At the recent AUVSI/TRB conference in San Francisco, there was much talk of upcoming regulation, particularly from NHTSA. Secretary of Transportation Foxx and his NHTSA staff spoke with just vague hints about what might come in the proposals due this fall. Generally, they said good things, namely that they are wary of slowing down the development of the technology. But they said things that suggest other directions.

Today, Robin Chase wrote an article wondering if robocars will improve or ruin our cities and asked for my comment on it. It's a long article, and I have lots of comment, since I have been considering these issues for a while. On this site, I spend most of my time on the potential positive future, though I have written various articles on downsides and there are yet more to write about.

At the recent AUVSI/TRB symposium, a popular research topic was platooning for robocars and trucks. Platooning is perhaps the oldest practical proposal when it comes to car automation because you can have the lead vehicle driven by a human, even a specially trained one, and thus resolve all the problems that come from road situations too complex for software to easily handle.

It's common for people to write that those who vote for a minor party in an election are "throwing away" their vote. Here's a recent article by my friend Clay Shirky declaring there's no such thing as a protest vote and many of the cases are correct, but the core thesis is wrong. Instead, I will argue that outside the swing states, you are throwing away your vote if you vote for a major party candidate.

To be clear, if you are in one of the crucial swing states where the race is close -- and trust me, you know that from the billions of dollars of ad spend in your state, as well as from reading polls -- then you should vote for the least evil of the two party candidates as you judge it. And even in most of the country, (non-swing) you should continue to vote for those if you truly support them. But in a non-swing state, in this election in particular, you have an additional option and an additional power.

Consider here in California, which is very solidly for Clinton. Nate Silver rates it as 99.9% (or higher) to go for Clinton. A vote for Clinton or Trump here is wasted. It adds a miniscule proportion to their totals. Clinton will fetch around 8 million votes. You can do the un-noticed thing of making it 8 million and 1, and you'll bump her federally by an even tinier fraction. Your vote can make no difference to the result (you already know that) and nor will it be noticed in the totals. You're throwing it away, getting an insignificant benefit for its use.

Of course, the 3rd party candidates had no chance of winning California, or the USA. And while they like to talk a pretend bluster about that, they know that. You know that. Their voters know that. 3rd party voters aren't voting to help their candidate win, any more than Trump voters imagine their vote could help him win California, or Clinton voters imagine they could affect her assured victory.

Third party voters, however, will express their support for other idea in the final vote totals. If Jill Stein gets 50,000 votes in California, making it 50,001 doesn't make a huge difference, but it makes 160 times as much difference to her total than a Clinton vote does, or 100x what a Trump vote does. Gary Johnson is doing so well this year (polling about 8% of national popular vote) that his voters won't do quite as much to his total, but still many times more improvement than the major party votes. Clay argues that "nobody is receiving" the message of your vote for a third party, but the truth is, your vote for Clinton in California or Trump in Texas is a message that has even less chance of being received.

A big difference this year is that the press are paying attention to the minor parties. This year, you will see much more press on Johnson's and Stein's totals. It is true that in other years, the TV networks would often ignore those parties. In some case, TV network software is programmed to report only the top two results, and to make the percentages displayed add up to 100%. This is wrong of the networks, but I suspect there is less chance of it happening. Johnson will probably appear in those totals. Web sites and newspapers have generally reported the proper totals.

Does anybody look at these totals for minor candidates? Some don't, but the big constituency for them is others interested in minor parties. People want a tribe. Many people don't want to support something unless they see they are not alone, that others are supporting it. Johnson and Stein's poll numbers are already galvanizing many more votes for them.

This is how third parties arise, and it happens a lot outside the USA. In the USA it has't happened since the Republicans arose in the 1850s, tied to the collapse of the Whigs. Prior to that multiple parties were more common. Of course, there have been several runs at new parties (Perot/Reform, Dixiecrat and American Independent) which did not succeed. But if everybody refuses to actually vote for the 3rd parties they support because it is viewed as a waste, of course no 3rd parties will ever arise. Having a slim chance at that is one of the things to drive 3rd party voters, because that slim chance still means making a bigger difference than a meaningless extra vote for a major party.

This is how most political change happens. Because people see they are not alone. That's how small marches and protests grow into bigger ones until leaders are toppled. It's how small movements within big parties, and whole 3rd parties rise.

Social media are jam packed with analysis of the rise of Donald Trump these days. Most of us in what we would view as the intellectual and educated community are asking not just why Trump is a success, but as Trevor Noah asked, "Why is this even a contest?" Clinton may not be, as the Democrats claim, the most qualified person ever to run, but she's certainly decently qualified, and Trump is almost the only candidate with no public service experience ever to run. Even his supporters readily agree he's a bit of a buffoon, that he says tons of crazy things, and probably doesn't believe most of the things he says. (The fact that he doesn't actually mean many of the crazy things has become the primary justification of those who support him.)

But it is a contest, and while it looks like Clinton will probably win it is also disturbing to me to note that in polls broken down by race and sex, Trump is actually ahead of Clinton by a decent margin among my two groups -- whites and males. (Polls have been varying a lot in the weeks of the conventions.) Whites and males have their biases and privileges, of course, but they are very large and diverse groups, and again, to the coastal intellectual view, this shouldn't even be a contest. (It's also my view as a foreigner of libertarian leanings and no association with either party.)

The things stacked in favour of the Republican nominee

There have been lots of essays examining the reason for Trump's success. Credible essays have described a swing to nationalism and/or authoritarianism which Trump has exploited. Trump's skill at marketing and memes is real. His appeal to paternalism and strength works well (Lakeoff's "strong father" narrative.) The RNC also identified Hillary Clinton as a likely nominee 2 decades ago, and since then has put major effort into discrediting her, much more time than it's ever had to work on other opponents. And Clinton herself certainly has her flaws and low approval ratings, even within her own party.

It is also important to note that the chosen successor of a Democratic incumbent has never in history defeated the Republican. (In 1856 Buchanan defeated the 1st ever Republican nominee, Fremont, but was Franklin Pierce's opponent at the convention.) This stacks the deck in favour of this year's Republican. Of course, Wilson, Cleveland, Roosevelt the 2nd, Carter and Clinton the 1st all defeated incumbent Republicans, so Democrats are far from impotent.

The specific analysis of this election is interesting, but my concern is about the broader trend I see, a much bigger geopolitical trend arising from technology, globalization, income inequality and redistribution among nations as well as the decline of religion and the classic lifetime middle class career. This big topic will get more analysis in time here. I was particularly interested in this recent article linking globalization and the comparative reduced share for the U.S. middle class. The ascendancy of the secular, western, technological, intellectual capitalist liberal elite is facing an increasing backlash.

Where Trump's support comes from

Trump of course begins, as Clinton does, with a large "base." There is an element of the Republican base that will never tolerate voting for Clinton almost no matter how bad Trump is. There is a similar Democratic contingent. This base has been boosted by that 2 decade anti-Clinton campaign.

Today I want to look at some implications of Tesla's Master Plan Part Deux which caused some buzz this week. (There was other news of course, including the AUVSI/TRB meeting which I attended and will report on shortly, forecast dates from Volvo, BMW and others, hints from Baidu, Faraday Future and Apple, and more.)

In Musk's blog post he lays out these elements of Tesla's plan

• Integrating generation and storage (with SolarCity and the PowerWall and your car.)
• Expand into trucks and minibuses
• More autonomy in Tesla cars
• Hiring out your Tesla as a robotaxi when not using it

Except for the first one, all of these are ideas I have covered extensively here. It is good to see an automaker start work in these directions. As such while I will mostly agree with what Tesla is saying, there are a few issues to discuss.

Electric (self-driving) minibus and Trucks

In my article earlier this year on the future of transit I laid out why transit should mostly be done with smaller (van sized) vehicles, taking ad-hoc trips on dynamic paths, rather than the big-vehicle, fixed-route, fixed-schedule approach taken today. The automation is what makes this happen (especially when you add the ability of single person robocars to do first and last miles.) Making the bus electric can make it greener, though making it run full almost all the time is far more important for that.

The same is true for trucks, but both trucks and buses have huge power needs which presents problems for having them be electric. Electric's biggest problem here is the long recharge time, which puts your valuable asset out of service. For trucks, the big win of having a robotruck is that it can drive 24 hours/day, you don't want to take that away by making it electric. This means you want to look into things like battery swap, or perhaps more simply tractor swap. In that case, a truck would pull in to a charging station and disconnect from its trailer, and another tractor that just recharged would grab on and keep it going.

The success of carpool apps

The cell phone ride hail apps like Uber and Lyft are now reporting great success with actual ride-sharing, under the names UberPool, LyftLines and Lyft Carpool. In addition, a whole new raft of apps to enable semi-planned and planned carpooling are out making changes.

It's not surprising there is huge debate about the fatal Tesla autopilot crash revealed to us last week. The big surprise to me is actually that Tesla and MobilEye stock seem entirely unaffected. For many years, one of the most common refrains I would hear in discussions about robocars was, "This is all great, but the first fatality and it's all over." I never believed it would all be over, but I didn't think there would barely be a blip.

There's been lots of blips in the press and online, of course, but most of it has had some pretty wrong assumptions. Tesla's autopilot is a distant cousin of a real robocar, and that would explain why the fatality is no big deal for the field, but the press shows that people don't know that.

Tesla's autopilot is really a fancy cruise control. It combines several key features from the ADAS (Advance Driver Assist) world, such as adaptive cruise control, lane-keeping and forward collision avoidance, among others. All these features have been in cars for years, and they are also combined in similar products in other cars, both commercial offerings and demonstrated prototypes. In fact, Honda promoted such a function over 10 years ago!

Tesla's autopilot primarily uses the MobilEye EyeQ3 camera, combined with radars and some ultrasonic sensors. It doesn't have a lidar (the gold standard in robocar sensors) and it doesn't use a map to help it understand the road and environment.

Most importantly, it is far from complete. There is tons of stuff it's not able to handle. Some of those things it can't do are known, some are unknown. Because of this, it is designed to only work under constant supervision by a driver. Tesla drivers get this explained in detail in their manual and when they turn on the autopilot.

ADAS cars are declared not to be self-driving cars in many state laws

This is nothing new -- lots of cars have lots of features to help drive (including the components used like cruise controls, each available on their own) which are not good enough to drive the car, and only are supposed to augment an alert driver, not replace one. Because car companies have been selling things like this for years, when the first robocar laws were drafted, they made sure there was a carve-out in the laws so that their systems would not be subject to the robocar regulations companies like Google wanted.

The Florida law, similar to other laws, says:

The term [Autonomous Vehicle] excludes a motor vehicle enabled with active safety systems or driver assistance systems, including, without limitation, a system to provide electronic blind spot assistance, crash avoidance, emergency braking, parking assistance, adaptive cruise control, lane keep assistance, lane departure warning, or traffic jam and queuing assistant, unless any such system alone or in combination with other systems enables the vehicle on which the technology is installed to drive without the active control or monitoring by a human operator.

The Tesla's failure to see the truck was not surprising

There's been a lot of writing (and I did some of it) about the particulars of the failure of Tesla's technology, and what might be done to fix it. That's an interesting topic, but it misses a very key point. Tesla's system did not fail. It operated within its design parameters, and according to the way Tesla describes it in its manuals and warnings. The Tesla system, not being a robocar system, has tons of stuff it does not properly detect. A truck crossing the road is just one of those things. It's also poor on stopped vehicles and many other situations.

Tesla could (and in time, will) fix the system's problem with cross traffic. (MobilEye itself has that planned for its EyeQ4 chip coming out in 2018, and freely admits that the EyeQ3 Tesla uses does not detect cross traffic well.) But fixing that problem would not change what the system is, and not change the need for constant monitoring that Tesla has always declared it to have.

Today at Starship, we announced our first pilot projects for robotic delivery which will begin operating this summer. We'll be working with a London food delivery startup Pronto as well as German parcel company Hermes and the Metro Group of retailers, plus Just Eat restaurant food delivery to trial on-your-schedule delivery of packages, groceries and meals to people's homes.

Executive Summary: A rundown of different approaches for validation of self-driving and driver assist systems, and a recommendation to Tesla and others to have countermeasures to detect drivers not watching the road, and permanently disable their Autopilot if they show a pattern of inattention.

The recent fatality for a man who was allowing his car to be driven by the Tesla "autopilot" system has ignited debate on whether it was appropriate for Tesla to allow their system to be used as it was.

Tesla's autopilot is a driver assist system, and Tesla tells customers it must always be supervised by an alert driver ready to take the controls at any time. The autopilot is not a working self-driving car system, and it's not rated for all sorts of driving conditions, and there are huge numbers of situations that it is not designed to handle and can't handle. Tesla knows that, but the public, press and Tesla customers forget that, and there are many Tesla users who are treating the autopilot like a real self-driving car system, and who are not paying attention to the road -- and Tesla is aware of that as well. Press made this mistake as well, regularly writing fanciful stories about how Tesla was ahead of Google and other teams.

Brown, the driver killed in the crash, was very likely one of those people, and if so, he paid for it with his life. In spite of all the warnings Tesla may give about the system, some users do get a sense of false security. There is debate if that means driver assist systems are a bad idea.

There have been partial self-driving systems that require supervision since the arrival of the cruise control. Adaptive cruise control is even better, and other car companies have released autopilot like systems which combine adaptive cruise control with lane-keeping and forward collision avoidance, which hits the brakes if you're about to rear end another car. Mercedes has sold a "traffic jam assist" like the Telsa autopilot since 2014 that only runs at low speeds in the USA. You can even go back to a Honda demo in 2005 of an autopilot like system.

With cruise control, you might relax a bit but you know you have to pay attention. You're steering and for a long time even the adaptive cruise controls did not slow down for stopped cars. The problem with Tesla's autopilot is that it was more comprehensive and better performing than earlier systems, and even though it had tons of things it could not handle, people started to trust it with their lives.

Tesla's plan can be viewed in several ways. One view is that Tesla was using customers as "beta testers," as guinea pigs for a primitive self-drive system which is not production ready, and that this is too much of a risk. Another is that Tesla built (and tested) a superior driver assist system with known and warned limitations, and customers should have listened to those warnings.

Neither is quite right. While Tesla has been clear about the latter stance, with the knowledge that people will over-trust it, we must face the fact that it is not only the daring drivers who are putting themselves at risk, it's also others on the road who are put at risk by the over-trusting drivers -- or perhaps by Tesla. What if the errant car had not gone under a truck, but instead hit another car, or even plowed into a pedestrian when it careened off the road after the crash?

At the same time, Tesla's early deployment approach is a powerful tool for the development and quality assurance of self-drive systems. I have written before about how testing is the big unsolved problem in self-driving cars. Companies like Google have spent many millions to use a staff of paid drivers to test their cars for 1.6 million miles. This is massively expensive and time consuming, and even Google's money can't easily generate the billions of miles of testing that some feel might be needed. Human drivers will have about 12 fatalities in a billion miles, and we want our self-driving cars to do much better. Just how we'll get enough verification and testing done to bring this technology to the world is not a solved problem.

A Tesla blog post describes the first fatality involving a self drive system. A Tesla was driving on autopilot down a divided highway. A truck made a left turn and crossed the Tesla's lanes. A white truck body against a bright sky is not something the MobilEye camera system in the Tesla perceives well, and it is not designed for cross traffic.

With Mobility on Demand, you don't buy a car, you buy rides. That's certainly Uber's plan, and is a plan that makes sense for Google, Apple and other no-car companies. But even Daimler, with Car2Go/Car2Come, BMW with DriveNow and GM with Lyft plan to sell you a ride rather than a car, because it's the more lucrative thing to do.

So what does that car of the future look like? There is no one answer, because in this world, the car that is sent to pick you up is tailored to your trip. The more people traveling, the bigger the car is. If your trip does not involve a highway, it may not be a car capable of the highway. If your trip is up to a mountain cabin, it's more like an SUV, but you never use an SUV to go get a bottle of milk the way we do today. If it's for a cruise to the beach on a sunny day, the roof may have been removed at the depot. If it's for an overnight trip to a country home, it may be just beds.

I outlined many of these changes in this article on design changes in cars but today I will focus on the incredibly cheap and simple design of what should become the most common vehicle made, namely the car designed for a short urban trip by one person. That's 80% of trips and around 45% of miles, so this should be a large fraction of the fleet. I predict a lot of these cars will be made every year -- more than all the cars made today, even though they are used as taxis and shared among many passengers. What does it look like?

Small

A car for 1-2 people will be small. It will probably be around 1.5m wide, narrow enough that you can fit two in a lane, and have it park very efficiently when it has to wait. If it's for just one person, it won't be very long either. For two people, there will be a "face to face" configuration which is longer and an "tandem" configuration which is a bit shorter. The 2 person vehicles aren't a lot bigger or heavier than the one person, so they might be the most common cars, since you can serve a solo rider fairly efficiently with one, even if not perfectly efficient.

A car that is so narrow can't corner very fast. A wide stance is much more stable. There are a few solutions to that, including combinations of these:

• The wheels bank independently, allowing the vehicle to lean like a motorcycle when in corners. This is the best solution, but it costs some money.
• Alternately it's a two wheeler, which is also able to lean, but has other tricks like the LIT Motors C-1 to stay upright.
• It's electric, and has all the batteries in the floor, giving it a very low center of gravity. (One extreme example of this is the Tango, which uses lead batteries deliberately to give it that stability.)
• It never goes on fast roads, so it never needs to corner very fast, and its precision robot driving assures it never corners so fast as to become unstable, and it plans its route accordingly.

Not super aerodynamic

The car already has a big win when it comes to aerodynamic drag by only being half-width. The non-highway version probably gives back a bit of that because you don't need to worry as much about that if you are not going fast. Energy lost to drag goes up with the square of velocity. So a 30mph car has 1/4 the drag of a 60mph car, and 1/8th the drag of a similar car of full width. The highway car needs to be shaped as close to a "teardrop" as you can, but the city car can get away with being a bit taller for more comfortable seating and entry/exit.

Political debate is going overboard these days. I travel overseas all the time and if I reveal I live in the USA, you can't stop people from asking about Trump. It's getting frustrating and boring. But to avoid contentious topics, let's talk about guns!

Elon Musk likes to say pretty controversial things off the cuff, and so do I, but he inspired a number of threads by saying at Re:Code that there's a billion to one chance we're living in base reality. To use his word, this world is almost surely a "simulation."

When I give talks on robocars, the most common question, asked almost all the time, is the one known as the "trolley problem" question, "What will the car do if it has to choose between killing one person or another" or other related dilemmas. I have written frequently about how this is a very low priority question in reality, much more interesting to philosophy classes than it is important. It is a super-rare event and there are much more important everyday ethical questions that self-driving car developers have to solve long before they will tackle this one.

In spite of this, the question persists in the public mind. We are fascinated and afraid of the idea of machines making life or death decisions. The tiny number of humans faced with such dilemmas don't have a detailed ethical debate in their minds; they can only go with their "gut" or very simple and quick reasoning. We are troubled because machines don't have a difference between instant and carefully pondered reactions. The one time in billions of miles(*) that a machine faces such a question it would presumably make a calculated decision based on its programming. That's foreign to our nature, and indeed not a task desired by programmers or vendors of robocars.

There have been calls to come up with "ethical calculus" algorithms and put them in the cars. As a programmer, I could imagine coding such an algorithm, but I certainly would not want to, nor would I want to be held accountable for what it does, because by definition, it's going to do something bad. The programmer's job is to make driving safer. On their own, I think most builders of robocars would try to punt the decision elsewhere if possible. The simplest way to punt the decision is to program the car to follow the law, which generally means to stay in its right-of-way. Yes, that means running over 3 toddlers who ran into the road instead of veering onto the sidewalk to run over Hitler. Staying in our lane is what the law says to do, and you are not punished for doing it. The law strongly forbids going onto the sidewalk or another lane to deliberately hit something, no matter who you might be saving.

We might not like the law, but we do have the ability to change it.

Thus I propose the following: Driving regulators should create a special panel which can rule on driving ethics questions. If a robocar developer sees a question which requires some sort of ethical calculation whose answer is unclear, they can submit that question to the panel. The panel can deliberate and provide an answer. If the developer conforms to the ruling, they are absolved of responsibility. They did the right thing.

The panel would of course have people with technical skill on it, to make sure rulings are reasonable and can be implemented. Petitioners could also appeal rulings that would impede development, though they would probably suggest answers and describe their difficulty to the panel in any petition.

The panel would not simply be presented with questions like, "How do you choose between hitting 2 adults or one child?" It might make more sense to propose formulae for evaluating multiple different situations. In the end, it would need to be reduced to something you can do with code.

Very important to the rulings would be an understanding of how certain requirements could slow down robocar development or raise costs. For example, a ruling that car must make a decision based on the number of pedestrians it might hit demands it be able to count pedestrians. Today's robocars may often be unsure whether a blob is 2 or 3 pedestrians, and nobody cares because generally the result is the same -- you don't want to hit any number of pedestrians. Likeways, requirements to know the age of people on the road demands a great deal more of the car's perception system than anybody would normally develop, particularly if you imagine you will ask it to tell a dwarf adult from a child.

Reports from Tesla suggest they are gathering huge amounts of driving data from logs in their cars -- 780 million miles of driving, and as much as 100 million miles in autopilot mode. This contrasts with the 1.6 million miles of test operations at Google. Huge numbers, but what do they mean now, and in the future?

Executive summary: Can our emotional fear of machines and the call for premature regulation be mollified by a temporary increase in liability which takes the place of specific regulations to keep people safe?

Here is the first report of a real Tesla autopilot crash. To be fair to Tesla, their owner warnings specify fairly clearly that the autopilot could crash in just this situation -- there is a stalled car partly in the lane, and the car in front of you swerves around it, revealing it with little time for you or the autopilot to react.

The deeper issue is the way that the improving quality of the Tesla Autopilot and systems like it are lulling drivers into a false sense of security. I have heard reports of people who now are trusting the Tesla system enough to work while being driven, and indeed, most people will get away with this. And as people get away with it more and more, we will see more people driving like this driver, not really prepared to react. This is one of the reasons Google decided not to make a system which requires driver takeover ever. As the system gets better, does it get more dangerous?

Some technical notes:

• This is one of the things LIDAR is much more reliable at seeing than cameras. Of course, whether you can swerve once the LIDAR sees it is another matter.
• On the other hand, this is where radar fails. I mean the stalled car is clear on radar, but it's stationary, so you can't tell it from the road or guardrail which are also stationary.
• This is one of the classic V2V value propositions, but it's not a good one. You don't need 10ms latency to have a stalled car tell you it is stalled. Far better that car report to a server that it's stalled and for everybody coming down that road to learn it, whether they have line of sight radio to the stall, or V2V at all. Waze already reports this just with human manual reporting and that's a really primitive way to do it.

Declaration of Amsterdam

Last month, various EU officials gathered in Amsterdam and signed the Declaration of Amsterdam which outlines a plan for normalizing EU laws around self-driving cars. The meeting also included a truck automation demo in the Netherlands and a self-drive transit shuttle demonstration. It's a fairly bland document, more an expression of the times, and it sadly spends a lot of time on the red herring of "connected" vehicles and V2V/V2I, which governments seem to love, and self-driving car developers care very little about.

Let's hope the regulatory touch is light. The reality is that even the people building these vehicles can't make firm pronouncements on their final form or development needs, so governments certainly can't do that, and we must be careful of attempts to "help" that hinder. We already have a number of examples of that happening in draft and real regulations, and we've barely gotten started. For now, government statements should be limited to, "let's get out of the way until people start figuring out how this will actually work, unless we see somebody doing something demonstrably dangerous that can't be stopped except through regulations." Sadly, too many regulators and commentators imagine it should be, "let's use our limited current knowledge to imagine what might go wrong and write rules to ban it before it happens."

Speech from the Throne

It was a sign of the times when her Majesty the Queen, giving the speech from the throne in the UK parliament, laid out some elements of self-driving car plans. The Queen drove jeeps during her military days, and so routinely drives herself at her country estates, otherwise she would be among the set of people most used to never driving.

The UK has 4 pilot projects in planning. Milton Keynes is underway, and later this year, a variation of the Ultra PRT pods in use at T5 of Heathrow airport -- they run on private tracks to the car park -- will go out on the open road in Greenwich. They are already signing up people for rides.

Car companies thinking differently

In deciding which car companies are going to survive the transition to robocars, one thing I look for is willingness to stop thinking like a traditional car company which makes cars and sells them to customers. Most car company CEOs have said they don't plan to keep thinking that way, but what they do is more important than what they say.

Uber has announced the official start of self-driving tests in Pittsburgh. Uber has been running their lab for over a year, and had various vehicles out there mapping and gathering data, but their new vehicle is sleeker and loaded with sensors - more than on Google's cars or most of the other research cars I have seen. You can see several lidars on the roof and bumpers, and a seriously big array of cameras and other sensors.

Today sees the un-stealthing of a new company called Otto which plans to build self-driving systems for long haul trucks. The company has been formed by a skilled team, including former members of Google's car team and people I know well. You can see their opening blog post

My entire focus on this blog, and the focus of most people in this space, has been on cars, particularly cars capable of unmanned operation and door-to-door service. Most of those not working on that have had their focus on highway cars and autopilots. The highway is a much simpler environment so much easier to engineer, but it operates at higher speeds so the cost of accidents is worse.

That goes doubly true for trucks that are fast, big and massive. At the same time, 99% of truck driving is actually very straightforward -- stay in a highway lane, usually the slow one, with no fancy moving about.

Some companies have done exploration of truck automation. Daimler/Freightliner has been testing trucks in Nevada. Volvo (trucks and cars together) has done truck and platooning experiments, notably the Sartre project some years ago. A recent group of European researchers did a truck demonstration in the Netherlands, leading up to the Declaration of Amsterdam which got government ministers to declare a plan to modify regulations to make self-driving systems legal in Europe. Local company Peloton has gone after the more tractable problem of two-truck platoons with a driver in each truck, aimed primarily at fuel savings and some safety increases.

Safety

While trucks are big and thus riskier to automate, they are also risky for humans to drive. Even though truck drivers are professionals who drive all day, there are still around 4,000 killed every year in the USA in truck accidents. More than half of those are truck drivers, but a large number of ordinary road users are also killed. Done well, self-driving trucks will reduce this toll. Just as with cars, companies will not release the systems until they believe they can match and beat the safety record of human drivers.

The Economics

Self-driving trucks don't change the way we move, but they will have a big economic effect on trucking. Driver pay accounts for about 25-35% of the cost of truck operation, but in fact early self-driving won't take away jobs because there is a serious shortage of truck drivers in the market -- companies can't hire enough of them at the wages they currently pay. It is claimed that there are 50,000 job openings unfilled at the present time. Truck driving is grueling work, sometimes mind-numbing, and it takes the long haul driver away from home and family for over a week on every long-haul run. It's not very exciting work, and it involves long days (11 hours is the legal limit) and a lot of eating and sleeping in truck stops or the cabin of the truck.

Average pay is about 36 cents/mile for a solo trucker on a common route. Alternately, loads that need to move fast are driven by a team of two. They split 50 cents/mile between them, but can drive 22 hours/day -- one driver sleeps in the back while the first one takes the wheel. You make less per mile per driver, but you are also paid for the miles you are sleeping or relaxing.

A likely first course is trucks that keep their solo driver who drives up to 11 hours -- probably less -- and have the software drive the rest. Nonstop team driving speed with just one person. Indeed, that person might be an owner-operator who is paying for the system as a businessperson, rather than a person losing a job to automation. The human would drive the more complex parts of the route (including heavy traffic) while the system can easily handle the long nights and sparse heartland interstate roads.

The economics get interesting when you can do things that are expensive for human drivers and teams. Aside from operating 22 or more hours/day at a lower cost, certain routes will become practical that were not economic with human drivers, opening up new routes and business models.

The Environment

Computer driven trucks will drive more regularly than humans, effectively driving in "hypermile" style as much as they can. That should save fuel. In addition, while I would not do it at first, the platooning experimented with by Peloton and Sartre does result in fuel savings. Also interesting is the ability to convert trucks to natural gas, which is domestic and burns cleaner (though it still emits CO2.) Automated trucks on fixed routes might be more willing to make this conversion.

Road wear

There is strong potential to reduce the damage to roads (and thus the cost of maintaining them, which is immense and seriously in arrears) thanks to the robotruck. That's because heavy trucks and big buses cause almost all the road wear today. A surprising rule of thumb is that road damage goes up with the 4th power of the weight per axle. As such an 80,000lb truck with 34,000lb on two sets of 2 axles and 6,000lb on the front axle does around 2,000 times the road damage of a typical car!