Autonomous driving paper index
A Comprehensive Review of End-to-End Autonomous Driving: Architectures and Emerging Trends
One-line summary
End-to-end autonomous driving is an emerging technology and a prominent research focus in both industry and academia.
Engineering notes
Key topics: end-to-end autonomous driving, autonomous driving, end-to-end, deployment, perception, planning, 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
End-to-end autonomous driving is an emerging technology and a prominent research focus in both industry and academia. By integrating perception, localization, decision-making, and control into a single model, end-to-end systems aim to streamline the traditional modular pipeline while introducing new challenges in safety validation and interpretability. Unlike existing surveys that predominantly catalog algorithms, this review proposes a novel function-oriented taxonomy by categorizing architectures into perception-integrated and planning-integrated paradigms. Beyond the architectural dimension, the analysis delves into critical safety and interpretability, emphasizing the fundamental gap between theoretical design and the reliability required for real-world deployment. Industrial applicability is examined through real-world examples of data closed-loop workflows and simulation testing, addressing practical constraints in latency and computing resources. Finally, the review addresses critical challenges, particularly long-tail data scarcity and the deficiency in human-like decision-making and outlines future directions toward achieving robust autonomy.
Links and sources
Need this topic turned into a technical roadmap?
Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.
Request B2B research
Comments