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Brad Ideas
Feb 20, 2018

Designing a metric to measure robocar safety -- what does insurance teach?
Topic: RobocarsThe most challenging problem for robocars today is proving they are safe. Yes, making them safe is very important, but they'll only be let on the roads by the companies making them if that safety level an be demonstrated.

You can't prove safety unless you can measure it. Even though we still don't fully understand everything about testing, it is time to start thinking of preliminary ways to do that. California requires all parties testing in the state to release disengagement reports, and while the reports are very interesting, they are not useful for comparison because each company has different rules about disengagement. In addition, the disengagement rate will depend greatly on the types of roads and traffic situations the car encounters.

(Waymo also just released a new safety report describing 4 million miles of real world testing and 2.7 billion in simulator.)

All cars operating (except the Waymo minivans in Phoenix) have a "safety driver" behind the wheel who is told to grab the wheel and intervene if they think an unsafe situation is present. They also do it if the system announces it has had a failure. I have taken Google's safety driver training; safety drivers go through advanced dri

Brad Ideas
Feb 17, 2018

Olympics Notebook 2018 -- streaming and Curling
Topic: MediaEvery 2 years I watch the Olympics and publish notes on the games, or in particular the coverage. Each time the technology has changed and that alters the coverage.

This year the big change is much more extensive and refined availability of streaming coverage. Since I desire to "cut the cord" and have no cable or satellite, this has become more important. Unfortunately the story is not all good.

Local recording is still by FAR the best I am still watching most of the games via recordings on my hard disk of the over the air NBC coverage. Using a local hard disk recording is so vastly superior to anything else that there's little comparison. These abilities, which are not available in streaming or "cloud DVR" are so seductive you can't go back:

Instantaneous seek to quickly move through 5 hour live recordings to find just what I want Instantaneous short jumps (MythTV lets me program the length) to quickly skip from the end of a run to the revelation of the score. Similarly to skip over timeouts and other boring sections. Smooth 2x and 3x fast forward, so you can follow things as they go. (Would be nice if captions were easy to add.) Smooth 1x-2x fast forward with sped-up pitch-adjusted audio. I watch most slower moving thins at about 1.3x Decent high-speed fast forward to go through an event (like Skiing or luge) looking for "the good parts." Automatic detection and

Brad Ideas
Feb 12, 2018

Local Motors hopes to win with 3D printed robocars
Topic: RobocarsThere are lots of players in the robocar space now -- car companies, startups, suppliers, high-tech companies, and two I did not talk as much about -- shuttles and delivery robots.

I didn't talk about shuttles that much because they are a stepping stone (at best, though that's pretty good) and a dead end (at worst.) But one company currently working on shuttles, Local Motors is different enough that they merit their own discussion. I've known Local Motors since their starting days as a croudsourced platform for car design for low-volume vehicles.

The focus of Local Motors is not the shuttle you see, but rather rapid development. Their goal is to be able to prototype and then deploy new hardware designs much faster than anybody else, partnering with the providers of the other components to get an edge in a very fast moving industry.

Local Motors began with a push on 3-D printing cars. They wanted to not just design and prototype the cars quickly, but also get them into production quickly in small and medium volumes. Creation of a production vehicle is a massive process, and takes 3 to 7 years even for the big auto OEMs who are experts at it. Almost everybody is scared of getting into that business, and every analysis of the Waymo/Apple/Uber vs. Car OEM battle has pointed to the lack of car development skills and resources as a big disadvantage for the hi

Brad Ideas
Feb 09, 2018

Uber and Waymo settle lawsuit in a giant victory for Uber
Topic: RobocarsIn a shocker, it was announced that Uber and Waymo (Google/Alphabet) have settled their famous lawsuit for around $245 million of Uber stock. No cash, and Uber agrees it won't use any Google hardware or software trade secrets -- which it of course had always denied that it ever did.

I think this is a tremendous victory for Uber. Google had proposed a $1B settlement early on that was rejected. Waymo had not yet provided all the evidence necessary to show damages, but one has to presume they had more to come that made Uber feel it settle. Of course, the cloud of a lawsuit and years of appeals over their programs and eventual IPO also were worth closing out.

What's great for Uber is that it's a stock deal. While the number is not certain, some estimates suggest that this amount of stock might not be much more than the shares of Uber lost by Anthony Levandowski when he was fired for not helping with the lawsuit. In other words, Uber fixes the problems triggered by Anthony's actions by paying off Waymo with the stock they used to buy Otto from Anthony. They keep the team (which is really what they bought, since at 7 months of age, Otto had done some impressive work but nothing worth $700M) and they get clear of the lawsuit.

The truth is, Uber can't be in a fight with Google. All Uber rides are booked through the platforms of Google and Apple. Without those platforms there is no Uber. I am not sugg

Brad Ideas
Feb 09, 2018

Review of the Light L16 computational camera
Topic: PhotographyIf you read my article about computational photography you will know I am very interested in the Light L16 camera which uses 16 small cameras (with cell-phone level sensors and different focal length lenses) to produce an image they hope will rival high end cameras like DSLRs.

The plan is an excellent one. I purchased the L16 but must sadly report it is "not yet the camera of the future" though I feel the general idea points the way there.

Some of the problems I have had with the L16 will be fixed in time. As a computational camera, they are doing software updates from time to time, improving the images and adding features. All cameras should be this way.

The L16 has lenses set for the field of view of 28mm, 70mm and 150mm on a full frame camera. A single shot uses up to 10 of these mini-cameras. Each camera has a mirror which both folds the lens to make it compact and offers the ability to slightly steer the aim of each one. The sensors are small 13 megapixel as might be put in cell phones.

(The lenses are much shorter than 28mm, 70mm and 150mm, but Light and I will refer to them by those numbers for simplicity, as is often done in small sensor cameras.)

Most of the expected benefits I wrote about for computational photography come from getting more than one image of your scene, either by taking multiple images at the same time (as the L16 can) or by taking images in quick succession of a scene that isn't chang

Brad Ideas
Feb 08, 2018

New "Shared Mobility Principles" have too much 2018 thinking.
Topic: RobocarsA new group has released a document called the "Shared Mobility Principles" for livable cities. It was started by Robin Chase (who built companies like ZipCar and others) and has had several of the mobile app taxi companies like Uber, Lyft, Didi and others sign on, though not Waymo, Cruise or the automakers.

Some of the documents principles are fairly "motherhood," but a few of them, especially the last, drift away from goals and into implementation and ideology. That's an unwise drift because we of 2018 don't know enough about how to do specific solutions. In addition, some of the goals are goals which have always seemed good but have turned out to easily be distorted to the wrong answers.

Here's the document with a critique of some of its tenets.

We plan our cities and their mobility together.

The sentiment is good, but urban planning tends to have a fairly poor track record, especially on transportation. Especially on rapidly changing technology. Planning, such as it is, should be very dynamic and adaptable to change, laying down few rules and instead observing and learning and correcting only when things go wrong. In particu

Brad Ideas
Feb 07, 2018

Robocars enter phase two as different strategies abound
Topic: RobocarsAt CES 2018, autos took over the show, and self-driving took over autos. At least in the industry, it's now mainstream. So what new approaches are teams taking, and how do they hope to win?

Waymo remains the leader by a very large margin, though not all agree with that. They were not present at CES, though Google was for the first time in many years. Most car companies had mention of self-driving plans but not too much to show specifically. That's because car companies are not ready to sell anything to customers yet. In fact, BMW's booth was all about driving and racing, with people lining up to drift in the parking lot. Suppliers, on the other hand, want to sell to car companies, so in spite of the word consumer in the show, they were there.

It is no longer so impressive to have a decent self-driving stack working at some level. Many suppliers, car companies, tech companies sand startups have this. It's easy to find demos of a car driving around some urban streets now. Not too long ago, simply being able to do that was impressive.

Now the key difference, which is much harder to see, is the difference between being able to drive for a day, and the ability to drive without incident for 20 years.

(The average human drives around 100,000 miles in 10 years, and according to recent estimate probably has one minor "ding" accident every 100,000 miles. An accident reported to police happens every 500,000 miles or 50 years. We all hope that robocars will be able

Brad Ideas
Jan 24, 2018

GM/Cruise vs. Motorcycle triggers first robocar accident lawsuit
Back in December a GM Cruise car had an accident with a lane-splitting motorcyclist in San Francisco. I didn't report on it because the police report blamed the motorcyclist, but the accident is possibly more complex, and the motorist has filed a lawsuit against GM..

That's not too surprising. As the first lawsuit against a self-driving car company, it assures fame for the lawyers, and involves a super deep pocketed defendant keen to come out of it looking good. One could be motivated to sue even if clearly in the wrong.

The accident is a somewhat complex one, which means there is some dispute over whether the biker was in the wrong. He was 'lane splitting' -- an action illegal most places but not in California. The Cruise vehicle moved to change lanes to the left. The biker then moved to pass on the right at 17mph, faster than the car going 12mph. The car decides it can't complete the lane change and aborts it. GM says it is 're-centering itself' and the biker glanced the side of it.

It's not clear from this description just what happened. Did the Cruise get all the way into the left lane and then come back to the right lane, getting in the way of the biker? Was the biker on the right side of the right lane, happy to see the car leaving to the right, then surprised when it came back? We don't know from the text description, but the vehicle's LIDAR and camera logs will have recorded everything in great detail.

That makes this part of the question boring. While GM has not published the data, they know exactly what happened, and in court all sides will know. There will be zero doubt on who violated the vehicle code. If it was the biker (who was cited by police as unlawfully passing on the right) things should be over fast.

If it was GM, then things should also be over fast because I can't imagine them wanting to fight that in court. They will make a more than generous settlement. The only thing that should make this thing not be over fast would be if the biker gets ambitious and does not accept even a generous settlement.

Regardless of who is at fault... While deciding vehicle code fault should be quick and unexciting, there are a few interesting questions to learn:

Even if the biker is at fault, is there something about the robocar's behaviour that was different from a human's which nonetheless could be a contributing factor to the accident? Did the robocar fail to perceive the biker, even if they had no duty to? Humans also fail to see bikers all the time, and we want robocars to do better at it. Lane splitting is a specialized issue in California, but everybody wants to drive in California. When did GM release the data to the plaintiff and/or police, or when will they? If not immediately, why? If the plaintiff gets 'ambitious' what does that say about other ambitious plaintiffs? In particular, is this accident one which would be resolved quickly and cheaply if humans were involved, but ends up being long and expensive because a robot and megacorporation are involved? I went into many of these questions in depth in my article on accidents.

Aborted lane change is unusual for a robocar The safety driver did see the biker, and took control, but too late. That might indicate a failure in perception (not seeing the biker) or a lack of a plan for what to do in this unusual situation. Aborting a lane change is already a highly unusual move for a robocar. Generally they will only initiate lane changes that they are confident can be completed. It could be another driver unexpectedly also att

Brad Ideas
Jan 22, 2018

Could digital money offer a new solution to addiction and gambling?
Topic: HealthTechnologyI've been mulling a bit over the philosophy of law, and one concept I have been exploring is that a key to understanding a major class of immoral acts is to look at attempts to exploit flaws in human cognition and physiology. There's been a reasonable amount of scientific study of the 'bugs' in the way humans think by economists, game theorists and psychologists, and while some of the bugs are debatable, some are fairly undisputed. This might help build moral codes.

There are a lot of consequences of this which need more study -- for example it might argue that a large fraction of modern marketing should perhaps be illegal rather than rewarded -- but for now I would like to focus on one of our most obvious bugs, namely addiction. Both psychological addictions, like to gambling, and physical ones, like nicotine.

This led to a potentially interesting idea -- the use of new digital currencies (such as cryptocurrencies) to regulate the purchase of addictive things.

For some people, gambling is addictive and life-destroying. For others, it is entertainment. Most places take a 'nanny state' approach and forbid gambling, but of late this has changed with governments running lotteries almost everywhere and legal gambling in many places.

Gamblin' Money One idea might look like this: All gambling would be required to be done only with a new digital currency. All wagers and winnings would be made and paid in this currency.

Gamblers could purchase this currency with regular money, but by default only up to some limit per month, a rough estimate of 'the amount you can afford to lose.' Most simply some fraction of your income or net worth, though one could imagine more complex formulae. You might even buy this currency when you file your taxes, where your income is plain to see. Places which sell the currency would need to get ID from the customer to record how much 'gamblin' money' you have purchased, but they should not record what money is yours for privacy reasons. You would also get a token linking the money to you which you keep private until challenged.

You could use the money at casinos, bookmakers and lotteries to gamble. If you won, you could now also gamble your winnings. Once you ran out, you could not gamble any more, legally. It would be very hard to gamble yourself into ruin, and the vast majority of people could enjoy gambling for entertainment, because they would never even consider going above their limit.

Today, almost all casinos track gamblers with loyalty programs, so the mechanism is already in place for the use of a digital currency. A good cryptocurrency would also allow full anonymity, with the following provision; as noted, you encode an identity into the coins you have in the currency. From time to time, you might face an audit check, where a casino security officer would as you to provide, then or later, the identity token tying your identity to the money you are using to gamble. If caught gambling anybody else's currency, you could be guilty of a crime. (So would the person who sold it to you, but it's harder to design a way to identify them and protect privacy on the currency -- I welcome designs that might do this.)

For those who like the aesthetics of casino chips, they could still exist, but with small chips inside them. You could then transfer your funds into the chips. (The casinos would like the better security, but they would have to always take lost

Brad Ideas
Jan 19, 2018

All about sensors: Advanced radar and more for the future of perception
Topic: RobocarsEarlier this week I talked about many of the LIDAR offerings of recent times. Today I want to look at two 'up and coming' sensor technologies: Advanced radar and thermal cameras.

I will begin by pointing readers to a very well done summary of car sensor technologies at EE Times which covers almost all the sensor areas. For those tracking the field it is a worthwhile resource.

Advanced radar Robocars have used radar from the earliest days. It's not that expensive, and has many superhuman capabilities -- it sees through fog and all other forms of weather, it has very long range, and it tells you how fast every target is moving.

What's not to love is the resolution, which is very poor. Radars if they are very good today will tell you where a target is within several degrees of azimuth (horizontal) and are even worse in the altitude. Radar is also noisy, and full of 'multipath' returns that bounced off something else in the environment. (That's actually a big feature when a signal from a car you can't see bounces off the road surface.)

Until MobilEye did it with cameras, car ADAS systems like adaptive cruise control and forward collision warnings all used radar. The low resolution meant they sometimes could not be sure what lane a car was in, and in the early days strange actions by adaptive cruise controls were common. Radars also have a problem with fixed objects or stalled cars. Their Doppler says they are stopped, and you're getting tons of radar returns from all the fixed objects of the world which you mostly have to ignore. Which means you ignore the stopped cars and pedestrians too. Famously, Tesla's radar (like most automotive radars) ignored the strong reflections coming from a truck crossing the road because they had the Doppler of a fixed object -- resulting in a fatality when the driver didn't intervene as expected.

Efforts are underway to make radar with much more resolution. There are a few ways to do this.

You can use much more bandwidth. That's not allowed in the usual radar bands which are limited to 4ghz, but there is some potential for ultra-wideband radar to get that bandwidth in the very high bands. You can have multiple radars and compare the returns from overlapping ones. This is how most automotive radars get their resolution today You can sweep, not like the classic aviation radars, but by using a phased array antenna system and digital processing. As you 'steer' the phased array beam in fine increments, you can get more information about where a target is. You can make a wider antenna array, as wide as the car to gain some resolution. In some cases you can create a synthetic aperture from the movement of the car, but usually that only works when looking to the left or right, not directly forward. When crossing fast streets, you still need to look to the sides. You can use new, smarter software, to decode radar signals and learn what they are reflecting off by looking not just at one reflection but how they change in time. Neural networks are a new tool to help with that. I saw two companies at CES promoting these techniques. Metawave of Palo Alto is using a combination of beamforming with antenna arrays, antennas made from less-exotic metamaterials and machine learning.

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