Air Force Set to Launch Next-to-Last GPS IIF Satellite

As reported by Wireless Design Mag: Air Force Space Command's Space and Missile Systems Center and its mission partners are scheduled to launch the 11th Boeing-built Global Positioning System IIF satellite aboard a United Launch Alliance Atlas V 401 launch vehicle Oct. 30 from Space Launch Complex 41 at Cape Canaveral Air Force Station, Florida.

The launch window is set to open at 12:17 p.m. EDT and will remain open for 19 minutes.

Ten GPS IIF satellites are currently on-orbit and meeting all mission requirements. Of the remaining satellites, GPS IIF-11 is awaiting launch and GPS IIF-12, the remaining IIF-series satellite, is in storage awaiting final processing and preparation for a Feb. 3 launch.

GPS IIF satellites provide improved signals that will enhance the precise global positioning, navigation and timing services supporting both the warfighter and the growing civilian needs of our global economy. GPS IIF provides improved navigational accuracy through advanced atomic clocks, a longer design life than previous GPS satellites, and a third operational civil signal -- L5 -- that benefits commercial aviation and safety-of-life applications.

"The GPS IIF satellites play a key role in our modernization effort to provide new space-based capabilities for users around the globe and for decades to come," said Lt. Gen. Samuel Greaves, the Space and Missile Systems Center commander and Air Force program executive officer for space. "We have successfully placed into operation 10 in a series of 12 procured Boeing-built space vehicles, and thanks to the exceptional team of government, industry and launch personnel we are poised to launch the 11th GPS IIF satellite aboard an Atlas V 401 launch vehicle later this week.”

Operated by AFSPC's 50th Space Wing at Schriever Air Force Base, located east of Colorado Springs, Colorado, the GPS constellation provides precise positioning, navigation and timing services worldwide seven days a week, 24 hours a day.

SMC, located at Los Angeles AFB in El Segundo, California, is the Air Force's center of acquisition excellence for acquiring and developing military space systems. Its portfolio includes the Global Positioning System, military satellite communications, defense meteorological satellites, space launch and range systems, satellite control networks, space based infrared systems, and space situational awareness capabilities.

Why Tesla’s Autopilot and Google’s Car are Entirely Different Animals

As reported by RoboHub: In the buzz over the Tesla autopilot update, a lot of commentary has appeared comparing this Autopilot with Google’s car effort and other efforts and what I would call a “real” robocar — one that can operate unmanned or with a passenger who is not paying attention to the road. We’ve seen claims that “Tesla has beaten Google to the punch,” but while the Tesla release is a worthwhile step forward, the two should not be confused as all that similar.

Tesla’s autopilot isn’t even particularly new. Several car makers have had similar products in their labs for several years, and some have released it to the public, at first in a “traffic jam assist” mode, but reportedly in full highway cruise mode outside the USA. The first companies to announce it were Cadillac with the “Super Cruise” and VW’s “Temporary Autopilot” — but they delayed that until much later.

Remarkably, Honda showed off a car ten years ago doing this sort of basic autopilot (without lane change) and sold only in the UK. They decided to discontinue the project, however. That this was actually promoted as an active product ten years ago will give you some clue as to how different this was from the bigger efforts.

Cruise products like these require constant human supervision. With regular cruise control, you could take your feet off the pedals, but might have to intervene fairly often either by using the speed adjust buttons or full control. Interventions could be several times a minute. Later came “Adaptive Cruise Control”, which still required you to steer and fully supervise, but would rarely require intervention on the pedals while driving on the highway — a few times an hour might be acceptable.

The new autopilot systems allow you to take your hands off the wheel but demand full attention. Users report needing to intervene rarely on some highways, but frequently on other roads. Once again, if you only need to intervene once an hour, the product could make your drive more relaxing.

Now consider a car that drives without supervision …

Human drivers have minor accidents about every 2,500 to 6,000 hours, depending on what figures you are using — that would be about once every 10 to 20 years of driving. A fatal accident takes place every 2,000,000 hours of driving — about once every 10,000 years for the typical driver, thankfully a much longer span than a person’s lifetime.

If a full robocar needs human intervention, logic tells you that it’s going to have an accident because there is nobody there to intervene. Just like with human drivers, most of the errors that would cause an accident are minor: running off the road, fender benders. Not every mistake that could cause a crash or a fatality causes one. Indeed, humans make mistakes that might cause a fatality far more often than every 2,000,000 hours, because we “get away” with many of them.

Even so, the difference is staggering. A cruise autopilot (such as Tesla’s) is a workable product if you have to correct it a few times an hour, whereas a full robocar product is only workable if you need to correct it only after decades or even lifetimes of driving. This is not a difference of degree, it is a difference of kind. It is why there is probably not an evolutionary path from the cruise/autopilot systems based on existing ADAS technologies to a real robocar. Doing many thousands times better will not be done by incremental improvement. It almost surely requires a radically different approach, and probably very different sensors.

To top it all off, a full robocar doesn’t just need to be great at avoiding accidents. If it’s running unmanned, with no human to help it at all, it needs a lot of other features and capabilities too.

The mistaken belief in an evolutionary path also explains why some people imagine robocars are many decades away. If you wanted evolutionary approaches to take you to 100,000x better, you would expect to wait a long time. When an entirely different approach is required, what you learn from the old approach doesn’t help you predict how the other approaches — including unknown ones — will do.

It does teach you something, though. By simply being on the road, Tesla will encounter all sorts of interesting situations its developers weren’t expecting, and they will use this data to train new generations of software that do better. They will learn things that help them make the revolutionary unmanned product they hope to build in the 2020s. This is a good thing.

Google and others have also been out learning that, and soon more teams will.

Yamaha Shows 'Motobot' Motorcycle-Riding Humanoid Robot

As reported by GizMag: Yamaha produced somewhat of a surprise at the Tokyo Motor Show today when it showed a motorcycle-riding robot. Unlike most two-wheeled debutants, Yamaha's new Motobot isn't starting out on a small capacity motorcycle, but release images show the humanoid robot riding Yamaha's most sporting motorcycle, the 1000cc R1M.

The aim of the exercise is to develop rider-support systems similar to those we are seeing developed in automobiles to make driving safer. "We want to apply the fundamental technology and know-how gained in the process of this challenge to the creation of advanced rider safety and rider-support systems and put them to use in our current businesses, as well as using them to pioneer new lines of business," says Yamaha's release.

It's no secret that DARPA catalyzed the massive leap forward in autonomous vehicles over the last decade when it held its inaugural DARPA Grand Challenge in 2004, but one of the less publicised entrants in that momentous race was Anthony Levandowski'sGhostrider Robot Team, which used the base of a Yamaha single-cylinder dirt bike to create the first autonomous motorcycle.

NASA Satellites Will Use GPS to Boost Hurricane Forecasts

As reported by Spectrum IEEE: Eight small NASA satellites and the existing GPS network could provide the first serious upgrade for hurricane intensity forecasting in decades. Once launched in a little less than a year, the mission’s boost to extreme weather prediction would go a long way toward giving authorities more time to plan coastal evacuations and prepare for the onslaught of 21st-century storms.

The Cyclone Global Navigation Satellite System (CYGNSS) consists of eight micro-satellites weighing just 27 kilograms each. NASA’s planned satellite constellation would have the capability of measuring wind speeds of up to 216 kilometers per hour; the equivalent of a category 4 hurricane. (That’s one notch weaker than Hurricane Patricia when it struck Mexico days ago.) The measurements—based on scattered GPS signals bouncing off the ocean’s surface—would work regardless of how heavy the rainfall was within the intense hurricane eyewalls where the storms’ most damaging wind forces exist.

Wind speed measurements inside hurricanes can currently prove tricky without the help of “hurricane hunter” aircraft flying reconnaissance missions inside the storms. That’s because existing weather satellites have difficulty measuring wind speeds inside storms due to radio absorption from heavy rain.

CYGNSS would solve that problem with the help of GPS satellite signals used for location and timekeeping services all over the world. Many GPS signals simply end up bouncing off the Earth’s land or ocean surface. Such reflected or scattered signals can provide valuable scientific information about the roughness of the ocean’s surface inside a hurricane. CYGNSS can then use computer algorithms to deduce the wind speed and hurricane intensity from that data.

Aaron Ridley, a professor of space weather at the University of Michigan and a lead on the CYGNSS project, explained the advantages of using GPS signals in a blog post:

One of the brilliant things about the CYGNSS satellites is that they don’t carry a transmitter. Instead, they use GPS signals, which are being transmitted by GPS satellites all day, everyday, across the globe. Some of these radio waves are measured by your smartphone to tell you where you are, but the vast majority of the signals are just absorbed by the ground, or reflected back to space. CYGNSS measures those signals that are reflected back to space. A benefit to using the GPS signals is that those radio waves go right through rain, so that CYGNSS can take measurements in the middle of a hurricane, just where other satellites don’t work well.

An added bonus of using GPS signals is that the CYGNSS satellites don’t have to carry their own radio transmitters. That reduced the mission’s overall weight and saved money, according to Ridley. CYGNSS cost just US $102 million to develop, build and test; a relative bargain for a weather forecasting tool that could save lives and better prepare coastal communities against storm devastation. Ridley and his colleagues also plan to save on launch costs by crowding all eight satellites aboard the same rocket.

Each CYGNSS satellite can receive up to four distinct GPS signals scattered or reflected from the Earth’s surface. The satellites also have receivers to detect coherent GPS signals sent directly from GPS satellites as a basis of comparison with the scattered signals. 

After the 2016 launch, the satellites will spread out above the Earth’s tropical regions to monitor tropical cyclones in both the Atlantic and Pacific oceans. Many existing satellites have polar low-Earth orbits that provide fairly poor coverage of hurricanes in the tropics. CYGNSS would help fill that gap by deploying in a global band between 35 degrees latitude north and south of the equator.

The wide swath of CYGNSS coverage would also enable more frequent measurements of tropical cyclone intensity. Simulations suggest CYGNSS would have an average “revisit time” of about five or six hours; much better coverage than satellites orbiting over the Earth’s poles. Not bad for a fairly low-cost effort by University of Michigan researchers and NASA’s Earth Science division.

Have Tesla and Apple Disrupted the Auto Industry Past the Point of No Return?

As reported by Quartz: The challenge that the old manufacturers are having is that they have to cannibalize the profits of their existing lines by making completely new vehicles from the ground-up to compete. So they mostly won’t.

The future of cars is battery electric vehicles; that’s just a reality. There are a bunch of reasons for that, but here are a few:

1. Electricity from generation to wheel is a lot cheaper than any of the proposed intermediaries such as hydrogen fuel cell and air carbon capture + electrolysed hydrogen fake-gas, or diesel.
2. The grid is decarbonizing, but you can’t buy carbon neutral gas or diesel.
3. The VW scandal is just making public what a lot of people already knew: it wasn’t possible to make gasoline or diesel engines significantly better in the compromised space between CO2 emissions, NOx and other pollutant emissions, mileage, performance and engine longevity. That road, amazing as it has been, has reached its end.
4. Electric cars just outperform everything else. I ran across a video of a 1968 Mustang fastback conversion to electric that give it 1.94 seconds to 60 mph and a top speed of 174. Teslas, obviously, are currently reaching 60 in 2.8 seconds with heavy, five-seven passenger luxury sedans. The quickest to-production cars in the world are gas-electric hybrids, because you can’t be fastest without electric motors these days. And the pitiful handful of fuel cell vehicles on the road are sluggish, because batteries are much more efficient at delivering electricity than fuel cells.

If you don’t believe me, how about the CEO of Aston Martin?

“Palmer said it’s inevitable that the entire industry will shift over to electricity, if only because it’s the most plausible way to deliver the power drivers expect.”

To make a good electric car:

1. You have to throw away your frames. All of them. To build an effective, long-range, high-performing electric car, you have to start with something like the Tesla power slab at or below the level of the axles.
2. You have to throw away all of your engine management software; all of the experience built up on getting amazing compromises out of an internal combustion engine is irrelevant when faced with an AC or DC motor.
3. You have to throw away your internal combustion motor. No hybrid, serial hybrid, range extender BS. You have to throw it away. And start with the assumption that you are going to achieve range, fast-charging, and performance by committing to electric motors and batteries.
4. You have to throw away all of your traction control systems. They are all designed around the ludicrously widely varying power output of an internal combustion engine, which changes literally every microsecond at every change of speed and driver input because those engines have such narrow power bands. Instead, you can rely on tremendously straightforward power to your wheels which is much more finely controllable. Your actual traction control results will be much better, but all of the hacks you built up will be useless.
5. You have to throw away all of your emission controls experience, knowledge, technology, investments, and branding. It’s completely unnecessary.
6. You have to throw away your entire fuel storage and delivery system. The tank, the lines, the pumps, the injection systems, all of it. It’s all obsolete.
7. You have to throw away your body panels. They all depend on the frame, the gas tank, the mechanical linkages, and taking up space that they don’t take up anymore.
8. You have to throw away your seat mounting systems, and possibly your seats. They expect a lot of wasted space due to motor and transmission drive shaft hump and gas tank that just aren’t there anymore. They depend on a frame which doesn’t exist anymore.

Tesla discovered this the hard way by trying to base the original Roadster on the great little Lotus Elise. They admit, somewhat ruefully, that it would have been a lot easier and cheaper to start from scratch. And they had no existing technical debt, politics, or any other barriers to making the right decision.

If you do all of that, what are the implications for an automobile manufacturer?

1. Virtually all reusability between existing models and the new models is gone. This is a complete disruption of the economics of the car industry.
2. The most powerful divisions within car companies lose almost all power.
3. Massive investment in new frames and panels is required.
4. Massive investment is required in new control systems.
5. Completely new supply chain partnerships have to be forged.
6. All of the executives and engineers who have made your company great on the back of internal combustion engines have to accept that they are back to close to zero. A lot of the engineers won’t have any role in the new world, or any way short of significant re-education and starting from junior positions to stay employed.

So what’s going to happen to the car industry?

1. All of the majors will continue to deny the reality of the situation and continue to bet on cars with traditional frames, limited batteries, limited electric range and performance, and with internal combustion engines continuing to do the heavy lifting.
2. New competitors such as Tesla and Apple will kick the traditional cars to the curb in every way. More competitors will enter as it becomes obvious to corporations outside of the automotive industry that a massive disruption is killing the traditional car companies, and that they are incapable of responding to it. Traditional electronic and electric motor companies will start wrapping cars around their expertise. Motorcycle companies such as Lightning and Zero will be approached to build cars instead of bikes.

Can we see this happening already?

Yes, BMW’s strategy is what I’ve outlined above. Their two existing cars, the i8 and the i3, are both inferior to the Tesla in most ways, both require gas engines to get more than a rather pitiful distance (and space for the engines, gas tanks, lines, and pumps are all set aside in the i3, so it’s not like you can do anything useful like extend the battery pack). The frames pretend to being unique but they still expect a lot of traditional crap being there, which is obsolete. And their strategy of electric motor components in their entire range by 2025 still has no plans for real electric cars that could compete with Tesla, just more crappy electric cars with internal combustion engines for real driving.

And BMW is one of the more innovative and adaptable traditional motor companies out there.

Most of the current major car companies will fail because they can’t adapt to the disruption that electrification is bringing to their industry. They will refuse to cannibalize their other products. They will refuse to shift power and money to the electric divisions. They will refuse to engineer true electric cars because the economics don’t make sense until they don’t have any money to do it, anyway.

This pattern has played out innumerable times over the past 100 years. Remember RCA? Philips? Control Data? Burroughs? Kodak?

Why Self-Driving Cars Must Be Programmed to Kill in the Most Ethical Manner

Self-driving cars are already cruising the streets. But before they can become widespread, carmakers must solve an impossible ethical dilemma of algorithmic morality.

As reported by MIT Technology Review: When it comes to automotive technology, self-driving cars are all the rage. Standard features on many ordinary cars include intelligent cruise control, parallel parking programs, and even automatic overtaking—features that allow you to sit back, albeit a little uneasily, and let a computer do the driving.

So it’ll come as no surprise that many car manufacturers are beginning to think about cars that take the driving out of your hands altogether (see  “Drivers Push Tesla’s Autopilot Beyond Its Abilities”). These cars will be safer, cleaner, and more fuel-efficient than their manual counterparts. And yet they can never be perfectly safe.

And that raises some difficult issues. How should the car be programmed to act in the event of an unavoidable accident? Should it minimize the loss of life, even if it means sacrificing the occupants, or should it protect the occupants at all costs? Should it choose between these extremes at random?

The answers to these ethical questions are important because they could have a big impact on the way self-driving cars are accepted in society.  Who would buy a car programmed to sacrifice the owner?

So can science help? Today, we get an answer of sorts thanks to the work of Jean-Francois Bonnefon at the Toulouse School of Economics in France and a couple of pals. These guys say that even though there is no right or wrong answer to these questions, public opinion will play a strong role in how, or even whether, self-driving cars become widely accepted.

So they set out to discover the public’s opinion using the new science of experimental ethics. This involves posing ethical dilemmas to a large number of people to see how they respond. And the results make for interesting, if somewhat predictable, reading. “Our results provide but a first foray into the thorny issues raised by moral algorithms for autonomous vehicles,” they say.

Here is the nature of the dilemma. Imagine that in the not-too-distant future, you own a self-driving car. One day, while you are driving along, an unfortunate set of events causes the car to head toward a crowd of 10 people crossing the road. It cannot stop in time but it can avoid killing 10 people by steering into a wall. However, this collision would kill you, the owner and occupant. What should it do?

One way to approach this kind of problem is to act in a way that minimizes the loss of life. By this way of thinking, killing one person is better than killing 10.

But that approach may have other consequences. If fewer people buy self-driving cars because they are programmed to sacrifice their owners, then more people are likely to die because ordinary cars are involved in so many more accidents. The result is a Catch-22 situation.

Bonnefon and co are seeking to find a way through this ethical dilemma by gauging public opinion. Their idea is that the public is much more likely to go along with a scenario that aligns with their own views.

So these guys posed these kinds of ethical dilemmas to several hundred workers on Amazon’s Mechanical Turk to find out what they thought. The participants were given scenarios in which one or more pedestrians could be saved if a car were to swerve into a barrier, killing its occupant or a pedestrian.

At the same time, the researchers varied some of the details such as the actual number of pedestrians that could be saved, whether the driver or an on-board computer made the decision to swerve and whether the participants were asked to imagine themselves as the occupant or an anonymous person.

The results are interesting, if predictable. In general, people are comfortable with the idea that self-driving vehicles should be programmed to minimize the death toll.

This utilitarian approach is certainly laudable but the participants were willing to go only so far. “[Participants] were not as confident that autonomous vehicles would be programmed that way in reality—and for a good reason: they actually wished others to cruise in utilitarian autonomous vehicles, more than they wanted to buy utilitarian autonomous vehicles themselves,” conclude Bonnefon and co.

And therein lies the paradox. People are in favor of cars that sacrifice the occupant to save other lives—as long they don’t have to drive one themselves.

Bonnefon and co are quick to point out that their work represents the first few steps into what is likely to be a fiendishly complex moral maize. Other issues that will need to be factored into future thinking are the nature of uncertainty and the assignment of blame.

Bonnefon and co say these issues raise many important questions: “Is it acceptable for an autonomous vehicle to avoid a motorcycle by swerving into a wall, considering that the probability of survival is greater for the passenger of the car, than for the rider of the motorcycle? Should different decisions be made when children are on board, since they both have a longer time ahead of them than adults, and had less agency in being in the car in the first place? If a manufacturer offers different versions of its moral algorithm, and a buyer knowingly chose one of them, is the buyer to blame for the harmful consequences of the algorithm’s decisions?”

These problems cannot be ignored, say the team: “As we are about to endow millions of vehicles with autonomy, taking algorithmic morality seriously has never been more urgent.”

Ref: arxiv.org/abs/1510.03346 : Autonomous Vehicles Need Experimental Ethics: Are We Ready for Utilitarian Cars? 

Transcontinental US Record Aboard Tesla Model S P85D with Autopilot Claimed

As reported by GizMag: Earlier this year, Carl Reese and Deena Mastracci made a 3,011-mile (4,846-km) drive from Los Angeles to New York in 58 hours and 51 minutes in a Tesla Model S P85D to set a record for the coast-to-coast journey for an electric vehicle. Now Reese and Mastracci, joined by Alex Roy, have beaten that record with the help of Tesla's new Autopilot software.

According to the Transcontinental Drivers Association, the yet-to-be-verified record-breaking drive left Redondo Beach, California on October 18 at 9:15 pm PST and arrived at the Red Ball Garage in New York on October 21 at 10:03 am EST – making for a distance of 2,995 mi (4,820 km) and a time of 57 hours and 48 minutes.

The drive relied on the newly-released Tesla Autopilot software, which was made available by software update to Tesla S and X owners on October 15. This provides semi-autonomous capabilities so the vehicle can be driven without touching the pedals or steering wheel on the highway.

The car uses cameras and radar to keep an eye on other vehicles, potential hazards and road markings. It can execute lane changes with only driver supervision, dodge swerving vehicles, park automatically, and prevent drivers from making potentially dangerous moves like driving over the divider.

The Association says that both the departure and arrival of the Tesla S were recorded by witnesses and the GPS tracking data will be submitted to verify the record.

"Deena and I have been planning this autonomous record for over 11 months," says Reese. "We knew we wanted to be the first group to make the cross-country attempt using the autonomous technology."