11 citations · 44 across the 17 of their papers we have counts for
5 papers · 1 filter
HYPER: Learned Hybrid Trajectory Prediction via Factored Inference and Adaptive Sampling
Xin Huang, Guy Rosman, Igor Gilitschenski +4
Modeling multi-modal high-level intent is important for ensuring diversity in trajectory prediction. Existing approaches explore the discrete nature of human intent before predicti…
Trajectory Prediction with Linguistic Representations
Yen-Ling Kuo, Xin Huang, Andrei Barbu +4
Language allows humans to build mental models that interpret what is happening around them resulting in more accurate long-term predictions. We present a novel trajectory predictio…
TIP: Task-Informed Motion Prediction for Intelligent Vehicles
Xin Huang, Guy Rosman, Ashkan Jasour +3
When predicting trajectories of road agents, motion predictors usually approximate the future distribution by a limited number of samples. This constraint requires the predictors t…
Fast nonlinear risk assessment for autonomous vehicles using learned conditional probabilistic models of agent futures
Ashkan Jasour, Xin Huang, Allen Wang +1
This paper presents fast non-sampling based methods to assess the risk for trajectories of autonomous vehicles when probabilistic predictions of other agents' futures are generated…
Risk Conditioned Neural Motion Planning
Xin Huang, Meng Feng, Ashkan Jasour +2
Risk-bounded motion planning is an important yet difficult problem for safety-critical tasks. While existing mathematical programming methods offer theoretical guarantees in the co…