
The evolution of transportation-as-a-service - billpaetzke
https://stratechery.com/2016/google-uber-and-the-evolution-of-transportation-as-a-service/
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petra
One guess: the routing problem(the vehicle routing problem) is a core computer
science problem, for decades. Tons of research have been done about it. I
don't expect Google or Uber to have any breakthroughs there, because it's pure
luck. But maybe they will, or maybe they'll will ackuire someone. Let's put it
down to pure luck.

But assuming no brekathrough happens: one company that has tons of experience
in that field is UPS, they are just finishing building a new system for
running their vehicle-routing for 50K routes in the US daily, ~120 points per
route, i.e. 600K customers daily. They invested ~$300 million in that
system(and they employe hundreds of phd's) and they say it will give them a
savings of less than 1% of revenue - just to get a sense how mature those
systems are.

On the other hand, it seems that have larger access to customers could enable
much more ideal routes, both in cost, customer time and maybe social factor(if
social matches will be part of ride sharing). So i believe that to be key to
winning.

And i don't think anybody can beat Google in marketing to android users, and
even in the US, with iPhone's 40% share(but more wealthy users) - that's avery
big advantage for Google.

On the other hand, i think Google prefer not to start a huge service that
employs many people, and than have self-driving cars make them unemployed and
suffer the huge reputational damage. So they won't go into true shared taxis
like ridewithvia.com seems to be doing very sucsessfuly, and instead stick
with wazer-rider , enabling drivers to give a lift to poeple for some very
modest fee.

So to a certain extent, the winner in that battle would be determined by which
approach of those two will win.

~~~
lern_too_spel
For this problem, they don't need to find the optimal routes, just reasonable
routes. Individual routes have only four stops at a time. No breakthroughs
required.

~~~
petra
Not choosing optimal routes would lead to a more expensive service, which is
critical for a commodity.

As for routes only having 4 stops - sure, but that's after you chosen which
users will drive in the same car/trip, which is hard in itself.

BTW the dial-a-ride problem is quite similar to the ridesharing problem, and
the complexity there is O(number_of_pickup_and_drop_points^2 ) [1]

[1][https://www.itu.dk/people/pagh/CAOS/DARP.pdf](https://www.itu.dk/people/pagh/CAOS/DARP.pdf)
\- altough it's a bit old, so maybe results have improved since.

~~~
lern_too_spel
If you compute routes that are close enough to optimal, it doesn't matter. If
you compute good enough routes quickly, that will likely reduce costs more
than computing the best routes slowly. There are enough other areas of
optimization that will give a better return on investment that it doesn't
necessarily make sense to invest in finding the actual best routes.

Also, this particular problem is much easier than you surmise. The problem
statement isn't a set of millions of cars sitting in particular locations with
a set of millions of riders with particular sources and destinations and
matching them and ordering routes to minimize fuel usage or median rider
travel time. The problem is of hundreds of nearby cars traveling existing
routes and matching a single new rider with a particular source and
destination to one of those cars. There is a secondary problem of where to
send empty cars that is more interesting.

~~~
petra
I agree. But that's true for current Uber .

But once we start talking about UberPool and via its pretty close for the
problem I describe, especially if we're talking about the commute , with a
possibility of people preordering rides sometime in advance(or even some
prediction abilities about that).

As for the other option, carpooling ,it depends how far will people be willing
to drive out of their way for that extra income. But being conservative and I
they won't go out of their way , the problem becomes assigning riders to a
million bus routes with small capacity, which seems to naturally break this
problem into many ,largely independent problems , and may prevent any big
exponential complexity.

Don't you agree ?

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rubidium
Uber actually transports people.

Ford actually builds cars.

Google... likes letting smart people do smart things.

While Ford may be the underdog in the race, I like its chances. It has the
operational experience to take a "works-in-concept" to "works-in-reality". The
software part, while difficult, is not the hardest part of "TaaS". The systems
part is.

~~~
oillio
I agree the systems part is the hard part. The software to monitor and control
thousands to millions of automated cars.

Ford has a large learning curve in order to figure out how to do that. It will
take a very different workforce to build and manage a software system of that
scale.

Google and Uber have been managing a system like that from the beginning, it
is in their DNA.

I could see Ford providing the hardware, while a different company deploys and
manages the customer facing operation. Demoting Ford to a vendor doesn't sound
like such a good thing for Ford though.

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oillio
The takeaway I get is that Uber has an edge on Google in the race for a fully
automated taxi service, because the have had more time to work on a more
sophisticated routing algorithm.

I am skeptical. As the article points out, it will take a considerable amount
of time to deploy any service, once the automated driving is good enough. If
Google gets to commercially viable automated driving sooner, it will have
plenty of time to refine their own routing algorithms during the rollout.

~~~
jessaustin
An interesting HN comment on vehicle routing from yesterday:

[https://news.ycombinator.com/item?id=12400611](https://news.ycombinator.com/item?id=12400611)

My sense is that this problem is solved to a much greater extent than
automated driving is.

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gnud
Hasn't transportation been a service you can buy for ages?

~~~
akgerber
Yes— but it hasn't been cost-competitive with a driver-owned car for daily
drivers (given free/subsidized parking and roadway space, as we have in the
US).

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MrQuincle
I would be surprised if the planning part is the most difficult part of
autonomous cars. Embodied intelligence is really nowhere yet. I've seen Google
using particle filters to represent other cars.

AI is just not advanced enough to cope with leaves on the road, a pedestrian
who wants to cross or not, a broken traffic light, a criminal who want to
steal your car, etc.

And everything as a service... Really, if we would have something that awesome
as an autonomous car, wouldn't we want to own it!?

I would! I want to talk to it. And I would like to have a bed and a bath in it
and have it go on a road trip with awesome beaches, castles, and sunsets.

~~~
semi-extrinsic
> Really, if we would have something that awesome as an autonomous car,
> wouldn't we want to own it!?

Because money. Let's say the first autonomous car is a Ford Fusion or similar,
normal cost $30k, autonomous cost $130k (for the sake of argument; we know
autonomous tech will be very expensive at least at first.)

Would a normal person buy the autonomous one? Not by a long shot.

But for a taxi company, saving as much as $100k/year on payroll expenses per
car (assuming shared between drivers), the $130k car is very attractive.

~~~
MrQuincle
If it will be successful, many will be sold and the price will come down
quickly.

I don't know why AI should stay expensive.

~~~
semi-extrinsic
iPhones are successful, many have been sold, yet the price has not gone down
quickly.

For autonomous cars, the best-case component price estimates I've seen for
solid-state LIDARs, assuming mass production, is $1000. I believe you need
four of those, and then you need ultrasound, radar and super-hi-res cameras.
And a big honking computer to process all that data. It's probably at least a
$10k premium over the normal car just in additional hardware costs, and that's
assuming mass production.

Then there's the cost of all that software development that companies will
want to recoup, plus the cost of collecting and live-updating a vast data set
of roads, pedestrian paths, local wildlife/other hazards, roadworks, local
laws and regulations etc. in every big city and small town in all the world,
to assist and confirm the information gathered by sensors in the car.

~~~
MrQuincle
Solid state should be cheap.

The real problem is that LIDAR instead of better "stereo camera data
processing" is development in hardware rather than brainware (AI).

There is indeed a lot that needs to be developed w.r.t. brainware. However,
I'm pretty sure it doesn't need to be recouped through selling cars. Brainware
is valuable in many more applications.

1\. Accessing the internet through Google vs Viv. 2. Household robots vs cars.
3. Agriculture.

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squozzer
About the only modification I would add to TaaS is making ride-sharing
optional -- a personal preference of mine, that might prove worthy of a
premium. If I liked sharing space with others, I would take a bus to work.

