# D2HDMap: Non-visible Driveline Map Prior for Online Vectorized HD Map Prediction

arXiv: https://arxiv.org/abs/2606.20725 · HTML: https://mlsanity.com/paper/2606.20725/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 32 of its 35 references that are in the map.
- First posted on arXiv 17 Jun 2026.

## Builds on (most cited first, 30 of 32)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [DINOv2: Learning Robust Visual Features without Supervision](https://mlsanity.com/paper/2304.07193/) (2023)
- [nuScenes: A multimodal dataset for autonomous driving](https://mlsanity.com/paper/1903.11027/) (2019)
- [Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting](https://mlsanity.com/paper/2301.00493/) (2023)
- [MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction](https://mlsanity.com/paper/2208.14437/) (2022)
- [HDMapNet: An Online HD Map Construction and Evaluation Framework](https://mlsanity.com/paper/2107.06307/) (2021)
- [VectorMapNet: End-to-end Vectorized HD Map Learning](https://mlsanity.com/paper/2206.08920/) (2022)
- [MapTRv2: An End-to-End Framework for Online Vectorized HD Map Construction](https://mlsanity.com/paper/2308.05736/) (2023)
- [StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Construction](https://mlsanity.com/paper/2308.12570/) (2023)
- [BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment](https://mlsanity.com/paper/2211.17111/) (2022)
- [Neural Map Prior for Autonomous Driving](https://mlsanity.com/paper/2304.08481/) (2023)
- [MapTracker: Tracking with Strided Memory Fusion for Consistent Vector HD Mapping](https://mlsanity.com/paper/2403.15951/) (2024)
- [Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps](https://mlsanity.com/paper/2311.04079/) (2023)
- [P-MapNet: Far-seeing Map Generator Enhanced by both SDMap and HDMap Priors](https://mlsanity.com/paper/2403.10521/) (2024)
- [Localization Is All You Evaluate: Data Leakage in Online Mapping Datasets and How to Fix It](https://mlsanity.com/paper/2312.06420/) (2023)
- [Enhancing Vectorized Map Perception with Historical Rasterized Maps](https://mlsanity.com/paper/2409.00620/) (2024)
- [Localization Requirements for Autonomous Vehicles](https://mlsanity.com/paper/1906.01061/) (2019)
- [MapDiffusion: Generative Diffusion for Vectorized Online HD Map Construction and Uncertainty Estimation in Autonomous Driving](https://mlsanity.com/paper/2507.21423/) (2025)
- [PrevPredMap: Exploring Temporal Modeling with Previous Predictions for Online Vectorized HD Map Construction](https://mlsanity.com/paper/2407.17378/) (2024)
- [SMART: Advancing Scalable Map Priors for Driving Topology Reasoning](https://mlsanity.com/paper/2502.04329/) (2025)
- [NeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark](https://mlsanity.com/paper/2306.04540/) (2023)
- [Enhancing Online Road Network Perception and Reasoning with Standard Definition Maps](https://mlsanity.com/paper/2408.01471/) (2024)
- [Exploring Real World Map Change Generalization of Prior-Informed HD Map Prediction Models](https://mlsanity.com/paper/2406.01961/) (2024)
- [LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating](https://mlsanity.com/paper/2501.02763/) (2025)
- [HisTrackMap: Global Vectorized High-Definition Map Construction via History Map Tracking](https://mlsanity.com/paper/2503.07168/) (2025)
- [SDTagNet: Leveraging Text-Annotated Navigation Maps for Online HD Map Construction](https://mlsanity.com/paper/2506.08997/) (2025)
- [Mind the map! Accounting for existing map information when estimating online HDMaps from sensor](https://mlsanity.com/paper/2311.10517/) (2023)
- [Enhancing Lane Segment Perception and Topology Reasoning with Crowdsourcing Trajectory Priors](https://mlsanity.com/paper/2411.17161/) (2024)
- [Uni-PrevPredMap: Extending PrevPredMap to a Unified Framework of Prior-Informed Modeling for Online Vectorized HD Map Construction](https://mlsanity.com/paper/2504.06647/) (2025)
- [SD++: Enhancing Standard Definition Maps by Incorporating Road Knowledge using LLMs](https://mlsanity.com/paper/2502.02773/) (2025)

## Built on by (most cited first, 2 of 2)

- [HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors](https://mlsanity.com/paper/2607.21281/) (2026)
- [PseudoMapLabeler: Confidence-Aware Pseudo-Label Generation for Semi-Supervised Online Mapping](https://mlsanity.com/paper/2608.12600/) (2026)

## Abstract (arXiv)

Accurate, up-to-date representations of road structures are critical for the safe operation of autonomous vehicles. Existing systems rely either on costly, maintenance-heavy high-definition (HD) maps which compromise safety when outdated, or purely sensor-based online mapping which struggles with long-range reliability and occlusion. Systems incorporating map prior information into online mapping seek to overcome drawbacks of both approaches by combining them in some way. We propose 'Driveline To HD Map' (D2HDMap), an online mapping system that injects a lightweight, non-visible driveline prior to guide the estimation of visible road structures such as lane dividers, road boundaries and crosswalks. This prior incurs less effort to create and update compared to full HD map priors used in other approaches. We also show that training with such a prior can improve generalization at inference time when no prior is available. Ablation studies conducted on the nuScenes and Argoverse 2 dataset demonstrate that models trained using a driveline prior largely retain performance even when priors are not available. On a geographically disjoint split, D2HDMap achieves 44.8 mAP, surpassing recent state-of-the-art. Additionally, noise-aware training substantially increases robustness to realistic localization error.
