8 papers
FleetAgent: Teleoperation Assistant for Autonomous Fleets via Vectorized V2N Messages
Juntong Peng, Qi Chen, Deyuan Qu +3
Large-scale autonomous fleets rely on teleoperation to resolve rare failures, yet streaming raw sensor data from many vehicles is costly, and remote operators can only monitor a li…
Localization-Guided Foreground Augmentation in Autonomous Driving
Jiawei Yong, Deyuan Qu, Qi Chen +2
Autonomous driving systems often degrade under adverse visibility conditions-such as rain, nighttime, or snow-where online scene geometry (e.g., lane dividers, road boundaries, and…
CooperDrive: Enhancing Driving Decisions Through Cooperative Perception
Deyuan Qu, Qi Chen, Takayuki Shimizu +1
Autonomous vehicles equipped with robust onboard perception, localization, and planning still face limitations in occlusion and non-line-of-sight (NLOS) scenarios, where delayed re…
M3CAD: Towards Generic Cooperative Autonomous Driving Benchmark
Morui Zhu, Yongqi Zhu, Yihao Zhu +4
We introduce MCAD, a comprehensive benchmark designed to advance research in generic cooperative autonomous driving. MCAD comprises 204 sequences with 30,000 frames. Each s…
From Features to Reference Points: Lightweight and Adaptive Fusion for Cooperative Autonomous Driving
Yongqi Zhu, Morui Zhu, Qi Chen +4
We present RefPtsFusion, a lightweight and interpretable framework for cooperative autonomous driving. Instead of sharing large feature maps or query embeddings, vehicles exchange…
Real-time Motion Planning for autonomous vehicles in dynamic environments
Mohammad Dehghani Tezerjani, Dominic Carrillo, Deyuan Qu +3
Recent advancements in self-driving car technologies have enabled them to navigate autonomously through various environments. However, one of the critical challenges in autonomous…