© tesla Electronics Production | September 19, 2016
Tesla’s still confident in its Autopilot
After the massive media reporting following the autopilot crash - Tesla is upgrading its autopilot to see the world – in radar.
In a blog post the company describes that the has been a number of small refinements with its version 8 update of the cars software. However, “the most significant upgrade to Autopilot will be the use of more advanced signal processing to create a picture of the world using the onboard radar. The radar was added to all Tesla vehicles in October 2014 as part of the Autopilot hardware suite, but was only meant to be a supplementary sensor to the primary camera and image processing system,” the company states. In the blog post the company goes on describing the problem that any metal surface with a dish shape is not only reflective, but also amplifies the reflected signal to many times its actual size – such as a soda can tossed to the road. With its concave bottom facing towards you can appear to be a large and dangerous obstacle, but you would definitely not want to slam on the brakes to avoid it. Which essentially means that the is a big problem in using radar to stop the car – false alarms. “Slamming on the brakes is critical if you are about to hit something large and solid, but not if you are merely about to run over a soda can. Having lots of unnecessary braking events would at best be very annoying and at worst cause injury,” the company writes. The first part of solving that problem is having a more detailed point cloud. Software 8.0 unlocks access to six times as many radar objects with the same hardware with a lot more information per object. The second part consists of assembling those radar snapshots, which take place every tenth of a second, into a 3D "picture" of the world. “It is hard to tell from a single frame whether an object is moving or stationary or to distinguish spurious reflections. By comparing several contiguous frames against vehicle velocity and expected path, the car can tell if something is real and assess the probability of collision,” the blog post explains it.