Optimizing Autonomous Obstacle Avoidance with PON Architecture and SDN-Based Dynamic Scheduling

Engineering notes

Key topics: autonomous driving system, autonomous driving, perception, 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

<div class="section abstract"> <div class="htmlview paragraph">This study addresses the challenges of communication delays and system stability in autonomous obstacle avoidance (AOA) systems under next-generation vehicular electronic/electrical architectures. A centralized PON-based architecture is proposed, leveraging XGSPON technology to enhance bandwidth capacity and reduce electromagnetic interference, while rigorously analyzing worst-case in-vehicle communication (IVOC) delays. To mitigate latency impacts, a Software-Defined Networking (SDN)-driven dynamic scheduling strategy prioritizes safety-critical data streams (e.g., environmental perception, motion control) through adaptive resource allocation. Further integrated with a robust H-infinity LQR controller, the co-design framework ensures precise trajectory tracking and suppresses steering oscillations under communication uncertainties. Simulation tests validate the framework's efficacy, demonstrating significant reductions in loop delays and improved dynamic stability in complex scenarios. This work bridges communication efficiency and control robustness, offering a scalable solution for advancing safety-critical autonomous driving systems.</div> </div>

Links and sources

Comments