Does Tesla’s Autosteer Make Cars Less Safe?

In 2016, a Tesla Model S T-boned a tractor trailer at full speed, killing its lone passenger instantly. It was running in Autosteer mode at the time, and neither the driver nor the car’s automatic braking system reacted before the crash. The US National Highway Traffic Safety Administration (NHTSA) investigated the incident, requested data from Tesla related to Autosteer safety, and eventually concluded that there wasn’t a safety-related defect in the vehicle’s design (PDF report).

But the NHTSA report went a step further. Based on the data that Tesla provided them, they noted that since the addition of Autosteer to Tesla’s confusingly named “Autopilot” suite of functions, the rate of crashes severe enough to deploy airbags declined by 40%. That’s a fantastic result.

Because it was so spectacular, a private company with a history of investigating automotive safety wanted to have a look at the data. The NHTSA refused because Tesla claimed that the data was a trade secret, so Quality Control Systems (QCS) filed a Freedom of Information Act lawsuit to get the data on which the report was based. Nearly two years later, QCS eventually won.

Looking into the data, QCS concluded that crashes may have actually increased by as much as 60% on the addition of Autosteer, or maybe not at all. Anyway, the data provided the NHTSA was not sufficient, and had bizarre omissions, and the NHTSA has since retracted their safety claim. How did this NHTSA one-eighty happen? Can we learn anything from the report? And how does this all align with Tesla’s claim of better-than-average safety line up? We’ll dig into the numbers below.

But if nothing else, Tesla’s dramatic reversal of fortune should highlight the need for transparency in the safety numbers of self-driving and other advanced car technologies, something we’ve been calling for for years now.

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Yes, You Can Put IoT On The Blockchain Using Python And The ESP8266

Last year, we saw quite a bit of media attention paid to blockchain startups. They raised money from the public, then most of them vanished without a trace (or product). Ethics and legality of their fundraising model aside, a few of the ideas they presented might be worth revisiting one day.

One idea in particular that I’ve struggled with is the synthesis of IoT and blockchain technology. Usually when presented with a product or technology, I can comprehend how and/or why someone would use it – in this case I understand neither, and it’s been nagging at me from some quiet but irrepressible corner of my mind.

The typical IoT networks I’ve seen collect data using cheap and low-power devices, and transmit it to a central service without more effort spent on security than needed (and sometimes much less). On the other hand, blockchains tend to be an expensive way to store data, require a fair amount of local storage and processing power to fully interact with them, and generally involve the careful use of public-private key encryption.

I can see some edge cases where it would be useful, for example securely setting the state of some large network of state machines – sort of like a more complex version of this system that controls a single LED via Ethereum smart contract.

What I believe isn’t important though, perhaps I just lack imagination – so lets build it anyway.

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Threading 3D Printed Parts: How To Use Heat-Set Inserts

We can make our 3D-printed parts even more capable when we start mixing them with some essential “mechanical vitamins.” By combining prints with screws, nuts, fasteners, and pins, we get a rich ecosystem for mechanism-making with capabilities beyond what we could simply print alone.

Today I’d like to share some tips on one of my favorite functional 3D-printing techniques: adding heat-set inserts. As someone who’s been installing them into plastic parts for years manually, I think many guides overlook some process details crucial to getting consistent results.

Make no mistake; there are a handful of insert guides already out there [1, 2]. (In fact, I encourage you to look there first for a good jump-start.) Over the years though, I’ve added my own finishing move (nothing exotic or difficult) which I call the Plate-Press Technique that gives me a major boost in consistency.

Join me below as I fill in the knowledge gaps (and some literal ones too) to send you back to the lab equipped with a technique that will give you perfectly-seated inserts every time.

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Putting The Brakes On High-Frequency Trading With Physics

In the middle of the East Coast’s slow broil in the summer of 2018, a curious phenomenon surfaced. As a tropical air mass settled in and smothered the metropolitan New York area, a certain breed of stock speculator began feeling the financial heat as the microwave signals linking together various data centers and exchanges began to slow down. These high-frequency traders rely on getting information a fraction of a second before other traders see the same thing and take advantage of minuscule price differences to make money hand over fist.

While you won’t catch us shedding many tears over the billions these speculators lost during the hot spell, we did find the fact that humidity can slow microwave propagation enough to make this a problem for them a fascinating subject, enough so that we covered it in some detail at the time. While financial markets come and go and the technology to capitalize them changes at a breakneck pace, physics stays the same, and it can make or break deals with no regard to the so-called fundamentals.

So it was with great interest that we happened upon Tom Scott’s recent video outlining how one new stock exchange is using physics to actually slow down stock trades, in an attempt to gain a competitive advantage over the other exchanges. In light of the billions lost over the summer to propagation delays amounting to a mere 10 microseconds, we couldn’t help but wonder how injecting a delay 35 times longer using a “magic shoebox” was actually good for business. It turns out to be an interesting story.

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Drops Of Jupyter Notebooks: How To Keep Notes In The Information Age

Our digital world is so much more interactive than the paper one it has been replacing. That becomes very obvious in the features of Jupyter Notebooks. The point is to make your data beautiful, organized, interactive, and shareable. And you can do all of this with just a bit of simple coding.

We already leveraged computer power by moving from paper spreadsheets to digital spreadsheets, but they are limited. One thing I’ve seen over and over again — and occasionally been guilty of myself — is spreadsheet abuse. That is, using a spreadsheet program to do something I probably ought to write a program to do. For those times that you want something quick but want something more than a spreadsheet, you should check out Jupyter Notebooks. The system is most commonly associated with Python, but it isn’t Python-specific. There are over 100 languages supported — many community-developed. You can even install a C++ interpreter backend for it. Because of the client/server architecture, it is very simple to share notebooks with other users.

You can — in theory — use Jupyter for anything you could use Python for. In practice, it seems to get a lot of workout with people analyzing large data sets, doing machine learning, and similar tasks.

The Good: Simple, Powerful, Extensible

The idea is simple. Think of a Markdown-enabled web page that can connect to a backend (a kernel, in Jupyter-speak). The backend can run on your machine or remotely and will support some kind of language — often Python. The document has cells that line up vertically (like a single wide spreadsheet column). For example, here’s a simple notebook I created to explain how a bunch of sine waves add up to a square wave:

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When Will Our Cars Finally Speak The Same Language? DSRC For Vehicles

At the turn of the 21st century, it became pretty clear that even our cars wouldn’t escape the Digital Revolution. Years before anyone even uttered the term “smartphone”, it seemed obvious that automobiles would not only become increasingly computer-laden, but they’d need a way to communicate with each other and the world around them. After all, the potential gains would be enormous. Imagine if all the cars on the road could tell what their peers were doing?

Forget about rear-end collisions; a car slamming on the brakes would broadcast its intention to stop and trigger a response in the vehicle behind it before the human occupants even realized what was happening. On the highway, vehicles could synchronize their cruise control systems, creating “flocks” of cars that moved in unison and maintained a safe distance from each other. You’d never need to stop to pay a toll, as your vehicle’s computer would communicate with the toll booth and deduct the money directly from your bank account. All of this, and more, would one day be possible. But only if a special low-latency vehicle to vehicle communication protocol could be developed, and only if it was mandated that all new cars integrate the technology.

Except of course, that never happened. While modern cars are brimming with sensors and computing power just as predicted, they operate in isolation from the other vehicles on the road. Despite this, a well-equipped car rolling off the lot today is capable of all the tricks promised to us by car magazines circa 1998, and some that even the most breathless of publications would have considered too fantastic to publish. Faced with the challenge of building increasingly “smart” vehicles, manufacturers developed their own individual approaches that don’t rely on an omnipresent vehicle to vehicle communication network. The automotive industry has embraced technology like radar, LiDAR, and computer vision, things which back in the 1990s would have been tantamount to saying cars in the future would avoid traffic jams by simply flying over them.

In light of all these advancements, you might be surprised to find that the seemingly antiquated concept of vehicle to vehicle communication originally proposed decades ago hasn’t gone the way of the cassette tape. There’s still a push to implement Dedicated Short-Range Communications (DSRC), a WiFi-derived protocol designed specifically for automotive applications which at this point has been a work in progress for over 20 years. Supporters believe DSRC still holds promise for reducing accidents, but opponents believe it’s a technology which has been superseded by more capable systems. To complicate matters, a valuable section of the radio spectrum reserved for DSRC by the Federal Communications Commission all the way back in 1999 still remains all but unused. So what exactly does DSRC offer, and do we really still need it as we approach the era of “self-driving” cars?

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The Woeful World Of Worldwide E-Waste

How large is the cache of discarded electronics in your home? They were once expensive and cherished items, but now they’re a question-mark for responsible disposal. I’m going to dig into this problem — which goes far beyond your collection of dead smartphones — as well as the issues of where this stuff ends up versus where it should end up. I’m even going to demystify the WEEE mark (that crossed out trashcan icon you’ve been noticing on your gadgets), talk about how much jumbo jets weigh, and touch on circular economies, in the pursuit of better understanding of the waste streams modern gadgets generate.

Our lives are encountering an increasing number of “how do I dispose of this [X]” moments, where X is piles of old batteries, LCDs, desktop towers, etc. This leads to relationship-testing piles of garbage potential in a garage or the bottom of a closet. Sometimes that old gear gets sold or donated. Sometimes there’s a handy e-waste campaign that swings through the neighborhood to scoop that pile up, and sometimes it eventually ends up in the trash wrapped in that dirty feeling that we did something wrong. We’ve all been there; it’s easy to discover that responsible disposal of our old electronics can be hard.

Fun fact: the average person who lives in the US generates 20 kg of e-waste annually (or about 44 freedom pounds). That’s not unique, in the UK it’s about 23 kg (that’s 23 in common kilograms), 24 kg for Denmark, and on and on. That’s quite a lot for an individual human, right? What makes up that much waste for one person? For that matter, what sorts of waste is tracked in the bogus sounding e-waste statistics you see bleated out in pleading Facebook posts? Unsurprisingly there are some common definitions. And the Very Serious People people at the World Economic Forum who bring you the definitions have some solutions to consider too.

We spend a lot of time figuring out how to build this stuff. Are we spending enough time planning for what to do with the gear once it falls out of favor? Let’s get to the bottom of this rubbish.
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