Mr Izzedin Teeti
Thesis title: Predictive Algorithms for Advanced Autonomous Vehicle Perception
Start year: 2021
Supervisor(s): Dr Andrew Bradley, Professor Fabio Cuzzolin
My research focuses on proposing deep neural network architectures, including computational Theory of Mind, to predict other road users’ intentions and future trajectories like cars or pedestrians.
In general, prediction in autonomous vehicles is challenging due to the uncertainty about a user’s future intention or trajectory and the multimodality of agents behaviours, as one past trajectory can have multiple possible future trajectories. Further, being multi-agent environments, roads host agents characterised by different goals and features. For example, pedestrians possess more diverse and unpredictable trajectories than cars, which can only use a finite number of predefined lanes, in manners restricted by road rules and geometry.
Autonomous Driving and Intelligent Transport
Academic School / Department