Fri, 24 Mar 2017 11:16:09 -0700The recently released national noise map makes it strikingly clear just how much air travel contributes to the noise pollution in our lives. In my previous discussion of flying cars I expressed the feeling that the noise of flying cars is one of their greatest challenges. While we would all love a flying car (really a VTOL helicopter) that takes off from our back yards, we will not tolerate our neighbour having one if there is regular buzzing and distraction overhead and in the next yard. Helicopters are also not energy efficient, so real efforts for flying cars are fixed wing, using electric multirotors to provide vertical take-off but converting in some way to fixed wing flight, usually powered by those same motors in a different orientation. If batteries continue their path of getting cheaper, and more importantly lighter, this is possible. Fixed wing planes can be decently efficient — particularly when they travel as the crow flies — though they can have trouble competing with lightweight electric ground vehicles. Almost all aircraft today fly much faster than their optimum efficiency speed. There are a lot of reasons for this. One is the fact that maintenance is charged by the hour, not the mile. Another is that planes need powerful engines to take off, and people are in a hurry and want to use that powerful engine to fly fast once they get up there. Typical powered planes have a glide ratio (which is a good measure of their aerodynamic efficiency) around 10:1 to 14:1. That means for every foot they drop, they go forward 10 to 14 feet. Gliders, more properly known as “sailplanes” are commonly at a 50:1 glide ratio today and go even higher. Sailplane pilots can use that efficiency to enter slowly rising columns of air found over hot spots on the ground and “soar” around in a circle to gain altitude, staying up for hours. Silent flying is great fun, though the tight turns to rise in a thermal can cause nausea. Efficient sailplanes are also light and can have fairly bumpy rides. (Note as well that the extra weight of energy storage and motors and drag of propellers means a lower glide ratio.) It is the silent flight that is interesting. An autonomous high efficiency aircraft, equipped with redundant electric motors and power systems, need not run its engines a lot of the time. While you would never want to be constantly starting and stopping piston powered aircraft engines, electric engines can start and stop and change speed very quickly. The motors provide tremendous torque for fast response times. It would be insane to regularly land your piston powered aircraft without power, figuring you can just turn on the engine “if you need it.” It might not be that crazy to do it in an electric aircraft when you can get the engine up and operating in a fraction of a second with high reliability, and you have multiple systems, so even the rare failures can be tolerated. Both passengers and people on the ground would greatly appreciate planes that were silent most of the time, including when landing at short airstrips. It could make the difference for acceptance. For a more radical idea, consider my more futuristic proposal of airports that grab and stop planes with robotic platforms on cables. Such a system would even allow for mostly silent takeoff in electric aircraft. Making efficient aircraft VTOL is a challenge. They tend to have large wingspans and are not so suitable for backyards, even if they can hover. But the option for redundant multirotor systems makes possible something else — aircraft wings that unfold in the air. There are “flying cars” with folding wings which fold the wings up so the car can get on the road, but unfolding in the air is one of those things that is insane for today’s aircraft designs. A VTOL multirotor could rise up, unfold its wings, and if they don’t unfold properly, it can descend (noisily) on the VTOL system, either to where it took off form, or a nearby large area if [...]
Wed, 22 Mar 2017 12:59:05 -0700Recently we’ve seen a series of startups arise hoping to make robocars with just computer vision, along with radar. That includes recently unstealthed AutoX, the off-again, on-again efforts of comma.ai and at the non-startup end, the dedication of Tesla to not use LIDAR because it wants to sell cars today, before LIDARs can be bought at automotive quantities and prices. Their optimism is based on the huge progress being made in the use of machine learning, most notably convolutional neural networks, at solving the problems of computer vision. Milestones are dropping quickly in AI and particularly pattern matching and computer vision. (The CNNs can also be applied to radar and LIDAR data.) There are reasons pushing some teams this way. First of all, the big boys, including Google, already have made tons of progress with LIDAR. There right niche for a startup can be the place that the big boys are ignoring. It might not work, but if it does, the payoff is huge. I fully understand the VCs investing in companies of this sort, that’s how VCs work. There is also the cost, and for Tesla and some others, the non-availability of LIDAR. The highest capability LIDARs today come from Velodyne, but they are expensive and in short supply — they can’t make them to keep up with the demand just from research teams! Note, for more detailed analysis on this, read my article on cameras vs. lasers. For the three key technologies, these trends seem assured: LIDAR will improve price/performance, eventually costing just hundreds of dollars for high resolution units, and less for low-res units. Computer vision will improve until it reaches the needed levels of reliability, and the high-end processors for it will drop in cost and electrical power requirements. Radar will drop in cost to tens of dollars, and software to analyse radar returns will improve In addition, there are some more speculative technologies whose trends are harder to predict, such as long-range LWIR LIDAR, new types of radar, and even a claimed lidar alternative that treats the photons like radio waves. These trends are very likely. As a result, the likely winner continues to be a combination of all these technologies, and the question becomes which combination. LIDAR’s problem is that it’s low resolution, medium in range and expensive today. Computer Vision (CV)’s problem is that it’s insufficiently reliable, depends on external lighting and needs expensive computers today. Radar’s problem is super low resolution. Option one — high-end LIDAR with computer vision assist High end LIDARs, like the 32 and 64 laser units favoured by the vast majority of teams, are extremely reliable at detecting potential obstacles on the road. They never fail (within their range) to differentiate something on the road from the background. But they often can’t tell you just what it is, especially at a distance. It won’t know a car from a pickup truck, or 2 pedestrians from 3. It won’t read facial expressions or body language. It can read signs but only when they are close. It can’t see colours, such as traffic signals. The fusion of the depth map of LIDAR with the scene understanding of neural net based vision systems is powerful. The LIDAR can pull the pedestrian image away from the background, and then make it much easier for the computer vision to reliably figure out what it is. The CV is not 100% reliable, but it doesn’t have to be. Instead, it can ideally just improve the result. LIDAR alone is good enough if you take the very simple approach of “If there’s something in the way, don’t hit it.” But that’s a pretty primitive result that make brake too much for things you should not brake for. Consider a bird on the road, or a blowing trash bag. It’s a lot harder for the LIDAR system to reliably identify those things. On the other hand, the visions systems will do a very good job at recognizi[...]
Sun, 19 Mar 2017 17:46:43 -0700California has published updated draft regulations for robocars whose most notable new feature is rules for testing and operating unmanned cars, including cars which have no steering wheel, such as Google, Navya, Zoox and others have designed. This is a big step forward from earlier plans which would have banned testing and deploying those vehicles. That that they are ready to deploy, but once you ban something it’s harder to un-ban it. One type of vehicle whose coverage is unclear are small unmanned delivery robots, like we’re working on at Starship. Small, light, low speed, inherently unmanned and running mostly on the sidewalks they are not at all a fit for these regulations and presumably would not be covered by them — that should be made more explicit. Another large part of the regulations cover revoking permits and the bureaucracy around that. You can bet that this is because of the dust-up between the DMV and Uber/Otto a few months ago, where Uber declared that they didn’t need permits (probably technically true) but the DMV found it not at all in the spirit of the rules and revoked the licence plates on the cars. The DMV wants to be ready to fight those who challenge its authority. Intel buys MobilEye Intel has paid over $15B to buy Jerusalem based MobilEye. MobilEye builds ASIC-based camera/computer vision systems to do ADAS and has been steadily enhancing them to work as a self-driving sensor. They’ve done so well the stock market already got very excited and pushed them up to near this rich valuation — the stock traded at close to this for a while, but fell after ME said it would no longer sell their chips to Tesla. (Tesla’s first autopilot depended heavily on the MobilEye, and while ME’s contract with Tesla explicitly stated it did not detect things like cross-traffic, that failure to detect played a role in the famous Tesla autopilot fatal crash. In a surprising and wise move, Intel is going to move its other self-driving efforts to Israel and let MobilEye run them, rather than gobble them up and swallow/destroy them. ME is a smart company, fairly nimble, though it has too much focus on making low-cost sensors in a world where safety at high cost is better than less safety at low cost. (Disclaimer: I own some MBLY and made a nice profit on it in this sale.) MobilEye has been the leader in doing ADAS functions with just cameras and cameras+radar. Several other startups are attempting this, and of course so is Tesla in their independent effort. However, LIDAR continues to get cheaper (with many companies, including Quanergy, whom I advise, working hard on that.) The question may be shifting from will it be cameras or lasers? to “will it be fancy vision systems with low-end LIDAR, or will it be high-end LIDAR with more limited vision systems?” In fact, that question deserves another post. Waymo and Uber Lawsuit I am not going to comment a great deal on this lawsuit, because I am close with both sides, and have NDAs with both Otto and formerly with Google/Waymo. There are lots of press reports on the lawsuit, filed by Waymo accusing Anthony Levandowski (who co-founded Otto and helped found the car team at Google) of stealing a vast trove of Google’s documents and designs. This fairly detailed Bloomberg report has a lot of information, including reports that at an internal meeting, Anthony told his colleagues that any downloading he did was simply to allow work from home. The size of the lawsuit is staggering. Since Otto sold for 1% of Uber stock (worth over $750M) the dollar values are huge, particularly if, as Google alleges, they can demonstrate Uber encouraged wrongdoing. At the same time, if Google doesn’t prove their allegations, Otto and Anthony could file for what might be the largest libel lawsuit in history, since Google published their accusations not just in court filings, but in their blog. One reason that might not happen is that Uber [...]
Mon, 20 Feb 2017 14:15:43 -0800
I have so much paper that I’ve been on a slow quest to scan things. So I have high speed scanners and other tools, but it remains a great deal of work to get it done, especially reliably enough that you would throw away the scanned papers. I have done around 10 posts on digitizing and gathered them under that tag.
Recently, I was asked by a friend who could not figure out what to do with the papers of a deceased parent. Scanning them on your own or in scanning shops is time consuming and expensive, so a new thought came to me.
Set up a scanning table by mounting a camera that shoots 4K video looking down on the table. I have tripods that have an arm that extends out but there are many ways to mount it. Light the table brightly, and bring your papers. Then start the 4K video and start slapping the pages down (or pulling them off) as fast as you can.
(image) There is no software today that can turn that video into a well scanned document. But there will be. Truth is, we could write it today, but nobody has. If you scan this way, you’re making the bet that somebody will. Even if nobody does, you can still go into the video and find any page and pull it out by hand, it will just be a lot of work, and you would only do this for single pages, not for whole documents. You are literally saving the document “for the future” because you are depending on future technology to easily extract it. read more »
Sat, 18 Feb 2017 13:05:57 -0800Sooner than most expected, the Trump administration is in trouble. Many are talking about how to end it, or hasten that end. The Democrats don’t have the power to take down Trump prior to 2020. Not even after 2018. The revolt against Trump almost surely has to come from within his own party. While many Republicans dislike Trump, revolt within a party is extremely difficult and goes against all party instincts. Republicans will strongly resist fighting Trump as the left would like, or in a way which benefits the left. As such, the more the left approves of a method of fighting Trump, the less likely it is the Republicans would use it. This suggests a very different anti-Trump strategy than the obvious one followed by most. Many in the GOP would prefer not to have Trump, and are ready to be disloyal to him as their leader. They are not, however, prepared to be disloyal to their party and their movement. Career party members of both sides often will put loyalty to party ahead of loyalty to country, even though they would never admit that. This means that if the GOP does this, it must be for their own reasons, not the left’s, and it must clearly not appear to serve the left except in the broadest way. This creates a conundrum for the left fighting Trump. If they rally around something, such as a Trump error, they push the right to reluctantly defend Trump on that issue. Many GOP can’t stand Trump but support him because the alternative is victory for the left, and injury for their party. As such, the best strategy for the left may be to pull back, or stick only to issues that are clearly their own. The Democrats might consider strategies that are victories for the GOP. Conceding important items in congress in exchange for impeachment. The Republicans know the Democrats will vote for impeachment, so only a minority of Republicans need support it, but for them, a party divided like that is no victory. This may mean offering support for portions of Pence’s or the party’s agenda. Something so that the entire GOP can see it as a victory for their party. The Democrats lost in 2016, and they must accept that, and give up the hope that Trump’s fall would be good for the Democratic Party. They must accept only that it will be good for the country and neutral, or even slightly negative for the party. It’s a common human foible but politicians cringe from ever admitting they were wrong. Those who supported Trump, even holding their noses, won’t see themselves as having failed. They won’t go, “Oh, you Democrats were right, sorry about that.” The reason will need to be something new, something few people knew or talked about before now. People are just less likely to do the right thing if they know it’s what their opponents want them to do. The Democrats, however, are not a cohesive force. Even if “hold back and let the GOP do it” is the right plan, they will not embrace it in large numbers. Thus they will slow down the fall of Trump. This was a frequent mistake made during the election — the unprecedented level of contempt by the left for Trump and in particular for Trump supporters brought the Trump supporters together and made them stronger, rather than weakening them. It was a strong contributor to the Trump victory. This advice does not mean, “Only complain about Trump in a way that the right-wing will understand.” Normally that is the best approach. Here, the problem is that as soon as a complaint is seen as coming from the left, there will be resistance to acting on it. 2018 Some hold out for a change of Congress in 2018. It is quite normal for the President’s party — especially an unpopular President — to lose seats in the mid-terms. Unfortunately, the senate seats up in 2018 are far from likely to swing the senate to the Democrats. In fact, only 9 Republican sea[...]
Thu, 09 Feb 2017 14:26:30 -0800Caltrain is the commuter rail line of the San Francisco peninsula. It’s not particularly good, and California is the land of the car commuter, but a plan was underway to convert it from diesel to electric. This made news this week as the California Republican house members announced they want to put a stop to both this project, and the much larger California High Speed Rail that hopes to open in 2030. For various reasons they may be right about the high speed rail but stop the electric trains? Electric trains are much better than diesel; they are cleaner and faster and quieter. But one number stands out in the plan. To electrify the 51 miles of track, and do some other related improvements is forecast to cost over 1.5 billion dollars. Around $30M per mile. So I started to ask, what other technology could we buy with $1.5 billion plus a private right-of-way through the most populated areas of silicon valley and the peninsula? Caltrain carries about 60,000 passengers/weekday (30,000 each way.) That’s about $50,000 per rider. In particular, what about a robotic transit line, using self-driving cars, vans and buses? Paving over the tracks is relatively inexpensive. In fact, if we didn’t have buses, you could get by with fairly meager pavement since no heavy vehicles would travel the line. You could leave the rails intact in the pavement, though that makes the paving job harder. You want pavement because you want stations to become “offline” — vehicles depart the main route when they stop so that express vehicles can pass them by. That’s possible with rail, but in spite of the virtues of rail, there are other reasons to go to tires. Fortunately, due to the addition of express trains many years ago, some stations already are 4 tracks wide, making it easy to convert stations to an express route with space by the side for vehicles to stop and let passengers on/off. Many other stations have parking lots or other land next to them allowing reasonably easy conversion. A few stations would present some issues. Making robocars for a dedicated track is easy; we could have built that decades ago. In fact, with their much shorter stopping distance they could be safer than trains on rails. Perhaps we had to wait to today to convince people that one could get the same safety off of rails. Another thing that only arrived recently was the presence of smartphones in the hands of almost all the passengers, and low cost computing to make kiosks for the rest. That’s because the key to a robotic transit line would be coordination on the desires of passengers. A robotic transit line would know just who was going from station A to station J, and attempt to allocate a vehicle just for them. This vehicle would stop only at those two stations, providing a nonstop trip for most passengers. The lack of stops is also more energy efficient, but the real win is that it’s more pleasant and faster. With private ROW, it can easily beat a private car on the highways, especially at rush hour. Another big energy win is sizing the vehicles to the load. If there are only 8 passengers going from B to K, then a van is the right choice, not a bus. This is particularly true off-peak, where vast amounts of energy are wasted moving big trains with just a few people. Caltrain’s last train to San Francisco never has more than 100 people on it. Smaller vehicles also allow for more frequent service in an efficient manner, and late night service as well — except freight uses these particular rails at night. (Most commuter trains shut down well before midnight.) Knowing you can get back is a big factor in whether you take a transit line at night. An over-done service with a 40 passenger bus every 2 seconds would move 72,000 people (but really 30,000) in one hour in one direction to Caltrain’s 30,000 in a day. So of cour[...]
Fri, 03 Feb 2017 21:32:36 -0800There’s been a lot of talk this week on the nature of free speech. I’m a very strong defender of free speech, so I felt it would be worth laying out some of the reasons why “the first amendment is not just the law, it’s a good idea.” While I am not speaking for any particular organization, and am not a lawyer nor giving legal advice, my background includes things like: Being the subject of the first big internet censorship battle, in 1987. Being a plaintiff in ACLU v. Reno, which we won 9-0 in the supreme court, for which I was named a “Champion of Free Speech” by the ACLU. 20 years with the Electronic Frontier Foundation, including 10 as chairman. Two recent events has caused much debate. A viral video of somebody punching Richard B. Spencer, a man who gathers attention by promoting neo-nazi and whites-first rules has caused people to ask, “Isn’t it OK to punch a Nazi?” You see Spencer declaring “Hail Trump” and people doing Nazi salutes in one famous video. There have also been two attempts by Breitbart writer Milo Yiannopoulos to speak at UC Davis and UC Berkeley that have been met with protests, calls that he be banned from speaking, and cancellations of his talks due to fear of violence. At UCB, a large group of apparent “black bloc” anarchists invaded a peaceful protest with violent acts and resulted in chaos and cancellation of the talk. For a free speech supporter, the situation is fairly clear. No, it’s not OK to punch a Nazi (or in this case a wannabe neo-nazi) simply for what he says or what he is, even if it’s so-called “hate speech.” (In fact, that we don’t punch people for what they say is one of the important things that makes us better than Nazis.) And universities should not distinguish among speakers who are legitimately invited by members of the university community because of the content of their messages, even if it is hugely unpopular, offensive and hateful. Here’s why: Speech can be evil. But censorship is more evil. It is a common mistake of those who say, “I am all in favour of free speech, but….” to imagine that we support free speech because speech is pure and can’t cause harm. This is the “sticks and stones” philosophy, but if you follow it, then it follows that if you can show that some speech is, unlike most speech, actually harmful, it is then OK to ban it. While some speech is indeed harmless, important speech is powerful. It evokes change in the world, for good or ill. Speech can do great good and great harm. Consider the book “The Communist Manifesto” which advocates that to bring about an ideal communist society, one must begin with armed revolution and a “dictatorship of the proletariat” that uses draconian methods to work towards the pure goal. That idea has been used to create such dictatorships, and they have all been horrors. These dictatorships (particularly Stalin and Mao) perverted the ideas but used the ideals to justify acts which killed many tens of millions — leaving the Nazi holocaust in the dust. You can’t get much more evil or more proven harm. Yet we don’t ban that book. Lots of speech is evil, but we have found no way to determine that reliably or in advance. As such, giving any entity the power to decide what speech is good and what is evil is a more dangerous proposition than just allowing all speech. For just as the idea in The Communist Manifesto have led to the death of millions, so much of the good in the world is also attributable to other ideas and books, including ones which were banned. We can’t grant an agency the power to decide what is good or bad without having them stamp out too much of the good. Nobody has the crystal ball that can do this, and history [...]
Wed, 01 Feb 2017 19:56:22 -0800California published its summary of all the reports submitted by vendors testing robocars in the state. You can read the individual reports — and they are interesting, but several other outlines have created summaries of the reports calculating things like the number of interventions per mile. On these numbers, Google’s lead is extreme. Of over 600,000 autonomous miles driven by the various teams, Google/Waymo was 97% of them — in other words 30 times as much as everybody else put together. Beyond that, their rate of miles between disengagements (around 5,000 — a 4x improvement over 2015) is one or two orders of magnitude better than the others, and in fact for most of the others, they have so few miles that you can’t even produce a meaningful number. Only Cruise, Nissan and Delphi can claim enough miles to really tell. Tesla is a notable entry. In 2015 they reported driving zero miles, and in 2016 they did report a very small number of miles with tons of disengagements from software failures (one very 3 miles.) That’s because Tesla’s autopilot is not a robocar system, and so miles driven by it are not counted. Tesla’s numbers must come from small scale tests of a more experimental vehicle. This is very much not in line with Tesla’s claim that it will release full autonomy features for their cars fairly soon, and that they already have all the hardware needed for that to happen. Unfortunately you can’t easily compare these numbers: Some companies are doing most of their testing on test tracks, and they do not need to report what happens there. Companies have taken different interpretations of what needs to be reported. Most of Cruise’s disengagements are listed as “planned” but in theory those should not be listed in these reports. But they also don’t list the unplanned ones which should be there. Delphi lists real causes and Nissan is very detailed as well. Others are less so. Many teams test outside California, or even do most of their testing there. Waymo/Google actually tests a bunch outside California, making their numbers even bigger. Cars drive all sorts of different roads. Urban streets with pedestrians are much harder than highway miles. The reports do list something about conditions but it takes a lot to compare apples to apples. (Apple is not one of the companies filing a report, BTW.) One complication is that typically safety drivers are told to disengage if they have any doubts. It thus varies from driver to driver and company to company what “doubts” are and how to deal with them. Google has said their approach is to test any disengagement in simulator, to find out what probably would have happened if the driver did not disengage. If there would have been a “contact” (accident) then Google considers that a real incident, and those are more rare than is reported here. Many of the disengagements are when software detects faults with software or sensors. There, we do indeed have a problem, but like human beings who zone out, not all such failures will cause accidents or even safety issues. You want to get rid of all of them, to be sure, but if you are are trying to compare the safety of the systems to humans, it’s not easy to do. It’s hard to figure out a good way to get comparable numbers from all teams. The new federal guidelines, while mostly terrible, contain an interesting rule that teams must provide their sensor logs for any incident. This will allow independent parties to compare incidents in a meaningful way, and possibly even run them all in simulator at some level. It would be worthwhile for every team to be required to report incidents that would have caused accidents. That requires a good simulator, however, and it’s hard for the law to demand[...]
Tue, 31 Jan 2017 12:00:53 -0800
I generally pay very little attention when companies issues a press release about an “alliance.” It’s usually not a lot more than a press release unless there are details on what will actually be built.
The recent announcement that Uber plans to buy some self-driving cars from Daimler/Mercedes is mostly just such an announcement — a future intent, when Mercedes actually builds a full self-driving car, that Uber will buy some. This, in spite of the fact that Uber has its own active self-driving system in development, and that it paid stock worth $760M to purchase freshly-minted startup Otto to accelerate that.
This shows a special advantage that Uber has over other players here. Their own project is very active, but unlike others, it doesn’t cripple Uber if it fails. Uber’s business is selling rides, and it will continue to be. If Uber can’t do it with its own cars, it can buy somebody else’s. Uber does not have the intention to make cars (neither does Google and that’s probably true of most other non-car companies.) There are many companies who will make cars to order for you. But if Google’s self-drive software (and hardware) project fails, they are left with very little. If Uber’s fails, they are still very much in business, but not as much in control of the underlying vehicles. As long as there are multiple suppliers for Uber to choose from, they are good.
One nightmare for the car companies is the reduction in value of their brands. If you summon “UberSelect” (the luxury Uber) you don’t care if it is a Lexus or Mercedes that shows up. As long as it’s a decent luxury car, you are good, because you are not buying the car, you are using it for 20 minutes. Uber is the brand you are trusting — and car companies fear that. I presume one thing that Daimler wants from this announcement is to remind people that they are a leader and may well be the supplier of cars to companies like Uber. But will they be in charge of the relationship? I doubt it.
Lyft should have the same advantage — but it took a $500M investment from GM which strongly pressures it to use whatever solution GM creates. Of course, if GM’s project fails, Lyft still has the freedom to use another, including Mercedes.
A lawsuit from Tesla against former Tesla autopilot team leader Sterling Anderson and former head of Google Chauffeur (now Waymo) Chris Urmson reveals little, other than the two have a company which will get a lot of attention in the space. But that’s enough. Google’s project is the most advanced one in the world. I was there and worked for Chris in its early days. Tesla’s is not necessarily the most advanced technologically — it has no LIDAR development — but it’s way ahead of others in terms of getting out there and deploying to gain experience, which has given it a headstart, especially in camera/radar based systems. The leaders of the two projects together will cause a stir in the auto business.
Wed, 25 Jan 2017 15:53:14 -0800
Earlier I posted my gallery of CES gadgets, and included a photo of the eHang 184 from China, a “personal drone” able, in theory, to carry a person up to 100kg.
Whether the eHang is real or not, some version of the personal automated flying vehicle is coming, and it’s not that far away. When I talk about robocars, I am often asked “what about flying cars?” and there will indeed be competition between them. There are a variety of factors that will affect that competition, and many other social effects not yet much discussed.
There are two visions of the flying car. The most common is VTOL — vertical takeoff and landing — something that may have no wheels at all because it’s more a helicopter than a car or airplane. The recent revolution in automation and stability for multirotor helicopters — better known as drones — is making people wonder when we’ll get one able to carry a person. Multirotors almost exclusively use electric motors because you must adjust speed very quickly to get stability and control. You also want the redundancy of multiple motors and power systems, so you can lose a rotor or a battery and still fly.
This creates a problem because electric batteries are heavy. It takes a lot of power to fly this way. Carrying more batteries means more weight — and thus more power needed to carry the batteries. There are diminishing returns, and you can’t get much speed, power or range before the batteries are dead. OK in a 3 kilo drone, not OK in a 150 kilo one.
Lots of people are experimenting with combining multirotor for takeoff and landing, and traditional “fixed wing” (standard airplane) designs to travel any distance. This is a great deal more efficient, but even so, still a challenge to do with batteries for long distance flight. Other ideas including using liquid fuels some way. Those include just using a regular liquid fuel motor to run a generator (not very efficient) or combining direct drive of a master propeller with fine-control electric drive of smaller propellers for the dynamic control needed.
Another interesting option is the autogyro, which looks like a helicopter but needs a small runway for takeoff.
Some “flying car” efforts have made airplanes whose wings fold up so they can drive on the road. These have never “taken off” — they usually end up a compromise that is not a very good car or a very good plane. They need airports but you can keep driving from the airport. They are not, for now, autonomous.
Some want to fly most of their miles, and drive just short distances. Some other designs are mostly for driving, but have an ability to “short hop” via parasailing or autogyro flying when desired. read more »
Thu, 19 Jan 2017 21:40:34 -0800
NHTSA released the report from their Office of Defects Investigation on the fatal Tesla crash in Florida last spring. It’s a report that is surprisingly favorable to Tesla. So much so that even I am surprised. While I did not think Tesla would be found defective, this report seems to come from a different agency than the one that recently warned comma.ai that:
It is insufficient to assert, as you do, that the product does not remove any of the driver’s responsibilities” and “there is a high likelihood that some drivers will use your product in a manner that exceeds its intended purpose.”
The ODI report rules that Tesla properly considered driver distraction risks in its design of the product. It goes even further, noting that after the introduction of Tesla autopilot (including driving by those monitoring it properly, those who were distracted, and those who drove with it off) still had a decently lower accident rate for mile than drivers of Teslas before autopilot. In other words, while the autopilot without supervision is not good enough to drive on its own, the autopilot even with the occasionally lapsed supervision that is known to happen, combined with improved AEB and other ADAS functions, is still overall a safer system than not having the autopilot at all.
This will provide powerful support for companies developing autopilot style systems, and companies designing robocars who wish to use customer supervised driving as a means to build up test miles and verification data. They are not putting their customers at risk as long as they do it as well as Tesla. This is interesting (and the report notes that evaluation of autopilot distraction is not a settled question) because it seems probable that people using the autopilot and ignoring the road to do e-Mail or watch movies are not safer than regular drivers. But the overall collection of distracted and watchful drivers is still a win.
This might change as companies introduce technologies which watch drivers and keep them out of the more dangerous inattentive style of use. As the autopilots get better, it will become more and more tempting, after all.
Tesla stock did not seem to be moved by this report. But it was also not moved by the accident or other investigations — it actually went on a broadly upward course for 2 months following announcement of the fatality.
The ODI’s job is to judge if a vehicle is defective. That is different from saying it’s not perfect. Perfection is not expected, especially from ADAS and similar systems. The discussion about the finer points of whether drivers might over-trust the system are not firmly settled here. That can still be true without the car being defective and failing to perform as designed, or being designed negligently.
Thu, 19 Jan 2017 12:08:12 -0800
(image) I go to CES first to see the cars but it’s also good to see all the latest gadgets. My gallery, with captions you will see at the bottom as you page through them, provides photos and comments on interesting and stupid products and gadgets for this year.
CES always contains an amazing array of “What are they thinking?” products. This year, more than ever, we had more things that were made “smart” and “connected” for little reason one can discern. I was quite disappointed to read various media lists of top gadgets of CES 2017 and not find a single one that was actually exciting. There are a few that will be exciting one day — the clothes folding robot, the human carrying drone — but they are not here yet.
Mon, 16 Jan 2017 21:08:38 -0800Recently we’ve seen two essays by people I highly respect in the field of AI and robotics. Their points are worthy of reading, but in spite of my respect, I have some differences of course. The first essay comes from Andrew Ng, head of AI (and thus the self-driving car project) at Baidu. You will find few who can compete with Andrew when it comes to expertise on AI. (Update: This essay is not recent, but I only came upon it recently.) In Wired he writes that Self-Driving Cars Won’t Work Until We Change Our Roads—And Attitudes. And the media have read this essay as being much more strong about changing the roads than he actually writes. I have declared it to be the “first law of robocars” that you don’t change the infrastructure. You improve your car to match the world you are given, you don’t ask the world to change to help your cars. There are several reasons I promote this rule: As soon as you depend on a change in the world in order to drive safely, you have vastly limited where you can deploy. You declare that your technology will be, for a very long time, a limited area technology. You have to depend on, and wait for others to change the world or their attitudes. It’s beyond your control. When it comes to cities and infrastructure, the pace of change is glacial. When it comes to human behaviour, it can be even worse. While it may seem that the change to infrastructure is clearer and easier to plan, the reality is almost assuredly the opposite. That’s because the clever teams of developers, armed with the constantly improving technologies driven by Moore’s law, have the ability to solve problems in a way that is much faster than our linear intuitions suggest. Consider measuring traffic by installing tons of sensors, vs. just getting everybody to download Waze. Before Waze, the sensor approach seemed clear, if expensive. But it was wrong. As noted, Andrew Ng does not actually suggest that much change to the infrastructure. He talks about: Having road construction crews log changes to the road before they do them Giving police and others who direct traffic a more reliable way to communicate their commands to cars Better painting of lane markers More reliable ways to learn the state of traffic lights Tools to help humans understand the actions and plans of robocars Logging construction The first proposal is one I have also made, because it’s very doable, thanks to computer technology. All it requires at first blush is a smartphone app in the hands of construction crews. Before starting a project, they would know that just as important as laying out cones and signs is opening the app and declaring the start of a project. The phone has a GPS and can offer a selection of precise road locations and log it. Of course, the projects should be logged even before they begin, but because that’s imperfect, smartphone logging is good enough. You could improve this by sticking old smartphones in all the road construction machines (old phones are cheap and there are only so many machines) so that any time a machine stops on a road for very long, it sends a message to a control center. Even emergency construction gets detected this way. Even with all that, cars still need to detect changes to the road (that’s easy with good maps) and cones and machines. Which they can do. Police redirection I think the redirection problem is more difficult. Many people redirect traffic, even civilians. However, I would be interested to see Ng’s prediction on how hard it is to get neural network based recognizers to understand all the common gestures. Considering that computers are now getting better at readi[...]
Sun, 15 Jan 2017 17:30:39 -0800CES has become the big event for major car makers to show off robocar technology. Most of the north hall, and a giant and valuable parking lot next to it, were devoted to car technology and self-driving demos. Gallery of CES comments Earlier I posted about many of the pre-CES announcements and it turns out there were not too many extra events during the show. I went to visit many of the booths and demos and prepared some photo galleries. The first is my gallery on cars. In this gallery, each picture has a caption so you need to page through them to see the actual commentary at the bottom under the photo. Just 3 of many of the photos are in this post. To the left you see BMW’s concept car, which starts to express the idea of an ultimate non-driving machine. Inside you see that the back seat has a bookshelf in it. Chances are you will just use your eReader, but this expresses and important message — that the car of the future will be more like a living, playing or working space than a transportation space. Nissan The main announcement during the show was from Nissan, which outlined their plans and revealed some concept cars you will see in the gallery. The primary demo they showed involved integration of some technology worked on by Nissan’s silicon valley lab leader, Maarten Sierhuis in his prior role at NASA. Nissan is located close to NASA Ames (I myself work at Singularity University on the NASA grounds) and did testing there. Their demo showed an ability to ask a remote control center to assist a car with a situation it doesn’t understand. When the car sees something it can’t handle, it stops or pulls over, and people in the remote call center can draw a path on their console to tell the car where to go instead. For example, it can be drawn how to get around an obstacle, or take a detour, or obey somebody directing traffic. If the same problem happens again, and it is approved, the next car can use the same path if it remains clear. I have seen this technology a number of places before, including of course the Mars rovers, and we use something like it at Starship Technologies for our delivery robots. This is the first deployment by a major automaker. Nissan also committed to deployment in early 2020 as they have before — but now it’s closer. You can also see Nissan’s more unusual concepts, with tiny sensor pods instead of side-view mirrors, and steering wheels that fold up. Startups Several startups were present. One is AIMotive, from Hungary. They gave me a demo ride in their test car. They are building a complete software suite, primarily using cameras and radar but also able to use LIDAR. They are working to sell it to automotive OEMs and already work with Volvo on DriveMe. The system uses neural networks for perception, but more traditional coding for path planning and other functions. It wasn’t too fond of Las Vegas roads, because the lane markers are not painted there — lanes are divided only with Bott’s Dots. But it was still able to drive by finding the edge of the road. They claim they now have 120 engineers working on self-driving systems in Hungary. read more » [...]
Tue, 10 Jan 2017 13:30:24 -0800
You may have seen a lot of press around a dashcam video of a car accident in the Netherlands. It shows a Tesla in AutoPilot hitting the brakes around 1.4 seconds before a red car crashes hard into a black SUV that isn’t visible from the viewpoint of the dashcam. Many press have reported that the Tesla predicted that the two cars would hit, and because of the imminent accident, it hit the brakes to protect its occupants. (The articles most assuredly were not saying the Tesla predicted the accident that never happened had the Tesla failed to brake, they are talking about predicting the dramatic crash shown in the video.)
The accident is brutal but apparently nobody was hurt.width="640" height="360" src="https://www.youtube.com/embed/om3z1yLQtwo" frameborder="0" allowfullscreen>
The press speculation is incorrect. It got some fuel because Elon Musk himself retweeted the report linked to, but Telsa has in fact confirmed the alternate and more probable story which does not involve any prediction of the future accident. In fact, the red car plays little to no role in what took place.
Tesla’s autopilot uses radar as a key sensor. One great thing about radar is that it tells you how fast every radar target is going, as well as how far away it is. Radar for cars doesn’t tell you very accurately where the target is (roughly it can tell you what lane a target is in.) Radar beams bounce off many things, including the road. That means a radar beam can bounce off the road under a car that is in front of you, and then hit a car in front of it, even if you can’t see the car. Because the radar tells you “I see something in your lane 40m ahead going 20mph and something else 30m ahead going 60mph” you know it’s two different things. read more »
Wed, 04 Jan 2017 23:20:43 -0800Thursday night I am heading off to CES, and it’s become the main show it seems for announcing robocar news. There’s already a bunch. BMW says it will deploy a fleet of 40 cars in late 2017 Bumping up the timetables, BMW has declared it will have a fleet of 40 self-driving series 7 cars, using BMW’s technology combined with MobilEye and Intel. Intel has recently been making a push to catch up to Nvidia as a chipmaker supplier to automakers for self-driving. It’s not quite said what the cars will do, but they will be trying lots of different roads. So far BMW has mostly been developing its own tech. More interesting has been their announcement of plans to sell rides via their DriveNow service. This was spoken of a year ago but not much more has been said. Intel also bought 15% of “HERE” the company formerly known as Navteq and Nokia. Last year, the German automakers banded together to buy HERE from Nokia and the focus has been on “HD” self-driving maps. Hyundai, Delphi show off cars There are demo cars out there from Delphi and a Hyundai Ioniq. Delphi’s car has been working for a while (it’s an Audi SUV) but recently they have also added a bunch of MobilEye sensors to it. Reports about the car are good, and they hope to have it ready by 2019, showing up in 2020 or 2021 cars on dealer lots. Toyota sticks to concepts Toyota’s main announcement is the Concept-i meant to show off some UI design ideas. It’s cute but still very much a car, though with all the silly hallmarks of a concept — hidden wheels, strangely opening doors and more. Quanergy announces manufacturing plans for $250 solid state LIDAR Quanergy (Note: I am on their advisory board) announced it will begin manufacturing this year of automotive grade $250 solid state LIDARs. Perhaps this will stop all the constant articles about how LIDAR is super-expensive and means that robocars must be super-expensive too. The first model is only a taste of what’s to come in the next couple of years as well. New Ford Model has sleeker design Ford has become the US carmaker to watch (in addition to Tesla) with their announcement last year that they don’t plan to sell their robocars, only use them to offer ride service in fleets. They are the first and only carmaker to say this is their exclusive plan. Just prior to CES, Ford showed off a new test model featuring smaller Velodyne pucks and a more deliberate design. I have personally never understood the desire to design robocars to “look like regular cars.” I strongly believe that, just like the Prius, riders in the early robocars will want them to look distinctive, so they can show off how they are in a car of the future. Ford’s carm based on the Fusion hybrid, is a nice compromise — clearly a robocar with its sensors, but also one of sleek and deliberate design. Nvidia keeps its push Nvidia has a new test car they have called BB8. (Do they have to licence that name?) It looks fairly basic, and they show a demo of it taking somebody for a ride with voice control, handling a lot of environments. It’s notable that at the end, the driver has to take over to get to the destination, so it doesn’t have everything, nor would we expect it. NVIDIA is pushing their multi-GPU board as the answer to how to get a lot of computing power to run neural networks in the car. What’s coming Announcements are due tomorrow from Nissan and probably others. I’ll report Friday from the show floor. See you there. [...]
Tue, 03 Jan 2017 00:40:37 -0800Yesterday’s post about the flaws in the so-called “popular vote” certainly triggered some debate (mostly on Facebook.) To clarify matters, I thought I would dive a little deeper about what the two types of Presidential elections in the USA are so different they can’t be added together in a way that isn’t misleading. These matters are studied both by statisticians, who focus on the science of measurement, particularly of things about groups, and election theorists, who also are interested in that but add the study of votes/polls which do not deliberately sample a subset of a population, but attempt to consider the will of the entire group. Both of them are highly concerned about how to deal with the fact a substantial fraction of the population may not participate. One way to look at the difference is to consider this: An election is not supposed to be just a measurement. It is that, but more than that it is an action. It is the actual enactment of the will of the voters. While there are government officials who count the votes and report on them, a person is not put into office by those officials. Rather, it is the voters who put the candidate into office through their votes. (In Canada, it’s different. The Queen and her Governor-General technically have the legal power, and they observe how the people voted and invite the winner to form a government in the Queen’s name.) Because voting is an act, rather than just an expression of opinion, we have come to deal with the non-participators as still acting. By not registering to vote or not showing up, they have still taken an action; they have deferred to the others to select the winner. We tolerate this, though we don’t like it. Low turnouts reduce confidence in the results, and they also mean that election results can be more easily manipulated through “get out the vote” efforts. On the other hand, we get quite upset when people don’t vote for other reasons outside their own will, particularly if somebody else impeded their ability to vote, or manipulated them into not voting. Both voting and not voting must be acts of the free person. Election theorists join with statisticians in some ways. All are interested in making sure that the aggregate will that comes from counting the votes most accurately reflects the aggregate will of the voters. We debate the merits of different counting systems. Many feel that multi-candidate ballots/preferential ballots do a much better job than first-past-the-post plurality systems. But in all case the counting system is simply the means of calculating the voters’ will so it can be enacted. In the US Presidential elections, in spite of what is written on the ballot, the voters are appointing a slate of members of the electoral college. This is done independently in each state. In the swing states, all is as you would expect. Candidates campaign. Major efforts are made to woo voters and to get voters to come out. Voters go to the polls knowing and expecting that their will shall be done. They expect they might be part of the group which gets to designate the slate of electors. In the safe states, it’s very different. In these states, who the electors will be is already well established from polls and the historical patterns of the state. The voters will picks the electors, but it’s a foregone conclusion. Nobody campaigns. There are no major efforts to get out the vote. There will be other races on the ballots which will bring out voters, who will vote within the known constraints. A decen[...]
Sun, 01 Jan 2017 13:18:11 -0800The common statistic reported after the US election was that Clinton “won the popular vote” by around 3 million votes over Trump. This has caused great rancour over the role of the electoral college and has provided a sort of safety valve against the shock Democrats (and others) faced over the Trump victory. I’m here with concerning analysis, which I offer because it is a mistake on the part of the US left to underestimate the magnitude of Trump’s victory, or to imagine it was only because of a flaw in the system which he gamed better than Clinton. The problem is that the US does not officially have a thing called “the popular vote.” That exists nowhere in its rules. There is no popular election of the President. Rather, there 54 elections with popular votes in 51 jurisdictions, which newspaper reporters then sum up into a number they incorrectly describe as “the national popular vote.” Of course, Clinton did win that invalid sum by around 3M votes. But bad statistical practice by the press, though it has created a common convention — for many decades — of calling that number “the popular vote,” does not make it valid. True popular votes involve all voters being free and equal, and we criticise any foreign election that pretends to call itself a popular vote when the voters are not free and equal. A popular vote, by its proper definition, is the vote total in a single election. Not 54 of them. As such, the sum is no more a popular vote total than adding the results of the 2008 and 2012 votes would get you a popular vote for or against Obama. It’s especially invalid because it’s really summing two fairly different types of results. True Popular vote totals from “swing” states where both candidates actively campaigned, turnout was higher, and voters expected their votes to count Low-accuracy popular vote totals from “safe states” which candidates did not contest, and where voters knew their vote would not change the result Statisticians will tell you these are two very different animals. We probably wish we knew who would have won the popular vote, if there had been a real national popular vote. Because there was no such vote, the hard answer is we don’t know what its result would be. In particular, with a statistically invalid sum like the published national popular vote, it is incorrect to say one party “won” or “lost.” There is no actual contest to win or lose, and while you can pretend that a higher total is winning, it is not a mathematically valid conclusion. We do know that in the 16 contested regions, Trump surpassed Clinton in a simple sum by about 500,000 votes. (As you would expect, since he needed to win the swing states to win the college.) In the uncontested states, where the Presidential choice was closer to a self-selected survey than a vote, a sum of those popular votes has her about 3.4M more than Trump. While you can’t add popular votes, each popular vote is a statistic, and you can combine statistics if you follow correct statistical procedures. There are many factors which will introduce error into the results from non-contested states, making it harder to figure out what the actual popular vote might have been. Voters knew their votes didn’t matter. Many stayed home; these states had generally lower voter turnout. The states with the lowest turnout (HI, WV, TN, TX, OK, AR, AZ, NM, MS, NY, CA, IN, UT) were generally safe states with large margins. Average tu[...]
Thu, 22 Dec 2016 09:58:47 -0800The California DMV got serious in their battle with Uber and revoked the car registrations for Uber’s test vehicles. Uber had declined to register the cars for autonomous testing, using an exemption in that law which I described earlier. The DMV decided to go the next step and pull the more basic licence plate every car has to have if based in California. Uber announced it would take the cars to another state. While I’m friends with the Uber team, I have not discussed this matter with them, so I can only speculate why it came to this. As noted, Uber was complying with the letter of the law but not the spirit, which the DMV didn’t like. At the same time, the DMV kept pointing out that registering was really not that hard or expensive, so they can’t figure out why Uber stuck to its guns. (Of course, Uber has a long history of doing that when it comes to cities trying to impose old-world taxi regulations on them.) The DMV is right, it’s not hard to register. But with that registration comes other burdens, in particular filing regular public reports on distance traveled, interventions and any accidents. Companies doing breakthrough R&D don’t usually work under such regimes, and I am speculating this might have been one of Uber’s big issues. We’ve all see the tremendous amount of press that Google has gotten over accidents which were clearly not the fault of their system. The question is whether the public’s right to know (or the government’s) about risks to public safety supersedes the developer’s desires to keep their research projects proprietary and secret. It’s clear that we would not want a developer going out on the roads and having above-average numbers of accidents and keeping it hidden. And it may also be true that we can’t trust the developers to judge the cause of fault, because they could have a bias. (Though on most of the teams I have seen, the bias has been a safety paranoid one, not the other way around.) Certainly when we let teens start to drive, we don’t have them make a public report of any accidents they have. The police and DMV know, and people who get too many tickets or accidents get demerits and lose licences when it is clear they are a danger to the public. Perhaps a reasonable compromise would have been that all developers report all problems to the DMV, but that those results are not made public immediately. They would be revealed eventually, and immediately if it was determined the system was at fault. Uber must be somewhat jealous of Tesla. Tesla registered several cars under the DMV system, and last I saw, they sent in their reports saying their cars had driven zero miles. That’s because they are making use of the same exemption that Uber wanted to make use of, and saying that the cars are not currently qualifying as autonomous under the law. Pacifica Minivans released by Waymo/Google Waymo has unveiled its 4th generation vehicle, a fleet of 100 Chrysler Pacifica minivans. The partnership was announced in May and the new vehicle has various custom modifications As you can see, the van still has Waymo’s custom 360 degree LIDAR dome on top, and two sensors at the back top corners, plus other forward sensors. The back sensors I would guess to be rear radar — which lets you make lane changes safely. We also see three apparent small LIDARs, one on the front bumper, and the other two on the sides near the windshield pillars with what may be side-view radars. A bumper LI[...]
Mon, 19 Dec 2016 10:06:34 -0800
Everybody should have off-site backup of their files. For most people, the biggest threat is fire, but here in California, the most likely disaster you will encounter is an earthquake. Only a small fraction of houses will burn down, but everybody will experience the big earthquake that is sure to come in the next few decades. Of course, fortunately only a modest number of houses will collapse, but many computers will be knocked off desks or have things fall on them.
To deal with this, I’ve been keeping a copy of my data in my car — encrypted of course. I park in my driveway, so nothing will fall on the car in a quake, and only a very large fire would have risk of spreading to the car, though it’s certainly possible.
The two other options are network backup and truly remote backup. Network backup is great, but doesn’t work for people who have many terabytes of storage. I came back from my latest trip with 300gb of new photos, and that would take a very long time to upload if I wanted network storage. In addition, many TB of network storage is somewhat expensive. Truly remote storage is great, but the logistics of visiting it regularly, bringing back disks for update and then taking them back again is too much for household and small business backup. In fact, even being diligent about going down to the car to get out the disk and update is difficult.
A possible answer — a wireless backup box stored in the car. Today, there are many low-cost linux based NAS boxes and they mostly run on 12 volts. So you could easily make a box that goes into the car, plugs into power (many cars now have 12v jacks in the trunk or other access to that power) and wakes up every so often to see if it is on the home wifi, and triggers a backup sync, ideally in the night. read more »