Trajectory Prediction with Linguistic Representations

no code implementations • 19 Oct 2021 • Yen-Ling Kuo, Xin Huang, Andrei Barbu, Stephen G. McGill, Boris Katz, John J. Leonard, Guy Rosman

Language allows humans to build mental models that interpret what is happening around them resulting in more accurate long-term predictions.

Trajectory Prediction

TIP: Task-Informed Motion Prediction for Intelligent Vehicles

no code implementations • 17 Oct 2021 • Xin Huang, Guy Rosman, Ashkan Jasour, Stephen G. McGill, John J. Leonard, Brian C. Williams

When predicting trajectories of road agents, motion predictors usually approximate the future distribution by a limited number of samples.

Autonomous Driving Decision Making +1

HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling

no code implementations • 5 Oct 2021 • Xin Huang, Guy Rosman, Igor Gilitschenski, Ashkan Jasour, Stephen G. McGill, John J. Leonard, Brian C. Williams

Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction.

Trajectory Prediction

CARPAL: Confidence-Aware Intent Recognition for Parallel Autonomy

no code implementations • 18 Mar 2020 • Xin Huang, Stephen G. McGill, Jonathan A. DeCastro, Luke Fletcher, John J. Leonard, Brian C. Williams, Guy Rosman

Predicting driver intentions is a difficult and crucial task for advanced driver assistance systems.

Autonomous Driving Decision Making +2

DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling

no code implementations • 28 Nov 2019 • Xin Huang, Stephen G. McGill, Jonathan A. DeCastro, Luke Fletcher, John J. Leonard, Brian C. Williams, Guy Rosman

Vehicle trajectory prediction is crucial for autonomous driving and advanced driver assistant systems.

Autonomous Driving Generative Adversarial Network +2