KREUZADER (Posts tagged autonomous vehicles)

1.5M ratings
277k ratings

See, that’s what the app is perfect for.

Sounds perfect Wahhhh, I don’t wanna
Split-Second ‘Phantom’ Images Can Fool Tesla’s Autopilot
Safety concerns over automated driver-assistance systems like Tesla’s usually focus on what the car can’t see, like the white side of a truck that one Tesla confused with a bright sky in 2016,...

Split-Second ‘Phantom’ Images Can Fool Tesla’s Autopilot

Safety concerns over automated driver-assistance systems like Tesla’s usually focus on what the car can’t see, like the white side of a truck that one Tesla confused with a bright sky in 2016,  leading to the death of a driver. But one group of researchers has been focused on what autonomous driving systems might see that a human driver doesn't—including “phantom” objects and signs that aren’t really there, which could wreak havoc on the road.

Researchers at Israel’s Ben Gurion University of the Negev have spent the last two years experimenting with those “phantom” images to trick semi-autonomous driving systems. They previously revealed that they could use split-second light projections on roads to successfully trick Tesla’s driver-assistance systems into automatically stopping without warning when its camera sees spoofed images of road signs or pedestrians. In new research, they’ve found they can pull off the same trick with just a few frames of a road sign injected on a billboard’s video. And they warn that if hackers hijacked an internet-connected billboard to carry out the trick, it could be used to cause traffic jams or even road accidents while leaving little evidence behind.

Source: Wired
tesla computer vision autonomous vehicles
A popular self-driving car dataset is missing labels for hundreds of pedestrians
Machine learning, the process of teaching computer algorithms to perform new tasks by example, is poised to transform industries from agriculture to insurance. But ML...

A popular self-driving car dataset is missing labels for hundreds of pedestrians

Machine learning, the process of teaching computer algorithms to perform new tasks by example, is poised to transform industries from agriculture to insurance. But ML models can only be as good as the data on which they’re trained.

One much-hyped area where machine learning is going to bring about societal change is in the advent of self-driving cars. But with great power comes great responsibility; a poorly trained self driving car can, quite literally, lead to human fatalities.

That’s why we were surprised and concerned when we discovered that a popular dataset (5,100 stars and 1,800 forks) being used by thousands of students to build an open-source self driving car contains critical errors and omissions.

Source: blog.roboflow.ai
machine learning neural networking machine vision autonomous vehicles
Experimental Security Research of Tesla Autopilot
“Tesla Autopilot can identify the wet weather through image recognition technology, and then turn on the wipers if necessary. Based on our research, with an adversarial example craftily generated in...

Experimental Security Research of Tesla Autopilot

Tesla Autopilot can identify the wet weather through image recognition technology, and then turn on the wipers if necessary. Based on our research, with an adversarial example craftily generated in the physical world, the system will be interfered and return an “improper” result, then turn on the wipers.

Tesla Autopilot recognizes lanes and assists control by identifying road traffic markings. Based on the research, we proved that by placing interference stickers on the road, the Autopilot system will capture these information and make an abnormal judgement, which causes the vehicle to enter into the reverse lane.

After compromised the Autopilot system on the Tesla Model S(ver 2018.6.1), Keen Lab further proved that we can control the steering system through the Autopilot system with a wireless gamepad, even when the Autopilot system is not activated by the driver.

Source: keenlab.tencent.com
autonomous vehicles artificial intelligence tesla
A Classical Math Problem Gets Pulled Into the Modern World
“ Sum of squares meets the real world in the field of optimization. Optimization theory is concerned with finding the best way to do something amid constraints — like finding the best route...

A Classical Math Problem Gets Pulled Into the Modern World

Sum of squares meets the real world in the field of optimization. Optimization theory is concerned with finding the best way to do something amid constraints — like finding the best route to work given the current traffic conditions and a stop you need to make along the way. Scenarios like these can often be distilled into polynomial equations. In such cases, you solve, or “optimize” the scenario, by finding the minimum value taken by the polynomial.

[…]

Because the minimum value of a polynomial is hard to compute directly, researchers infer it by other means. And this is where nonnegativity, and the question of whether a polynomial is a sum of squares, comes in. “Certifying nonnegativity is really the heart of all optimization problems,” said Rekha Thomas, a mathematician at the University of Washington.

Source: quantamagazine.org
mathematics autonomous vehicles
Report: Software bug led to death in Uber’s self-driving crash
“The fatal crash that killed pedestrian Elaine Herzberg in Tempe, Arizona, in March occurred because of a software bug in Uber’s self-driving car technology, The Information’s Amir Efrati...

Report: Software bug led to death in Uber’s self-driving crash

The fatal crash that killed pedestrian Elaine Herzberg in Tempe, Arizona, in March occurred because of a software bug in Uber’s self-driving car technology, The Information’s Amir Efrati reported on Monday. According to two anonymous sources who talked to Efrati, Uber’s sensors did, in fact, detect Herzberg as she crossed the street with her bicycle. Unfortunately, the software classified her as a “false positive” and decided it didn’t need to stop for her.

Source: Ars Technica
uber artificial intelligence autonomous vehicles
MIT Breaks Autonomous Drone Speed Limits By Not Sweating Obstacles“NanoMap uses forward-looking depth sensors that put together an idea of its immediate environment, creating a local 3D data structure. It then uses an algorithm to search that...

MIT Breaks Autonomous Drone Speed Limits By Not Sweating Obstacles

NanoMap uses forward-looking depth sensors that put together an idea of its immediate environment, creating a local 3D data structure. It then uses an algorithm to search that structure. It searches back in time to find a view from its past that resembles its current view. Basically, it gathers just enough information to know that it’s in a “certain area”, and then plans its flight path accordingly. It doesn’t attempt to calculate its exact location and orientation as other models do. It only gets the data it needs not to run into something, and isn’t concerned with exact position and location. They’re calling this idea “pose uncertainty”.

Source: hackaday.com
drone autonomous vehicles
Building Ford’s Next-Generation Autonomous Development Vehicle“Mediated perception requires the creation of high-resolution 3D maps of the environment where the autonomous car will be driving. These maps encompass everything the virtual driver system...

Building Ford’s Next-Generation Autonomous Development Vehicle

Mediated perception requires the creation of high-resolution 3D maps of the environment where the autonomous car will be driving. These maps encompass everything the virtual driver system knows about the road before the car even starts driving — locations of stop signs, crosswalks, traffic signals and other static things. When out on the road, the virtual driver uses its LiDAR, radar and camera sensors to continuously scan the area around the car and compare — or mediate — what it sees against the 3D map. This allows it to precisely locate the vehicle’s position on the road, and to identify and understand what’s around it. Mediated perception also includes the system that knows the rules of the road, so it can prepare and abide by those rules.

Direct perception complements mediated perception by using the sensors to see the vehicle’s positioning on the road, as well as dynamic entities — like pedestrians, cyclists and other cars. The sensors can even help interpret hand signals, such as a police officer in the road directing traffic. Naturally, the capacity for direct perception requires even more sophisticated software and computing power to identify and classify various entities, especially pedestrians who are on the move.

Source: medium.com
ford autonomous vehicles
Uber defies demand to cease self-driving“Uber has been told its self-driving cars are illegal - but it is refusing to take them off San Francisco’s roads.
The company started testing the vehicles this week, but the Department of Motor Vehicles (DMV)...

Uber defies demand to cease self-driving

Uber has been told its self-driving cars are illegal - but it is refusing to take them off San Francisco’s roads.

The company started testing the vehicles this week, but the Department of Motor Vehicles (DMV) has said the firm must have a test permit.

Uber said it did not need one as they have a safety driver at the wheel, and is going to ignore the demand.

Source: bbc.com
uber autonomous vehicles