8 papers
RT-VLA: Real-Time Vision-Language-Action Models via Knowledge Distillation
Xiangyu Huang, Zhenlin Hua, Han Zhou +2
Vision-Language-Action (VLA) models have shown strong potential for end-to-end autonomous driving by jointly modeling visual perception, language reasoning, explainability and acti…
Safe2Drive: Evaluating Safe Driving Behaviors of E2E Autonomous Driving Models
Nishad Sahu, Kalpana Panda, Congyuan Yu +3
Recent end-to-end (E2E) autonomous driving policies achieve high driving scores in closed-loop simulations. Yet it remains unclear whether these policies handle common safety-criti…
DriveSafer: End-to-End Autonomous Driving with Safety Guidance
Shounak Sural, Raj Rajkumar
End-to-End (E2E) autonomous driving models have shown growing capability in recent years, with performance improving on increasingly challenging benchmarks. However, modern generat…
BEVMAPMATCH: Multimodal BEV Neural Map Matching for Robust Re-Localization of Autonomous Vehicles
Shounak Sural, Ragunathan Rajkumar
Localization in GNSS-denied and GNSS-degraded environments is a challenge for the safe widespread deployment of autonomous vehicles. Such GNSS-challenged environments require alter…
ObjectTransforms for Uncertainty Quantification and Reduction in Vision-Based Perception for Autonomous Vehicles
Nishad Sahu, Shounak Sural, Aditya Satish Patil +2
Reliable perception is fundamental for safety critical decision making in autonomous driving. Yet, vision based object detector neural networks remain vulnerable to uncertainty ari…
Physics-Informed Neural Controlled Differential Equations for Scalable Long Horizon Multi-Agent Motion Forecasting
Shounak Sural, Charles Kekeh, Wenliang Liu +2
Long-horizon motion forecasting for multiple autonomous robots is challenging due to non-linear agent interactions, compounding prediction errors, and continuous-time evolution of…