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.

翻译：以驾驶员为中心的路径表示在直观的驾驶引导系统中起着至关重要的作用。本文提出了OLRA，一种低成本的基于地图定位的框架，通过将基于地图的导航路径与摄像头检测到的车道标记进行匹配，生成与驾驶员视角对齐的路径。这一对齐过程同时提升了车辆定位精度和视觉路径一致性。为弥合不同范式间的评估差距，我们引入了实用的路径评估指标，并将OLRA与代表性直接生成方法OpenPilot进行基准对比。在nuScenes数据集上的实验结果表明，OLRA在复杂路段以及超过20米距离的路径估计中均优于OpenPilot，实现了更低的整体欧氏误差。本研究有望推动未来低成本、基于地图定位的路径生成方法的研究。