119 citations · 404 across the 72 of their papers we have counts for
21 papers · 1 filter
Closing the Loop on Runtime Monitors with Fallback-Safe MPC
Rohan Sinha, Edward Schmerling, Marco Pavone
When we rely on deep-learned models for robotic perception, we must recognize that these models may behave unreliably on inputs dissimilar from the training data, compromising the…
Refining Obstacle Perception Safety Zones via Maneuver-Based Decomposition
Sever Topan, Yuxiao Chen, Edward Schmerling +4
A critical task for developing safe autonomous driving stacks is to determine whether an obstacle is safety-critical, i.e., poses an imminent threat to the autonomous vehicle. Our…
trajdata: A Unified Interface to Multiple Human Trajectory Datasets
Boris Ivanovic, Guanyu Song, Igor Gilitschenski +1
The field of trajectory forecasting has grown significantly in recent years, partially owing to the release of numerous large-scale, real-world human trajectory datasets for autono…
Language Conditioned Traffic Generation
Shuhan Tan, Boris Ivanovic, Xinshuo Weng +2
Simulation forms the backbone of modern self-driving development. Simulators help develop, test, and improve driving systems without putting humans, vehicles, or their environment…
Multi-Predictor Fusion: Combining Learning-based and Rule-based Trajectory Predictors
Sushant Veer, Apoorva Sharma, Marco Pavone
Trajectory prediction modules are key enablers for safe and efficient planning of autonomous vehicles (AVs), particularly in highly interactive traffic scenarios. Recently, learnin…
Risk-Averse Trajectory Optimization via Sample Average Approximation
Thomas Lew, Riccardo Bonalli, Marco Pavone
Trajectory optimization under uncertainty underpins a wide range of applications in robotics. However, existing methods are limited in terms of reasoning about sources of epistemic…