用摄像头车道线匹配地图，低成本实现更准的导航路线生成
Effective and Low-cost Lane-based Map Localization for Vehicle-Centric Route Generation
- 通过摄像头检测车道线与地图路径对齐，提升定位精度
- 在20米外路段和复杂路况下误差更低，整体欧式距离更小
- 适合低算力车载系统，推动低成本导航研究
以驾驶员为中心的路径表示在直观驾驶引导系统中至关重要。本文提出OLRA，一种基于地图定位的低成本框架，通过将基于地图的导航路径与摄像头检测到的车道线进行匹配，生成与驾驶视角对齐的路线。该对齐过程同时提升了车辆定位精度与视觉路径一致性。为弥合不同范式间的评估差距，我们引入实用的路线评估指标，并将OLRA与代表性的直接生成方法OpenPilot进行对比。在nuScenes数据集上的实验结果表明，OLRA在复杂道路段及20米以上距离的路径估计中表现更优，整体欧氏误差更低。本研究有望推动低成本、基于地图定位的路径生成方法的未来发展。
原文摘要 · Abstract (English)
Driver-centric route representation plays a vital role in intuitive driving guidance systems. This paper presents OLRA, a low-cost, map-localization-based framework that derives driver-view-aligned routes by matching map-based navigation routes with camera-detected lane markings. This alignment process mutually enhances vehicle localization accuracy and visual route consistency. To bridge the evaluation gap across different paradigms, we introduce practical route evaluation metrics and benchmark OLRA against OpenPilot, a representative direct-generation approach. Experimental results on the nuScenes dataset demonstrate that OLRA outperforms OpenPilot in complex road segments and in route estimation at distance beyond 20 meters, achieving lower overall Euclidean error. This study is expected to promote future research in low-cost, maplocalization-based route generation methods.
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