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Found 5 papers, 1 papers with code
MAAD: A Model and Dataset for "Attended Awareness" in Driving
Our model takes as input scene information in the form of a video and noisy gaze estimates, and outputs visual saliency, a refined gaze estimate, and an estimate of the person's attended awareness.
NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles
In this work, we propose the world's first closed-loop ML-based planning benchmark for autonomous driving.
CARPAL: Confidence-Aware Intent Recognition for Parallel Autonomy
Predicting driver intentions is a difficult and crucial task for advanced driver assistance systems.
DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling
Vehicle trajectory prediction is crucial for autonomous driving and advanced driver assistant systems.
Uncertainty-Aware Driver Trajectory Prediction at Urban Intersections
In this paper, we propose a variational neural network approach that predicts future driver trajectory distributions for the vehicle based on multiple sensors.
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