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Map-Matching-Based Localization Using Camera and Low-Cost GPS For Lane-Level Accuracy
For self-driving systems or autonomous vehicles (AVs), accurate lane-level localization is a necessity for performing complex driving maneuvers. Classical GNSS based methods are usually not accurate enough to have lane-level localization to support the AV’s maneuvers. LiDAR-based localization can pr...
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Published in: | Procedia computer science 2022, Vol.198, p.255-262 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | For self-driving systems or autonomous vehicles (AVs), accurate lane-level localization is a necessity for performing complex driving maneuvers. Classical GNSS based methods are usually not accurate enough to have lane-level localization to support the AV’s maneuvers. LiDAR-based localization can provide accurate localization. However, the LiDAR price is still one of the big issues preventing this kind of solution from becoming wide-spread commodities. Therefore, in this work, we propose a low-cost solution for lane-level localization using a vision-based system and a low-cost GPS to achieve high precision lane-level localization. Experiments in real-world and real-time demonstrate that the proposed method achieves good lane-level localization accuracy, outperforming solutions based on only GPS. |
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ISSN: | 1877-0509 1877-0509 |
DOI: | 10.1016/j.procs.2021.12.237 |