Title:	Vehicle Behavior Prediction Using Deep Learning
DNr:	Berzelius-2024-328
Project Type:	LiU Berzelius
Principal Investigator:	Erik Frisk <erik.frisk@liu.se>
Affiliation:	Linköpings universitet
Duration:	2024-09-01 – 2025-03-01
Classification:	20201
Homepage:	https://liu.se/medarbetare/erifr93
Keywords:

Abstract

A pivotal aspect of advancing self-driving vehicles is equipping them with the ability to accurately forecast the behavior (motion and intention) of surround- ing road users. However, merely making accurate predictions is not sufficient. To enable safe and robust decision-making processes, it is crucial that these methods also effectively handle the multimodality and uncertainty in forecasted behaviors. As a natural consequence, probabilistic modeling has become a cor- nerstone in devising robust trajectory prediction methods. In this project, we seek to explore the potential of generative modeling for trajectory prediction applications.