ExelMap: Explainable Element-based HD-Map Change Detection and Update
Lena Wild, Ludvig Ericson, Rafael Valencia, Patric Jensfelt

TL;DR
ExelMap introduces an explainable, element-based approach for detecting and updating changes in HD maps, improving safety and reliability for autonomous driving by precisely localizing map alterations.
Contribution
The paper proposes ExelMap, a novel explainable method for element-based HD map change detection and updating, addressing limitations of existing approaches and providing a comprehensive real-world evaluation.
Findings
ExelMap effectively identifies changed map elements in real-world scenarios.
Current metrics are inadequate for evaluating change detection performance.
ExelMap outperforms prior methods in localization and explainability.
Abstract
Acquisition and maintenance are central problems in deploying high-definition (HD) maps for autonomous driving, with two lines of research prevalent in current literature: Online HD map generation and HD map change detection. However, the generated map's quality is currently insufficient for safe deployment, and many change detection approaches fail to precisely localize and extract the changed map elements, hence lacking explainability and hindering a potential fleet-based cooperative HD map update. In this paper, we propose the novel task of explainable element-based HD map change detection and update. In extending recent approaches that use online mapping techniques informed with an outdated map prior for HD map updating, we present ExelMap, an explainable element-based map updating strategy that specifically identifies changed map elements. In this context, we discuss how currently…
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Taxonomy
TopicsMedical Image Segmentation Techniques
