Self-driving cars, like human drivers, perform better when they are familiar with the road environment and able to anticipate the behavior of other vehicles. To achieve this, autonomous driving companies often dedicate significant amounts of time, effort, and resources towards constructing high-definition (HD) maps. These maps create a semantic layer that enables detection of lane boundaries, road signals, crosswalks, traffic lights, and other elements, allowing autonomous vehicles to travel safely.
When a leading US-based AV company needed a partner to help build, enhance, and maintain HD maps to improve their autonomous driving experience across multiple markets, they partnered with Us to label their HD maps, camera logs, still images, videos, LiDAR point clouds, and more.
Together with the Client, we hired and trained full-time teammates to handle their HD map labeling needs using their web-based tooling. We developed a comprehensive solution framework from hiring & training to HD map labeling and quality management that ensures our teammates are well-equipped and can deliver high-quality results following a 4-step HD map labeling process.
Through these efforts, we were able the following results, enabling them to double their overall production rate and remain a top competitor in the AV industry with all KPIs met and surpassed:
Find out more how TaskUs’ AI Services could provide your AV business with accurate and up-to-date HD map labeling by downloading the case study HD Mapping for an Autonomous Driving Company.
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