[PLUG-TALK] Driving in Cities: How Ants Commute

[Keith Lofstrom]

On Jan 19, 2015, at 10:31, Larry Brigman <larry.brigman at gmail.com> wrote:
> Put those sensors and controls into the cars and remove the control from what we currently 
> call drivers.  That would put things into a much more orderly flow.
 
On Mon, Jan 19, 2015 at 12:42:13PM -0800, Russell Johnson wrote:
> Isn’t that exactly what Google is doing with their self drive cars?

Because AI is becoming capable of doing what is very difficult
for humans (logic, accounting, playing chess, indexing the web),
we presume that what is easy for humans (visual/acoustic pattern
recognition, movement tracking and response) must be easy for
computers.  Not even remotely true.

Your brain is primarily a sight/sound/tactile processor, with
a powerful social computer and a very weak logic processor. 
It is easy to duplicate and exceed the recently evolved logic
processor.  The social processor evolved over a million years,
and the movement processor over a billion years.  The movement
processor is so optimized (down to the molecular level) that
the general task is mindbogglingly complex, well beyond the
technological state of the art.

I talked with Wes at the clinic about a "skyrail" system to
lower cars into the flow of freeway traffic, and pluck them back
out again - a very artificial and constrained driving task, 
though still somewhat beyond current AI capabilities.  The
long exit-free westbound stretch of I-84 from 181st to 47th
would be a great place to try this.  With more geeks and 
fewer lawyers, Tokyo might be better.  Broadly applied, this
technology would eliminate the need for high self-powered
onramp acceleration, huge high horsepower engines, and all
the weight and pollution that entails.

The general driving task - looking for anomalies in the road,
predicting the behavior of other drivers, pedestrians, animals,
etc. - involves rapidly building a dynamic world model with
human social knowledge.  A ball bounces into the road - slam
on the brakes, there may be a kid chasing it.  A pine cone
bounces into the freeway - slam on the brakes and risk getting
rear ended?  Probably not.  That is a huge social calculation,
on top of powerful visual computing, performed in milliseconds.
We invented controlled-access freeways to intentionally remove
most of the anomalies, permitting safe operation at high speed.

Still, every accident and low-vision weather condition creates
dangerous anomalies, like the half-a-dozen trucks rear-ending
each other on I-84 near Baker a few days ago.  Those were 
attentive, skilled, professional drivers on a proper freeway;
what would Google do?

Google can't even do searches right - lately, they seem to be
doing template matching rather than logical winnowing of their
gigantic corpus.  There's no way children will be safe from a
Google-controlled template-driven car, even with fast frame rates
and human-scale visual pattern processing milliseconds away.
Human drivers are not perfect, of course, but most drivers
avoid many frightening accidents far more often than they fail.

What computers CAN add to driving is "virtual omniscience",
information about the road ahead that drivers don't have.
Route planning and congestion observation is easy, congestion
prediction is possible.  Debris on the road from an accident
three days ago?  Diff to the scene from a week ago, magnify
the anomalies, and present them on the heads-up display to
the driver, while notifying the highway maintenance crew
to clean up the dangerous stuff (at night, when the roads
are empty but the stuff is hard to see).

It is annoying that programmers spend so much time attempting
to bypass excellent human pattern recognition and doing a
lousy job, when there are tasks that people are very poor at
which can be automated easily and profitably.  Humans, plus
tools that compensate for weaknesses, can be an incredibly
powerful combination, far more capable and cost-effective
than humans or computers alone.

Keith

-- 
Keith Lofstrom          keithl at keithl.com