Nobody Wants to Let Google Win the War for Maps All Over Again
bloomberg.com
bloomberg.com
It seems kind of tautological that they're using autonomous vehicles to create maps because they need maps for autonomous vehicles.
Yeah, I know, specialty equipment... but still.
Actually, what seems really odd is that new maps are that big of a deal. The cars need maps for normal navigation, sure, but you wouldn't expect that they would rely on anything too precise for safety reasons alone. The cars need to be able to adapt to possibly changing conditions and can't misbehave (at all) just because a street closed, cones are on the street, etc.
Unlike conventional digital maps, self-driving maps require almost-constant updates. The slightest variation on the road—a construction zone that pops up overnight, or a bit of debris—could stop a driverless car in its tracks. “It’s the freak thing that happens that’s going to make autonomous not work,” said McNally, the analyst.
I would call an autonomous vehicle that couldn't handle some debris "fundamentally broken".
Seriously, this mapping thing smells like a boondoggle.
Unless your "true-AI" stops to ask locals for directions, its going to need some sort of GPS. Can't say I'm looking forward to arguing with my car about how it should have taken a left on Main St, instead of a right.
GPS ≠ navigation assistance. You can infer where you are on a conceptual map from reading your surroundings, especially signage. Getting a latitude/longitude estimate from the GPS network and trying to match it with an overly precise and possibly out of date map isn't the only way to infer your current position. It's only useful when you don't already know where you are, and computers are good at precisely remembering the path they took from the last known observed reference.
Plus, self-driving cars need to be aware of their surroundings, and not solely rely on blindly following a hyper-precise map as a prescription of the road details ahead. Having the local observations become the canonical precision knowledge, and keeping the map as conceptual knowledge of how roads connect places, implicitly gains a lot of this sort of benefit.
It's interesting to note that the first in-car navigation system used no GPS: it relied solely on inertial navigation and map-fitting to determine its location. For navigation, an autonomous car needs something like that as backup for GPS. All the actual driving needs to be done with on-board sensors, though.
I'd be surprised if the lidar units aren't being used for a similar algorithm.
https://www.fastcompany.com/3047828/who-needs-gps-the-forgot...
Live demo: https://www.youtube.com/watch?v=CHCCjlSWbHE
> Cheap dead reckoning sensors have so much error and drift right now as to be mostly useless for driving.
I don't think anyone's saying that it would be used for the driving part (i.e. car control), just as an option for orienting the car in the wider world beyond its direct perception.
I don't think they do. It's just more data that gets mixed in with multiple streams of real-time sensor data.
> Seriously, this mapping thing smells like a boondoggle.
It makes sense to me that autonomous cars would simultaneously be map users and map creators because I assume that data is shared with other vehicles. It's going to drive the cost of the map making way down. I think eventually the company with the biggest fleet will have the best maps, perhaps even real-time. Waze does this now but it relies on user reporting.
Pick two points in your town: say your home and your office. Imagine a stranger had to get from one to the other, and they know how to drive. The map if for all the information that stranger does not have.
Without map you also need time. In some cases, a lot of it. Not all cities have perfect grid structure and there are one-way streets that can mess you up a lot. In the city where I live it would be really time consuming, because there's a huge pedestrian-only area in the center and many the streets around it are one way, or turning is prohibited at some crossroads so you cannot suddenly decide that you made a mistake and you want to make a U-turn and go back.
Without maps you need time or luck.
OK, how does a first time visitor with a rental car get a sense of direction and distance without a map or driving directions from a local?
How do you reliably solve the beginner's mind problem for a self-driving computer?
Without a baseline input, the car will have to rely on the passengers to do back-seat driving which defeats the point of driverless.
This is not common at all in Europe. Sure, we have a general idea of the direction ("it's with of Paris") but we would not use that for anything else. Especially the building case was weird to me, I woukd have said "the side chose to the entrance" rather than "SE"
It's easy to imagine reasons to have detailed maps in the areas they are operating even if their systems are not wholly dependent on the maps. Stuff like being able to more quickly analyze how well the system is characterizing the environment or reducing power consumption or the map is necessary above a certain speed or …
GM made a detailed map of limited access highways in North America just to geofence the super cruise control in the new Cadillacs, so I'm also not sure the duplication of effort matters all that much.
If you have a self-driving car that's pretty safe, but you can make it even safer with maps, and those maps are going to be accurate 99.9% of the time, the 0.1% of the time will be less safe, but overall you've significantly reduced your risk of an accident, and maybe you can even mitigate the risk by doing things like slowing down when your maps aren't accurate, the same way human drivers slow down when there are cones on the street.
The issue isn't so much that they "couldn't handle" some debris, but that "handling" something is not a yes/no proposition.
Having said that, I haven't worked for these groups, so I don't really know what these maps are used for, maybe these maps are just used for localization because GPS isn't accurate enough.
The debris type information should only be useful in terms of routing.
Most don't have a lot of useful data they collect/maintain themselves. It's often easier and cheaper to buy it from some party who gets others to pay for it as well, spreading costs. I used to think like you do, back when I didn't realize just how much work it is to maintain, and then to provide it to all stakeholders in the formats they require. Here in the EU there was a big push 10-ish year ago to make all this information free, at various levels; see e.g. the INSPIRE directive and all work that that caused. Nowadays people have experience with just how much work it is, and have experienced that the promised benefits didn't quite realize (for various reasons). Most enthusiasm is gone, I feel.
(as a researcher, all this data becoming free/easy to download has been a huge quality of life improvement for me; but no more than that. I don't feel there is that much new stuff going on that wasn't possible before. Sure, before you had to chase people for weeks and sign all sorts of agreements, but the end results were more or less the same for professionals. Interested amateurs at home would give up in the past, but they didn't/don't produce all that much useful anyway.)
https://www.census.gov/geo/maps-data/data/tiger.html
While useful for taking the US Census, the TIGER data isn't really suitable for most navigation tasks. At best it can be used as a base layer to build a geospatial dataset.
OpenStreetMap did this about a decade ago:
https://wiki.openstreetmap.org/wiki/TIGER
That being said, the current administration is looking to cut TIGER funding, not increase it.
For the foreseeable future getting mapping data suitable for navigation in the US is going to be the job of private for-profit companies.
The lack of differentiation is a big problem if you want to pick which way to go when driving around though.
Of course, this isn't really a new problem. People have died following roads on paper maps that weren't suitable for, say, winter travel.
But, I think we need to stop thinking of the tech monopoly problem in principled, abstract terms. That's hard because it's how law works, and how our moral instincts genrally work.
Bloomberg's data monopoly does/did pay well, give them a nice moat and such. But, it couldn't be leveraged in the same way modern data monopolies can. It didn't permeate into new areas every day. It didn't have all these consequences (eg killing privacy) of scale. They din't lock up a dominant position in categories (eg smartphones, cars) that wouldn't exist for a decade or three.
Bloomberg's market position is more conventional. Being a monopoly gives them pricing power, and nicer margins. That is tame by today's standards.
Today's monopolies can't even be reasoned about in the language of antitrust. they don't act as trusts, generally. Market share is obscure. How do you determine the effects of reduced price competition for maps? It's free. The whole logic of econometrically calculating the harm to a consumer is irelevant.
Yet, the idea that Google owns your phone, browser, search engine, drives your car and controls the ads you see 100 times a day.... That's still a worrying thoguht. Economically, it's easy to see (eg search->maps->phones->cars) how one monopoly leads to another and they strengthen eachother.
First, the fact that it's within reach is amazing. It's one of those wierd cases where regular people instinctively put it in the "mars colony" category of futurism while sober insiders had to bring us back to a more optimistic view.
Now, there is a lot to worry about in the current landscape of giant tech companies, and this article is another example. But, there are things to awe at too.
Having self driving within reach... it's a result of massive effort. Amazing technology, and complexes of technology it is built on. This includes the manufacturing technology producing the cheap components.
All of this cam from (1) fairly blue sky intiatives (2) with extremely long and uncertain payback periods and (3) tremendous strategic money-where-your-mouths are foresight. When I realized what G where doing with street-view, I thought it was crazy. More a sign of overexuberance and too much money. Turns out, it was en route to maps dominance which was en route to transportation dominance (and phone dominance).
IDK if this is unprecedented, but it's fairly unrivaled in today's world. We don't see IBM or Intel, Toyota or McKesson thinking this big or this far. Definitely not banks or money businesses. Not cities or countries, generally.
I mean an equivalent in health/medicine would be taking the ideas from TED talks. A personalized health revolution. Nanobots or curing death like Aubrey de Grey keeps talking about.
I'm already hearing the "regulations" explanation. Medicine is restrained by surgeon generals, parliaments and national health setups. I don't think that argument holds at this scale. Self driving cars require re-rwriting our transport rules, and probably massive the physical infrastruucture. The technology will have sucked up billions decades before it makes a penny. The guiding idea is that "if we have a true self driving car, the other stuff will sort." Same applies to medicine. If it's better enough, it'll take.
It's hard to peer back and determine of something was inevitable or not, but I suspect self driving wasn't. It could have happened (could will happen? tenses are hard) decades later, if not for the fairly outrageous decisions of a small number of people.
I think a Mars colony is closer than self driving cars. You need basically strong AI for fully self-driving cars. You just need a ton of money and an incentive for Mars colonies. Most of the science for going to Mars is already there, as well as the tech. I don't think we even truly have the science for wide spread, all-weather, all-terrain self driving cars.
We can't assume the pure chaos of Cairo or Delhi requires the same model. Self-driving might only need basic Roomba-level collision avoidance and basic pathfinding for a place where the humans navigate with the expectation that every object, moving or not, is a collision waiting to happen.
Think about how much of rules-based driving is about avoiding hitting people who aren't following the rules. If you start off assuming there are no rules, the model is simpler: everything the sensors pick up could come flying at you at any moment, so plan accordingly, and stop or slow down if you can't find a path that avoids an impact.
In any case, I don't think we should be assuming infrastructure will remain the same. If self driving does replace driving, the infrastructure will change. Point problems (eg, computer can't handle these 43 tricky roads or intersections, those problems will be solvable be changing the road. It might just be adjusting so gns or minor parking rule changes.
There's a chicken-egg problem, which is why getting some of the way on existing infrastructure is smart. It also avoids scaring finance ministers, but ultimately infrastructure will meet driverless cars part way.
That said, we redo intersections because they have a lot of accidents all the time. I'm not sure why intersections that self-driving vehicles have particular problems with would be any different. I can also imagine having some sort of RF "beacon" that gets used for construction sites and the like to flag drivers that they need to take over manual control in a mile or whatever.
Of course, it doesn't get you to the futurist vision of self-driving cars in that you can't share cars and you need a licensed, sober human in the vehicle but it has the advantage of being very achievable in the fairly near-term while still being a really nice feature.
There is a solution for most problems people try to solve with self-driving cars: more cycling, better public transport, denser cities. Look at London: car use is heavily discouraged (20mph speed limit, congestion charge, expensive parking) and still the whole thing works like a charm.
I find dense cities don't work for everyone. Car towns are still nicer for the disabled, the elderly, and families with young children. Especially if stairs or snow enter the picture.
There is probably a way to build dense cities that work for people that need wheels and canes to function, but rebuilding cities to provide ramps, elevators, wide doors, and secure motor scooter parking is also expensive. There is also a last-mile problem for public trolleys and buses to be both available to the disabled and efficient for general use. That's why I think self-driving vehicles have a lot of promise. It probably makes more sense to have a larger fleet of smaller busses and then another set of small busses or vans for people who need a ramp up into the bus, locking mechanisms so their chair doesn't roll around, etc.
Car towns are the worst for the elderly. Most elderly don't feel comfortable driving but in the US, they're all but forced to do it to escape the house. Anywhere else, they can get out and socialize. Getting physical and mental exercise. You're also likely to find nicer single-floor homes (good condos with elevators) rather than "old people warehouses". As for snow, do you really want drivers with failing eyesight and reaction time to be driving on snow and ice? Or even shoveling out their car, for that matter?
I have young children. How many articles have we seen here about kids walking to school or childhood independence? Being car-bound makes that extraordinarily difficult or impossible. At this point, I struggle to think of an advantage of a "car town" for kids. Less time spent getting dressed in the winter, maybe? I suppose when they're older and even more "free range", I'll have to worry about how far they've gotten on the bus or train without me. I'll consider that being a victim of success though.
I'm talking about people who can't do stairs anymore. They're not walking a few blocks or driving cars. They're taking shuttles places or taking trips with the family. Shuttling the elderly around is cheaper and simpler in car towns. Scooting around NYC or downtown SF with Grampa in his wheelchair is rough. Rougher still when it's cold, raining, or hot. It's often bad for their health, even.
Car towns, maybe just because they are newer on average, are easier to deal with.
* basically never having to illegally park just to function
* car towns have plenty of bathrooms and indoor places to stop and relax
* elevators and handicap accessibility is much more common; dense cities are lousy staircases, steps, and narrow aisles
* keep gear in the trunk (changes of clothes, extra diapers, umbrellas, ponchos, picnic lunches, etc.)
* buckling a tired kid in a car is safer and more convenient than dragging them across intersections
* a screaming kid in a car is nicer all around than a screaming kid on a train
* getting around a dense town with luggage is rough: cabs don't stop, big/extra suitcases on buses is rough, and there are stairs everywhere
The math changes, of course, if everyone in your party is old enough, healthy enough, and responsible enough to carry their own gear. Some families with kids are in this category. But most families aren't that way, at least through different seasons.
1. Better safety - I find it very likely that self-driving cars will reduce the amount of traffic incidents. Algorithm will likely act more stable than human driver.
2. Better fuel consumption - again, more optimised driving patterns.
3. Better convenience - you can drink and drive(well, car will drive), you can sleep and drive, you can work and drive.
4. Better transport - self-driving trucks don't need breaks, are not likely to be overworked and will likely not block motoways taking over another truck going 2 km/h slower (yey European highways!).
5. Better vehicle utilization - we will be able to reduce total number of vehicles and all the congestion, environment pollution and money that comes with it.
While solution you mentioned really improve quality of life in cities, they do not ultimately solve issues inherent to car transport, where car transport is actually preferred/best solution.
I agree that this only applies in cities though, and public transport may not help much in rural areas.
If that happens, it's a way out of the car trap that we are currently in, directly, but also because more people living without cars will lead to more infrastructure for people living without cars.
Denser cities don't help that much, because you'd still have the massive scope of inter-city travel. The whole of Great Britain is only a couple hundred miles long in its longest axis, so it's not an applicable model.
The Seattle Metro area is working on that. Building out just a few mass transit lines here, not nearly enough, is going to take until 2050.
By which time the built lines will already be far over capacity.
> more cycling
I love cycling, but Seattle is built on hills. A lot of them. Very steep ones. Also it rains, rather frequently, up to 150 days of the year.
Electric bikes help solve the hill problem, harder to solve the issue of everyone going around smelling like a wet dog. Tech companies may offer on site showers, but a lot of other companies don't care enough about their employees to bother.
But even with all that aside (I am a huge fan of mass transit), let's take a look at driving between metros. Right now mass transit between metros typically involves going from one city center to another. So in a world of amazing quality mass transit, it is a trip to DT of your home city, a ride to another city, then a trip to your final destination.
Replace that with on call self driving cars. Picked up at home, and get dropped off close to your destination in another city. Within that city, and within your own city, use mass transit.
With the light rail Seattle is building out, my commute from one of the surrounding cities consists of driving to a park and ride transfer station (because even though I live on a main thoroughfare, mass transit isn't coming anywhere near me in my entire lifetime!), then taking mass transit in to the city.
If I avoid rush hour, my travel time to city is 15 to 20 minutes.
An autonomous car picking me up and taking me into the city makes a lot of sense. Indeed, I'd prefer if all the money (and decades of work!) being spent connecting the cities around Seattle was instead spent building incredible high quality mass transit within Seattle, and the surrounding cities.
At that point, serious change to the layout of cities could happen. Transit could get ran everywhere, huge parking lots removed, lots of housing built close to work, and people who want to would be able to live close to work, helping ease congestion.
Self driving cars make that possible.
The technology that is being built in America needs to be built up around the, unfortunate, fact that we have suburbs. You cannot relocate the majority of the country's populous. There are 700k people in Seattle, and 3 million in the surrounding urban area!
Come to think of it, I see zero reasons why you won't own measurements of your self-driving car, and choose to upload them. Yes corporations may try to pass it as their intellectual property, we should fend them so hard they roll back into XIX century.
That's one consumer protection law away.
And no, I don't believe in "being friends with OSM". I believe in owning your data.
“If you buy the car you own the data stream, and must be able to keep it private; read, modify and re-distribute it; and sell it” is a good idea.
> I believe in owning your data
Gentle political note. This sounds more radical than it is or than your argument needs it to be. The first suggestion stands well enough on its own.
* Come on Transport for London, it's high time to show some leadership here.
Basically it's just a combination of the SLAM tracking being successfully used already in VR and AR headsets like Windows "MR" and Oculus' Santa Cruz with the usual data-consolidating ways of Larry's Basilisk. I have a suspicion this may be the intended final purpose of all the nice Project Tango research.
Obviously you could also use the database for things like photo location-tagging. Similarly, smartphone car navigation apps would want to be able to be able to use the data being collected for self-driving cars, too. You could also imagine self-driving street-sweepers taking advantage of the pedestrian-area data (or indeed helping to harvest it).
Interestingly it's the opposite for cyclists. There, Google chooses "quiet" routes, sometimes sending me via paths where cycling isn't allowed. Could be a London mapping issue though.
Quote: > The game is always prompting the player about his location. In this regard, Michael Carney from PandoDaily said, “To capture a Portal, and harvest the “energy” contained therein for his respective team, a user must physically go to a location and check in. additional energy is available by travelling specific walking paths, bike paths, and inner-city routes dictated by the company, all while the user’s Android device is transmitting GPS and accelerometer data. In some cases, the user will be required to photograph locations or objects along those routes.”
Google is unfortunately still the winner here.
I do. Google greatly enhanced my life, esp. Driving and directions.
I was an adult BI and speak from experience
Also, Apple maps in my area has been quietly, but steadily improving. Still not as many POIs as Google, but nicer interface and turn-by-turn (IMO).
Wade it is. Yes the chat function is largely useless the report incident function is cool!
Are you sure? Someone just did an interesting analysis (admittedly, very small data space but a long-term test), found that Waze claims faster routes than they typically achieve.
Update: Ah, @dogecoinbase linked to it: https://arturrr.com/2018/02/19/navigation-apps/
Zurich Switzerland -> Austrian Alps
Heavy traffic, incidents along the road, gridlock ...> Waze got us there FASTEST.
"ATTENTION" "WAZE HAS JUST FOUND A FASTER ROUTE".
Competed against iPhone & Google Maps.
Same way return drive. ... So two data points I guess.
Austrian Alps -> Zurich
Plus ... I use it daily... So three data points then.
I've experienced something interesting a few times in high-traffic situations (closed highways/etc) where byways produce time estimates which are instantly implausible as many people attempt to take them. It's interesting to think of methods Waze could use to predict optimal paths while accounting for its own effect on traffic.