468 citations · 900 across the 17 of their papers we have counts for
5 papers · 1 filter
RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios
Wenhao Ding, Yulong Cao, Ding Zhao +2
Simulation plays a crucial role in the development of autonomous vehicles (AVs) due to the potential risks associated with real-world testing. Although significant progress has bee…
Dolphins: Multimodal Language Model for Driving
Yingzi Ma, Yulong Cao, Jiachen Sun +2
The quest for fully autonomous vehicles (AVs) capable of navigating complex real-world scenarios with human-like understanding and responsiveness. In this paper, we introduce Dolph…
ADoPT: LiDAR Spoofing Attack Detection Based on Point-Level Temporal Consistency
Minkyoung Cho, Yulong Cao, Zixiang Zhou +1
Deep neural networks (DNNs) are increasingly integrated into LiDAR (Light Detection and Ranging)-based perception systems for autonomous vehicles (AVs), requiring robust performanc…
Reinforcement Learning with Human Feedback for Realistic Traffic Simulation
Yulong Cao, Boris Ivanovic, Chaowei Xiao +1
In light of the challenges and costs of real-world testing, autonomous vehicle developers often rely on testing in simulation for the creation of reliable systems. A key element of…
Language-Guided Traffic Simulation via Scene-Level Diffusion
Ziyuan Zhong, Davis Rempe, Yuxiao Chen +5
Realistic and controllable traffic simulation is a core capability that is necessary to accelerate autonomous vehicle (AV) development. However, current approaches for controlling…