Comparison of Different Methods for Time Sequence Prediction in Autonomous Vehicles

no code implementations • 16 Jul 2020 • Teng Liu, Bin Tian, Yunfeng Ai, Long Chen, Fei Liu, Dongpu Cao

As a combination of various kinds of technologies, autonomous vehicles could complete a series of driving tasks by itself, such as perception, decision-making, planning, and control.

Autonomous Vehicles Decision Making +2

AutoMine: An Unmanned Mine Dataset

no code implementations • CVPR 2022 • Yuchen Li, Zixuan Li, Siyu Teng, Yu Zhang, YuHang Zhou, Yuchang Zhu, Dongpu Cao, Bin Tian, Yunfeng Ai, Zhe XuanYuan, Long Chen

The main contributions of the AutoMine dataset are as follows: 1. The first autonomous driving dataset for perception and localization in mine scenarios.

Autonomous Driving

Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives

no code implementations • 17 Mar 2023 • Siyu Teng, Xuemin Hu, Peng Deng, Bai Li, Yuchen Li, Dongsheng Yang, Yunfeng Ai, Lingxi Li, Zhe XuanYuan, Fenghua Zhu, Long Chen

Intelligent vehicles (IVs) have gained worldwide attention due to their increased convenience, safety advantages, and potential commercial value.

Autonomous Driving Motion Planning

FusionPlanner: A Multi-task Motion Planner for Mining Trucks via Multi-sensor Fusion

no code implementations • 14 Aug 2023 • Siyu Teng, Luxi Li, Yuchen Li, Xuemin Hu, Lingxi Li, Yunfeng Ai, Long Chen

Firstly, we propose a multi-task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi-sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation.

Motion Planning Scheduling +1