Mapper aims to be first end-to-end provider of machine readable maps
Autonomous Vehicle Technology announces 2019 ACES Award Winner in Autonomy | Mapping
High-definition maps are a critical input and resource for autonomous vehicles. UC Berkeley spinout Mapper says it is building the world’s largest repository of precise, up-to-date, 3D, machine-readable base maps for many autonomous use cases, with its customers having the ability to dictate which cities they need mapped to move their business forward. It claims to be the first end-to-end provider of machine-readable maps in that it collects the geographical data, converts the data into high-quality maps, and provides the maps to its developer partners at scale via a subscription service.
The company’s maps capture the underlying geometry of the streetscapes and locations of all the lanes and traffic system with high accuracy and without LiDAR. It has developed its technology with lower costs by using unique modeling and data compression techniques, and gathers the data by providing freelance drivers an app that instructs them on tasks and routes to complete. Ultimately, the drivers collectively obtain enough data of an entire city to create a map, and the map remains available to be constantly updated to reflect ongoing changes to the environment.
By making maps available as a service, the cost of access can be cut drastically, as maps can be cross-sold to multiple customers. Similar to server utilization, road utilization at any given time for any given autonomous vehicle company will be dramatically lower and the cost of internally maintaining upto- date maps everywhere will not unnecessary.
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