Here's a few Robocar updates.

First of all, the TED talk given by Sebastian Thrun, leader of the Google self-driving car team (disclaimer: they are a consulting client) is up on the TED web site. This is one of the short TED talks, so he does not get to go into a lot of depth, but notable is one of the first public showings of video of the Google car in action on ordinary city streets. (The first was at PodCarCity, but video was not made available on the web.)

A few recent Robocar updates for you:

Google took its car down to the TED conference in Long Beach and did a few demo drives for people. In this mashable story you can catch some videos, inside and outside, of the car driving around a cone-based course on top of a parking lot near TED.

A release from the National Federation for the Blind reports a blind person driving and avoiding obstacles on the Daytona speedway. They used a car from the TORC team at Virginia Tech, one of the competitors in the Darpa Grand Challenges. In effect, the blind driver replaced the "drive by wire" component of a robocar with a more intelligent and thinking human also able to feel acceleration and make some judgements.

As readers of this blog surely know, for several years I have been designing, writing and forecasting about the technology of self-driving "robocars" in the coming years. I'm pleased to announce that I have recently become a consultant to the robot car team working at Google.

Of course all that work will be done under NDA, and so until such time as Google makes more public announcements, I won't be writing about what they or I are doing. I am very impressed by the team and their accomplishments, and to learn more I will point you to my blog post about their announcement and the article I added to my web site shortly after that announcement. It also means I probably won't blog in any detail about certain areas of technology, in some cases not commenting on the work of other teams because of conflict of interest. However, as much as I enjoy writing and reporting on this technology, I would rather be building it.

My philosophical message about Robocars I have been saying for years, but it should be clear that I am simply consulting on the project, not setting its policies or acting as a spokesman.

My primary interest at Google is robocars, but many of you also know my long history in online civil rights and privacy, an area in which Google is often involved in both positive and negative ways. Indeed, while I was chairman of the EFF I felt there could be a conflict in working for a company which the EFF frequently has to either praise or criticise. I will be recusing myself from any EFF board decisions about Google, naturally.

The "burning" question for electric cars is how to compare them with gasoline. Last month I wrote about how wrong the EPA's 99mpg number for the Nissan Leaf was, and I gave the 37mpg number you get from the Dept. of Energy's methodology. More research shows the question is complex and messy.

So messy that the best solution is for electric cars to publish their efficiency in electric terms, which means a number like "watt-hours/mile." The EPA measured the Leaf as about 330 watt-hours/mile (or .33 kwh/mile if you prefer.) For those who really prefer an mpg type number, so that higher is better, you would do miles/kwh.

Then you would get local power companies to publish local "kwh to gallon of gasoline" figures for the particular mix of power plants in that area. This also is not very easy, but it removes the local variation. The DoE or EPA could also come up with a national average kwh/gallon number, and car vendors could use that if they wanted, but frankly that national number is poor enough that most would not want to use it in the above-average states like California. In addition, the number in other countries is much better than in the USA.

The local mix varies a lot. Nationally it's about 50% coal, 20% gas, 20% nuclear and 10% hydro with a smattering of other renewables. In some places, like Utah, New Mexico and many midwestern areas, it is 90% or more coal (which is bad.) In California, there is almost no coal -- it's mostly natural gas, with some nuclear, particularly in the south, and some hydro. In the Pacific Northwest, there is a dominance by hydro and electricity has far fewer emissions. (In TX, IL and NY, you can choose greener electricity providers which seems an obvious choice for the electric-car buyer.)

Understanding the local mix is a start, but there is more complexity. Let's look at some of the different methods, staring with an executive summary for the 330 wh/mile Nissan Leaf and the national average grid:

• Theoretical perfect conversion (EPA method): 99 mpg-e(perfect)
• Heat energy formula (DoE national average): 37 mpg-e(heat)
• Cost of electricity vs. gasoline (untaxed): 75 mpg-e($)
• Pollution, notably PM2.5 particulates: Hard to calculate, could be very poor. Hydrocarbons and CO: very good.
• Greenhouse Gas emissions, g CO2 equivalent: 60 mpg-e(CO2)

Like just about everybody, I hate the way travel through airports has become. Airports get slower and bigger and more expensive, and for short-haul flights you can easily spend more time on the ground at airports than you do in the air. Security rules are a large part of the cause, but not all of it.

In this completely rewritten essay, I outline the design on a super-cheap airport with very few buildings, based on a fleet of proto-robocars. I call them proto models because these are cars we know how to build today, which navigate on prepared courses on pavement, in controlled situations and without civilian cars to worry about.

In this robocar airport, which I describe first in a narrative and then in detail, there are no terminal buildings or gates. Each plane just parks on the tarmac and robotic stairs and ramps move up and dock to all its doors. (Catering trucks, fuel trucks and luggage robots also arrive.) The passengers arrive in a perfect boarding order in robocars that dock at the ramps/steps to let them get on the plane through every entrance. Luggage is handled by different robots, and is checked and picked up not in carousels and check-in desks, but at curbs, parking lots, rental car centers and airport hotels.

The change is so dramatic that (even with security issues) people could arrive at airports for flights under 20 minutes before take-off, and get out even faster. Checked luggage would add time, but not much. I also believe you could build a high capacity airport for a tiny fraction of the cost of today's modern multi-billion dollar edifices. I believe the overall experience would also be more pleasant and more productive for all.

This essay is a long one, but I am interested in feedback. What will work here, and what won't? Would you love to fly through this airport or hate it? This is an airport designed not to give you a glorious building in which to wait but to get you through it without waiting most of the time.

The airport gets even better when real robocars, that can drive on the streets to the airport, come on the scene.

Give me your feedback on The Robocar Airport.

Key elements of the design include:

I've written frequently about how driving fatalities are the leading cause of death for people from age 5 to 45, and one of the leading overall causes of death. I write this because we hope that safe robocars, with a much lower accident rate, can eliminate much of this death.

I decided to gather together all my thoughts on how robocars will affect urban design. There are many things that might happen, though nobody knows enough urban planning to figure out just what will happen. However, I felt it worthwhile to outline the forces that might be at work so that urban geographers can speculate on what they will mean. It is hard to make firm predictions.

The folks at the SARTRE road train project have issued an update one year into their 3 year project. This is an EU-initiated project to build convoy technology, where a professional lead driver in a truck or bus is followed by a convoy of closely packed cars which automatically follow based on radio communications (and other signals) with the lead. They have released a new video on their progress from Volvo.

Two bits of robocar news from last week. I had been following the progress of the Stanford/VW team that was building a robotic Audi TT to race to the top of Pikes Peak. They accomplished their run in September, but only now made the public announcement of it. You can find photos and videos with the press release or watch a video on youtube.

Today, I was challenged with the question of how well robocars would deal with deer crossing the road. There are 1.5 million collisions with deer in the USA every year, resulting in 200 deaths of people and of course many more deer. Many of the human injuries and crashes have come from trying to swerve to avoid the deer, and skidding instead during the panic.

At present there is no general purpose computer vision system that can just arbitrarily identify things -- which is to say you can't show it a camera view of anything and ask, "what is that?" CV is much better at looking for specific things, and a CV system that can determine if something is a deer is probably something we're close to being able to make. However, I made a list of a number of the techniques that robots might have to do a better job of avoiding collisions with animals, and started investigating thoughts on one more, the "flying bumper" which I will detail below.

Spotting and avoiding the deer

• There are great techniques for spotting animal eyes using infrared light bouncing off the retinas. If you've seen a cheap flash photo with the "red eye" effect you know about this. An IR camera with a flash of IR light turns out to be great at spotting eyes and figuring out if they are looking at you, especially in darkness.
• A large number of deer collisions do take place at dusk or at night, both because deer move at these times and humans see badly during them. LIDAR works superbly in darkness, and can see 100m or more. On dry pavement, a car can come to a full stop from 80mph in 100m, if it reacts instantly. The robocar won't identify a deer on the road instantly but it will do so quickly, and can thus brake to be quite slow by the time it travels 100m.
• Google's full-map technique means the robocar will already have a complete LIDAR map of the road and terrain -- every fencepost, every bush, every tree -- and of course, the road. If there's something big in the LIDAR scan at the side of the road that was not there before, the robocar will know it. If it's moving and more detailed analysis with a zoom camera is done, the mystery object at the side of the road can be identified quickly. (Radar will also be able to tell if it's a parked or disabled vehicle.)
• They are expensive today, but in time deep infrared cameras which show temperature will become cheap and appear in robocars. Useful for spotting pedestrians and tailpipes, they will also do a superb job on animals, even animals hiding behind bushes, particularly in the dark and cool times of deer mating season.
• Having spotted the deer, the robocar will never panic, the way humans often do.
• The robocar will know its physics well, and unlike the human, can probably plot a safe course around the deer that has no risk of skidding. If the ground is slick with leaves or rain, it will already have been going more slowly. The robocar can have a perfect understanding of the timings involved with swerving into the oncoming traffic lane if it is clear. The car can calculate the right speed (possibly even speeding up) where there will be room to safely swerve.
• If the oncoming traffic lane is not clear, but the oncoming car is also a robocar, it might some day in the far future talk to that car both to warn it and to make sure both cars have safe room to swerve into the oncoming lane.
• Areas with major deer problems put up laser sensors along the sides of the road, which detect if an animal crosses the beam and flash lights. A robocar could get data from such sensors to get more advanced warning of animal risks areas.

Getting the deer to move

There might be some options to get the deer to get out of the way. Deer sometimes freeze; a "deer in the headlights." A robocar, however, does not need to have visible headlights! It may have them on for the comfort of the passengers who want to see where they are going and would find it spooky driving in the dark guided by invisible laser light, but those comfort lights can be turned off or dimmed during the deer encounter, something a human driver can't do. This might help the deer to move.

Many people wonder whether robocars will just suffer the curse of regular cars, namely traffic congestion. They are concerned that while robocars might solve many problems of the automobile, in many cities there just isn't room for more roads. Can robocars address the problems of congestion and capacity? What about combined with ITS (Intelligent Transportation Systems) efforts to make roads smarter for human driven cars?

I think the answer is quite positive, for a number of different reasons. I have added a new Robocar essay:

I've written before about solutions to "range anxiety" -- the barrier to adoption of electric cars which derives from fear that the car will not have enough range and, once out of power, might take a very long time to recharge. It's hard to compete with gasoline's 3 minute fill-up and 300 mile ranges. Earlier I proposed an ability to quickly switch to a rental gasoline car if running out of range.

I'm at the Pod Car City conference, taking place today and tomorrow in San Jose for PRT developers and customers. Some news tidbits from the conference:

There's news about the world's two small PRT (Personal Rapid Transit) projects, which are both fairly robocar like, in that they involve self-steered rubber tired vehicles.

The AutoNOMOS team at Freie Universität Berlin led by Raul Rojas has shown a demo of their robocar acting as what I have called a whistlecar. Their latest car, named "Made in Germany" performed an autonomous taxi pickup for the press which you can see played out in this video.

This weekend's announcement that Google had logged 140,000 miles of driving in traffic with their prototype robocars got lots of press, but it's not the only news of teams making progress. A team at TU Braunschweig in Germany has their own model which has been driving on ordinary city streets with human oversight. You can watch a video of the car in action though there is a lot of B-roll in that video, so seek ahead to 1:50 and particularly 3:20 for the inside view of the supervisor's hands hovering just over the self-turning steering wheel. There is some information on Stadtpilot here, but we can see many similarities, including the use of the Velodyne 64 line LIDAR on the roof and a typical array of sensors, and more use of detailed maps.

The team at Vislab in Milan has completed most of their Milan to Shanghai autonomous car journey which I have been following. You can read their blog or watch video (sometimes live) of their trip. A lot of the blog has ended up being not about the autonomous challenges, but just the challenges of taking a fleet of very strange looking vehicles in a convoy across Eastern Europe and Asia. For example, they have trucks which can carry their robocars inside, and once decided it was simpler to cross a border into Hungary this way. However, they left driving the vehicles, and the exit officials got very concerned that there was no record of the robocars coming into the country. I presume it wasn't hard to convince them they were not smuggling Hungarian robocars out.

Just released in a New York Times article and sidebar about highways and video, Google has unveiled an internal robot car project that has attained a remarkable level of robotic driving sooner than I and many others had predicted.

There was a bit of a stir when Google last week announced that one of the winners of their 10^100 contest would be Shweeb, a pedal-powered monorail from New Zealand that has elements of PRT. Google will invest $1M in Shweeb to help them build a small system, and if it makes any money on the investment, that will go into transportation related charities.

While I had a preference that Google fund a virtual world for developing and racing robocars I have come to love a number of elements about Shweeb, though it's not robocars and the PRT community seems to not think it's PRT. I think it is PRT, in that it's personal, public and, according to the company, relatively rapid through the use of offline stations and non-stop point to point trips. PRT is an idea from the sixties that makes sense but has tried for almost 50 years to get transit planners to believe in it and build it. A micro-PRT has opened as a Heathrow parking shuttle, but in general transit administrators simply aren't early adopters. They don't innovate.

What impresses me about Shweeb is its tremendous simplicity. While it's unlikely to replace our cars or transit systems, it is simple enough that it can actually be built. Once built, it can serve as a testbed for many of PRT's concepts, and go through incremental improvements.

An Italian team has built a prototype robot they call Dustbot which is aimed (in a backwards way) at the deliverbot vision.