collaborators

5 papers

cs.RO2020

Beelines: Motion Prediction Metrics for Self-Driving Safety and Comfort

Skanda Shridhar, Yuhang Ma, Tara Stentz +3

The commonly used metrics for motion prediction do not correlate well with a self-driving vehicle's system-level performance. The most common metrics are average displacement error…

cs.LG2020

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…

eess.SP2020

Goal-Directed Occupancy Prediction for Lane-Following Actors

Poornima Kaniarasu, Galen Clark Haynes, Micol Marchetti-Bowick

Predicting the possible future behaviors of vehicles that drive on shared roads is a crucial task for safe autonomous driving. Many existing approaches to this problem strive to di…

cs.LG2020

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…

cs.RO2020

Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps

Sai Yalamanchi, Tzu-Kuo Huang, Galen Clark Haynes +1

Motion prediction of surrounding vehicles is one of the most important tasks handled by a self-driving vehicle, and represents a critical step in the autonomous system necessary to…