5 papers
OpenLongTail: Generative Scaling of Long-Tail Driving Data
Lulin Liu, Nuo Chen, Yan Wang +15
Scaling robust driving policies is fundamentally bottlenecked by the scarcity of edge cases in curated datasets. While the real world continuously captures these critical events, s…
Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes
Kaicong Huang, Talha Azfar, Weisong Shi +1
Reliable autonomous driving relies on large-scale, well-labeled data and robust models. However, manual data collection is resource-intensive, and traditional simulation suffers fr…
ICanC: Improving Camera-based Object Detection and Energy Consumption in Low-Illumination Environments
Daniel Ma, Ren Zhong, Weisong Shi
This paper introduces ICanC (pronounced "I Can See"), a novel system designed to enhance object detection and optimize energy efficiency in autonomous vehicles (AVs) operating in l…
Slope Considered Online Nonlinear Trajectory Planning with Differential Energy Model for Autonomous Driving
Zhaofeng Tian, Lichen Xia, Weisong Shi
Achieving energy-efficient trajectory planning for autonomous driving remains a challenge due to the limitations of model-agnostic approaches. This study addresses this gap by intr…
EMATO: Energy-Model-Aware Trajectory Optimization for Autonomous Driving
Zhaofeng Tian, Lichen Xia, Weisong Shi
Autonomous driving lacks strong proof of energy efficiency with the energy-model-agnostic trajectory planning. To achieve an energy consumption model-aware trajectory planning for…