
-
MP3: A Unified Model to Map, Perceive, Predict and Plan
High-definition maps (HD maps) are a key component of most modern self-d...
read it
-
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction
Over the last few years, we have witnessed tremendous progress on many s...
read it
-
End-to-end Interpretable Neural Motion Planner
In this paper, we propose a neural motion planner (NMP) for learning to ...
read it
-
Diverse Complexity Measures for Dataset Curation in Self-driving
Modern self-driving autonomy systems heavily rely on deep learning. As a...
read it
-
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles
As self-driving systems become better, simulating scenarios where the au...
read it
-
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving
Self-driving vehicles need to anticipate a diverse set of future traffic...
read it
-
Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs
In this paper, we tackle the problem of spatio-temporal tagging of self-...
read it
-
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction
We present a novel method for testing the safety of self-driving vehicle...
read it
-
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations
In this paper we propose a novel end-to-end learnable network that perfo...
read it
-
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles
The motion planners used in self-driving vehicles need to generate traje...
read it