16 citations · 33 across the 4 of their papers we have counts for
5 papers
MAAD: A Model and Dataset for "Attended Awareness" in Driving
Deepak Gopinath, Guy Rosman, Simon Stent +4
We propose a computational model to estimate a person's attended awareness of their environment. We define attended awareness to be those parts of a potentially dynamic scene which…
NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles
Holger Caesar, Juraj Kabzan, Kok Seang Tan +6
In this work, we propose the world's first closed-loop ML-based planning benchmark for autonomous driving. While there is a growing body of ML-based motion planners, the lack of es…
CARPAL: Confidence-Aware Intent Recognition for Parallel Autonomy
Xin Huang, Stephen G. McGill, Jonathan A. DeCastro +4
Predicting driver intentions is a difficult and crucial task for advanced driver assistance systems. Traditional confidence measures on predictions often ignore the way predicted t…
DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling
Xin Huang, Stephen G. McGill, Jonathan A. DeCastro +4
Vehicle trajectory prediction is crucial for autonomous driving and advanced driver assistant systems. While existing approaches may sample from a predicted distribution of vehicle…
Uncertainty-Aware Driver Trajectory Prediction at Urban Intersections
Xin Huang, Stephen McGill, Brian C. Williams +2
Predicting the motion of a driver's vehicle is crucial for advanced driving systems, enabling detection of potential risks towards shared control between the driver and automation…