1 citations · 2 across the 8 of their papers we have counts for
9 papers
WZPlanner: Safe End-to-End Path Planning for Autonomous Driving in Work Zones
Nishad Sahu, Changzhong Qian, Guangzhou Cai +3
Work zones alter lane geometry through temporary traffic controls and closures that may be absent from on-board maps, challenging autonomous vehicle (AV) perception and planning. G…
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…
ContextVLM: Zero-Shot and Few-Shot Context Understanding for Autonomous Driving using Vision Language Models
Shounak Sural, Naren, Ragunathan Rajkumar
In recent years, there has been a notable increase in the development of autonomous vehicle (AV) technologies aimed at improving safety in transportation systems. While AVs have be…
ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions
Shounak Sural, Nishad Sahu, Ragunathan Rajkumar
The fusion of multimodal sensor data streams such as camera images and lidar point clouds plays an important role in the operation of autonomous vehicles (AVs). Robust perception a…