Date: April 25, 2019
Presenter: Dr. Malika Meghjani (SMART)
Supervisor: Prof. Daniela RUS (MIT-CSAIL)
Abstract: In this talk, I will present a context and intention aware motion planner for autonomous driving in urban environments. Unlike highways, urban environments require the drivers to follow traffic signs and signals while using their best judgment for anomalous situations. In such scenarios, a self-driving car needs to understand and take into account the uncertainties of the environment and the intentions of the surrounding vehicles, to plan its action accordingly. Our Partially Observable Markov Decision Process (POMDP) based planner, models the intentions of the neighboring vehicles using a neural network, and integrates the road contextual information to reduce environment uncertainty and thus speed up the planning process.