[lucasjung]

>In just a couple of years the DARPA challenge yielded cars that can drive themselves in complex urban environments.

I imagine with sufficient smart people working on it, flying airplanes in relatively uncluttered sky would yield results faster.

As I mentioned, many of the tasks of flying airplanes have been successfully automated. However, there are significant complexities that pilots must deal with that don't apply to cars, and most of those still require human intervention, especially in-flight emergencies. If your car engine quits, you pull over to the shoulder, turn on your hazard lights, and call AAA. If your aircraft engine quits, the response is much more complex. If the power steering on your car quits, you do pretty much the same thing as described above. If your flight controls malfunction in an airplane, the response is much more complex. If your car catches on fire, you do the same as above, plus get out. If your airplane catches on fire, you've got a much bigger problem. I could go on, but I think that gets the idea across.

Also, the sky is not "relatively uncluttered." There are a lot of airplanes flying at any given moment, and most of them are concentrated onto airways. It gets even worse in the terminal area: lots and lots of planes coming and going to and from many different directions, all in a very small piece of sky.

>As for see-and-avoid, perhaps it works for obstacles on the ground, but other aircraft are moving so fast, is it really feasile to eyeball them before they are on you? Perhaps in pursuit, but at any significant angle they flash past at hundreds of miles an hour. Only radar etc has a chance of identifying/avoiding at those speeds.

I am alive today because, on countless occasions, I and my fellow aviators have looked outside, seen another aircraft, and maneuvered to avoid a potential collision. I think that you really don't have an accurate mental image of how this works, so I'll try to explain a little bit:

Consider two airliners cruising at 424 kts each, one heading due West, the other due North. The rate of closure is 600 kts. Depending on the atmospheric conditions, they will be visible to each other at about 10 nautical miles, which gives them an entire minute to spot each other and maneuver to avoid a collision. Even if it's two sueprsonic fighters flying right at each other at 600 kts each, they still have thirty seconds to spot each other. A much more realistic scenario would involve two aircraft in the terminal area, where they would be moving much more slowly, giving them much more time to see each other and respond.

I think the most dangerous situations are where two aircraft are on headings that are different by less than forty-five degrees: they are basically next to each other, closing from each other's sides where they are less likely to be spotted. The rate of closure is probably very low, but that's more than made up for by the awkward situation in regards to field of view from many cockpits.

[yread]

> If your airplane catches on fire

I think that unmanned plane has actually a much better chance of surviving fire, it could have an inert atmosphere, or it could be unpressurized so fires would be much less frequent. Also fires happen mostly on freight planes (lately UPS and Asiana) and freight planes would be probably easier to certify for unmanned flying than passenger planes.

> I am alive today because, on countless occasions, I and my fellow aviators have looked outside, seen another aircraft, and maneuvered to avoid a potential collision.

Isn't this what Traffic collision avoidance system (TCAS) is for? The pilots already have to do as they are told by TCAS (after the collision over Switzerland). Surely managing traffic of obedient agents with known limits of performance isn't that hard - if all the planes were unmanned there wouldn't be problems

However, the points that you mentioned about other emergencies and passenger traffic still stand.

[lucasjung]

>it could have an inert atmosphere

This would be very costly to implement, and probably very heavy. That being said, inert gases are used in places where arcing is likely (e.g. radar waveguides).

>or it could be unpressurized so fires would be much less frequent

I really don't think this would have a significant impact on the frequency of fires. Plus, a lot of avionics need particular environmental conditions, in some cases including pressurization.

>Also fires happen mostly on freight planes

High-power electronics, such as military radars, also pose an increased risk of fire.

>freight planes would be probably easier to certify for unmanned flying than passenger planes.

If you only cared about the contents of the plane, this would be true. But what happens when a flaming ball of wreckage that used to be an unmanned freight plane plows into a suburban neighborhood, a school, or a downtown skyscraper?

>Isn't this what Traffic collision avoidance system (TCAS) is for? The pilots already have to do as they are told by TCAS (after the collision over Switzerland).

TCAS isn't all it's cracked up to be. First of all, it only works if the other plane has a transponder (there are still plenty of light civil aircraft out there with no transponders). Second, there are different versions out there with different levels of accuracy. The older kind are not very accurate at all, and basically serve only to give the pilot a general idea of where to look in order to spot the traffic and avoid the collision the old-fashioned way. The more accurate kind only works if both aircraft involved have the necessary equipment.

As for the collision over Switzerland, the reason for that rule is that the collision happened in part because TCAS and ATC gave conflicting instructions: one told plane A to go up and plane B to go down, the other told plane A to go down and plane B to go up. One crew did what TCAS said, the other did what ATC said, and they both ended up descending. So the reason for this rule isn't that TCAS is a magical panacea for midairs, but rather a way to consistently resolve any future such conflicts between TCAS and ATC.

>Surely managing traffic of obedient agents with known limits of performance isn't that hard - if all the planes were unmanned there wouldn't be problems

If all the planes were unmanned, then managing traffic would be much easier, but that still leaves other issues, like where a plane ends up when it malfunctions and crashes. It would also require a wholesale changeover that simply isn't plausible.

[rohit89]

> TCAS isn't all it's cracked up to be. First of all, it only works if the other plane has a transponder (there are still plenty of light civil aircraft out there with no transponders).

Why hasn't it been made mandatory that all aircrafts should have a standardized transponder ? It scares me a bit that, at the end of the day, we rely on pilots avoiding collisions by sight.

[lucasjung]

>Why hasn't it been made mandatory that all aircrafts should have a standardized transponder ?

In some parts of the world, it may be. For example, I don't know if Europe allows for aircraft without transponders. Even in the U.S. you must have a transponder to enter certain types of airspace (e.g. the airspace around major airports). As far as I know, no matter where you are in the world, you must have a transponder to fly IFR.

Installing a transponder is a non-trivial expense, especially in older aircraft (which are the aircraft most likely to not have transponders). For a lot of small aircraft in the U.S. this would represent an unnecessary burden on the owners. For example, crop dusters: they typically fly around low and slow in areas with very little traffic, under day VFR conditions, so they have no need to interact with ATC and therefore no real use for a transponder.

>It scares me a bit that, at the end of the day, we rely on pilots avoiding collisions by sight.

We don't rely solely on this: we have transponders (with TCAS in some cases), ATC radar, and (in some cases) airborne radar. All of these tools help us to avoid collisions. Unfortunately, none of them are 100% effective, and in most of the situations where they all fail, the good old Mark I Eyeball usually saves the day. See-and-avoid isn't perfect, either (if it was, we'd never have midairs), but it is still the most effective tool available for avoiding an impending collision.

[spitfire]

Because they cost an arm and a leg for small aircraft. Think $20K.

Unfortunately regulations and liability costs make anything in aviation expensive. So most small planes are running around without tcas.

[marshallp]

Your objections are about things that a human can't do much about either, or if they could, a computer could do just as well or better.

(If your plane engine quits - what would a human do? whatever it is, a computer could be programmed to as well. Near collisions - a constantly vigilant computer vision system watching out the window is more likely to avoid collision than a pilot with 30 seconds of reaction time.)

[lucasjung]

>If your plane engine quits - what would a human do?

This depends on a lot of factors. Some of them are things that a computer can probably be programmed to consider properly (e.g. specific cause of failure). Other factors require judgment, such as your more general situation: depending on where you are and what else is going wrong, you might chose to land the airplane at the nearest appropriate airfield, or you might choose to continue on to an airfield farther away where you can get better support while attempting to restart the failed engine on your way there, or you might decide that you have to get it on the ground right now, and that empty farmer's field over there looks good enough.

In case of more catastrophic failures like fire, computers become even more problematic because the sensors they depend on for inputs can be damaged or destroyed, leaving them with insufficient information to act properly.

>Near collisions - a constantly vigilant computer vision system watching out the window is more likely to avoid collision than a pilot with 30 seconds of reaction time.

People with a lot of money and resources have been trying to develop a fully autonomous system for avoiding impending collisions. They will almost certainly eventually succeed, but so far they haven't even come close to being as visual scan by human pilots.

[EDIT: resolved ambiguous use of "field.")

[marshallp]

A billion dollars was spent by the eu in the 80s on self-driving cars. They didn't completely succeed. It looked like noone would succeed for 30 years. And yet, bang, when the competition's opened up, a couple of guys from stanford do it.

I believe the technology to solve the problem is out there, it's just a matter of the right people trying at it.

Computer vision is close to being solved. Look at kinect, kinect 2/google goggles. People inside google/microsoft are racing at this. I'm sorry, i have to disagree with your pessimistic attitude on this.

With regard to fire - fire can kill human pilots too. With sensors, you can create a multiply redundant system - put in 20 extra sensors. With humans it's not possible.

[lucasjung]

Nothing you say addresses my broader point that there are currently too many situations in aviation where the complexity of the decisions involved exceeds our current capacity for automation.

A billion dollars was spent by the eu in the 80s on self-driving cars. They didn't completely succeed. It looked like noone would succeed for 30 years. And yet, bang, when the competition's opened up, a couple of guys from stanford do it. I believe the technology to solve the problem is out there, it's just a matter of the right people trying at it.

If they tried in the '80s and the guys from Stanford did it in the 2000's, then it was almost 30 years before anyone succeeded. I think that success had a lot more to do with technology maturing over time than it did with "the right people trying at it."

>Computer vision is close to being solved. Look at kinect, kinect 2/google goggles. People inside google/microsoft are racing at this.

This really depends on what you mean by "solved." Kinect is a hell of a long way from what you would need to avoid collisions in a 3D space. Kinect basically just has to deal with the outlines of objects at a relatively narrow set of distances. When your sensor is moving in three dimensions and you are trying to track an object that is also moving in three dimensions it gets a heck of a lot harder, even if you are using radar (which gives you range). If you're trying to figure out range based on the apparent size of an object of unknown actual size, it gets even harder.

>I'm sorry, i have to disagree with your pessimistic attitude on this.

I'm actually quite optimistic that it will happen, just not for many years yet.

>With regard to fire - fire can kill human pilots too. With sensors, you can create a multiply redundant system - put in 20 extra sensors. With humans it's not possible.

If your engine is out on a wing and it catches fire, the fire sensors will tell you so, and shortly thereafter they will most likely be destroyed and tell you nothing further. An engine on fire out on the wing is not going to burn up the pilot. The pilot can look out the window and quickly and easily assess the condition of the engine and the wing: did it burn out, or is it raging out of control, or maybe there are subtle signs that indicate something in-between? Maybe with enough fire sensors scattered all over the plane a computer could make a similar assessment, but you're talking about a lot of extra money and weight, and you still have the problem that your sensors are going to burn up shortly after going off and then you have no idea if the fire has gone away or if it has just stopped spreading. Someday maybe you can give the computer a camera to "look" at the wing to make the same kind of assessment that a human pilot can make, but that is a very long way off.

[marshallp]

You have two main pessimisms

- computer vision problems (e.g. plane catches fire, how do you tell how much fire etc.)

- tracking other objects in 3d while in moving in 3d at high speed

The question is - can humans do this? If yes, computers can do it eventually. The only question is how long away is this. What we know from machine learning, is that data is important. If you can gather enough data you can do anything. So really, your problems are a question of data collection. It is not a technically difficult problem. (By the way, one of the problems you have in aerospace is, is that you're control theory heavy rather than pro-ai, which means you end up not being able to solve the difficult problems.)

Also, the eu 80s project ended around early 90s, and the grandle challenge win was only 15 years later, not 30. Had the challenge been tried 5 years earlier, it would have worked. The algorithms and hardware was already sufficient.

[lucasjung]

I hardly think it's pessimistic to say, "this problem is really hard, and it's going to take years to solve." I'm confident that they will be solved, which some of my peers might even consider a naively optimistic attitude.

>The question is - can humans do this? If yes, computers can do it eventually.

This logic is deeply, deeply flawed. I happen to believe that computers can eventually perform the tasks under discussion, but "humans can do it" is not one of the reasons why I believe that.

>So really, your problems are a question of data collection. It is not a technically difficult problem.

When it comes to tracking airborne targets with airborne radar, data collection actually is a technically difficult problem. The combination of waveform, antenna design, transmitter design, receiver design, tracker design, etc. present a set of engineering tradeoffs in effective range, range resolution, azimuth resolution, weight, size, flase positive and false negative rates on radar returns, and other performance characteristics. Even the very best airborne radars provide data which is limited, especially in terms of accuracy and precision.

>By the way, one of the problems you have in aerospace is, is that you're control theory heavy rather than pro-ai, which means you end up not being able to solve the difficult problems.

A little more about my background: my BS is in EE, with a specialization in microcomputer interfacing (I took a lot of CS classes). In grad school, my stability and control prof had actually done some pioneering work in incorporating non-linear logic into stability and control systems (don't try this at home, kids). In addition to stability and control, my other focus for my MS was avionics. The prof who taught most of my avionics classes was actually from the CS department (his undergraduate background was EE, with a specialization in radar). One of the things that kind of surprised me about aero, having come from EE, was how broad the discipline is. Before going back to school for aero, I thought that getting a degree in aeronautical engineering would be primarily about aerodynamics, with a smattering of other stuff. Instead, I discovered that everyone gets a little bit of everything (aerodynamics, propulsion, structures, stability and control, avionics), and then specializes in one or two particular areas. By the PhD level, people who have specialized in areas other than aerodynamics have largely forgotten most of what they learned about it as undergrads. It's an incredibly heterogeneous field: propulsion and structures guys have more in common with MechEs than with other AeroEs; avionics and stability and control guys have more in common with EEs than with other AeroEs; etc. So to characterize the discipline, or any individual within it, as "control theory heavy rather than pro-ai," displays a deep misunderstanding of the character of the community. I guarantee you that there are plenty of AI experts working in the aero field.

>Also, the eu 80s project ended around early 90s, and the grandle challenge win was only 15 years later, not 30. Had the challenge been tried 5 years earlier, it would have worked. The algorithms and hardware was already sufficient.

This just reinforces my broader point: success came not as a result of some innovative genius applying a novel new approach but rather because the technology had matured--over the course of several years--to the point where success had become not only possible but likely. Radar tracking is currently experiencing big advances for that same reason. The theory behind Space-Time Adaptive Processing (STAP) has been around for decades, but the available technology has not been up to the task of implementing it effectively. In the past we've resorted to less effective tracking methods such as MTI, but in the last decade or so the technology has finally made STAP reasonable to implement.