The thesis activity, having identified a particular application domain, will consist of the study, design, development, and testing/validation of perception and sensor fusion algorithms useful for a contextual understanding of the environment, providing output information to be used later as inputs for path planning and control algorithms for autonomous vehicles.
Internship main topic:
Proposed architectures for driver assistance systems (ADAS) and/or autonomous driving include a perception module dedicated to estimating contextual conditions such as the status of other agents (pedestrians and vehicles), horizontal and vertical road markings, and road surface conditions. Such information is usually inferred through the use of machine learning (e.g., computer vision) and sensor fusion algorithms using onboard sensors (cameras, lidar, radar) as input.
Candidate requirements/Course of study:
Computer Engineering, Electronics, or Automation.
Location: Naples
