An uncrewed vehicle or unmanned vehicle is a vehicle without a person on board. Uncrewed vehicles can either be under telerobotic control—remote controlled or remote guided vehicles—or they can be autonomously controlled—autonomous vehicles—which are capable of sensing their environment and navigating on their own.
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Deep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects,
Explores trajectory forecasting in autonomous vehicles, focusing on deep learning models for predicting human trajectories in socially-aware transportation scenarios.
Explores generative models for trajectory forecasting in autonomous vehicles, including discriminative vs generative models, VAES, GANS, and case studies.