The future of computer-driven cars and deliverbots
The NTSB (National Transportation Safety Board) has released a preliminary report on the fatal Tesla crash with the full report expected later this week. The report is much less favourable to autopilots than their earlier evaluation.
How will robocars fare in a disaster, like Harvey in Houston, Irma, or the tsunamis in Japan or Indonesia, or a big Earthquake, or a fire, or 9/11, or a war?
These are very complex questions, and certainly most teams developing cars have not spent a lot of time on solutions to them at present. Indeed, I expect that these will not be solved issues until after the first significant pilot projects are deployed, because as long as robocars are a small fraction of the car population, they will not have that much effect on how things go. Some people who have given up car ownership for robocars -- not that many in the early days -- will possibly find themselves hunting for transportation the way other people who don't own cars do today.
It's a different story when, perhaps a decade from now, we get significant numbers of people who don't own cars and rely on robocar transportation. That means people who don't have any cars, not the larger number of people who have dropped from 2 cars to 1 thanks to robocar services.
I addressed a few of these questions before regarding Tsunamis and Earthquakes.
A few key questions should be addressed:
Most of these issues revolve around fleets. Privately owned robocars will tend to have steering wheels and be usable as regular cars, and so only improve the situation. If they encounter unsafe roads, they will ask their passengers for guidance, or full driving. (However, in a few decades, their passengers may no longer be very capable at driving but the car will handle the hard parts and leave them just to provide video-game style directions.)
An immediately positive thing is the potential ability for private robocars to, once they have taken their owners to safety, drive back into the evacuation zone as temporary fleet cars, and fetch other people, starting with those selected by the car's owner, but also members of the public needing assistance. This should dramatically increase the ability of the car fleet to get people moved.
Nonetheless, it is often noted that in a robocar taxi world, there don't need to be nearly as many cars in a city as we have today. With ideal efficiency, there would be exactly enough seats to handle the annual peak, but few more. We might drop to just 1/4 of the cars, and we might also have many of them be only 1 or 2 seater cars. There will be far fewer SUVs, pickup trucks, minivans and other large cars, because we don't really need nearly as many as we have today.
For those in Silicon Valley, I will be giving a talk at the monthly autonomous vehicle enthusiast meetup. Some time ago I did my general talk, but this one will get into the meat on some of the big myths and issues. With luck we'll get some good debate going.
Almost all robocars use maps to drive. Not the basic maps you find in your phone navigation app, but more detailed maps that help them understand where they are on the road, and where they should go. These maps will include full details of all lane geometries, positions and meaning of all road signs and traffic signals, and also details like the texture of the road or the 3-D shape of objects around it. They may also include potholes, parking spaces and more.
The maps perform two functions. By holding a representation of the road texture or surrounding 3D objects, they let the car figure out exactly where it is on the map without much use of GPS. A car scans the world around it, and looks in the maps to find a location that matches that scan. GPS and other tools help it not have to search the whole world, making this quick and easy.
Google, for example, uses a 2D map of the texture of the road as seen by LIDAR. (The use of LIDAR means the image is the same night and day.) In this map you see the location of things like curbs and lane markers but also all the defects in those lane markers and the road surface itself. Every crack and repair is visible. Just as you, a human being, will know where you are by recognizing things around you, a robocar does the same thing.
Some providers measure things about the 3D world around them. By noting where poles, signs, trees, curbs, buildings and more are, you can also figure out where you are. Road texture is very accurate but fails if the road is covered with fresh snow. (3D objects also change shape in heavy snow.)
Once you find out where you are (the problem called "localization") you want a map to tell you where the lanes are so you can drive them. That's a more traditional computer map, though much more detailed than the typical navigation app map.
Some teams hope to get a car to drive without a map. That is possible for simpler tasks like following a road edge or a lane. There you just look for a generic idea of what lane markings or road edges should look like, find them and figure out what the lanes look like and how to stay in the one you want to drive in. This is a way to get a car up and running fast. It is what humans do, most of the time.
Most teams try to do more than driving without a map because software good enough to do that is also software good enough to make a map. To drive without a map you must understand the geometry of the road and where you are on it. You must understand even more, like what to do at intersections or off-ramps.
Creating maps is effectively the act of saying, "I will remember what previous cars to drive on this road learned about it, and make use of that the next time a car drives it."
Put this way it seems crazy not to build and use maps, even with the challenges listed below. Perhaps some day the technology will be so good that it can't be helped by remembering, but that is not this day.
There are many strong advantages of having the map:
One intermediate goal might be to have cars that can drive with only a navigation map, but use more detailed maps in "problem" areas. This is pretty similar, except in database size, with automatic map generation with human input only on the problem areas. If your non-map driving is trustworthy, such that it knows not to try problem areas, you could follow the lower cost approach of "don't map it until somebody's car pulled over because it could not handle an area."
There are two or three components of the maps people are building, in order to perform the functions above. At the most basic level is something not too far above the navigation maps found in phones. That's a vector map, except with lane level detail. Such maps know how many lanes there are, and usually what lanes connect to what lanes. For example, they will indicate that to turn right, you can use either of the right two lanes at some intersections.
Earlier I noted that Nidi Kalra of Rand spoke at the AVS about Rand's research suggesting that purely road testing robocars is an almost impossible task, because it would take hundreds of millions to a billion miles of driving to prove that a robocar is 10% better than human drivers.
(If the car is 10x better than humans, it doesn't take that long, but that's not where the first cars will be.)
This study has often been cited as saying that it's next to impossible to test robocars. The authors don't say that -- their claim is that road testing will not be enough, and will take too long to really work -- but commenters and press have taken it further to the belief that we'll never be able to test.
The mistake is that while it could take a billion miles to prove a vehicle is 10% safer than human drivers, that is not the goal. Rather, the goal is to decide that it's unlikely it is much worse than that number. It may seem like "better than X" and "not worse than X" are the same thing, but they are not. The difference is where you give the benefit of the doubt.
Consider how we deal with new drivers. We give them a very basic test and hand them a licence. We presume, because they are human teens, that they will have a safety record similar to other human teens. Such a record is worse than the level for experienced drivers, and in fact one could argue it's not at all safe enough, but we know of no way to turn people into experienced drivers without going through the risky phase.
If a human driver starts showing evidence of poor skills or judgments -- lots of tickets, and in particular multiple accidents, we pull their licence. It actually takes a really bad record for that to happen. By my calculations the average human takes around 20 years to have an accident that gets reported to insurance, and 40-50 years to have one that gets reported to police. (Most people never have an injury accident, and a large fraction never have any reported or claimed accident.)
Today's news is preliminary, but a U.S. house committee panel passed some new federal regulations which suggest sweeping change in the US regulatory approach to robocars.
I have recently managed to dig up some old documents from the earliest days of car regulation. Here is a report from NHTSA on the state of affairs near the turn of the 20th century.
In recent years, we've seen much excitement about the idea of carriages and coaches with the addition of "motors" which can propel the carriage without relying entirely on the normal use of horses or other beasts of burden. These "Horseless carriages," sometimes also known as "auto mobile" are generating major excitement, and prototypes have been generated by men such as Karl Benz and Armand Peugeot, along with the Duryea brothers, Ransom Olds and others in the the USA. The potential for these carriages has resulted in many safety questions and many have asked if and how NHTSA will regulate safety of these carriages when they are common.
Previously, NHTSA released a set of 4, and later 5 levels to classify and lay out the future progression of this technology.
Level zero is just the existing rider on horseback.
Level one is the traditional horse drawn carriage or coach, as has been used for many years.
A level 2 carriage has a motor to assist the horses. The motor may do the work where the horses trot
along side, but at any time the horses may need to take over on short notice.
In a level 3 carriage, sometimes the horses will provide the power, but it is allowed to switch over entirely to the "motor," with the
horses stepping onto a platform or otherwise being raised to avoid working them. If the carriage approaches an area it can't handle, or the motor has problems,
the horses should be ready, with about 10-20 seconds notice, to step back on the ground and start pulling. In some systems the horse(s) can be in a hoist which can raise or lower them from the trail.
A Level 4 carriage is one which can be pulled entirely by a motor in certain types of terrain or types of weather -- an operating domain --
but may need a horse at other times. There is no need for a sudden switch to the horses, which should be pulled in a trailer so
they can be hitched up for travel outside the operating domain.
The recently added fifth level is much further in the future, and involves a "horseless" carriage that can be auto mobile in all situations, with no need for any horse at all. (It should carry a horse for off-road use or to handle breakdowns, but this is voluntary.)
In San Francisco, I'm just back from the annual Automated Vehicle Symposium, co-hosted by the AUVSI (a commercial unmanned vehicle organization) and the Transportation Research Board, a government/academic research organization. It's an odd mix of business and research, but also the oldest self-driving car conference. I've been at every one, from the tiny one with perhaps 100-200 people to this one with 1,400 that fills a large ballroom.
Tuesday morning did not offer too many surprises. The first was an announcement by Toyota Research Institute of a $100M venture fund. Toyota committed $1B to this group a couple of years ago, but surprisingly Gil Pratt (who ran the DARPA Robotics Challenge for humanoid-like robots) has been somewhat a man of mixed views, with less optimistic forecasts.
Different about this VC fund will be the use of DARPA like "calls." The fund will declare, "Toyota would really like to see startups solving problem X" and then startups will apply, and a couple will be funded. It will be interesting to see how that pans out.
At CES, Nissan showed off their plan to have a remote control room to help robocars get out of sticky situations they can't understand like unusual construction zones or police directing traffic. Here, they showed it as further along and suggested it will go into operation soon.
This idea has been around for a while (Nissan based it on some NASA research) and at Starship, it has always been our plan for our delivery robots. Others are building such centers as well. The key question is how often robocars need to use the human assistance, and how you make sure that unmanned vehicles stay in regions where they can get a data connection through which to get help. As long as interventions are rare, the cost is quite reasonable for a larger fleet.
This answers the question that Rod Brooks (of Rethink Robotics and iRobot) recently asked, pondering how robocars will handle his street in Cambridge, where strange things like trucks blocking the road to do deliveries, are frequently found.
It's a pretty good bet that almost all our urban spaces will have data connectivity in the 2020s. If any street doesn't have solid data, and has frequent bizarre problems of any type, yet is really important for traversal by unmanned vehicles -- an unlikely trifecta -- it's quite reasonable for vehicle operators to install local connectivity (with wifi, for example) on that street if they can't wait for the mobile data companies to do it. Otherwise, don't go down such streets in empty cars unless you are doing a pickup/drop-off on the street.
Karl Iagenemma of nuTonomy told the story of moving their cars from Singapore, where driving is very regulated and done on the left, to Boston where it is chaotic and done on the right.
I've written a few times that perhaps the biggest unsolved problem in robocars is how to know we have made them safe enough. While most people think of that in terms of government certification, the truth is that the teams building the cars are very focused on this, and know more about it than any regulator, but they still don't know enough. The challenge is going to be convincing your board of directors that the car is safe enough to release, for if it is not, it could ruin the company that releases it, at least if it's a big company with a reputation.
While very few details have come out, Reuters reports that new proposed congressional bills on self-driving cars will reverse many of the provisions I critiqued in the NHTSA regulations last year.
Plans are underway to ask for a legal mandate to install radio communications devices in all new cars, starting around 2020. These radios would do "vehicle to vehicle" (v2v) and vehicle to infrastructure communication using a wifi-derived protocol called DSRC.
Waymo (Google) has announced a pilot project in Phoenix offering a full ride service, with daily use, in their new minivans. Members of the public can sign up -- the link is sure to be overwhelmed with applicants, but it has videos and more details -- and some families are already participating. There's also a Waymo Blog post. I was in Phoenix this morning as it turns out, but to tell real estate developers about robocars, not for this.
There are several things notable about Waymo's pilot:
There has been much speculation recently because of some departures from Apple's car team that they had given up. In fact, last week they applied for self-driving car test plates for California. I never thought they had left the game.
Luminar, a bay area startup, has revealed details on their new LIDAR. Unlike all other commercial offerings, this is a LIDAR using 1.5 micron infrared light. They hope to sell it for $1,000.
A new report from Navigant Research includes the chart shown below, ranking various teams on the race to robocar deployment. It's causing lots of press headlines about how Ford is the top company and companies like Google and Uber are far behind.
I elected not to buy the $3800 report, but based on the summary I believe their conclusions are ill founded to say the least.
The recently released national noise map makes it strikingly clear just how much air travel contributes to the noise pollution in our lives. In my previous discussion of flying cars I expressed the feeling that the noise of flying cars is one of their greatest challenges.
Recently we've seen a series of startups arise hoping to make robocars with just computer vision, along with radar. That includes recently unstealthed AutoX, the off-again, on-again efforts of comma.ai and at the non-startup end, the dedication of Tesla to not use LIDAR because it wants to sell cars today, before LIDARs can be bought at automotive quantities and prices.
California has published updated draft regulations for robocars whose most notable new feature is rules for testing and operating unmanned cars, including cars which have no steering wheel, such as Google, Navya, Zoox and others have designed.
This is a big step forward from earlier plans which would have banned testing and deploying those vehicles. That that they are ready to deploy, but once you ban something it's harder to un-ban it.
Caltrain is the commuter rail line of the San Francisco peninsula. It's not particularly good, and California is the land of the car commuter, but a plan was underway to convert it from diesel to electric. This made news this week as the California Republican house members announced they want to put a stop to both this project, and the much larger California High Speed Rail that hopes to open in 2030.
California published its summary of all the reports submitted by vendors testing robocars in the state. You can read the individual reports -- and they are interesting, but several other outlines have created summaries of the reports calculating things like the number of interventions per mile.
I generally pay very little attention when companies issues a press release about an "alliance." It's usually not a lot more than a press release unless there are details on what will actually be built.