The future of computer-driven cars and deliverbots
Robocar news continues after CES with announcements from the Detroit Auto Show (and a tiny amount from the TRB meeting.)
Google doesn't talk a lot about their car, so address by Chris Urmson at the Detroit Auto Show generated a lot of press. Notable statements from Chris included:
Day 3 at CES started with a visit to BMW's demo. They were mostly test driving new cars like the i3 and M series cars, but for a demo, they made the i3 deliver itself along a planned corridor. It was a mostly stock i3 electric car with ultrasonic sensors -- and the traffic jam assist disabled. When one test driver dropped off the car, they scanned it, and then a BMW staffer at the other end of a walled course used a watch interface to summon that car.
After a short Day 1 at CES a more full day was full of the usual equipment -- cameras, TVs, audio and the like and visits to several car booths.
I've expanded my gallery of notable things with captions with cars and other technology.
A reasonable volume of robocar related stuff here at CES. I just had a few hours today, and went to see the much touted Mercedes F015 "Luxury in Motion." This is a concept and not a planned vehicle, but it draws together a variety of ideas -- most of which we've seen before -- with some new explorations.
Yesterday's note on Here's maps brought up the question of the wisdom of map-based driving. While I addressed this a bit earlier let me add a bit more detail.
I see new articles on robocars in the press every day now, though most don't say a lot new. Here, however, are some of the recent meaningful stories from the last month or two while I've been on the road. There are other sites, like the LinkedIn self-driving car group and others, if you want to see all the stories.
Uber is spreading fast, and running into protests from the industries it threatens, and in many places, the law has responded and banned, fined or restricted the service. I'm curious what its battles might teach us about the future battles of robocars.
Taxi service has a history of very heavy regulation, including government control of fares, and quota/monopolies on the number of cabs. Often these regulations apply mostly to "official taxis" which are the only vehicles allowed to pick up somebody hailing a cab on the street, but they can also apply to "car services" which you phone for a pick-up. In addition, there's lots of regulation at airports, including requirements to pay extra fees or get a special licence to pick people up, or even drop them off at the airport.
The heavy regulation had a few justifications:
Most of these needs are eliminated when you summon from an app on your phone. You can choose from several competing companies, and even among their drivers, with no market failure. Cabs don't cruise looking for fares so they won't cause much congestion. Drivers and companies can have reputations and safety records that you can look up, as well as safety certifications. The only remaining public interest is the question of a living wage.
Taxi regulations sometimes get stranger. In New York (the world's #1 taxi city) you must have one of the 12,000 "medallions" to operate a taxi. These medallions over time grew to cost well north of $1 million each, and were owned by cab companies and rich investors. Ordinary cabbies just rented the medallions by the hour. To avoid this, San Francisco made rules insisting a large fraction of the cabs be owned by their drivers, and that no contractual relationship could exist between the driver and any taxi company.
This created the situation which led to Uber. In San Francisco, the "no contract" rule meant if you phoned a dispatcher for a cab, they had no legal power to make it happen. They could just pass along your desire to the cabbie. If the driver saw somebody else with their arm up on the way to get you, well, a bird in the hand is worth two in the bush, and 50% of the time you called for a cab, nobody showed up!
Uber came into that situation using limos, and if you summoned one you were sure to get one, even if it was more expensive than a cab. Today, that's only part of the value around the world but crazy regulations prompted its birth.
I'm going to call all these services (Uber, Lyft, Sidecar and to some extent Hail-O) "Online Ride" services.
When I talk about robocars, I often get quite opposite reactions:
I predict neither extreme will be true. I predict the market will offer all options to the public, and several options will be very popular. I am not even sure which will be the most popular.
In addition, people will mix these models. Families that own 2 or more cars will switch to owning fewer cars and hiring for extra use and special uses. For example, if you own a 2 person car, you would summon a larger taxi when 3 or more are together. In particular, parents may find that they don't want to buy a car for their teen-ager, but would rather just subsidize their robotaxi travel. Parents will want to do this and get logs of where their children travel, and of course teens will resist that, causing a conflict.
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 against it.
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:
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.
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.
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.
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.
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.
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.
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.
I've been musing more on the future of the city under the robocar, and many visions suggest we'll have more sprawl. Earlier I have written visions of Robocar Oriented Development and outlined all the factors urban planners should look at.
In the essay linked below, I introduce the concept of a medium density urban neighbourhood that acts like a higher density space thanks to robocars functioning like the elevators in the high-rises of high density development.
A whole raft of recent robocar news.
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.
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.
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.
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.
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.
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.
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.
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.
Yesterday saw:
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.
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.