High-precision positioning, perception and safe navigation for automated heavy-duty mining trucks

L Chen, Y Li, L Li, S Qi, J Zhou, Y Tang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Autonomous driving technology has achieved significant breakthroughs in open scenarios,
enabling the deployment of excellent positioning, detection, and navigation algorithms on …

Spatiotemporal Receding Horizon Control with Proactive Interaction Towards Autonomous Driving in Dense Traffic

L Zheng, R Yang, Z Peng, MY Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In dense traffic scenarios, ensuring safety while keeping high task performance for
autonomous driving is a critical challenge. To address this problem, this paper proposes a …

Multi-step Continuous Decision Making and Planning in Uncertain Dynamic Scenarios through Parallel Spatio-temporal Trajectory Searching

D Li, S Cheng, S Yang, W Huang… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Autonomous driving in urban scenarios faces uncertain dynamic changes, especially in
China, where a dense mixture of cars, cyclists and pedestrians travel together on roads with …

Spatiotemporal receding horizon control with proactive interaction towards safe and efficient autonomous driving in dense traffic

L Zheng, R Yang, Z Peng, MY Wang, J Ma - arXiv preprint arXiv …, 2023 - arxiv.org
In dense traffic scenarios, ensuring safety while keeping high task performance for
autonomous driving is a critical challenge. To address this problem, this paper proposes a …

Risk-Aware Net: An Explicit Collision-Constrained Framework for Enhanced Safety Autonomous Driving

Z Yu, M Zhu, X Chu - IEEE Robotics and Automation Letters, 2024 - ieeexplore.ieee.org
Motion planning is a vital part of autonomous driving. To ensure the safety of autonomous
vehicles, motion planning algorithms need to precisely model potential collision risks and …

IR-STP: Enhancing Autonomous Driving With Interaction Reasoning in Spatio-Temporal Planning

Y Chen, J Cheng, L Gan, S Wang, H Liu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Considerable research efforts have been devoted to the development of motion planning
algorithms, which form a cornerstone of the autonomous driving system (ADS). Nonetheless …

Task-Driven Autonomous Driving: Balanced Strategies Integrating Curriculum Reinforcement Learning and Residual Policy

J Shi, T Zhang, Z Zong, S Chen, J Xin… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Achieving fully autonomous driving in urban traffic scenarios is a significant challenge that
necessitates balancing safety, efficiency, and compliance with traffic regulations. In this …

An Online Energy Management System Based on Minimum-Time Speed Planning for Autonomous Underwater Vehicles

SNH Eimeni, A Khosravi - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Velocity of autonomous underwater vehicles (AUVs) plays a significant role in the energy
consumption of these vehicles, as well as their other capabilities, such as localization …

Safe and Real-Time Consistent Planning for Autonomous Vehicles in Partially Observed Environments via Parallel Consensus Optimization

L Zheng, R Yang, M Zheng, MY Wang, J Ma - arXiv preprint arXiv …, 2024 - arxiv.org
Ensuring safety and driving consistency is a significant challenge for autonomous vehicles
operating in partially observed environments. This work introduces a consistent parallel …

Trajectory Planning for Autonomous Vehicle Using Iterative Reward Prediction in Reinforcement Learning

H Park - arXiv preprint arXiv:2404.12079, 2024 - arxiv.org
Traditional trajectory planning methods for autonomous vehicles have several limitations.
Heuristic and explicit simple rules make trajectory lack generality and complex motion. One …