Autonomous driving paper index
Introduction
One-line summary
The field of transportation is undergoing a profound transformation driven by the convergence of control systems, machine learning, and system optimization.
Engineering notes
Key topics: autonomous driving, autonomous vehicle, control. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
The field of transportation is undergoing a profound transformation driven by the convergence of control systems, machine learning, and system optimization. This synergy is accelerating the evolution of connected and autonomous vehicles (CAVs), which are moving beyond heavy reliance on human drivers. Autonomous vehicles (AVs) execute driving tasks with minimal human intervention, while connected vehicles (CVs) are equipped with communication modules to enable information exchange. The integration of these two technologies - CAVs - makes vehicles as decision-making agents in safety-critical networked systems, paving the way for building a transportation system that is safer, more efficient, and sustainable. This book explores how control, learning, and optimization tackle the core challenges of scalability, coordination, and uncertainty under constraints in CAVs.
Links and sources
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