239 citations · 307 across the 5 of their papers we have counts for
5 papers
Physically Feasible Vehicle Trajectory Prediction
Harshayu Girase, Jerrick Hoang, Sai Yalamanchi +1
Predicting the future motion of actors in a traffic scene is a crucial part of any autonomous driving system. Recent research in this area has focused on trajectory prediction appr…
Interaction-Based Trajectory Prediction Over a Hybrid Traffic Graph
Sumit Kumar, Yiming Gu, Jerrick Hoang +2
Behavior prediction of traffic actors is an essential component of any real-world self-driving system. Actors' long-term behaviors tend to be governed by their interactions with ot…
Map-Adaptive Goal-Based Trajectory Prediction
Lingyao Zhang, Po-Hsun Su, Jerrick Hoang +2
We present a new method for multi-modal, long-term vehicle trajectory prediction. Our approach relies on using lane centerlines captured in rich maps of the environment to generate…
Joint Interaction and Trajectory Prediction for Autonomous Driving using Graph Neural Networks
Donsuk Lee, Yiming Gu, Jerrick Hoang +1
In this work, we aim to predict the future motion of vehicles in a traffic scene by explicitly modeling their pairwise interactions. Specifically, we propose a graph neural network…
Benchmarking Model-Based Reinforcement Learning
Tingwu Wang, Xuchan Bao, Ignasi Clavera +7
Model-based reinforcement learning (MBRL) is widely seen as having the potential to be significantly more sample efficient than model-free RL. However, research in model-based RL h…