Think Your Way To Work In A Mind-Controlled Tesla

When you own an $80,000 car, a normal person might be inclined to never take it out of the garage. But normal often isn’t what we do around here, so seeing a Tesla S driven by mind control is only slightly shocking.

[Casey_S] appears to be the owner of the Tesla S in question, but if he’s not he’ll have some ‘splaining to do. He took the gigantic battery and computer in a car-shaped case luxury car to a hackathon in Berkley last week and promptly fitted it with the gear needed to drive the car remotely. Yes, the Model S has steering motors built in, but Tesla hasn’t been forthcoming with an API to access such functions. So [Casey_S] and his team had to cobble together a steering servo from a windshield wiper motor and a potentiometer mounted to a frame made of 2x4s. Linear actuators attach to the brake and accelerator pedals, and everything talks to an Arduino.

The really interesting part is that the whole thing is controlled by an electroencephalography helmet and a machine learning algorithm that detects when the driver thinks “forward” or “turn right.” It translates those thoughts to variables that drive the actuators. Unfortunately, space constraints kept [Casey_S] from really putting the rig through its paces, but the video after the break shows that the system worked well enough to move the car forward and steer a little.

There haven’t been too many thought-controlled cars featured here before, but we have covered a wheelchair with an EEG interface.

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[Geohot]’s Self-Driving Car Cancelled

George [Geohot] Hotz has thrown in the towel on his “comma one” self-driving car project. According to [Geohot]’s Twitter stream, the reason is a letter from the US National Highway Traffic Safety Administration (NHTSA), which sent him what basically amounts to a warning to not release self-driving software that might endanger people’s lives.

This comes a week after a post on comma.ai’s blog changed focus from a “self-driving car” to an “advanced driver assistance system”, presumably to get around legal requirements. Apparently, that wasn’t good enough for the NHTSA.

When Robot Cars Kill, Who Gets Sued?

20160530_165433On one hand, we’re sorry to see the system go out like that. The idea of a quick-and-dirty, affordable, crowdsourced driving aid speaks to our hacker heart. But on the other, especially in light of the recent Tesla crash, we’re probably a little bit glad to not have these things on the road. They were not (yet) rigorously tested, and were originally oversold in their capabilities, as last week’s change of focus demonstrated.

Comma.ai’s downgrade to driver-assistance system really begs the Tesla question. Their autopilot is also just an “assistance” system, and the driver is supposed to retain full control of the car at all times. But we all know that it’s good enough that people, famously, let the car take over. And in one case, this has led to death.

Right now, Tesla is hiding behind the same fiction that the NHTSA didn’t buy with comma.ai: that an autopilot add-on won’t lull the driver into overconfidence. The deadly Tesla accident proved how that flimsy that fiction is. And so far, there’s only been one person injured by Tesla’s tech, and his family hasn’t sued. But we wouldn’t be willing to place bets against a jury concluding that Tesla’s marketing of the “autopilot” didn’t contribute to the accident. (We’re hackers, not lawyers.)

Should We Take a Step Back? Or a Leap Forward?

Stepping away from the law, is making people inattentive at the wheel, with a legal wink-and-a-nod that you’re not doing so, morally acceptable? When many states and countries will ban talking on a cell phone in the car, how is it legal to market a device that facilitates taking your hands off the steering wheel entirely? Or is this not all that much different from cruise control?

What Tesla is doing, and [Geohot] was proposing, puts a beta version of a driverless car on the road. On one hand, that’s absolutely what’s needed to push the technology forward. If you’re trying to train a neural network to drive, more data, under all sorts of conditions, is exactly what you need. Tesla uses this data to assess and improve its system all the time. Shutting them down would certainly set back the progress toward actually driverless cars. But is it fair to use the general public as opt-in Guinea pigs for their testing? And how fair is it for the NHTSA to discourage other companies from entering the field?

We’re at a very awkward adolescence of driverless car technology. And like our own adolescence, when we’re through it, it’s going to appear a miracle that we survived some of the stunts we pulled. But the metaphor breaks down with driverless cars — we can also simply wait until the systems are proven safe enough to take full control before we allow them on the streets. The current halfway state, where an autopilot system may lull the driver into a false sense of security, strikes me as particularly dangerous.

So how do we go forward? Do we let every small startup that wants to build a driverless car participate, in the hope that it gets us through the adolescent phase faster? Or do we clamp down on innovation, only letting the technology on the road once it’s proven to be safe? We’d love to hear your arguments in the comment section.

Newsflash: A Bunch Of Arduinos Is Not An Autonomous Car

Nobody’s perfect. Sometimes you’re up late at night writing a blog post and you stumble upon an incredible story. You write it up, and it ends up being, well, incredible. IEEE Spectrum took the bait on this video (embedded below) where [Keran McKenzie] claims to have built a self-driving car for under $1,000 AUS with Arduinos.

The video is actually pretty funny, and we don’t think it’s intended to be a mass-media hoax as much as a YouTube joke. After letting the car “take over” for a few seconds, it swerves and [Keran] pretends to have hit something. (He’s using his knees people!) There are lots of takes with him under the car, and pointing at a single wire that supposedly makes the whole thing work. Yeah, right.

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Self-Driving R/C Car Uses An Intel NUC

Self-driving cars are something we are continually told will be the Next Big Thing. It’s nothing new, we’ve seen several decades of periodic demonstrations of the technology as it has evolved. Now we have real prototype cars on real roads rather than test tracks, and though they are billion-dollar research vehicles from organisations with deep pockets and a long view it is starting to seem that this is a technology we have a real chance of seeing at a consumer level.

A self-driving car may seem as though it is beyond the abilities of a Hackaday reader, but while it might be difficult to produce safe collision avoidance of a full-sized car on public roads it’s certainly not impossible to produce something with a little more modest capabilities. [Jaimyn Mayer] and [Kendrick Tan] have done just that, creating a self-driving R/C car that can follow a complex road pattern without human intervention.

The NUC's-eye view. The green line is a human's steering, the blue line the computed steering.
The NUC’s-eye view. The green line is a human’s steering, the blue line the computed steering.

Unexpectedly they have eschewed the many ARM-based boards as the brains of the unit, instead going for an Intel NUC mini-PC powered by a Core i5 as the brains of the unit. It’s powered by a laptop battery bank, and takes input from a webcam. Direction and throttle can be computed by the NUC and sent to an Arduino which handles the car control. There is also a radio control channel allowing the car to be switched from autonomous to human controlled to emergency stop modes.

They go into detail on the polarizing and neutral density filters they used with their webcam, something that may make interesting reading for anyone interested in machine vision. All their code is open source, and can be found linked from their write-up. Meanwhile the video below the break shows their machine on their test circuit, completing it with varying levels of success.

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[Geohot] Selling His “Self-Driving” Car Tech For $1k By New Year

This week [Geohot] announced the launch of his self-driving car hardware. This is the natural extension of his proof-of-concept shown off in December which he parlayed into a Silicon Valley startup called comma.ai. [Geohot], whose real name is [George Hotz], is well known for jailbreaking the iPhone and making Sony look like idiots when they retroactively crippled Linux support on PS3. He has hardware chops.

Initial self-driving add-on hardware only works with Honda and Acura models that already have lane-keeping assist features because those vehicles already have built-in front radar. The package, which replaces the rear view mirror, adds a front facing camera. Those lucky (or brave, foolish, daring?) beta users can trade $999 and $24/month for what is currently a green 3D printed enclosure with some smartphone-like hardware inserted.

The company has taken an interesting approach to acquiring data needed for this particular flavor of self-driving. [Hotz] is teasing a chance at beta test invites to those who contribute driving data to the company. This is as simple as downloading an app to your phone and letting it roll from your windshield as you go bumper to bumper from Mountain View to San Francisco. That’s right, the plan is to support just that stretch of the nation’s highway system — although [Hotz] did make a brazen estimate of 90% of commutes for 90% of users within a year. Hey, it’s a startup so it’s either that, selling to a bigger fish, or closing their doors.

That narrow route support is actually an interesting constraint. In fact, the company is most interesting because of its chosen constraints: a small subset of cars, a chosen stretch of highway, and dare we say sanity when it comes to self-driving expectations. Grandiose claims have the general public thinking a vehicle with no human driver will slide up to your stoop and take you anywhere you want to go. That is a dauntingly difficult engineering challenge (dare we say impossible). What [Hotz] is selling is a more stress-free commute, not a nap in the back seat. You still need to be paying attention at all times.

Will this system work? Undoubtedly the engineering is possible (Tesla is already doing it). The biggest question mark that remains is human nature. This system demands your attention even though you’re doing nothing. That seems unrealistic — users are bound to lapse in attention much more frequently than if they were the primary driver. The question then becomes, will people pay attention at the very rare yet very crucial moments, and can a system like this prevent more fatal accidents than it causes?

[via Engadget]

Autonomous Truck Teaches Itself To Powerslide

When you’re a teenager new to the sensations of driving, it seems counterintuitive to “turn into the skid”, but once you’ve got a few winters of driving under your belt, you’re drifting like a pro. We learn by experience, and as it turns out, so does this fully autonomous power-sliding rally truck.

Figuring out how to handle friction-optional roadways is entirely the point of the AutoRally project at Georgia Tech, which puts a seriously teched-up 1/5 scale rally truck through its paces on an outdoor dirt track. Equipped with high-precision IMU, high-resolution GPS, dual front-facing cameras, and Hall-effect sensors on each wheel sampled at 70 Hz, the on-board Quad-core i7 knows exactly where the vehicle is and what the relationship between it and the track is at all times. There’s no external sensing or computing – everything needed to run the track is in the 21 kg truck. The video below shows how the truck navigates the oval track on its own with one simple goal – keep the target speed as close to 8 meters per second as possible. The truck handles the red Georgia clay like a boss, dealing not only with differing surface conditions but also with bright-to-dark lighting transitions. So far the truck only appears to handle an oval track, but our bet is that a more complex track is the next step for the platform.

While we really like the ride-on scale of this autonomous chase vehicle, other than that there haven’t been too many non-corporate self-driving vehicle hacks around here lately. Let’s hope that AutoRally is an indication that the hackers haven’t ceded the field to Google entirely. Why let them have all the fun?

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Self-Driving Cars Get Tiny

There’s a car race going on right now, but it’s not on any sort of race track. There’s a number of companies vying to get their prototype on the road first. [Anurag] has already completed the task, however, except his car and road are functional models.

While his car isn’t quite as involved as the Google self driving car, and it doesn’t have to deal with pedestrians and other active obstacles, it does use a computer and various sensors to make decisions about how to drive. A Raspberry Pi 2 takes the wheel in this build, taking input from a Pi camera and an ultrasonic distance sensor. The Pi communicates to another computer over WiFi, where a neural network operates to make decisions about how to drive the car. It also makes decisions based on a database of pictures of the track, so it has a point of reference to go by.

The video of the car in action is worth a look. It’s not perfect, but it’s quite an accomplishment for this type of project. The possibility that self-driving car models could drive around model sets like model railroad hobbyists create is intriguing. Of course, this isn’t [Anurag]’s first lap around the block. He’s already been featured for building a car that can drive based on hand gestures. We’re looking forward to when he can collide with model busses.

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