Ford announces major investment in self-driving startup Civil Maps

16 Jul 2016

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Ford has announced a major investment in a self-driving startup called Civil Maps, which uses computer maps to create an infrastructure for fully autonomous vehicles to plug in and safely navigate to or from a destination.

The company raised $6.6 million from Ford, Motus ventures and others to accelerate development of autonomous car technology.

While automakers had already invested resources in autonomous car technology, or the related operation of vehicle sharing, this comes as among the first investments in the broader facilitation of autonomous infrastructure.

Using data crowdsourced, processed, and transmitted by Civil Maps, fully autonomous vehicles would be able to identify on-road and off-road features, understand what they meant, and detect changes, allowing them to react like human drivers, Civil Maps differentiated itself further by shrinking the data needed to build multi-dimensional, highly precise maps to guide self-driving cars via AI (artificial intelligence) programming. Currently this type of mapping  required thousands of human hours and could take as much as six months to complete. According to Civil Maps it could do the same task faster and more accurately.

Apart from mapping technology, the company planned to speed up production development and deployment with several automakers and tech co-developers. ''By creating and managing live semantic maps of all the roads in America, the company is providing a technology essential for the leap to fully autonomous vehicles that can transform the future of transportation,'' igitaltrends.com cited Jim DiSanto, managing director of Motus Ventures.

The autonomous car sector and in recent times had drawn huge investments with machine-learning startup FiveAI raising $2.7 million to create the smart autonomous cars of tomorrow using AI.

It promised to bypass the need to ''survey, maintain, and share detailed 3D maps'' of the world's roads, instead building a map of the world in real time as it goes along.

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