Civil Maps, which uses spatial data to create "extremely accurate localization", claims its technology is better suited to autonomous vehicles and mobile networks than existing mapping technologies.
This is what the streets of London look like to a driverless car
The company is targeting its maps at the fully automated end of the autonomous vehicle spectrum, such as Google's self-driving cars, rather than cars like Tesla's, which currently require the driver be ready to take over controls.
Civil Maps' software uses 3D data from sensors such as cameras and high-resolution laser imaging captured by Lidar technology, and organises the information into machine-readable maps. It claims its artificial intelligence software allows it to cut data storage and transmission requirements, making it better suited to use mobile networks for crowdsourcing map data on the fly.
"Autonomous vehicles require a totally new kind of map," said Sravan Puttagunta, CEO of Civil Maps. "Civil Maps' scalable map generation process enables fully autonomous vehicles to drive like humans do - identifying on-road and off-road features even when they might be missing, deteriorated or hidden from view and letting a car know what it can expect along its route. We are honored to work with Ford and the rest of our investor team to pave the way for fully autonomous vehicles at continental scale."
Civil Maps existing investors include Chinese auto-maker SAIC Motor Co and Stanford-StartX Fund.
For Ford, the investment is the firm's latest step to advance self-driving car technology. Ford joined Google, Uber, Lyft, and Volvo earlier this year to create the Self-Driving Coalition for Safer Streets group, which aims to promote the concept of self-driving cars and influence legislation. Ford also launched Ford Smart Mobility this year, focusing on developing and investing in mobility services and technology.