no code implementations • 9 Apr 2024 • Senkang Hu, Zhengru Fang, Zihan Fang, Yiqin Deng, Xianhao Chen, Yuguang Fang
In addition, the single-vehicle autonomous driving systems lack of the ability of collaboration and negotiation with other vehicles, which is crucial for the safety and efficiency of autonomous driving systems.
no code implementations • 1 Feb 2024 • Yuang Zhang, Haonan An, Zhengru Fang, Guowen Xu, Yuan Zhou, Xianhao Chen, Yuguang Fang
Moreover, in the context of collaborative perception, it is important to recognize that not all CAVs contribute valuable data, and some CAV data even have detrimental effects on collaborative perception.
no code implementations • 3 Jan 2024 • Senkang Hu, Zhengru Fang, Yiqin Deng, Xianhao Chen, Yuguang Fang
Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system.
1 code implementation • 28 Nov 2023 • Senkang Hu, Zhengru Fang, Xianhao Chen, Yuguang Fang, Sam Kwong
To address these challenges, we propose a unified domain generalization framework applicable in both training and inference stages of collaborative perception.
no code implementations • 15 Sep 2023 • Senkang Hu, Zhengru Fang, Haonan An, Guowen Xu, Yuan Zhou, Xianhao Chen, Yuguang Fang
To address these issues, we propose ACC-DA, a channel-aware collaborative perception framework to dynamically adjust the communication graph and minimize the average transmission delay while mitigating the side effects from the data heterogeneity.
no code implementations • 1 Feb 2022 • Wei Wei, Jingjing Wang, Jun Du, Zhengru Fang, Chunxiao Jiang, Yong Ren
Simulations show that underwater disturbances have a large impact on the system considering communication delay.