In Cabin Occupancy Monitoring using sub-THz radar

The alarming increase in child fatalities within vehicles has prompted the European New Car Evaluation Program (NCAP) to recommend the inclusion of a Child Presence Detection (CPD) system in new cars starting from 2020. The occupancy detection by seat locations inside vehicles is not only crucial for conventional vehicles but also holds significant importance for the functioning of autonomous vehicles, where the knowledge of passenger state, including the accurate classification of passengers and objects is crucial. While optical cameras are a viable option with large legacy of image processing algorithms, concerns related to privacy breaches may render them less favourable. Active sensors, radar in particular, offer a promising alternative, provided their performance meets the criteria for reliable occupancy mapping and classification.

This PhD research project is dedicated on the development of an intelligent in-cabin occupancy monitoring system. The primary objective is to implement cutting-edge sub-THz radar technology along with feature-based and image-based machine learning algorithms. The system's primary function will be the detection and accurate classification of occupants into categories such as child, adult, and pet. This innovative approach aims to significantly enhance overall safety, aligning with the evolving landscape of automotive safety standards and the increasing integration of autonomous technologies.