Civil Maps, creator of the world's first edge-based HD mapping and localization platform for self-driving cars, today announced it has teamed up with Renovo, the software technology company behind AWare, to provide highly automated vehicle makers and technology providers with seamless access to Civil Maps' vehicular cognition stack. Through this technical collaboration, self-driving systems and other automotive modules that integrate with Renovo's AWare, the first OS built specifically for automated mobility, will be immediately compatible with several key aspects of Civil Maps' platform, a lightweight, highly scalable solution to HD map creation, usage, and continental-scale crowdsourcing. Moving forward, the two companies will work together to standardize abstraction layers that sit between Civil Maps' mapping and localization systems and OEM sensor configurations, decision engines, human machine interfaces (HMIs), and control systems. This collaboration will result in a universal interface, architected by Renovo, that will provide plug-and-play compatibility with Civil Maps' vehicular cognition stack for all other modules in the fast-growing AWare ecosystem, thereby providing significant time and cost savings for developers. "Interoperability is the right direction for the industry and we are excited to take this step forward with Renovo," said Sravan Puttagunta, CEO and Co-founder of Civil Maps.

If you have followed the development of the Internet, starting with the birth of ARPANET (Advanced Research Projects Agency Network) during the Cold War, its evolution might seem interesting but gradual, until it suddenly exploded and changed our lives. After Tim Berners-Lee brought the World Wide Web into existence, the Internet of the early days became practically unrecognizable. This is how technology often develops – very slowly, and then suddenly, very quickly. Self-driving cars also seem to be following this path. In the last few months, we have seen breakthrough after breakthrough that makes autonomous vehicles less "a distant eventuality" and more "a fast-approaching reality."

The weight of the automotive and tech industries is fully behind the move toward self-driving cars. Cars with "limited autonomy"--i.e., the ability to drive themselves under certain conditions (level 3) or within certain geofenced locations (level 4)--should be on our roads within the next five years. But a completely autonomous vehicle--capable of driving anywhere, any time, with human input limited to telling it just a destination--remains a more distant goal. To make that happen, cars are going to need to know exactly where they are in the world with far greater precision than currently possible with technology like GPS. And that means new maps that are far more accurate than anything you could buy at the next gas station--not that a human would be able to read them anyway.

Everyone's been there: driving in the pitch dark, attempting to decipher signs, handle sharp turns, and weave through multiple lanes of whizzing traffic. It's a difficult situation even for an experienced human driver--so how can a car that's driving itself pull it off? An autonomous vehicle must know its precise location, the location of other cars around it, the route to its destination, and any possible obstacles in its path. To deliver that information, automakers are turning to technology developed by San Francisco-based startup Civil Maps. The 30-employee company says it can give cars data that's more accurate and more frequently updated than competing self-driving systems.

Civil Maps' uses AI and sensor data to create maps for autonomous vehicles. Ford is expanding its involvement in self-driving car technology by joining a $6.6m funding round for 3D map-maker Civil Maps. The seed round was led by Motus Ventures, which was joined by Ford, Wicklow Capital, StartX Stanford, and Yahoo cofounder Jerry Yang's AME Cloud Ventures. Mapping technology is seen as a key piece in the autonomous vehicle race, as German auto-makers' acquisition of Here maps from Nokia last year illustrated. 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.

Startup Civil Maps has a plan to get human-piloted cars to hasten their own demise. Autonomous vehicles like those being tested by Google, Uber, and major automakers rely on 3-D maps that record the position of curbstones and traffic lights with high accuracy. The maps are usually created by driving around in vehicles outfitted with expensive sensors. Civil Maps wants to use consumer cars as a low-cost mapping workforce instead, taking advantage of the sensors being added to premium models for advanced cruise control and crash avoidance. Those cheaper sensors can't match those in a dedicated mapping vehicle.

A key component driving the development of driverless cars is machine learning and other artificial intelligence capabilities along with computer vision approaches used for image and signal processing. Ford Motor Co., which is targeting fully autonomous vehicles for ride sharing by 2021, unveiled a series of machine learning and machine vision deals as it doubles the size of it Silicon Valley research campus. The U.S. carmaker (NYSE: F) announced an acquisition and others investments on Tuesday (Aug. Ford also disclosed a licensing deal with machine vision specialist Nirenberg Neuroscience, who is credited with cracking the code the eye uses to transmit visual information to the brain. Furthering its autonomous vehicle initiative, Ford also announced an investment in the 3-D mapping startup, Civil Maps.

A California start-up working on artificial intelligence-powered mapping software for self-driving cars today received 6.6 million from a group of investors that includes the Ford Motor Company. Like other automakers, Ford is testing its autonomous car technology in Michigan and on public roads in California, where its engineers are evaluating the sensors that detect and track objects in the vehicle's view. But the company's investment in the AI mapping start-up, called Civil Maps, reflects the important role that AI and machine learning play in interpreting information from those sensors. Civil Maps has developed software that can process raw 3D data from LiDAR (high-resolution laser imaging), cameras, and other sensors on autonomous vehicles into a machine-readable format. "Autonomous vehicles require a totally new kind of map," the company's CEO Sravan Puttagunta said in a statement.

A setup in California is using AI-inspired mapping software for self-driving cars in its repertoire. It recently got a donation of 6.6 million from a few investing companies. One of these was Ford Motors. Ford is busy road-testing its high technology on the thoroughfares of California and Michigan. The technicians of the company are looking closely at the sensors and other odds and ends in the self-driving vehicles.The AI mapping startup is titled Civil Maps and it is now all ready to engage in some valuable research mainly funded by Ford Motors.

One of the biggest misconceptions about Google's self-driving car right now is that you can't pull up Google Maps, pick a destination and tell the car to go there. That's because to learn new routes, the car has to be "trained" by a human driver at least once or twice first. But now a number of organizations, including Ford Motor Company, Stanford University and an investment firm run by Yahoo co-founder Jerry Yang, have invested 6.6 million into a company that promises to leapfrog that navigation issue by creating cheap, detailed maps that driverless cars will be able to read on the fly. And these maps will be created by regular drivers such as yourself, according to Civil Maps, the company behind the idea. In that respect, the concept is a bit like another Google-owned product, Waze.