Advanced Driver Assistance Systems (ADAS) in cars

Conventional ADAS technology can detect some objects, do basic classification, alert the driver of hazardous road conditions, and in some cases, slow or stop the vehicle. This level of ADAS is great for applications like blind spot monitoring, lane change assistance, and forward collision warnings. 

NVIDIA DRIVE™ PX 2 AI car computers take driver assistance to the next level. They take advantage of deep learning and include a software development kit (SDK) for autonomous driving called DriveWorks. This SDK gives developers a powerful foundation for building applications that leverage computationally intensive algorithms for object detection, map localization, and path planning.

With NVIDIA self-driving car solutions, a vehicle's ADAS can discern a police car from a taxi; an ambulance from a delivery truck; or a parked car from one that is about to pull out into traffic. It can even extend this capability to identify everything from cyclists on the sidewalk to absent-minded pedestrians.


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  1. Governments all over the world pay much attention on the poisonous gas limitation and the efficiency of vehicle fuel. It is predicated that the energy saving driver assist system will be applied widely in the future. Although, the solution of driver assist system is decided by many elements, such as the navigation and remote information processing, the related market will expand until the next decade.

  2. Propelled Driver Assistance Systems, or ADAS, is a term alluding to different, innovative, in-vehicle frameworks that are intended to expand street wellbeing by helping drivers turn out to be better mindful of the street and its potential dangers and additionally different drivers around them.

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