用车联网协同生成高精地图，实时更新车道线信息。
Leveraging V2X for Collaborative HD Maps Construction Using Scene Graph Generation
- 通过车载摄像头提取车道线并构图，利用车联网上传至云端
- 在nuScenes数据集上关联预测性能优于现有方法
- 适合自动驾驶车队实时地图构建与维护
高精地图在自动驾驶导航中至关重要，可弥补车载感知传感器的精度不足。传统高精地图依赖专用测绘车辆，成本高且无法实时反映基础设施变化。本文提出HDMapLaneNet框架，利用车联网（V2X）通信与场景图生成技术，协同构建局部高精地图的几何层。该方法从前视相机图像中提取车道中心线，将其表示为图结构，并通过V2X将数据传至云端进行全局聚合。在nuScenes数据集上的初步实验表明，其关联预测性能优于当前最先进的方法。
原文摘要 · Abstract (English)
High-Definition (HD) maps play a crucial role in autonomous vehicle navigation, complementing onboard perception sensors for improved accuracy and safety. Traditional HD map generation relies on dedicated mapping vehicles, which are costly and fail to capture real-time infrastructure changes. This paper presents HDMapLaneNet, a novel framework leveraging V2X communication and Scene Graph Generation to collaboratively construct a localized geometric layer of HD maps. The approach extracts lane centerlines from front-facing camera images, represents them as graphs, and transmits the data for global aggregation to the cloud via V2X. Preliminary results on the nuScenes dataset demonstrate superior association prediction performance compared to a state-of-the-art method.
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