Submitted by brad on Mon, 2014-10-27 10:52.
There’s been a lot of press recently about an article in Slate by
Lee Gomes which paints a pessimistic picture of the future of
robocars, and particularly Google’s project. The Slate article
is a follow-on to a similar article in MIT Tech Review
Gomes and others seem to feel that they and the public were led to believe that
current projects were almost finished and ready to be delivered any day, and
they are disappointed to learn that these vehicles are still research projects
and prototypes. In a classic expression of the Gartner Hype Cycle there are
now predictions that the technology is very far away.
Both predictions are probably wrong. Fully functional robocars that can drive almost
everywhere are not coming this decade, but nor are they many decades away.
But more to the point, less-functional robocars are probably coming this decade — much sooner than
these articles expect, and these vehicles are much more useful and commercially
viable than people may expect.
There are many challenges facing developers, and those challenges will
keep them busy refining products for a long time to come. Most of those
challenges either already have a path to solution, or constrain a future vehicle
only in modest ways that still allow it to be viable. Some of the problems
are in the “unsolved” class. It is harder to predict when those
solutions will come, of course, but at the same time one should remember that
many of the systems in today’s research vehicles were in this class just a
few years ago. Tackling hard problems is just what these teams are good at
doing. This doesn’t guarantee success, but neither does it require you bet
And very few of the problems seem to be in the “unsolvable without human-smart AI” class,
at least none that bar highly useful operation.
Gomes’ articles have been the major trigger of press, so I will go over those issues
in detail here first. Later, I will produce an article that has even
more challenges than listed, and what people hope to do about them. Still, the critiques are written almost as though they
expected Google and others, rather than make announcements like “Look at the new milestone we are pleased to
have accomplished” to instead say, “Let’s tell you all the things we haven’t done yet.”
Gomes begins by comparing the car to the Apple Newton, but forgets that
9 years after the Newton fizzled we had the success of the Palm Pilot, and
10 years after that Apple came back with the world-changing iPhone. Today, the pace of
change is much faster than in the 80s.
Here are the primary concerns raised:
Maps are too important, and too costly
Google’s car, and others, rely on a clever technique that revolutionized
the DARPA challenges. Each road is driven manually a few times, and the
scans are then processed to build a super-detailed “ultramap” of all the
static features of the road. This is a big win because big server
computers get to process the scans in as much time as they need,
and see everything from different angles. Then humans can review and
correct the maps and they can be tested. That’s hard to beat, and you
will always drive better if you have such a map than if you don’t.
Any car that could drive without a map would effectively be a car that’s
able to make an adequate map automatically. As things get closer to that,
making maps will become cheaper and cheaper.
Naturally, if the road differs from the map, due to construction or
other changes, the vehicle has to notice this. That turns out to be
fairly easy. Harder is assuring it can drive safely in this situation.
That’s still a much easier problem than being able to drive safely
everywhere without a map, and in the worst case, the problem of the
changed road can be “solved” by just the ability to come to a safe stop.
You don’t want to do that super often, but it remains the fail-safe
out. If there is a human in the car, they can guide the vehicle in this.
Even if the vehicle can’t figure out where to go to be safe, the human
can. Even a remote human able to look at transmitted pictures can help
the car with that — not live steering, but strategic guidance.
This problem only happens to the first car to encounter the surprise construction.
If that car is still able to navigate (perhaps with human help,) the map can be quickly rebuilt, and
if the car had to stop, all unmanned cars can learn to avoid the zone.
They are unmanned, and thus probably not in a hurry.
The cost of maps
In the interests of safety, a lot of work is put into today’s maps. It’s a cost
that somebody like Google or Mercedes can afford if they need to, (after all, Google’s already
scanned every road
in many countries multiple times) but it would be high for smaller players. read more »
Submitted by brad on Sun, 2014-10-26 14:22.
A recent newspaper column where people complained about carpool cheats got me thinking — could cheating actually be a solution to some carpool problems?
For many years, the wisdom was that carpool lanes were helping traffic and the environment, but that wisdom has been changing, and it is now seen that the lanes actually hurt (at least the traffic) in many cases. As such, the new approach is to build “managed lanes” and in particular the High-Occupancy-Toll (HOT) lanes which let solo drivers pay to use the lane. In addition, low emission cars and motorcycles usually get to use the lanes solo.
Why does this help? It turns out that a typical configuration of 3 solo lanes and one carpool lane is performing badly when the carpool lane is well under capacity. The ideal road would have all 4 lanes running just under 100% capacity (which is around 2,000 cars per hour, or 8,000 for the whole road.) At rush hour, however, the lanes often collapse in congestion to stop and go, which can drop as low as 1,300 vehicles/hour.
Carpool approaches suggest that if you have one carpool lane running at less than capacity (and thus congestion free and highly attractive) that you will make people choose to carpool. Each carpool takes a car or two off the road, which is a win for congestion (and the environment.)
Consider one carpool situation, where the carpool lane is running free at 50% of capacity, and the other 3 lanes are at 100% of capacity. You’re now moving 7,000 vehicles/hour instead of 8,000, but that would be OK if it’s because you took more than 1,000
vehicles off the road.
Unfortunately that’s not even remotely true. The vast majority of the carpools on the road are natural carpools that would have happened anyway. Couples or families travelling together. “Kidpools” where in almost all cases no car was taken off the road. The permitted solo drivers in low emission vehicles and motorcycles don’t remove cars, but are greener. The number of “induced” carpools — carpools that were created because of the attractive travel time offered by the carpool lane — is quite low. Perhaps as low as 10%, but likely not more than 20%. HOV-3 lanes may have more induced carpools.
To make it worse, consider a carpool lane at 70% usage (good) but the 3 other lanes in congestion, and now getting 1,500 vehicles per hour. We’ve dropped our road to just 5,900 cars per hour. And at 20% induced carpools we only took 280 cars off the road, for a total of 6,180 instead of our ideal of 8,000. There is a zone of congestion where moving another 500 cars from the solo lanes to the carpool lane would relieve the congestion in the solos, and we would get closer to our 8,000.
That’s what HOT lanes are about. By charging a fee, they move solo drivers who are willing to pay to use the underutilized carpool lane, and we remove them from the solos, increasing their throughput as well. It’s a win-win-win. HOT lanes adjust the price — if the carpool lane is starting to fill up, the price jacks up. The goal is to keep the carpool lane enough below 100% capacity that it flows smoothly, which is good for flow and also what makes it attractive in the first place to make those induced carpools.
With HOT, you can have 1,000 carpoolers and 900 paying solos and also 200 induced carpools so the lane is now delivering the equivalent of 2,100 vehicles/hour and everybody wins. Letting efficient solos use the lane doesn’t involve money, but subsidizes efficient vehicles.
Without HOT, the bizarre conclusion is that cheaters are helping move traffic along. Cheaters only cheat when the carpool lane is going really well — ie. underutilized — and the solo lanes are getting congested. Cheaters take some load off the solo lanes and make use of the wasted capacity. They will not cheat if the carpool lane is not beating the solo lanes by a nice margin. If the carpool lane gets overloaded, they are going to leave it — why risk the ticket?
I should note that I have never, ever deliberately cheated in the carpool lane. (Like most, once or twice I have forgotten what time it was for a minute or two.) I am not trying to justify cheating, and in fact one concern is that some cheaters will read this and imagine they are doing a service. Cheaters are helping the system, but in a completely unfair and inappropriate way.
One reason we don’t have more HOT lanes, now that people realize that they are better, is that it costs a lot of money to put them in. Part of that money is for infrastructure — gantries, transponders, signs with prices, enforcement teams, operations teams. The biggest cost comes from the fact that generally people like to make HOT lanes truly separate from the main lanes, with a double line, and entry/exit only allowed at certain points. That means restriping or even new construction.
Many of the world’s transit systems work on an honour system. You have to buy a ticket, but nothing checks this. Instead, if you are caught on board without a ticket, you pay a fat fine. The fine is often calculated to balance the enforcement level, so that a regular cheater will be caught enough that it’s more expensive to cheat than to buy tickets. But often not a lot more expensive, as it turns out.
What if HOT lanes were the same way? Go ahead and cheat! Install random enforcement stations with cameras, and enforce enough so that any regular “cheater” gets fines which are calculated to collect as much or more money than the tolls.
The obvious flaw here is that this only works for the regular cheater. It’s too random, and an occasional lane user (or tourist) would be taking a big gamble, without enough use to balance it out. So we can add payment by cell phone to even things out.
Before leaving, or after arriving, tell your phone or browser you will be using or did use the lane. (The reason to do it in advance is
you will get a better price.) Your phone can show you the price, and some road signs will display it as well. This gives you a token which includes the time and your licence plate. If you get a fine notice, you can nullify it by providing the token.
(If you don’t care about privacy, you could register the licence plate directly. But I do care about privacy.)
This works with minimal new infrastructure. And payment via phone would be set to be cheaper than the average payment you would pay through random fines, so most people would do it. And all this happens with minimal new infrastructure, as long as you don’t need to reconfigure the lanes.
Enforcement can involve cameras, which may or may not be recording. You need enough of them so that people don’t just briefly switch out of the carpool lane just before coming to a camera, so this has some infrastructure cost. The camera would record the photo of the front seats of your car, and your plate. In isolate carpool lanes this does work better.
This is aimed at places where 2 is a carpool. It means something controversial. Carpoolers must share the front seat. And that means no kidpooling with children small enough to be required to ride in the back seat. Some people will hate that (parents) and some will love it (those who feel that kidpooling is unfair because it almost never causes an induced carpool.) This controversy can be some what mitigated by offering a discount to people who declare they are kidpooling (or better, multi-family kidpooling) with occasional checks.
It’s also an issue for Taxis, Uber and people with chauffeurs. Forcing the latter to pay won’t bother many people. Taxis can be given special status. Ad-hoc taxis, like Uber, can be told, “hey, just make the ride in the front if you want a free entry.” Is that such a big burden? If so, alternate systems can be set up, including requesting a token over the smartphone which can be compared to audited records of fares.
The camera stations could also photograph in through the sides of vehicles. Tinted side windows would not get to be carpools. This is harder than just doing the front, and harder to hide. And there would still be occasional live human observers, to the extent that cost allows.
To avoid risk of people wanting to use phones while driving, we simply allow you to buy a retroactive token within a day of your trip. (You don’t learn about your fine for a couple of days.) You could do that on the web, on a smartphone, by text (retroactive only) or even at any convenience store or gas station that has a payment machine. (This idea is not new. A decade ago I drove a toll road in Melbourne which lets you buy a toll pass at a gas station after you drive the road.)
Or, of course, just pay the fines if they are not that much more expensive, on average than buying tokens.
Even carpoolers could register that they carpooled, in case a problem comes up. Users will want to register an e-mail address or app address with the system under their plate to get notices of fines. If you don’t, notices would come by postal mail. If somebody else registers your plate and you don’t, it might delay notice of fines but you would fix this after the first one.
If the typical toll is $3, and the fine is $300, you probably would get a fine notice you need to nullify perhaps every 75 uses on average. This makes paying cheaper. The smartphone app would also notice when you travel the route and remind you.
To protect privacy, the system would not remember tokens it issues, and it would erase all images once it was confirmed the car was legit (carpool, allowed vehicle or had a token.) Only the images of non-carpools who did not respond with their token would be retained for issuing fines to their car.
There can be problems with photo enforcement if it is dark (as it is during winter for portions of rush hour) or in places where the sun is at just the wrong angle. The latter can be fixed because we know just where the sun will be. The former is more challenging. Cameras would need to be placed in line with suitable street lights, and have larger lenses. During the day used cell phones in rainproof cases with tiny solar panels could do the job at low cost.
Submitted by brad on Wed, 2014-10-22 13:26.
In late August, I visited Singapore to give an address at a special conference announcing a government sponsored collaboration involving their Ministry of Transport, the Land Transport Authority and A-STAR, the government funded national R&D centre. I got a chance to meet the minister and sit down with officials and talk about their plans, and 6 months earlier I got the chance to visit A-Star and also the car project at the National University of Singapore. At the conference, there were demos of vehicles, including one from Singapore Technologies, which primarily does military contracting.
Things are moving fast there, and this week, the NUS team announced they will be doing a live public demo of their autonomous golf carts and they have made much progress. They will be running the carts over a course with 10 stops in the Singapore Chinese and Japanese Gardens. The public will be able to book rides online, and then come and summon and direct the vehicles with their phones. The vehicles will have a touch tablet where the steering wheel will go. Rides will be free. Earlier, they demonstrated not just detecting pedestrians but driving around them (if they stay still) but I don’t know if this project includes that.
This is not the first such public demo - the CityMobil2 demonstration in Sardinia ran in August, on a stretch of beachfront road blocked to cars but open to bicycles, service vehicles and pedestrians. This project slowed itself to unacceptably slow speeds and offered a linear route.
The Singapore project will also mix with pedestrians, but the area is closed to cars and bicycles. There will be two safety officers on bicycles riding behind the golf carts, able to shut them down if any problem presents, and speed will also be limited.
Singapore is interesting because they have a long history of transportation innovation, and good reason for it. As a city-state, it’s almost all urban, and transportation is a real problem. That’s why congestion charging was first developed in Singapore, along with other innovations. Every vehicle in Singapore has a transponder, and they use them not just for congestion tolling, but to pay for parking seamlessly in almost all parking lots and a few other tricks.
In spite of this history of innovation, Singapore is also trending conservative — this might dampen truly fast innovation, but this joint project is a good start. Though I advised them that private projects will be able to move faster than public sector ones, in my view.
The NUS project is a collaboration with MIT, involving professor Emilio Frazzoli. Their press release has more details, including maps showing the route is non-linear but the speed is slow.
Submitted by brad on Tue, 2014-10-21 14:33.
Some recent announcements have caused lots of press stir, and I have not written much about them, both because of my busy travel schedule, but also because there is less news that we might imagine.
Tesla is certainly an important company to watch. As the first successful start-up car company in the USA, they are showing they know how to do things differently, taking advantage of the fact that they don’t have a baked in knowledge of “how a car company works” the way other companies do. Tesla’s announcements of plans for more self-driving are important. Unfortunately, the announcements around the new dual-motor Model S involve offerings quite similar to what can be found already in cars from Mercedes, Audi and a few others. Namely advanced ADAS and the combination of lane-keeping and adaptive cruise control to provide a hands-off cruise control where you must keep your eyes on the road.
One notable feature demonstrated by Tesla is automatic lane change, which you trigger by hitting a turn signal. That’s a good interface, but it must be made clear to people that they still have the duty to check that it’s safe to change lanes. It’s not that easy for a robocar’s sensors, especially the limited sensor package in the Telsa, to see a car coming up fast behind you in the next lane. On some highways relative speeds can get pretty high. You’re not likely to be hit by such cars, but in some cases that’s because they will probably brake for you, not because you did a fully safe lane change.
Much more interesting are Elon Musk’s predictions of a real self-driving car in 5 to 6 years. He means one where you can read a book, or even, as he suggests, go to sleep. Going to sleep is one of the greatest challenges, almost as hard as operating unmanned or carrying a drunk or disabled person. You won’t likely do that just with cameras — but 5 to 6 years is a good amount of time for a company like Tesla.
Another unusual thing about Tesla is that while they are talking about robocars a lot, they have also built one of the finest driver’s cars ever made. The Model S is great fun to drive, and has what I call a “telepathic” interface sometimes — the motors have so much torque that you can almost think about where you want to go and the vehicle makes it happen. (Other examples of telepathic interfaces include touch-typing and a stickshift.) In some ways it is the last car that people might want to automate. But it’s also a luxury vehicle, and that makes self-driving desirable too.
Another recent announcement creating buzz is Audi’s self-driving race car on a test track in Germany. Audi has done racing demos several times now. They are both important but also unimportant. It definitely makes sense to study how to control a car in extreme, high performance situations. To understand the physics of the tires so fully that you can compete in racing will teach lessons of use in danger situations (like accidents) or certain types of bad weather.
At the same time, real-world driving is not like racing, and nobody is going to be doing race-like driving on ordinary streets in their robocar. 99.9999% of driving consists of “staying in your lane” and some other basic maneuvers and so racing is fun and sexy but not actually very high on the priority list. (Not that teams don’t deserve to spend some of their time on a bit of fun and glory.) The real work of building robocars involves putting them through all the real-world road situations you can put them through, both real and in some cases simulated on a track or in a computer.
Google first showed its system to many people by having it race figure-8s on the roof parking lot at the TeD conference. The car followed a course through a group of cones at pretty decent speed and wowed the crowd with the tight turns. What most of the crowd didn’t know was that the cones were only there for show, largely. The car was guiding itself from its map of all the other physical things in the parking lot — line markers, pavement defects and more. The car is able to localize itself fine from those things. The cones just showed the public that it really was following the planned course. At the same time, making a car do that is something that was accomplished decades ago, and is used routinely to run “dummy cars” on car company test tracks.
A real demo turns out to be very boring, because that’s how being driven should be. I’m not saying it’s bad in any way to work on racing problems. The only error would be forgetting that the real-world driving problems are higher priority and success in them is less dramatic but more impressive in the technical sense.
This doesn’t mean we won’t see more impressive demos soon. Many people have shown off automatic braking. Eventually we will see demos of how vehicles respond in danger situations — accidents, pedestrians crossing into the road and the like. A tiny part of driving but naturally one we care about. And we will want them to understand the physics of what the tires and vehicle are capable of so that they perform well, but not so they can find the most efficient driving line on the track.
There was some debate about having a new self-driving car contest like the DARPA grand challenges, and a popular idea was man vs. machine, including racing. That would have been exciting. We asked ourselves whether a robot might have an advantage because it would have no fear of dying. (It might have some “fear” of smashing its owners very expensive car.) Turns out this happens on the racetrack fairly often with new drivers who try to get an edge by driving like they have no fear, that they will win all games of chicken. When this happens, the other drivers get together to teach that new driver a lesson. A lesson about cooperating and reciprocation in passing and drafting. So the robots would need to be programmed with that as well, or their owners would find a lot of expensive crashes and few victories.
Submitted by brad on Mon, 2014-10-13 20:59.
Here’s an interview with me in the latest Wall Street Journal on the subject of robocars and seniors.
This has always been a tricky question. Seniors are not early adopters, so the normal instinct would be to expect them to fear a new technology as dramatic as this one. Look at the market for simplified cell phones aimed at seniors who can’t imagine why they want a smartphone. Not all are like this, but enough are to raise the question.
Sometimes this barrier is broken. Pictures of grandchildren in e-mail brought grandparents online, as did video calls with them. Necessity overcomes the fear of change.
As people get older, they start losing driving ability. They die more often in accidents, eventually surpassing the rates of reckless teens, because they are more fragile, and they make mistakes that cause other people to hit them. Many seniors report troubles with vision at night, and they stop driving at night. In some cases, they get their licences taken away by the state — though the AARP and others fight this so it’s rare — or their kids take away their keys when things get really dangerous. And the kids become a taxi service for their parents.
The boomer generation, which took over the suburbs and exurbs have nice houses with minimal transit. Some find themselves leaving that home because they can’t drive any more and they will become a shut-in if they don’t do something.
The robocar offers answers to many of these problems. Safe transportation for those with disabilities. (Eventually even mild dementia.) Inexpensive taxi transportation anywhere, including those low-transit suburbs. And a chance to video chat with the grandchildren while on the way.
It’s no surprise that retirement communities are discussed as an early deployment zone for robocars. In those communities, you have a controlled street environment — often with heavy use of NEVs/golf carts already. You have people losing the ability to drive who have limited mobility needs. If they can get to basic shopping and a few other locations (including transit hubs to travel further) they can do pretty well.
Until the robocar came along, we were all doomed to lose the freedom cars gave us. This is no longer going to happen.
Submitted by brad on Tue, 2014-09-23 12:07.
I’ve been on the road a lot, talking in places like Singapore, Shenzen and Hong Kong, and visiting Indonesia which is a driving chaos eye-opener. In a bit over 10 hours I will speak at Swiss Re’s conference on robocars and insurance in Zurich. While the start will be my standard talk, in the latter section we will have some new discussion of liability and insurance.
A live stream of the event should be available at http://swissre.adobeconnect.com/theautonomouscar/ I talk at 8:45am Central European Summer Time.
A lot of news while I’ve been on the road — driving permits in California, new projects and the Singapore effort I was there at the announcement of. And lots of non-news that got people very excited like the “revelation” that Google’s car doesn’t drive in snow (nobody thought it could) or on all roads (nobody even suggested this) or that it was forced to add a steering wheel for testing (this was always planned, Google participating in the hearings writing those laws.) And lots of car company announcements from the ITS world congress (a conference that 2 years ago barely acknowledged the presence of self-driving cars.)
More to come later.
Submitted by brad on Fri, 2014-08-22 18:59.
There’s another video presentation by me that I did while visiting Big Think in NYC.
This one is on The NSA, Snowden and the “tradeoff” of Privacy and Security.
Earlier, I did a 10 minute piece on Robocars for Big Think that won’t be news to regular readers here but was reasonably popular.
Submitted by brad on Mon, 2014-08-11 09:09.
Earlier this year, I started a series on fixing U.S. democracy. Today let me look at the problem I identified as #3: Voter turnout and the excessive power of GOTV.
In a big political campaign, fundraising is king, and most of the money goes to broadcast advertising. But a lot of that advertising, a lot of the other money, and most of the volunteer effort goes to something else called GOTV or “Get Out the Vote.” Come to help a campaign and it’s likely that’s what you will be asked to do.
US elections have terrible turnout. Under 50% in the 1996 Presidential election, and only 57% in more recent contested elections. In off-years and local elections, the turnout is astonishingly low. Turnout is very low in certain minorities as well.
Because turnout is so low, the most cost effective way to gain a vote for your side is to convince somebody who weakly supports you to show up at the polls on election day. Your ads may pretend to attempt to sway people from the other side, or the small number of “undecideds,” but a large fraction of the ads are just trying to make sure your supporters take the trouble to vote. Most of them won’t, but those you can get count as much as any other vote you get. So you visit and phone all these mild supporters, you offer them rides to the polling place, you do everything legal you can to identify them and get them out, and in some cases, to scare the supporters of your opponent.
Is this how a nation should elect its leaders? By who can do the best job at getting the lukewarm supporters to make the trip on election day? It seems wrong. I will go even further, and suggest that the 45% or more who don’t vote are in some sense “disenfranchised.” Clearly not in the strong sense of that word, where we talk about voter suppression or legal battles. But something about the political system has made them feel it is too much of a burden to vote and so they don’t. Those who do care find that hard to credit, they think of them as just lazy, or apathetic, and wonder if we really want to hear the voice of such people.
GOTV costs money, and as such, it is a large factor in what corrupts our politics. If GOTV becomes less effective, it can help reduce the influence of money in politics. It’s serious work. Many campaigns send out people to canvass the neighbourhoods not to try to sway you, but just to figure out who is worth working on for GOTV.
Many countries in the world make it compulsory to vote. If your name is not checked off at the polling place, you get fined. Australia is often given as an example of this, with a 91% turnout, though countries like Austria and New Zealand do better without compulsory voting. But it does seem to make a difference. read more »
Submitted by brad on Thu, 2014-08-07 18:49.
Last month I wrote about paradoxes involving bitcoin and other cryptocurrency mining. In particular, I pointed out that while many people are designing alternative coins so that they are hard to mine with ASICs — and thus can be more democratically mined by people’s ordinary computers or GPUs — this generates a problem. If mining is done on ordinary computers, it becomes worthwhile to break into ordinary computers and steal their resources for mining. This has been happening, even with low powered NAS box computers which nobody would ever bother to mine on if they had to pay for the computer and its electricity. The attacker pays nothing, so any mining capacity is good.
Almost any. In Bitcoin, ASIC mining is so productive that it’s largely a waste of time to mine with ordinary CPUs even if you get them for free, since there is always some minor risk in stealing computer time. While ordinary computers are very hard to secure, dedicated ASIC mining rigs are very simple special purpose computers, and you can probably secure them.
But in a recently revealed attack thieves stole bitcoins from miners by attacking not the ASIC mining rigs, but their internet connections. The rigs may be simple, but the computers they flow their data through, and the big network routers, are less so. Using BGP redirection, it is suspected, the thieves just connected the mining rigs to a different mining pool than the one they thought they joined. And so they worked away, mining hard, and sometimes winning the bitcoin lottery, not for their chosen pool, but the thieves’ pool.
It’s not hard to imagine fixes for this particular attack. Pools and rigs can authenticate more strongly, and pools can also work to keep themselves more secure.
But we are shown one of the flaws of almost all digital money systems. If your computer can make serious money just by computing, or it can spend money on your behalf without need for a 2nd factor authentication, then it becomes very worthwhile for people to compromise your system and steal your computer time or your digital money. Bitcoin makes this even worse by making transactions irrevocable and anonymous. For many uses, those are features, but they are also bugs.
For the spending half, there is much effort in the community to build more secure wallets that can’t just spend your money if somebody takes over your computer. They rely on using multiple keys, and keeping at least one key in a more secure, even offline computer. Doing this is very hard, or rather doing it with a pleasant and happy user interface is super hard. If you’re going to compete with PayPal it’s a challenge. If somebody breaks into my PayPal account and transfers away the money there, I can go to PayPal and they can reverse those transactions, possibly even help track down the thieves. It’s bad news if a merchant was scammed but very good news for me.
One could design alternate currencies with chargebacks or refundability, but Bitcoin is quite deliberate in its choice not to have those. It was designed to be like cash. The issue is that while you could probably get away keeping your cash in your mattress and keeping a secure house, this is a world where somebody can build robots that can go into all the houses it can find and pull the cash out of the mattresses without anybody seeing.
Submitted by brad on Thu, 2014-08-07 15:17.
Ok, I’m not really much of a fan of banning anything, but the continued reports of massive thefts of password databases from web sites are not slowing down. Whether the recent Hold Security report of discovering a Russian ring that got a billion account records from huge numbers of websites is true or not, we should imagine that it is.
As I’ve written before there are two main kinds of password using sites. The sites that keep a copy of your password (ie. any site that can e-mail you your password if you forget it) and the sites who keep an encrypted/hashed version of your password (these can reset your password for you via e-mail if you forget it.) The latter class is vastly superior, though it’s still an issue when a database of encrypted passwords is stolen as it makes it easier for attackers to work out brute-force attacks.
Sites that are able to e-mail you a lost password should be stamped out. While I’m not big on banning, it make make sense that a rule require that any site which is going to remember your password in plain form have a big warning on the password setting page and login page:
This site is going to store your password without protection. There is significant risk attackers will someday breach this site and get your ID and password. If you use these credentials on any other site, you are giving access to these other accounts to the operators of this site or anybody who compromises this site.
Sites which keep a hashed password (including the Drupal software running this blog, though I no longer do user accounts) probably should have a lesser warning too. If you use a well-crafted password unlikely to be checked in a brute-force attack, you are probably OK, but only a small minority do that. Such sites still have a risk if they are taken over, because the taken over site can see any passwords typed by people logging in while it’s taken over.
Don’t feel too guilty for re-using passwords. Everybody does it. I do it, in places where it’s no big catastrophe if the password leaks. It’s not the end of the world if one blog site has the multi-use password I use on another blog site. With hundreds of accounts, there’s no way to not re-use with today’s tools. For my bank accounts or other accounts that could do me harm, I keep better hygene, and so should you.
But in reality we should not use passwords at all. Much better technology has existed for many decades, but it’s never been built in a way to make it easy to use. In particular it’s been hard to make it portable — so you can just go to another computer and use it to log into a site — and it’s been impossible to make it universal, so you can use it everywhere. Passwords need no more than your memory, and they work for almost all sites.
Even our password security is poor. Most sites use your password just to create a session cookie that keeps you authenticated for a long session on the site. That cookie’s even easier to steal than a password at most sites. read more »
Submitted by brad on Wed, 2014-07-30 13:01.
A whole raft of recent robocar news.
UK to modify laws for full testing, large grants for R&D
The UK announced that robocar testing will be legalized in January, similar to actions by many US states, but the first major country to do so. Of particular interest is the promise that fully autonomous vehicles, like Google’s no-steering-wheel vehicle, will have regulations governing their testing. Because the US states that wrote regulations did so before seeing Google’s vehicle, their laws still have open questions about how to test faster versions of it.
Combined with this are large research grant programs, on top of the £10M prize project to be awarded to a city for a testing project, and the planned project in Milton Keynes.
Jerusalem’s MobilEye going public in largest Israeli IPO
The leader in doing automated driver assist using cameras is Jerusalem’s MobilEye. This week they’re going public, to a valuation near $5B and raising over $600 million. MobilEye makes custom ASICs full of machine vision processing tools, and uses those to make camera systems to recognize things on the road. They have announced and demonstrated their own basic supervised self-driving car with this. Their camera, which is cheaper than the radar used in most fancy ADAS systems (but also works with radar for better results) is found in many high-end vehicles. They are a supplier to Tesla, and it is suggested that MobilEye will play a serious role in Tesla’s own self-driving plans.
As I have written, I don’t believe cameras are even close to sufficient for a fully autonomous vehicle which can run unmanned, though they can be a good complement to radar and especially LIDAR. LIDAR prices will soon drop to the low $thousands, and people taking the risk of deploying the first robocars would be unwise to not use LIDAR to improve their safety just to save a few thousand for early adopters.
Chinese search engine Baidu has robocar (and bicycle) project
Baidu is the big boy in Chinese search — sadly a big beneficiary of Google’s wise and moral decision not to be collaborators on massive internet censorship in China — and now it’s emulating Google in a big way by opening its own self-driving car project.
Various stories suggest a vehicle which involves regular handoff between a driver and the car’s systems, something Google decided was too risky. Not many other details are known.
Also rumoured is a project with bicycles. Unknown if that’s something like the “bikebot” concept I wrote about 6 years ago, where a small robot would clamp to a bike and use its wheels to deliver the bicycle on demand.
Why another search engine company? Well, one reason Google was able to work quickly is that it is the world’s #1 mapping company, and mapping plays a large role in the design of robocars. Baidu says it is their expertise in big data and AI that’s driving them to do this.
Velodyne has a new LIDAR
The Velodyne 64 plane LIDAR, which is seen spinning on top of Google’s cars and most of the other serious research cars, is made in small volumes and costs a great deal of money — $75,000. David Hall, who runs Velodyne, has regularly said that in volume it would cost well under $1,000, but we’re not there yet. He has released a new LIDAR with just 16 planes. The price, while not finalized, will be much higher than $1K but much lower than $75K (or even the $30K for the 32 plane version found on Ford’s test vehicle and some others.)
As a disclaimer, I should note I have joined the advisory board of Quanergy, which is making 8 plane LIDARs at a much lower price than these units.
Nissan goes back and forth on dates
Conflicting reports have come from Nissan on their dates for deployment. At first, it seemed they had predicted fairly autonomous cars by 2020. A later announcement by CEO Carlos Ghosn suggested it might be even earlier. But new reports suggest the product will be less far along, and need more human supervision to operate.
FBI gets all scaremongering
Many years ago, I wrote about the danger that autonomous robots could be loaded with explosives and sent to an address to wreak havoc. That is a concern, but what I wrote was that the greater danger could be the fear of that phenomenon. After all, car accidents kill more people every month in the USA than died at the World Trade Center 13 years ago, and far surpass war and terrorism as forms of violent death and injury in most nations for most of modern history. Nonetheless, an internal FBI document, released through a leak, has them pushing this idea along with the more bizarre idea that such cars would let criminals multitask more and not have to drive their own getaway cars. read more »
Submitted by brad on Wed, 2014-07-23 15:32.
I have many more comments pending on my observations from the recent AUVSI/TRB Automated Vehicles Symposium, but for today I would like to put forward an observation I made about two broad schools of thought on the path of the technology and the timeline for adoption. I will call these the aggressive and conservative schools. The aggressive school is represented by Google, Induct (and its successors) and many academic teams, the conservative school involves car companies, most urban planners and various others.
The conservative (automotive) view sees this technology as a set of wheels that has a computer.
The aggressive (digital) school sees this as a computer that has a set of wheels.
The conservative view sees this as an automotive technology, and most of them are very used to thinking about automotive technology. For the aggressive school, where I belong, this is a computer technology, and will be developed — and change the world — at the much faster pace that computer technologies do.
Neither school is probably entirely right, of course. It won’t go as gung-ho as a smartphone, suddenly in every pocket within a few years of release, being discarded when just 2 years old even though it still performs exactly as designed. Nor will it advance at the speed of automotive technology, a world where electric cars are finally getting some traction a century after being introduced.
The conservative school embraces the 4 NHTSA Levels or 5 SAE levels of technology, and expects these levels to be a path of progress. Car companies are starting to sell “level 2” and working on “level 3” and declaring level 4 or 5 to be far in the future. Google is going directly to SAE level 4.
The two cultures do agree that the curve of deployment is not nearly-instant like a smartphone. It will take some time until robocars are a significant fraction of the cars on the road. What they disagree on is how quickly that has a big effect on society. In sessions I attended, the feeling that the early 2020s would see only a modest fraction of cars being self-driving meant to the conservatives that they would not have that much effect on the world.
In one session, it was asked how many people had cars with automatic cruise control (ACC.) Very few hands went up, and this is no surprise — the uptake of ACC is quite low, and almost all of it is part of a “technology package” on the cars that offer it. This led people to believe that if ACC, now over a decade old, could barely get deployed, we should not expect rapid deployment of more complete self-driving. And this may indeed be a warning for those selling super-cruise style products which combine ACC and lanekeeping under driver supervision, which is the level 2 most car companies are working on.
To counter this, I asked a room how many had ridden in Uber or its competitors. Almost every hand went up this time — again no surprise. In spite of the fact that Uber’s cars represent an insignificant fraction of the deployed car fleet. In the aggressive view, robocars are more a service than a product, and as we can see, a robocar-like service can start affecting everybody with very low deployment and only a limited service area.
This dichotomy is somewhat reflected in the difference between SAE’s Level 4 and NHTSA’s. SAE Level 4 means full driving (including unmanned) but in a limited service area or under other limited parameters. This is what Google has said they will make, this is what you see planned for services in campuses and retirement communities. This is where it begins, and grows one region at a time. NHTSA’s levels falsely convey the idea that you slowly move to fully automated mode and immediately do it over a wide service area. Real cars will vary as to what level of supervision they need (the levels) over different times, streets and speeds, existing at all the levels at different times.
Follow the conservative model and you can say that society will not see much change until 2030 — some even talk about 2040. I believe that is an error.
Another correlated difference of opinion lies around infrastructure. Those in the aggressive computer-based camp wish to avoid the need to change the physical infrastructure. Instead of making the roads smart, make the individual cars smart. The more automotive camp has also often spoken of physical changes as being more important, and also believes there is strong value in putting digital “vehicle to vehicle” radios in even non-robocars. The computer camp is much more fond of “virtual infrastructure” like the detailed ultra-maps used by Google and many other projects.
It would be unfair to claim that the two schools are fully stratified. There are researchers who bridge the camps. There are people who see both sides very well. There are “computer” folks working at car companies, and car industry folks on the aggressive teams.
The two approaches will also clash when it comes to deciding how to measure the safety of the products and how they should be regulated, which will be a much larger battle. More on that later.
Submitted by brad on Mon, 2014-07-14 13:59.
It’s a big week for Robocar conferences.
In Berkeley, yesterday I attended and spoke at the “Robotics: Science and Systems” conference which had a workshop on autonomous vehicles. That runs to Wednesday, but overlapping and near SF Airport is the Automated Vehicles Symposium — a merger of the TRB (Transportation Research Board) and AUVSI conferences on the same topic. 500 are expected to attend.
Yesterday’s workshop was pretty good, with even a bit of controversy.
- Ed Olson on more of the lessons from aviation on handoff between automation and manual operation. This keeps coming up a a real barrier to some of the vehicle designs that have humans share the chores with the system.
- Jesse Levinson of Stanford’s team showed some very impressive work in automatic calibration of sensors, and even fusion of LIDAR and camera data, aligning them in real time in spite of movement and latency. This work will make sensors faster, more reliable and make fusion accurate enough to improve perception.
- David Hall, who runs Velodyne, spoke on the history of their sensors, and his plans for more. He repeated his prediction that in large quantities his sensor could cost only $300. (I’m a bit skeptical of that, but it could cost much, much less than it does today.) David made the surprising statement that he thinks we should make dedicated roads for the vehicles. (Surprising not just because I disagree, but because you could even get by without much LIDAR on such roads.)
- Marco Panove of Stanford showed research they did on Taxi models from New York and Singapore. The economics look very good. Dan Fagnant also presented related research assuming an on-demand semi shared system with pickup stations in every TAZ. It showed minimal vacant miles but also minimal successful rideshare. The former makes sense when it’s TAZ to TAZ (TAZs are around a square mile) but I would have thought there would be more rideshare. The conclusion is that VMT go up due to empty miles, but that rideshare can partially compensate, though not as much as some might hope.
- Ken Laberteaux of Toyota showed his research on the changing demographics of driving and suburbs. Conclusion: We are not moving back into the city, suburbanization is continuing. Finding good schools continues to drive people out unless they can afford private school are are childless.
The event had a 3-hour lunch break, where most went to watch some sporting event from Brazil. The Germans at the conference came back happier.
Some good technical talks presented worthwhile research
- Sheng Zhao and a team from UC Riverside showed a method to get cm accuracy in position and even in pose (orientation) from cheap GPS receivers, by using improved math on phase-matching GPS. This could also be combined with cheap IMUs. Most projects today use very expensive IMUs and GPSs, not the cheap ones you find in your cell phone. This work may lead to being able to get reliable data from low cost parts.
- Matthew Cornick and a team from Lincoln Lab at MIT showed very interesting work on using ground penetrating radar to localize. With GPR, you get a map of what’s below the road — you see rocks and material patterns down several feet. These vary enough, like the cracks and lines on a road, and so you can map them, and then find your position in that map — even if the road is covered in snow. While the radar units are today bulky, this offers the potential for operations in snow.
- A team from Toyota showed new algorithms to speed up the creation of the super-detailed maps needed for robocars. Their algorithms are good at figuring out how many lanes there are and when they start and stop. This could make it much cheaper to build the ultramaps needed in an automatic way, with less human supervision.
The legal and policy sessions got more heated.
- Bryant Walker Smith laid out some new proposals for how to regulate and govern torts about the vehicles.
- Eric Feron of Georgia Tech made proposals for how to do full software verification. Today formally proving and analysing code for correctness takes 0.6 hours per line of code — it’s not practical for the 50 million line (or more) software systems in cars today. Jonathan argues it can be made cheaper, and should be done. Note that fully half the cost of developing the 787 aircraft was software verification!
The final session, on policy included:
- Jane Lappin on how DoT is promoting research.
- Steve Shladover on how we’re all way to optimistic on timelines, and that coming up with tests to demonstrate superior safety to humans is very far away, since humans run 65,000 hours between injury accidents.
- Myself on why regulation should keep a light touch, and we should not worry too much about the Trolley Problem — which came up a couple of times.
- Raj Rajkumar of CMU on the success they have had showing the CMU/GM car to members of congress.
Now on to the AVS tomorrow.
Submitted by brad on Sat, 2014-07-12 11:29.
In the last few months, I have found myself asked many times about a concept for solar roadways. Folks from Idaho proposing them have gotten a lot of attention with FHWA funding, a successful crowdfunding and even an appearance at Solve for X. Their plan is hexagonal modules with strong glass, with panels and electronics underneath, LED lights, heating elements for snow country and a buried conduit for power cables, data and water runoff. In addition, they hope for inductive charging plates for electric vehicles.
This idea has come up before, but since these folks built a small prototype, they generated tremendous attention. But they haven’t spoken at all about the cost, and that concerns me, because with all energy projects, the financial math is 99% of the issue. That’s true of infrastructure projects as well.
There are two concepts here. The first is, can you make a cost effective manufactured road panel? Roads are quite expensive today, but they are just asphalt gravel and other industrial materials whose cost is measured the range of $50 to $100 per ton. A chart from Florida suggests that basic rural asphalt roads cost about $9 per square foot, all-in, including labour and grading (it’s flat there) and about $4/square foot for milling and resurfacing. Roadway modules could be factory made (by robots) but still would require more labour to install, but I still think it is a very tall order for a manufactured surface to not cost a great deal more, even an order of magnitude more than plain road. Paved roads need maintenance, and that’s expensive. It is proposed that these panels would be cheaper to maintain as you just swap them out, but I am again skeptical of this math. Indeed, one of the major barriers to proposals for electric roads (which can charge cars) is that putting anything in the road makes it prohibitively more expensive to maintain.
I won’t say this is impossible — but it’s all about the math. We need to see math that would show that the modular manufactured pavement approach can compete. I’m happy for that math to include future technologies, like robot assembly and placement (though realize that we’ll probably see road construction with simpler materials also done by robots even sooner.) Let’s see the numbers, how cheap can it get?
All of this is without the solar panels inside (or the electronics.) Because the solar panels have their own math. The only synergy is this: If the modular roadway can be made so that it costs only a bit more than other approaches, it offers us “free land” to put the panels, and it’s connected land in long strips to run power wires.
How valuable is free land? Well, cropland in the USA costs an average of about 10 cents per square foot. 23 cents in California. 3 cents/square foot in the rural west. Much more, of course, in urban places. The land is not that important, so the other value comes from having a nice, manufactured place in which to put solar panels.
Today solar panels are still costly. They are just getting down (primarily thanks to cheap Chinese money) to our grid price. Trends suggest they will get lower and become cost effective as a variable source of power. But until they get really, really cheap, you want to use them most efficiently.
To use solar panels at their best, you don’t want to lie them flat (except in the tropics) but rather you want to tilt them just just a bit below the angle of your latitude. Conventional wisdom also points them south, though it’s actually better for the grid and most people’s power demands if you point them south-west, losing a few percent of their output but getting more of it to match peak demand. Putting them flat costs you 20 to 30% of their output. (You can also have them motorized and gain even more, but it’s usually not cost-effective, and will become less cost-effective as panels get cheaper and motors don’t.)
To use solar panels at their best, you also want to put them where it’s very sunny. Finally you want to first put them where the local power comes from coal. When you have gotten rid of most of the coal, you can start putting them elsewhere. You can put panels in less sunny places which have power from hydro, nuclear or natural gas, but you’re really wasting your money. The ideal places are Arizona and New Mexico, with tons of sun and lots of coal. And lots of cheap, fairly low-value land.
To be fair, the biggest cost of the panels will soon be the hardware they are mounted in, along with the wires and electronics to connect them, and so perhaps these road modules could compete by being cheap hardware for that. But it seems not too likely.
In cities, rooftops provide another source of free land, much of it slanted about right and pointed in roughly the right direction. With lower cost than tearing up roads. But to be fair, right now one of the bigger cost elements is getting permits to do the construction and electrical work. Roads are far from bureaucracy-free, but at least it scales — you get permits for a big project all at once, not one house at a time. But we can solve that problem for houses if we really want to as well.
So my challenge to the solar roadway team is to show us the math. No, we don’t need to see what it cost to make your prototypes. I am sure they are very expensive, but that’s beside the point. I want to see a plan for how low the cost can go in theory, even assuming future technologies. And compare that to how low the cost for the alternatives can go in theory. And then factor in how things don’t get to that theoretical point due to bureaucracy, unions and other practicalities. Compare panels in the road to panels by the side of the road, tilted and not being driven over. Look at what paved roads cost in practice to what they could cost in theory to get an idea of how close you can actually get, or come up with a really convincing reason why one approach is immune from the problems of another.
And if that math says yes, go at it. But if it doesn’t, focus on where the math tells you to go.
Submitted by brad on Sat, 2014-06-28 10:47.
Everybody knows about bitcoin, but fewer know what goes on under the hood. Bitcoin provides the world a trustable ledger for transactions without trusting any given party such as a bank or government. Everybody can agree with what’s in the ledger and what order it was put there, and that makes it possible to write transfers of title to property — in particular the virtual property called bitcoins — into the ledger and thus have a money system.
Satoshi’s great invention was a way to build this trust in a decentralized way. Because there are rewards, many people would like to be the next person to write a block of transactions to the ledger. The Bitcoin system assures that the next person to do it is chosen at random. Because the winner is chosen at random from a large pool, it becomes very difficult to corrupt the ledger. You would need 6 people, chosen at random from a large group, to all be part of your conspiracy. That’s next to impossible unless your conspiracy is so large that half the participants are in it.
How do you win this lottery to be the next randomly chosen ledger author? You need to burn computer time working on a math problem. The more computer time you burn, the more likely it is you will hit the answer. The first person to hit the answer is the next winner. This is known as “proof of work.” Technically, it isn’t proof of work, because you can, in theory, hit the answer on your first attempt, and be the winner with no work at all, but in practice, and in aggregate, this won’t happen. In effect, it’s “proof of luck,” but the more computing you throw at the problem, the more chances of winning you have. Luck is, after all, an imaginary construct.
Because those who win are rewarded with freshly minted “mined” bitcoins and transaction fees, people are ready to burn expensive computer time to make it happen. And in turn, they assure the randomness and thus keep the system going and make it trustable.
Very smart, but also very wasteful. All this computer time is burned to no other purpose. It does no useful work — and there is debate about whether it inherently can’t do useful work — and so a lot of money is spent on these lottery tickets. At first, existing computers were used, and the main cost was electricity. Over time, special purpose computers (dedicated processors or ASICs) became the only effective tools for the mining problem, and now the cost of these special processors is the main cost, and electricity the secondary one.
Money doesn’t grow on trees or in ASIC farms. The cost of mining is carried by the system. Miners get coins and will eventually sell them, wanting fiat dollars or goods and affecting the price. Markets, being what they are, over time bring closer and closer the cost of being a bitcoin miner and the reward. If the reward gets too much above the cost, people will invest in mining equipment until it normalizes. The miners get real, but not extravagant profits. (Early miners got extravagant profits not because of mining but because of the appreciation of their coins.)
What this means is that the cost of operating Bitcoin is mostly going to the companies selling ASICs, and to a lesser extent the power companies. Bitcoin has made a funnel of money — about $2M a day — that mostly goes to people making chips that do absolutely nothing and fuel is burned to calculate nothing. Yes, the miners are providing the backbone of Bitcoin, which I am not calling nothing, but they could do this with any fair, non-centralized lottery whether it burned CPU or not. If we can think of one.
(I will note that some point out that the existing fiat money system also comes with a high cost, in printing and minting and management. However, this is not a makework cost, and even if Bitcoin is already more efficient doesn’t mean there should not be effort to make it even better.)
Naturally, many people have been bothered by this for various reasons. A large fraction of the “alt” coins differ from Bitcoin primarily in the mining system. The first round of coins, such as Litecoin and Dogecoin, use a proof-of-work system which was much more difficult to solve with an ASIC. The theory was that this would make mining more democratic — people could do it with their own computers, buying off-the-shelf equipment. This has run into several major problems:
- Even if you did it with your own computer, you tended to need to dedicate that computer to mining in the end if you wanted to compete
- Because people already owned hardware, electricity became a much bigger cost component, and that waste of energy is even more troublesome than ASIC buying
- Over time, mining for these coins moved to high-end GPU cards. This, in turn caused mining to be the main driver of demand for these GPUs, drying up the supply and jacking up the prices. In effect, the high end GPU cards became like the ASICs — specialized hardware being bought just for mining.
- In 2014, vendors began advertising ASICs for these “ASIC proof” algorithms.
- When mining can be done on ordinary computers, it creates a strong incentive for thieves to steal computer time from insecure computers (ie. all computers) in order to mine. Several instances of this have already become famous.
The last point is challenging. It’s almost impossible to fix. If mining can be done on ordinary computers, then they will get botted. In this case a thief will even mine at a rate that can’t pay for the electricity, because the thief is stealing your electricity too. read more »
Submitted by brad on Tue, 2014-06-24 16:25.
Five years ago, I posted a rant about the excess of customer service surveys we’re all being exposed to. You can’t do any transaction these days, it seems, without being asked to do a survey on how you liked it. We get so many surveys that we now just reject these requests unless we have some particular problem we want to complain about — in other words, we’re back to what we had with self-selected complaints. The value of surveys is now largely destroyed, and perversely, as the response rates drop and the utility diminishes, that just pushes some companies to push even harder on getting feedback, creating a death spiral.
A great example of this death spiral came a few weeks ago when I rode in an Uber and the driver had a number of problems. So this time I filled out the form to rate the driver and leave comments. Uber’s service department is diligent, and actually read it, and wrote me back to ask for more details and suggestions, which I gave.
That was followed up with:
Hi Brad Templeton,
We’d love to hear what you think of our customer service. It will only take a second, we promise. This feedback will allow us to make sure you always receive the best possible customer service experience in future.
If you were satisfied in how we handled your query, simply click this link.
If you weren’t satisfied in how we handled your ticket, simply click this link.
A survey on my satisfaction with the survey process! Ok, to give Uber some kudos, I will note:
- They really did try to make this one simple, just click a link. Though one wonders, had I clicked I was unsatisfied, would there have been more inquiry? Of course I was unsatisfied — because they sent yet another survey. The service was actually fine.
- At least they addressed me as “Hi Brad Templeton.” That’s way better than “Dear Brad” like the computer sending the message pretending it’s on a first-name basis with me. Though the correct salutation should be “Dear Customer” to let me know that it is not a personally written message for me. The ability to fill in people’s names in form letters stopped being impressive or looking personal in the 1970s.
This survey-on-a-survey is nice and short, but many of the surveys I get are astoundingly long. They must be designed, one imagines, to make sure nobody who values their time ever fully responds.
Why does this happen? Because we’ve become so thrilled at the ability to get high-volume feedback from customers that people feel it is a primary job function to get that feedback. If that’s your job, then you focus on measuring everything you can, without thinking about how the measurement (and over-measurement) affects the market, the customers and the very things you are try to measure. Heisenberg could teach these folks a lesson.
To work, surveys must be done on a small sample of the population, chosen in a manner to eliminate bias. Once chosen, major efforts should be made to assure people who are chosen do complete the surveys, which means you have to be able to truthfully tell them they are part of a small sample. Problem is, nobody is going to believe that when your colleagues are sending a dozen other surveys a day. It’s like over-use of antibiotics. All the other doctors are over-prescribing and so they stop working for you, even if you’re good.
The only way to stop this is to bring the hammer down from above. People higher up, with a focus on the whole customer experience, must limit the feedback efforts, and marketing professionals need to be taught hard in school and continuing education just why there are only so many they can do.
Submitted by brad on Tue, 2014-06-24 09:45.
Some recent press and talks:
Earlier in June I sat down with “Big Think” for an interview they have titled “Robocars 101” explaining some of the issues around the cars.
I also did a short interview on NPR’s “All Things Considered” not long after Google’s new car was announced. What you might find interesting is how I did it. I was at a friend’s house in Copenhagen and went into a quiet room where they called me on my cell phone. However, I also started a simple audio recorder app on my phone. When we were done, I shared the mp3 of a better sample from the same microphone with them, which they mixed in.
As a result, the interview sounds almost like it was done in-studio instead of over an international cell phone call.
Videos of my talks at Next Berlin at at Dutch Media Future Week 2014 are also up. And a shortened talk at Ontario Centers for Excellence Discovery 2014 in Toronto May 12. There we had the Governor General of Canada as our opening act. :-) That’s just 3 of the 11 events I was at on that trip.
Completely off the Robocar track is a short interview with CNBC where I advise people to invest in Bitcoin related technology, not in bitcoins.
Submitted by brad on Sun, 2014-06-22 20:51.
So far it’s been big players like Google and car companies with plans in the self-driving space. Today, a small San Francisco start-up named Cruise, founded by Kyle Vogt (a founder of the web video site Justin.tv) announces their plans to make a retrofit kit that will adapt existing cars to do basic highway cruise, which is to say, staying in a lane and keeping pace behind other cars while under a driver’s supervision.
I’ve been following Cruise since its inception. This offering has many similarities to the plans of major car companies, but there are a few key differences:
- This is a startup, which can be more nimble than the large companies, and having no reputation to risk, can be bolder.
- They plan to make this as a retrofit kit for a moderate set of existing cars, rather than custom designing it to one car.
They’re so dedicated to the retrofit idea that the Audi A4 they are initially modifying does not even have drive-by-wire brakes like the commonly used hybrid cars. Their kit puts sensors on the roof, and puts a physical actuator on the brake and another physical actuator on the steering wheel — they don’t make use of the car’s own steering motor. They want a kit that can be applied to almost any car the market tells them to target.
They won’t do every car, though. All vendors have a strong incentive to only support cars they have given some solid testing to, so most plans don’t involve retrofit at all, and of course Google has now announced their plans to design a car from scratch. Early adopters may be keen on retrofit.
I rode in the car last week during a demo at Alemeda air station, a runway familiar to viewers of Mythbusters. There they set up a course of small orange cones, which are much easier to see than ordinary lane markings, so it’s hard to judge how well the car does on lane markings. It still has rough edges, to be sure, but they don’t plan to sell until next year. In the trial, due to insurance rules, it kept under 40mph, though it handled that speed fine, though drifted a bit in wider parts of the “lane.”
On top is an aerodynamic case around a sensor pack which is based on stereo cameras and radar from Delphi. Inside is just a single button in the center arm console to enable and disable cruise mode. You take the car to the lane and push the button.
All stuff we’ve seen before, and not as far along, but the one key difference — being a nimble startup — may make all the difference. Only early adopters will pay the $10,000 for a product where you must (at least for now) still watch the road, but that may be all that is needed.
Submitted by brad on Sun, 2014-06-22 11:30.
On my recent wanderings in Europe, I became quite enamoured by Google’s
latest revision of transit directions. Google has had transit directions for
some time, but they have recently improved them, and linked them in more cities
to live data about where transit vehicles actually are.
The result not a mere incremental improvement, it’s a game-changing increase
in the utility of decent transit. In cities like Oslo and London, the tool
gives the user the ability to move with transit better than a native. In the
past, using transit, especially buses, as a visitor has always been so frustrating
that most visitors simply don’t use it, in spite of the much lower cost compared
to taxis. Transit, especially when used by an unfamiliar visitor, is slow and
complex, with long waits, missed connection and confusion about which bus
or line to take during shorter connections, as well as how to pay.
Not so any more. With a superhuman ability, your phone directs you to transit stops
you might not figure out from a map, where the right bus usually appears quite quickly.
Transfers are chosen to be quick as well, and directions are given as to which direction to
go, naming the final destination as transit signs often do, rather than the compass direction. It’s optimized by where the vehicles actually are and predicted to be, and this
will presumably get even better.
By making transit “just work” it becomes much more useful, and gives us a taste of the
robocar taxi world. That world is even easier, of course — door to door with no
connections and no need for you to even follow directions. But while Uber also shows us
that world well in user experience, Uber is expensive, as are cabs, while transit is closer
in cost to the anticipated robocar cost of well below $1/mile.
It also helps to have transit systems with passes or contactless pay cards, to avoid the hassles of payment.
Why does this work so well? In the transit-heavy cities, it turns out there are often 2, 3 or even 4 ways to get to your destination via different transit lines and connections. The software is able to pick among them in a way even a native couldn’t, and one is often leaving soon, and it finds it for you.
In some cities, there is not live data, so it only routes based on schedules. This cuts
the utility greatly. From a user experience standpoint, it is often better to give people
a wait they expect than to do a better job but not give accurate expectations.
What’s clear now is that transit agencies should have done this a lot sooner. Back in the 1980s
a friend of mine built one of the first systems which tracked transit vehicles and gave
you a way to call to see when the bus would come, or in some cases signs on the bus stops.
Nice as those were they are nothing compared to this. There is not much in this technology
that could not have been built some time ago. In fact, it could have been built even
before the smartphone, with people calling in by voice and saying, “I am at the corner of X and
Y and I need to get to Z” with a human helper. The cost would have actually been worth it
because by making the transit more useful it gets more riders.
That might be too expensive, but all this needed was the smartphone with GPS and a
data connection, and it is good that it has come.
In spite of this praise, there is still much to do.
- Routing is very time dependent. Ask at 1:00 and you can get a very different answer than you get asking at 1:02. And a different one at 1:04. The product needs a live aspect that updates as you walk and time passes.
- The system never figures out you are already on the bus, and so always wants to route you as though you were standing on the road. Often you want to change plans or re-look up options once you are on the vehicle, and in addition, you may want to do other things on the map.
- Due to how rapidly things change, the system also needs to display when multiple options are equivalent. For example, it might say, “Go to the train platform and take the B train northbound.” Then due to how things have change, you see a C train show up — do you get on it? Instead, it should say, “Take a B, C or E train going north towards X, Y or Z, but B should come first.”
- For extra credit, this should get smarter and combine with other modes. For example, many cities have bikeshare programs that let you ride a bike from one depot to another. If the system knew about those it could offer you very interesting routings combining bikes and transit. Or if you have your own bike and transit lines allow it on, you could use that.
- Likewise, you could combine transit with cabs, getting a convenient route with low walking but with much lower cab expense.
- Finally, you could also integrate with one-way car share programs like car2go or DriveNow, allowing a trip to mix transit, car, bike and walking for smooth movement.
- Better integration with traffic is needed. If the buses are stuck in traffic, it’s time to tell you to take another method (even cycling or walking) if time is your main constraint.
- Indoor mapping is needed in stations, particularly underground ones. Transit agencies should have beacons in the stations or on the tracks so phones can figure out where they are when GPS is not around. Buses could also have beacons to tell you if you got on the right one.
- The systems should offer an alert when you are approaching your stop. Beacons could help here too. For a while the GPS map has allowed the unfamiliar transit rider to know when to get off, but this can make it even better.
- This is actually a decent application for wearables and things like Google glass, or just a bluetooth earpiece talking in your ear, watching you move through the city and the stations and telling you which way to go, and even telling you when you need to rush or relax.
- In some cities going onto the subway means loss of signal. There, storing the live model for relevant lines in a cache would let the phone still come up with pretty good estimates when offline for a few minutes.
A later stage product might let you specify a destination and a time, and then it will buzz you when it’s time to start walking, and guide you there, through a path that might include walking, bike rides, transit lines and even carshare or short cab rides for a fast, cheap trip with minimal waiting, even when the transit isn’t all that good.