The output of this system provides actionable objects 360 degrees around the vehicle, enabling enhanced sensor fusion and functional redundancy to camera and lidar perception systems for safe autonomous planning and control. References. Samuel S. Blackman, “Multi-Target Tracking with Radar Applications”, Artech House, 1986 These vehicles need to not only understand their driver, but also be able to predict human behavior, which as we know can be relatively unpredictable. Tech is Expensive. Hardware installed in autonomous vehicles (think cameras, LiDAR systems, and RADAR) is used to capture the external world and help the vehicle make decisions.
With today’s 3D cameras, autonomous vehicles can reliably detect obstacles in their path. Modern systems deliver information so accurate that it can even be determined whether it is an ­object or a person causing. an obstruction. Precise detection of the surrounding area is a crucial basis for the successful application of autonomous vehicles.
Driverless vehicles offer the promise of increased options for public transportation, as nearly everyone’s autonomous car could be used for shuttling commuters from one location to the next. For example, say you take your self-driving car to work, and instead of your vehicle simply sitting in a garage, it goes and starts shuttling other

If vehicles are to be fully autonomous, they need to perceive and track objects in the environment even under non-ideal conditions. There are certain scenarios in which the currently used sensor stack of cameras, lidars, and radars cannot be relied upon.

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Light Detection And Ranging (LIDAR) LIDAR, RAdio Detection And Ranging (RADAR) and Camera are the environment sensors. central to the autonomous car operation. They are used to detect and classify
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    • cameras used in autonomous cars