AI 中文总结
针对路边VRU感知难题，提出CLIFE框架，集成无目标在线校准与轻量级后期融合跟踪于单嵌入式设备，无需云卸载。经实验验证，该框架提升了传感器感知能力与鲁棒性，核心运行高效，为下游安全应用提供基础并减少相关开销。
AI 中文摘要
在遮挡、可变光照和多样天气条件下，尤其是在严格的边缘计算和延迟约束下，对弱势道路使用者（VRU）进行可靠的路边感知仍然具有挑战性。现有的多传感器融合系统依赖云或服务器级基础设施，在现实世界的十字路口存在部署差距。我们提出了CLIFE，这是一个原生边缘相机-激光雷达融合框架，它在单个嵌入式设备上完全集成了无目标在线校准和轻量级后期融合跟踪，无需云卸载。CLIFE按需自适应优化相机-激光雷达对齐，并以每帧O(N log N)的成本执行多传感器融合和轨迹关联。我们在查塔努加的12个信号交叉口部署了CLIFE，并使用跨越不同白天、夜间和天气条件的同步相机-激光雷达数据在一个代表性交叉口进行了深入评估。我们的实验表明，融合架构在不同环境和交通条件下显著提高了单个传感器的感知范围和鲁棒性。后期融合核心在Jetson AGX Thor上以53.2 FPS运行，确保了实时交叉口规模应用的高吞吐量。通过将感知集中在边缘，CLIFE为下游安全应用提供了可部署的基础，同时减少了运营多交叉口走廊的机构的带宽和校准开销。
英文摘要
Reliable roadside perception of vulnerable road users (VRUs) remains challenging under occlusions, variable lighting, and diverse weather conditions, particularly under strict edge-computing and latency constraints. Existing multi-sensor fusion systems rely on cloud or server-grade infrastructure, creating a deployment gap at real-world intersections. We present CLIFE, an edge-native camera-LiDAR fusion framework that integrates targetless online calibration and lightweight late-fusion tracking entirely on a single embedded device, without cloud offloading. CLIFE adaptively refines camera-LiDAR alignment on demand and performs multi-sensor fusion and track association with O(N log N) per-frame cost. We deploy CLIFE across 12 signalized intersections in Chattanooga and conduct an in-depth evaluation at a representative intersection using synchronized camera-LiDAR data that spans diverse daytime, nighttime, and weather conditions. Our experiments demonstrate that the fusion architecture substantially enhances the perceptual range and robustness of the individual sensors under varied environmental and traffic conditions. The late-fusion core operates at 53.2 FPS on the Jetson AGX Thor, ensuring high throughput for real-time intersection-scale applications. By centering perception at the edge, CLIFE provides a deployable foundation for downstream safety applications, while reducing bandwidth and calibration overhead for agencies operating multi-intersection corridors.
CommentsAccepted for publication at the 2026 IEEE 29th International Conference on Intelligent Transportation Systems (ITSC 2026). 8 pages, 7 figures
