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 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 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 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.
Submitted by brad on Mon, 2014-06-09 19:48.
I’m in the home stretch of a long international trip — photos to follow — but I speak tomorrow at Lincoln Center on how computers (and robocars) will change the worlds of finance. In the meantime, Google’s announcement last month has driven a lot of news in the Robocar space worthy of reporting.
On the lighter side, this video from the Conan O’Brien show highlights the issues around people’s deep fear of being injured by machines. While the video is having fun, this is a real issue that will dominate the news when the first accidents and injuries happen. I cover that in detail in my article about accidents but the debate will be a major one.
Nissan announced last year that it would sell cars in 2020. Now that Tesla has said 2016, Google has said civilians will be in their small car within a year and Volvo has said the same will happen in Sweden by 2017, Nissan CEO Carlos Ghosn has said they might do it 2 years earlier.
As various locations rush to put in robocar laws, in Europe they are finally getting around to modifying the Vienna convention treaty, which required a human driver. However, the new modifications, driven by car companies, still call for a steering wheel that a driver can use to take over (as do some of the US state laws.) These preclude Google’s new design, but perhaps with a bit of advance warning, this can be fixed. Otherwise, changing it again will be harder. Perhaps the car companies — none of whom have talked about anything like Google’s car with no controls — will be happy with that.
The urban test course at the University of Michigan, announced not very long ago, is almost set to open — things are moving fast, as they will need to if Michigan is to stay in the race. Google’s new prototype, by the way, is built in Michigan. Google has not said who but common speculation names not a major car company, but one of their big suppliers.
The Ernst & Young auto research lab (in Detroit) issued a very Detroit style forecast for autonomous vehicles which said their widespread use was 2 decades away. Not too surprising for such a group. Consultants are notoriously terrible at predictions for exponential technology. Their bad smartphone predictions are legendary (and now erased, of course.) A different study predicts an $87 billion market — but the real number is much larger than that.
This article where top car designers critique Google’s car illustrates my point from last week how people with car company experience are inclined to just not get it. But at the same time some of the automotive press do get it.
Submitted by brad on Sun, 2014-06-01 05:15.
It’s not too surprising that the release of images of Google’s prototype robocar have gotten comments like this:
Revolutionary Tech in a Remarkably Lame Package from Wired
A Joy Ride in Google’s Clown Car says Re/Code
I’ve also seen comparisons to the Segway, and declarations that limited to 25 mph, this vehicle won’t get much adoption or affect the world much.
Google’s own video starts with a senior expressing that it’s “cute.”
I was not involved in the specifics of design of this vehicle, though I pushed hard as I could for something in this direction. Here’s why I think it’s the right decision.
First of all, this is a prototype. Only 100 of this design will be made, and there will be more iterations. Google is all about studying, learning and doing it again, and they can afford to. They want to know what people think of this, but are not scared if they underestimate it at first.
Secondly, this is what is known as a “Disruptive Technology.” Disruptive technologies, as described in the Silicon Valley bible “The Innovators Dilemma” are technologies that seem crazy and inferior at first. They meet a new need, not well understood by the incumbent big companies. Those big companies don’t see it as a threat — until years later, they are closing their doors. Every time a disruptive technology takes over, very few of the established players make it through to the other side. This does not guarantee that Google will dominate or crush those companies, or that everything that looks silly eventually wins. But it is a well established pattern.
This vehicle does not look threatening — not to people on the street, and not to existing car companies and pundits who don’t get it. Oh, there are many people inside those car companies who do get it, but the companies are incapable of getting it in their bones. Even when their CEOs get it, they can’t steer the company 90 degrees — there are too many entrenched forces in any large company. The rare exception are founder-led companies (like Google and Facebook and formerly Apple and Microsoft) where if the founder gets it, he or she can force the company to get it.
Even large companies who read this blog post and understand it still won’t get it, not most of the time. I’ve talked to executives from big car companies. They have a century of being car companies, and knowing what the means. Google, Tesla and the coming upstarts don’t.
One reason I will eventually move away from my chosen name for the technology — robocar — along with the other popular names like “self-driving car” is that this future vehicle is not a car, not as we know it today. It is no more a “driverless car” than a modern automobile is a horseless carriage. 100 years ago, the only way they could think of the car was to notice that there was no horse. Today, all many people notice about robocars is that no human is driving. This is the thing that comes after the car.
Some people expected the car to look more radical. Something like the Zoox or ATMBL by Mike and Maaike (who now work in a different part of Google.) Cars like those will come some day, but are not the way you learn. You start simple, and non threatening, and safe. And you start expensive — the Google prototype still has the very expensive Velodyne LIDAR on it, but trust me, very soon LIDAR is going to get a lot less expensive.
The low speed is an artifact of many things. You want to start safe, so you limit where you go and how fast. In addition, US law has a special exception from most regulations for electric vehicles that can’t go more than 25mph and stick to back roads. Some may think that’s not very useful (turns out they are wrong, it has a lot of useful applications) but it’s also a great way to start. Electric vehicles have another big advantage in this area. Because you can reverse electric motors, they can work as secondary brakes in the event of failure of the main brake system, and can even be secondary steering in case of failure of the steering system at certain speeds. (Google has also said that they have two steering motors in order to handle the risk of failure of one steering motor.) Electric vehicles are not long-range enough to work as taxis in a large area, but they can handle smaller areas just fine.
If you work in the auto industry, and you looked at this car and saw a clown car, that’s a sign you should be afraid.
Submitted by brad on Wed, 2014-05-28 00:40.
In what is the biggest announcement since Google first revealed their car project, it has announced that they are building their own car, a small low-speed urban vehicle for two with no steering wheel, throttle or brakes. It will act as a true robocar, delivering itself and taking people where they want to go with a simple interface. The car is currently limited to 25mph, and has special pedestrian protection features to make it even safer. (I should note that as a consultant to that team, I helped push the project in this direction.)
This is very different from all the offerings being discussed by the various car companies, and is most similar to the Navia which went on sale earlier this year. The Navia is meant as a shuttle, and up to 12 people stand up in it while it moves on private campus roads. It only goes 20 km/h rather than the 40 km/h of Google’s new car. Google plans to operate their car on public roads, and will have non-employees in test prototype vehicles “very soon.”
This is a watershed moment and an expression of the idea that the robocar is not a car but the thing that comes after the car, as the car came after the horse. Google’s car is disruptive, it seems small and silly looking and limited if you look at it from the perspective of existing car makers. That’s because that’s how the future often looks.
I have a lot to say about what this car means, but at the same time, very little because I have been saying it since 2007. One notable feature (which I was among those pushing for inside) is a soft cushion bumper and windshield. Clearly the goal is always to have the car never hit anybody, but it can still happen because systems aren’t perfect and sometimes people appear in front of cars quickly making it physically impossible to stop. In this situation, cars should work to protect pedestrians and cyclists. Volvo and Autoliv have an airbag that inflates on the windshield bars, which are the thing that most often kills a cyclist. Of the 1.2 million who are killed in car accidents each year, close to 500,000 are pedestrians, mostly in the lower income nations. These are first steps in protecting them as well as the occupants of the car.
The car has 2 seats (side-by-side) and very few controls. It is a prototype, being made at first in small quantities for testing.
More details, and other videos, including a one of Chris Urmson giving more details, can be found at the new Google Plus page for the car. Also of interest is this interview with Chris.
I’m in Milan right now about to talk to Google’s customers about the car — somewhat ironic — after 4 weeks on the road all over Europe. 2 more weeks to go! I will be in Copenhagen, Amsterdam, London and NYC in the coming weeks, after having been in NYC, Berlin, Krakow, Toronto, Amsterdam, Copenhagen, Oslo, the fjords and Milan. In New York, come see me at Singularity U’s Exponential Finance conference June 10-11.
Submitted by brad on Mon, 2014-04-28 12:44.
News from Google’s project is rare, but today on the Google blog they described new achievements in urban driving and reported a number of 700,000 miles. The car has been undergoing extensive testing in urban situations, and Google let an Atlantic reporter get a demo of the urban driving which is worth a read.
You will want to check out the new video demo of urban operations:
While Google speakers have been saying for a while that their goal is a full-auto car that does more than the highway, this release shows the dedication already underway towards that goal. It is the correct goal, because this is the path to a vehicle that can operate vacant, and deliver, store and refuel itself.
Much of the early history of development has been on the highway. Most car company projects have a focus on the highway or traffic jam situations. Google’s cars were, in years past, primarily seen on the highways. In spite of the speed, highway driving is actually a much easier task. The traffic is predictable, and the oncoming traffic is physically separated. There are no cyclists, no pedestrians, no traffic lights, no stop signs. The scariest things are on-ramps and construction zones. At low speed the highway could even be considered a largely solved problem by now.
Highway driving accounts for just over half of our miles, but of course not our hours. A full-auto car on the highway delivers two primary values: Fewer accidents (when delivered) and giving productive time back to the highway commuter and long distance traveller. This time is of no small value, of course. But the big values to society as a whole come in the city, and so this is the right target. The “super-cruise” products which require supervision do not give back this time, and it is debatable if they give the safety. Their prime value is a more relaxing driving experience.
Google continues to lead its competitors by a large margin. (Disclaimer: They have been a consulting client of mine.) While Mercedes — which is probably the most advanced of the car companies — has done an urban driving test run, it is not even at the level that Google was doing in 2010. It is time for the car makers to get very afraid. Major disruption is coming to their industry. The past history of high-tech disruptions shows that very few of the incumbent leaders make it through to the other side. If I were one of the car makers who doesn’t even have a serious project on this, I would be very afraid right now.
Submitted by brad on Mon, 2014-04-21 13:24.
Many states and jurisdictions are rushing to write laws and regulations governing the testing and deployment of robocars. California is working on its new regulations right now. The first focus is on testing, which makes sense.
Unfortunately the California proposed regulations and many similar regulations contain a serious flaw:
The autonomous vehicle test driver is either in immediate physical control of the vehicle or is monitoring the vehicle’s operations and capable of taking over immediate physical control.
This is quite reasonable for testing vehicles based on modern cars, which all have steering wheels and brakes with physical connections to the steering and braking systems. But it presents a problem for testing delivery robots or deliverbots.
Delivery robots are world-changing. While they won’t and can’t carry people, they will change retailing, logistics, the supply chain, and even going to the airport in huge ways. By offering very quick delivery of every type of physical goods — less than 30 minutes — at a very low price (a few pennies a mile) and on the schedule of the recipient, they will disrupt the supply chain of everything. Others, including Amazon, are working on doing this by flying drone, but for delivery of heavier items and efficient delivery, the ground is the way to go.
While making fully unmanned vehicles is more challenging than ones supervised by their passenger, the delivery robot is a much easier problem than the self-delivering taxi for many reasons:
- It can’t kill its cargo, and thus needs no crumple zones, airbags or other passive internal safety.
- It still must not hurt people on the street, but its cargo is not impatient, and it can go more slowly to stay safer. It can also pull to the side frequently to let people pass if needed.
- It doesn’t have to travel the quickest route, and so it can limit itself to low-speed streets it knows are safer.
- It needs no windshield or wheel, and can be small, light and very inexpensive.
A typical deliverbot might look like little more than a suitcase sized box on 3 or 4 wheels. It would have sensors, of course, but little more inside than batteries and a small electric motor. It probably will be covered in padding or pre-inflated airbags, to assure it does the least damage possible if it does hit somebody or something. At a weight of under 100lbs, with a speed of only 25 km/h and balloon padding all around, it probably couldn’t kill you even if it hit you head on (though that would still hurt quite a bit.)
The point is that this is an easier problem, and so we might see development of it before we see full-on taxis for people.
But the regulations do not allow it to be tested. The smaller ones could not fit a human, and even if you could get a small human inside, they would not have the passive safety systems in place for that person — something you want even more in a test vehicle. They would need to add physical steering and braking systems which would not be present in the full drive-by-wire deployment vehicle.
Testing on real roads is vital for self-driving systems. Test tracks will only show you a tiny fraction of the problem.
One way to test the deliverbot would be to follow it in a chase car. The chase car would observe all operations, and have a redundant, reliable radio link to allow a person in the chase car to take direct control of any steering or brakes, bypassing the autonomous drive system. This would still be drive-by-wire(less) though, not physical control.
These regulations also affect testing of full drive-by-wire vehicles. Many hybrid and electric cars today are mostly drive-by-wire in ordinary operations, and the new Infiniti Q50 features the first steer-by-wire. However the Q50 has a clutch which, in the event of system failure, reconnects the steering column and the wheels physically, and the hybrids, even though they do DBW regenerative braking for the first part of the brake pedal, if you press all the way down you get a physical hydraulic connection to the brakes. A full DBW car, one without any steering wheel like the Induct Navia, can’t be tested on regular roads under these regulations. You could put a DBW steering wheel in the Navia for testing but it would not be physical.
Many interesting new designs must be DBW. Things like independent control of the wheels (as on the Nissan Pivo) and steering through differential electric motor torque can’t be done through physical control. We don’t want to ban testing of these vehicles.
Yes, teams can test regular cars and then move their systems down to the deliverbots. This bars the deliverbots from coming first, even though they are easier, and allows only the developers of passenger vehicles to get in the game.
So let’s modify these regulations to either exempt vehicles which can’t safely carry a person, or which are fully drive-by-wire, and just demand a highly reliable DBW system the safety driver can use.
Submitted by brad on Tue, 2014-04-08 22:35.
I read a lot of feeds, and there are now scores of stories about robocars every week. Almost every day a new publication gives a summary of things. Here, I want to focus on things that are truly new, rather than being comprehensive.
Mahindra “Rise” Prize
The large Indian company Mahindra has announced a $700,000 Rise prize for robocar development for India’s rather special driving challenges. Prizes have been a tremendous boost to robocar development and DARPA’s contests changed the landscape entirely. Yet after the urban challenge, DARPA declared their work was done and stopped, and in spite of various efforts to build a different prize at the X-Prize foundation, the right prize has never been clear. China has annual prizes and has done so for several years, but they get little coverage outside of China.
An Indian prize has merit because driving in India is very much different, and vastly more chaotic than most of the west. As such, western and east Asian companies are unlikely to spend a lot of effort trying to solve the special Indian problems first. It makes sense to spur Indian development, and of course there is no shortage of technical skill in India.
Many people imagine that India’s roads are so chaotic that a computer could never drive on them. There is great chaos, but it’s important to note that it’s slow chaos, not fast chaos. Being slow makes it much easier to be safe. Safety is the hard part of the problem. Figuring out just what is happening, playing subtle games of chicken — these are not trivial, but they can be solved, if the law allows it.
I say if the law allows it because Indians often pay little heed to the traffic law. A vehicle programmed to strictly obey the law will probably fail there without major changes. But the law might be rewritten to allow a robot to drive the way humans drive there, and be on an open footing. The main challenge is games of chicken. In the end, a robot will yield in a game of chicken and humans will know that and exploit it. If this makes it impossible for the robot to advance, it might be programmed to “yield without injury” in a game of chicken. This would mean randomly claiming territory from time to time, and if somebody else refuses to yield, letting them hit you, gently. The robot would use its knowledge of physics to keep the impact low enough speed to cause minor fender damage but not harm people. If at fault, the maker of the robot would have to pay, but this price in damage to property may be worthwhile if it makes the technology workable.
The reason it would make things workable is that once drivers understood that, at random, the robot will not yield (especially if it has the right-of-way) and you’re going to hit it. Yes, they might pay for the damage (if you had the right of way) but frankly that’s a big pain for most people to deal with. People might attempt insurance fraud and deliberately be hit, but they will be recorded in 3D, so they had better be sure they do it right, and don’t do it more than once.
Of course, the cars will have to yield to pedestrians, cylists and in India, cows. But so does everybody else. And if you just jump in front of a car to make it hit the brakes, it will be recording video of you, so smile.
New Vislab Car
I’ve written before about Vislab at the University of Parma. Vislab are champions of using computer vision to solve the driving problem, though their current vehicles also make use of LIDAR, and in fact they generally agree with the trade-offs I describe in my article contrasting LIDAR and cameras.
They have a new vehicle called DEEVA which features 20 cameras and 4 lasers. Like so many “not Google” projects, they have made a focus on embedding the sensors to make them not stand out from the vehicle. This continues to surprise me, because I have very high confidence that the first customers of robocars will be very keen that they not look like ordinary cars. They will want the car to stand out and tell everybody, “Hey, look, I have a robocar!” The shape of the Prius helped its sales, as well as its drag coefficient.
This is not to say there aren’t people who, when asked, will say they don’t want the car to look too strange, or who say, looking at various sensor-adorned cars, that these are clearly just lab efforts and not something coming soon to roads near you. But the real answer is neither ugly sensors nor hidden sensors, but distinctive sensors with a design flair.
More interesting is what they can do with all those cameras, and what performance levels they can reach.
I will also note that car uses QNX as its OS. QNX was created by friend I went to school with in Waterloo, and they’re now a unit of RIM/Blackberry (also created by classmates of mine.) Go UW!
Submitted by brad on Sat, 2014-03-15 15:09.
One sign of how interest is building is the large reaction to some recent concept prototypes for robocars, two of which were shown in physical form at the Geneva auto show.
The most attention came to the Swiss auto research company Ringspeed’s XchangE concept which they based on a Tesla. They including a steering wheel which could move from side to side (and more to the point, go to the middle, where it could be out of the way of the two front seats,) along with seats that could recline to sleeping positions or for watching a big-screen TV, and which could reverse for face-to-face seating.
Also attracting attention was the Link and Go, an electric shuttle. In this article it is shown on the floor with the face to face configuration.
This followed on buzz late last year over the announcement of Zoox and their Boz concept, which features a car that has no steering wheel, and is symmetrical front to back (so of course seating is face to face.) The Zoox model takes this down to the low level, with 4 independent wheel motors. I’ve met a few times with Zoox’s leader, Tim Kentley-Klay of Melbourne, and the graphics skills of he and his team, along with some dynamic vision, also generated great buzz.
All this buzz came even though none of these companies had anything to say about the self-driving technology itself, which remains 99% of the problem. And there have been a number of designers who have put out graphic concepts like these for many years, and many writers (your unhumble blogger included) who have written about them for years.
The Zoox design is fairly radical — a vehicle with no windshield and no steering wheel — it can never be manually driven and a full robocar. Depending on future technologies like cheap carbon fibre and cost-effective 3-D printing for medium volumes, it’s a more expensive vehicle that you could make, but there may be a certain logic to that. Tesla has shown us that there are many people who will happily pay a lot more to get a car that is unlike any other, and clearly the best. They will pay more than can be rationally justified.
Speaking of Tesla, a lot of the excitement around the Rinspeed concept was that it was based on a Tesla. That appears to have been a wise choice for Rinspeed as people got more excited about it than any other concept I’ve seen. The image of people reclining, watching a movie, brought home an image that has been said many times in print but not shown physically to the world in the same way.
It’s easy for me (and perhaps for many readers of this blog) to feel that these concepts are so obvious that everybody just gets them, but it’s clearly not true. This revolution is going to take many people by surprise.