Self-driving cars are theoretically ideal for safety. Take human limitations out of the mix and no one gets hurt, right? Not necessarily. A new IIHS study (via Autoblog) suggests that completely switching to autonomous technology would only prevent about a third of crashes if the systems “drive too much like people” — that is, focus on speed and convenience. Only 24 percent of crashes come down to sense or perception errors, while about 10 percent comes down to incapacitation (such as driving drunk). The rest comes down to errors in decision making, predictions and performance, and a self-driving system won’t automatically fix those.
The researchers pointed to Uber’s fatal collision with pedestrian Elaine Herzberg in 2018 as an example. The car’s autonomous hardware not only “struggled” to initially detect Herzberg, but also couldn’t predict where she was going and didn’t perform the evasive maneuver needed to save her life.
The crash rate would only drop further if cars prioritized safety over rider preference, the IIHS said, and that could frustrate people used to weaving around cars during their daily commute. They might drive more slowly than humans would when there’s low visibility or an abundance of foot traffic, for example.
It’s still early days for autonomous driving, and safety has taken higher priority for Uber and others in recent times. However, this study indicates that a driverless utopia might require a lot of patience and understanding. You’d safely get to where you were going — it would just take longer.
Earlier this year, Justine Haupt revealed a custom cellphone she built that eschewed unwanted battery-killing distractions like a touchscreen. In its place was an old-school rotary dial for placing calls, and while it looked antiquated, there were apparently enough people as fed up with the state of modern smartphones that Haupt has created a new version that she will actually build and sell.
Haupt’s original rotary cellphone was created with an open source design that allowed anyone to build their own, with firmware, build notes, and even the 3D models for printing the custom housing made available for download on their website. To make the build easier, Haupt created a starter kit offering the 3D printed housing for $50 (straight out of the 3D printer) as well as the cellphone’s mainboard for $90. But there were still lots of additional components that needed to be sourced to complete the build, including the dial that Haupt salvaged from a slim Western Trimline telephone.
Realizing the appeal of a distraction-free cellphone that excels at actually making calls (just look at the size of that antenna) extends well beyond hardware hackers and tinkerers, Haupt is currently developing a “mark 2″ version of the design that will be available as a ready-built device for those who don’t know the first thing about soldering. In addition to an upgrade from 3G to 4G which ensures the right networks will be active for at least another 10 years, the new version will include a larger electronic paper display, newly manufactured rotary dial parts instead of old salvaged hardware, and an SD card slot allowing a contact list to be added by just uploading a text file full of names and numbers.
Haupt is also teasing, “another VERY cool feature but won’t announce it until I’m sure I can do it” for their new rotary cellphone which remains a complete mystery for the time being. But a listing for the device on the website for Haupt’s new robotics company called Sky’s Edge claims it could be available as early as September. You can’t pre-order it yet, and it’s safe to assume the pandemic will probably result in some minor delays, but if you’re interested you can subscribe to updates on the project’s development, and notifications for when it’s finally available.
Kitty Hawk’s Flyer, the company’s first flying car project, is no more. The company has announced that it’s shutting down the initiative in a blog post, where it has also revealed that it’ll focus on its Heaviside plane going forward. According to TechCrunch, Kitty Hawk is laying off most of Flyer’s 70-person team, though a few employees will be transferred to Heaviside.
The original Flyer that debuted in 2017 was a one-seat, propeller-driven vehicle that looked like a flying motorcycle. Kitty Hawk introduced a new version one year later, and while it remained a single—seater, the updated 250-pound aircraft looked more like a mix of a drone and a stunt plane. The company put emphasis on how easy it is to pilot the Flyer — it was, after all, designed to be flown by anyone — so much so, that all it takes is two hours of training. Over the course of the project’s lifetime, Kitty Hawk built 111 Flyer machines and conducted over 25,000 crewed and uncrewed flights.
Unfortunately, it failed to find a way to turn the project into a viable business venture. “No matter how hard we looked, we could not find a path to a viable business,” Kitty Hawk CEO Sebastian Thrun told TechCrunch. The company had another project called Cora that developed two-seater autonomous taxis. Since that one evolved into a joint venture with Boeing, which will soon conduct passenger trials in New Zealand, Heaviside is its only known initiative at the moment.
Kitty Hawk revealed Heaviside, its all-electric plane, in 2019. Like Flyer, it’s a one-seater vehicle that’s capable of vertical take-off and landing (VTOL) like a helicopter, though it’s supposed to be 100 times quieter. “Going forward, we are doubling down on Heaviside as our primary platform,” its announcement reads. “But we would never have gotten here without launching and learning from Flyer, and the amazing team of people who built and operated it.”
Over the last few years, we’ve seen a lot of new technologies in the mobile market trying to address the problem of attempting to gather depth information with a camera system. There’s been various solutions by different companies, ranging from IR dot-projectors and IR cameras (structured light), stereoscopic camera systems, to the latest more modern time-of-flight special dedicated sensors. One big issue of these various implementations has been the fact that they’re all using quite exotic hardware solutions that can significantly increase the bill of materials of a device, as well as influence its industrial design choices.
Airy3D is a smaller new company that has been to date only active on the software front, providing various imaging solutions to the market. The company is now ready to transition to a hybrid business model, describing themselves as a hardware-enabled software company.
The company’s main product to fame right now is the “DepthIQ” platform – a hardware-software solution that promises to enable high-quality depth sensing to single cameras at a much cheaper cost than any other alternative.
At the heart of Airy3D’s innovation is an added piece of hardware to existing sensors in the market, called a transmissive diffraction mask, or TDM. This TDM is an added transmissive layer manufactured on top of the sensor, shaped with a specific profile pattern, that is able to encode the phase and direction of light that is then captured by the sensor.
The TDM in essence creates a diffraction pattern (Talbot effect) onto the resulting picture, that differs based on the distance of a captured object. The neat thing that Airy3D is able to do here, is employ advanced software algorithms that are able to decode this pattern, and transform the raw 2D image capture into a 3D depth map as well as a 2D image with the diffraction pattern compensated out.
Airy3D’s role in the manufacturing chain of a DepthIQ enabled camera module is designing the TDM grating which they then license out and cooperate with sensor manufacturers, who then integrate it into their sensors during production. In essence, the company would be partnering with any of the big sensor vendors such as Sony Semiconductor, Samsung LSI or Omnivision in order to produce a complete solution.
I was curious whether the company had any limits in terms of the resolution the TDM can be manufactured at, since many of today’s camera sensors employ 0.8µm pixel pitches and we’re even starting to see 0.7µm sensors coming to market. The company sees no issues in scaling the TDM grating down to 0.5µm – so there’s still a ton of leeway for future sensor generations for years to come.
Adding a transmissive layer on top of the sensor naturally doesn’t come for free, and there is a loss in sharpness. The company is quoting MTF sharpness reductions of around 3.5%, as well as a reduction of the sensitivity of the sensor due to TDM, in the range of 3-5% across the spectral range.
Camera samples without, and with the TDM
The company shared with us some samples of a camera system using the same sensor, once without the TDM, and once with the TDM employed. Both pictures are using the exact same exposure and ISO settings. In terms of sharpness, I wouldn’t say there’s major immediately noticeable differences, but we do see that the darker image with the TDM employed, a result of the reduced QE efficiency of the sensor.
The software processing is said to be comparatively light-weight compared to other depth-sensor solutions, and can be done on a CPU, GPU, DSP or even small FPGA.
The resulting depth discernation the solution is able to achieve from a single image capture is quite astounding – and there’s essentially no limit to the resolution that can be achieved as it scales with the sensor resolution.
More complex depth sensing solutions can add anywhere from $15 to $30 to the BOM of a device. Airy3D sees this technology to see the biggest adoption in the low- and mid-range, as usually the higher end is able to absorb the cost of other solutions, as also unlikely to be willing to make the make any sacrifice in image quality on the main camera sensors. A cheaper device for example would be able to have depth-sensing face ID unlocking with just a simple front camera sensor, which would represent notable cost savings.
Airy3D says they have customers lined up for the technology, and see a lot of potential for it in the future. It’s an extremely interesting way to achieve depth sensing given it’s a passive hardware solution that integrates into an existing camera sensor.
