What makes you think that sharing cat pictures isn't a trillion dollar industry?
Last time I check photo sharing apps and bird-in-pig games fetch and sell for more money than life saving cancer drugs.
There will be no more awkward social guessing games!
There might be little tricks you could do to make an autonomous car yield. Or if you see one about to park, maybe you could get really close to it, and it would try to find another spot instead of fighting for the spot. Or pedestrians might carelessly walk in front of it, knowing it will stop for them.
It will also be interesting to see how the technology changes as whole fleets of them are deployed. They will constantly be sending each other data: pothole detected on highway; I'm ahead of you and have braked suddenly; this road is congested, use alternate route; is there a parking spot close to my location?; tsunami warning - all cars go to high ground.
I guess someone will hack the software in his car to send a "road blocked" signal, so that he can drag race a friend on fifth avenue at rush hour. I also expect that it will become illegal to hack one's own car soon after that.
Of course you would need some form of hazard signaling which could be open to abuse (although it could be abused by human drivers anyway).
You can always monitor what cars are doing and if you find that some particular persons car is always behaving in a way that causes problems then you can potentially take legal action against them.
Also it is strange they are not working on a kind of transponder, that could be used between nearby cars to coordinate maneuvers(maybe I missed it on this article, but I think I read about somebody was developing it) . It will be usefull once robocars are more common.
Once self-driving cars become more commonplace, issues with eye-contact with pedestrians will naturally seek their own level as comfort ensues.
When a pedestrian jaywalks in front of an oncoming vehicle, he's depending on the fact that the driver isn't distracted, and can pick him out of the visual clutter at the sides of the road. I'm a good driver, but I still find that it can be difficult to spot a pedestrian who is standing among parked cars at dusk, especially considering that my rear-view mirror obstructs some of my vision further up the road on the right side, as it does for a lot of drivers.
An automated car should always be paying attention (especially since it can pay attention to lots of things at once) and doesn't have to depend on human eyesight to detect potential collisions - it can utilize lasers, infrared and other sensors.
I really would prefer to face the google.Canadian version rather the google.Paris or google.Rome tuned examples
How does self-driving cars fit in to Google's plans?
ETA: Downvoted for asking a serious question? WTH?
You summon a self-driving taxi to take you to Bob's Bistro--known throughout the city for its steaks, and your call is serviced by a car using Google self-driving software. Google knows who you are and knows where you are going.
The car's route planner determines that there is a route that is within 10% of optimal that takes the car past Sam's Steakhouse, and Sam is currently paying for a Google ad campaign targeted at self-driving passengers. The car takes you past Sam's where Sam has a hard-to-miss sign touting reviews that say his steaks are better than Bob's.
Google is clever so the car might even time this so that you'll hit a red light in front of Sam's to give you a better chance of seeing Sam's sign. If the sign is electronic the message you see comparing Sam's to Bob's might even be specifically targeted at you. A moment later when the next cab goes by, carrying a passenger to Carl's Crab Shack, that sign might have a message touting Sam's amazing surf'n'turf compared to Carl's.
Right now, you go to Google when you want to drive more traffic to your website. With self-driving vehicles, you'll go to Google when you want to drive more traffic to your brick and mortar site.
Generally, I'd expect that an automated taxi would operate under rules similar to current taxis - the obligation would be to take the customer to the destination via the most direct route specified, unless otherwise directed.
Taking someone on another route might constitute kidnapping - you're essentially transporting them against their will to somewhere they did not ask to go.
Further, wrt the optimal/most direct route thing:
* the algorithm could be tweaked to "adpresence" en-route fairly easily
* "most direct route" is an ambiguous term. There could be two routes that involve almost same distance in miles, but the slightly longer one is likely to take less time. Which constitutes most direct? It turns into an optimization problem, possibly with no obviously optimal point (particularly when you account for fuzziness needed to deal with unexpected traffic patterns, accidents, etc).
* Finally, the ad-laden route could be a free ride, whereas the "direct" route could be paid. This may or may not get around regulations, but as long as the time delta was not significantly bad, I would choose the ad route.
If you get in a cab and say "take me to $x" it is the cab driver's responsibility to take the best route. However, since metering is distance AND time based, there is a lot of wiggle room in what best route means. It is always an optimisation problem, and relies on imperfect data of the future conditions of the route. Further, in most american cities, there are many routes that are no more or less direct, as a result of the grid system. Therefore the car taking you on the route that goes past paid displays is not kidnapping. It is choosing 1 of n equivalent routes - the one most profitable for the operator, while still meeting the criteria of the user.
Further, even with advanced traffic and condition understanding available to a robotic car, the ability to choose optimal path will probably improve significantly, even when the small fudge factor to go past advertising is accounted for. So what if it is 30s less optimal on your ride to go past the advertised place, when the human cabbie would have chosen a route adding 5 minutes?
Obviously this can vary by municipality, but in most cities drivers are required to take the "most direct" route, rather than the "best" route, if for no other reason than the latter would be so subjective as to be useless for enforcement purposes.
So if you're in a New York taxi (for example), the driver in theory isn't allowed to take you off the most direct route without your permission, even if another path would be faster.
I'm at (1,1) and I want to get to (4,4). Assuming a restrictive interpretation of most direct and no one-way streets factored in, there are still two equally direct and valid paths:
(1,1) -> (1,4) -> (4,4)
(1,1) -> (4,1) -> (4,4)
Which is most direct? If the cab driver chooses to go with the later because his buddy pays him to go past the billboard at (3,1), what's to stop him? What's wrong with that?
 If most direct means "shortest path", then there are many more equivalent routes.
 One way streets also offer a nice choice of where to do turns around a block under favorable circumstances. Similarly road construction offers extra choices by detour.
Besides, it would not necessarily even have to redirect you past a different location, it could just stream an advert to the speakers in the car.
It could also be possible that some routes would be subsidized, like you could enter the location of one restaurant and a rival restaurant could offer to cover your fare if you went to them instead.
Another aspect is that you would need an easy way to split the fare amongst multiple passengers, I almost never take a taxi if I am traveling alone.
I'm sure any driverless cab would have the ability to ask to get out, but technically one might argue you're kidnapping someone as soon as you take them off the route they requested for any reason, if if there's an "opt-out"... at the level of an individual cab ride and human driver it's moot, but if you're operating a fleet of thousands of cabs, doing that over millions of rides, it could easily turn into a class-action suit.
Anyone play with the numbers? average web use vs. average AdWords profit vs. typical commute?
- Active internal displays that push ads based on detailed mapping information.
- Delivering you to a particular location after you look it up on Google. What's the Price per Delivery (PPD) on AdWords?
Bear in mind that there's a completely alternative model for car ownership; with fully automated vehicles, there's no absolute requirement for people to 'buy' a car - there could be shared metropolitan resources of cars, which would arrive and pick you up 'on demand' (much like a shared taxi service, subsided by subscription)
Also, given that Google would probably know the locations of all the cars at any point in time, they could also get very, very detailed traffic flow information. This they could use to further optimize traffic - i.e. load-balancing traffic through different routes - but also this could potentially be sold to other transit agencies, or even tied to demographic data to suggest where stores should open new premises.
Probably some more ideas/data sources and uses in here that I haven't considered too :)
I'm going to take an optimistic tack and say they're doing this for the PR benefits of being seen as creating new technology that gives people tools they never thought they could have, somewhat like Microsoft has done with the Kinect.
On the other hand cars are a great way of signaling things (like wealth, trendiness etc) and I think people like the idea of having their car.
To the contrary, it makes for the biggest crowdsourcing project ever.
It must be because they have some dire plan to find out where I get my tacos!
But they're not and aren't going to be overnight; what makes more sense is to gradually introduce the features a little at a time so that the move to complete autonomy is a small step instead of a leap. First, automatic parking. Then, collision detection warnings. Next, lane assist that steers you back into the lane when you drift. In the next few years, you'll start seeing "smart cruise control" that will drive for you on well-marked roads in mapped areas.
"Cadillac To Release Self-Driving Cars By 2015"
Maybe 10-15 years from now we'll be at the complete autonomy point.
No company is indispensable in the evolution of a market, but I think it is possible that abandoning the incremental approach and starting with the full problem will turn out to be the one to get us all the way there, instead of a car that can correct oversteer and warn us in 90% of situations that we're about to make a mistake. Of course, like with many products, once one group shows the way, the only thing holding everyone else back is patents and data (especially geographic in this case).
Robust? yes. Adaptive? yes. Complex? not really. Computer vision, road/object/hazard detection and avoidance and the like much much harder problems to solve.
What gave you that impression?
What do you define as a non-traditional company?
While I believe there's room for other companies to develop self-driving navigation systems, I think the Android example is pretty apt.
It's interesting to think about when self-driving cars will actually be in stores. By then, all navigation systems will meet strict safety guidelines and some standardised tests.
If all self-drivers are equally safe, the AI's driving style will become a differentiating factor. It seems to me like Google has an advantage in this type of development, although the future can certainly prove me wrong.
Of course that would depend on getting all the cars on the road to be self-driving - you don't want your crashless 500 pound Google car getting smashed by a behemoth human-driven Smart Car.
But if you significantly reduced the materials cost in the car, that opens a big margin for Google to trade in.
I guess you will need at least 100k vehicles, but with that number of vehicles, that $1B per year starts to look cheap ($10k times 100k = $1B)
The Google stuff is pretty cool, I notice they don't show the early videos of people running around the parking lot trying to get it to stop :-) But such things are to be expected in development. This is a technology I look forward to as it would simplify a lot of things.
Google and NASCAR produced a joke video about self-driving race cars:
* More info:
That's pretty interesting. I would have thought that they needed data at a faster rate than 15fps.
Of course the robocar isn't allowed to drive like an average human. It'll have to drive like a perfect human. Seems like that should be doable.
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Human reaction time is only about 5-10fps, so its not like 15fps sensor acquisition is worse (assuming the machine can react very quickly once it has sensor input.)
Perhaps it would make sense for government to step in like it did with electrical cars.
Edit: It seems the LIDAR they use costs 75000$. :-/
You are replacing a taxi drivers wages with sensors and mapping essentially. Not to mention extremely-well paid surgeons who clean up after drunk driving accidents, theatre nurses, insurance costs, cost of mechanics.....this technology has so many implications it's hard to visualise them all initially. It's going to be extremely disruptive to some industries, and a boon to others (e.g. where I live, rural pubs are in trouble. This could change all that - "get driven home at 200mph in perfect safety after a night getting smashed!" etc.)
I imagine a scenario where trucks will drive themselves at night, over the long distances, when few people are around, and when they get close to cities, a real truck driver will jump in and navigate to the end destination, in the day, when there's a lot of people around.
And not until people are used to self-driving trucks will the tech be available for personal transportation, even though the technology will be good enough and increase safety before that.
(In the same way self-flying airplanes will come to cargo transports first, and human transport much later)
Bringing down the cost of the LIDAR will be one major task, the other will be making this untouchable in the environment, IMO.
You could probably screw up the samples that would be taken from wherever your beam hits on the mirrors. But you could also shine a laser in someones eyes while they're driving and seriously impair them as well.
That being said, laser range-finding works well on diffuse surfaces; this is because when diffuse surfaces reflect, they reflect the incoming light in a broad hemisphere (or cone) which sends the laser pulse out in many directions. Consequently, the surface to measure can be at a variety of angles and still be picked up by the LIDAR sensors (the sensor doesn't care about strength, only time-to-return)
So in terms of "weirdly reflective" surfaces out there, almost everything is diffuse enough for LIDAR to work well. Car hoods, carbon fiber, chrome wheel covers, etc. The only exception is glass, where generally lasers travel straight through and don't return to the sensors. So LIDAR actually detects "holes" in these situations, as if other cars were driving with no windshield an all their windows down.
So the only real risk would be a large plane of glass in the middle of the highway with completely normal road behind it. LIDAR would miss the glass, and the cameras would not be able to see it either. Most real drivers would fail at that too though :D
So surely the automated car, when it sees data it does not expect, does not stop, because it must see data it does not expect often through multiple bounces, right?
The transition model of the cars environment is known, so it can reason that "there is a very small chance this reading represents a real object and is not noise, because i did not detect anything near this position over the last 20 frames, so I'm going to assign a very low probability to it." Hence you can clean up the data really well because you're measuring an outdoor environment, not a meteor shower (or anything else where objects could appear and disappear every frame due to high velocity).
Having said that - there is no real difficulty in making Lidar very cheap if you wanted to - it's all solid state
The expense idea makes no sense. This is software we're talking about, so the marginal cost is always going to be 0. It's also software that's likely going to have to through very expensive certification procedures to be allowed on the roads (or to be allowed by insurance companies). How could it possibly be economical for a manufacturer with 2% market share to do this on their own?
So could a smallish manufacturer at least build a better one, if not cheaper? It's hard to see why you'd expect that. Maybe if 20 of them tried, a couple of them would end up with a better technology than what could be bought. But even if that's true, it's not going to brighten the day of the remaining 18 manufacturers who ended up with substandard software. There's one obvious exception (regional differences - maybe Japanese drivers have very different preferences from German ones, or something).
Are there any integration benefits from making the software for self driving cars in-house? I can't think of any, but I'm not too familiar with the automotive industry. Maybe there's something obvious I'm missing.
Of course there's no guarantee that even if the future ends up as one of a few major in-house systems and a couple of successful publicly available ones, Google's solution would be one of the successful ones. Still seems like it's worth a shot.
In the mean time, on a completely non-commercial separate track, AI researchers should try to do more with less. Driving using only visible-light sensors is a challenge. AI is pushed forward by taking on challenges exactly like this, let's see the push continue.
These two tracks may in fact intersect. When your LIDAR and radar are caked with ice and mud, you'll want the car to be able to drive visually at least to a safe stopping point.
Cars are far-and-away the biggest killer of people in my age group. I sincerely hope that we are not going for true parity, and they will not end up driving like we do.
Using a couple stereoscopic pictures to get the lay of the land is a very, very error-prone process. Humans have to make do with it because we have very limited sensory equipment available to us. Computers can and should make use of the vastly superior technologies that they have at their disposal. One of the main points to this whole enterprise is to make better, safer cars by replacing the primary point of failure behind most collisions. Deliberately crippling the system in an effort to slavishly imitate the thing it's supposed to replace would be completely missing the point.
Commercial driverless cars will blow humans out of the water in safety and reliability. That is the goal and should be goal. To achieve the goal multiple sensors can and should be used.
But separately AI researchers will continue to improve and evolve their algorithms. One avenue for improvement is to operate with fewer sensors. A human driver can drive passably well on any road without LIDAR or radar or GPS. In time computers can and should be able to do the same. We will benefit from that capability, even if in general driverless cars make use of other sensors.
It uses all-electric vehicles and they even have a convoy mode where each car follows the lead vehicle closely to maximize the number of passengers and minimize wind resistance.
The guidance system is pretty primitive - it's all done in hardware with steel wheels on steel rails - but it makes it relatively difficult for it to go off-the-rails.
But a self-driving car that uses only visual sensors is clearly possible in the long run. And having that technology would only benefit multi-sensor cars. What if one or more sensors breaks when you are doing 85 mph with the whole family asleep? I'd certainly welcome the resiliency to operate on less input.
There are too many situations where one type of sensing isn't good enough (e.g. lasers scatter off snow and can't penetrate fog/dust, radar can get saturated by multiple corner reflectors, visual sucks at night, IR sucks in bright sun, etc). To reduce cost visual-only might be a good way to go, but it won't be versatile enough to cover all the necessary scenarios.
I'm just advocating we do the research, create some visual-only cars as proof of concept, solve those thorny AI problems. It's an artificial constraint, one which will produce engineering innovations which can then be applied back to real world products.
Sure our eyes have great resolution and batteries-included depth perception, but they can't see around 360 degrees around the car at 15 fps. Pros & cons
Policy search is AI. =)
Eyes not only have great resolution and depth perception, but are attached to an amazing pattern processing machine that looks forward in time to estimate the next set of perceptions. They're also very environment-invariant - sun, snow, heavy rain, fog, etc would screw a camera, but human eyes can handle it relatively gracefully.
My point was just to defend humans from the hyperbole that we drive all horribly today. We have cumulatively driven trillions of kilometers. Our cities and entire economies function because for the most part when you get into a car, you can expect to arrive at your destination. This is no small feat. But yes I look forward to self-driving cars vastly improving on "okay".