We're all knowledgeable about Google Street View, and there\’s doubt that highly detailed 3D maps of road environments plays a big role during the how autonomous vehicles sooner navigate and earn driving decisions. But collecting such data is expensive, time-consuming and consequently cannot be done frequently enough by dedicated mapping vehicles to help keep pace with adjustments to street layout and environment.
That's where crowdsourcing also comes in.
Mobileye, a pioneer in driver-assistance systems that\’s recently purchased by Intel, wants to create high-definition maps of streets and driving environments by sourcing video data from Two million cars already designed with front-facing cameras in their suite of safety systems. Specifically, Two million BMW, Volkswagen and Nissan cars will gather road imagery and upload it into the cloud in "low-bandwidth data packets" — about 10 kilobytes expertise per 1 kilometer driven — to manufacture a constantly updating 3-D map of road environments. Mobileye refers to this as Road Experience Management (REM) mapping, which is aggregated within the company's updateable RoadBook which is to be as used by Level 4 and Level 5 autonomous cars to generate driving and navigation decisions, into minute details.
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"REM is not only about mapping. Front-facing cameras on ADAS-equipped (Advanced Driver Assistance System) vehicles are intelligent agents that can double to collect dynamic data, for instance road and environmental conditions (hazards, construction, traffic density and weather), infrastructure, and parking availability," Mobileye says.
Mobileye's crowdsourced RoadBook data will first be put to work with in Level 2 and Level 3 cars (with an explanation in the amounts of autonomy, look at our primer here) which will take the market in 2019, additionally, the system will swiftly provide mapped data for more advanced autonomous vehicles. And as the cameras and sensors of cars equipped with autonomous driver-assist systems improve, so will the techniques helpful to create maps of driving environments.
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