22008

Thesis Type: Master Thesis for Computer Engineering, ICT for Smart Societies, Telecommunication Engineering or related fields

 Research Area: Connected Systems and Cybersecurity


  • Excellent software programming skills
  • Strong experience with Python/bash scripting and Linux environment
  • Good knowledge of C/C++ programming languages

A precise knowledge of other vehicles, road users and obstacles is crucial for autonomous vehicles to perform safe road manoeuvres. The connected and autonomous vehicles can receive support from the roadside infrastructure regarding the position of obstacles and of other road actors. The roadside infrastructure can exploit data from camera and/or LiDAR for identifying the objects. One key step in the information-gathering process is the computation of the object’s position. This step is particularly complex if only data from the camera are available. In this case, object georeferencing techniques must be applied.

The aim of the thesis is to implement an object georeferencing system to be used for computing the objects’ position in a road environment.

The first part of the thesis will be devoted to surveying the different georeferencing techniques that have been introduced in the literature. The target of the survey is to select the most promising techniques that can be used with data from a camera and/or from a LiDAR. The second part of the thesis will focus on a real implementation of the selected georeferencing techniques that will be tested and evaluated using data from a real system made of a visual camera and a solid-state LiDAR.

The student will have the possibility to work in an informal cutting-edge research laboratory using the latest available technologies of road sensors and exploiting a real-life testbed.

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