外观
论文arXiv 2608.095412 个月前
迈向协同联合感知与预测：框架、基线评估与部署视角
原文链接：Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectives（arXiv 2608.09541 · 发布日期：2026-08-10）
Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectives
面向CAV感知误差累积与遮挡，提出Co-P&P框架，并在融合策略评估和端到端原型中验证。
核心要点
- 问题聚焦V2X协同感知中的误差累积与视觉遮挡，并扩展到运动预测。
- 方法提出Co-P&P概念框架，统一协同感知与运动预测以提升态势感知。
- 实验比较不同融合策略，发现预测级融合整体性能低于检测级或跟踪级融合。
- 原型结合RENO点云共享与FutureDet，协作提升预测精度且神经压缩显著降带宽。
验证范围与局限：验证范围为融合策略实验和最小端到端原型；摘要未说明仿真或真机环境。
英文摘要 (Abstract)
Connected Autonomous Vehicles (CAVs) increasingly exploit Vehicle-to-Everything (V2X) communication to exchange multi-source sensor information, enabling advanced Collaborative Perception (CP) capabilities. Extending beyond these capabilities, this work focuses on Collaborative Joint Perception and Prediction (Co-P&P), a paradigm that unifies CP with motion prediction to mitigate two persistent challenges: the accumulation of perception errors and visual occlusions. We present a conceptual framework for Collaborative Joint Perception and Prediction (Co-P&P) that improves motion prediction of surrounding road users, thereby enhancing situational awareness in complex and dynamic traffic environments. Building upon our preliminary study, this extended version compares the performance of different fusion strategies and establishes baseline performance for a modular design of perception and prediction. Experimental results show that prediction-level fusion leads to a decline in overall system performance compared to detection-level or tracking-level fusion. We further implement a minimal end-to-end Co-P&P prototype that couples collaborative point-cloud sharing via the RENO neural codec with joint detection-forecasting via FutureDet, showing that collaboration improves forecasting accuracy while neural compression preserves this benefit at roughly 34x lower communication bandwidth.
作者：Lei Wan, Hannan Ejaz Keen, Alexey Vinel
来源
本页事实对应的公开页面，以原文为准。