In our last
exciting episode I promised to explore cooperative robotics, but there is an
unavoidable side issue that is worth at least one post in itself, one that
high-jacks the whole subject. What I am referring to is self-driving cars. It is not just that PRT and automobile automation
have such obvious similarities that makes the subject a prerequisite to
discussing PRT control. It is also the fact that self-driving cars may actually
change the definition and purpose of PRT.
Self-driving
cars are not just about following directions and staying on the road. Spinoff features
such as automatic braking for collision avoidance are already widely available in
everyday production models. Since self-driving features often involve
technologies that clearly can enhance safety, there is an “arms race” in this
regard. With communication between
vehicles (“I’m slamming on the brakes, so you better, too!”) and awareness of
real-time traffic, (such as could be monitored, compiled and reported by the
vehicles themselves) it is not hard to see how cars could be made to operate
within a sort of “hive mind,” to the benefit of the group. This is basically a
PRT operating system and is a wakeup call to self-steering PRT systems like
ULTra or ToGethere, whose technologies are getting leapfrogged by this trend. Notably,
the self-driving paradigm is proving that a high degree of autonomous control
is doable, challenging the centralized control schemes of only a few years
back.
Does self-driving
auto technology render PRT irrelevant? Do self-driving cars eliminate the same
problems that PRT was to solve?
The short
answer is no. The question does, however, illustrate how various flavors of PRT
have very different challenges in this new technological landscape. What, for
example, should the business model be for ULTra in a world transitioning to self-driving
taxis that may not need guideways or stations? Of course that may be quite a
ways off, and maybe it is Google who should be approaching ULTra. After all,
every cent ULTra has made is a cent more than Google has made on its robocars, with
Google putting all of their eggs in a business-model-basket that is still a bit
of a head-scratcher and is contingent on many unanswered questions when it comes to safety.
So far
Google and the others have seemingly only taken their vehicles out in decent
conditions, weather-wise, content to garner impressive numbers of miles without
incident. But how do they handle being behind a vehicle that is dropping
debris? Or on patchy “black ice?” Fresh snow or street flooding can completely obscure
where the road is. Timid response, in these instances, that would prevent
lawsuits is also the kind of driving that would snarl traffic. Imagine a car
that is afraid to go through ankle-deep water and so just stops! Can a robocar
understand when weather conditions are deteriorating too much to enter the
freeway or understand the significance of a funnel cloud? Humans usually know
when they should stay put or go back. Will Google be able to give that much
common sense to their cars? What about morality? Will they know to hit the
truck to avoid the woman with the baby carriage?
It has been
reported that, at least some states, they cannot dispense with manual controls
(such as a steering wheel) nor the human seated so as to operate them. This leads
one to wonder under what conditions the authorities would permit such use. Beyond
that, what is the profit model that trumps the obvious, added liability issues?
Do drivers really want to relinquish all control and do manufacturers really
want to sell mechanically stripped down cars with no sex appeal?
A safe
starting point would be a special lane or only going at fairly slow speeds.
(i.e. a mode similar to current pavement-running PRT systems) After all, many
localities allow golf cart type vehicles on public roads, and these need no
horns, airbags, seat belts, etc., as they don’t go that fast. While this would
probably be allowable, it does little to solve urban congestion and so, by
itself, risks irrelevancy.
Interestingly,
there are flavors of PRT that have just the opposite problem. SkyTran, for
example, is really built more for speed than for serving little stations in
every nook and cranny of a typical city. Suspended systems, in general, have
the potential to move people from one side of town to the other quite quickly
using an inexpensive, minimalistic track, but like all PRT, suffer from the
potential problem of not having a sufficient number stations and walk-up
customers to create the cash flow to pay-down the system components and still
provide a return on investment. It’s the old first and last mile problem. Could
self-driving automobiles be the answer to aggregating more PRT passengers at
fewer stations? Quite possibly.
Uber has
expressed interest in self-driving cars, and car sharing schemes like Zip Car raise
interesting questions about ownership. Why garage a vehicle that could be
gainfully employed elsewhere while you are not using it? Why own a vehicle at
all – especially if there is one parked close by that will come to you when
summoned?
Once upon a
time, PRT offered a unique combination of benefits that could not be had
otherwise. It was automated, elevated, personal, fast, but it was only practical
within an interdependent framework of technologies. Over time, developments in sensor,
communications and computing gave advantage to a variety of methodologies enabling
new designs that emphasized varying missions and business models. The emergence
of autonomous cars, it seems, puts a focus on one of the original themes, which
is a network of fast, elevated, non-stop corridors that are unencumbered by the
gridlock below. This mission is unthreatened by the self-driving car revolution
and, indeed, may well benefit from it. PRT, at this point, needs to be
considered not as a fleet of automated taxis, but as a network of personally navigable
urban wormholes. The automated taxi aspect is now only a means to an end, not
the end itself.
Originally
the idea was to space PRT stations so that each was reasonably within reach by
walking. Now perhaps each station could garage a half-dozen automated taxis,
giving such stations much broader reach. This associated service would not have
to extend very far to cut the number of stations to a fraction of what would
otherwise be required. This scheme works perfectly with car sharing, carpooling,
or even private ownership. Even if each fully self-driving “car” can only go a
few blocks, with similar vehicles and capabilities at each end of the PRT
“wormhole,” the combination could be very synergistic. The timing and payments between
the two systems could be integrated, even if under different ownership. On such
limited routes where the speed limits are low there is much less reason to
require a driver, meaning self-driving cars are clearly ready for this NOW. Where
special lanes could be created, ULTra is also ready to go as well.
Side note: The
above combination offers less advantage for the SMART PRT designs shown within
this blog because SMART is specifically designed to address the “last mile”
problem with vertical capabilities and stationless pickup and drop-off
capabilities. Of course any infrastructure, surface or elevated, will
undoubtedly face obstacles on certain routes, and so alternatives are always
welcome. That being said…
It is important
to note that slow, short-haul, self-driving “taxis” also offer synergy with
other forms of mass transit, such as light rail, subways, scheduled shuttles
and so forth. Even with limited routes, (There might be too much traffic on
public roads and no room for a special lane) phone apps could be used to locate
the nearest suitable pickup point. Such pickup points could enhance the value
of properties that are otherwise inconveniently remote from mass transit. Short
hauls to such existing transit hubs seems like a good business model for such a
product/service right now and deployment of such FULLY robotic vehicles, even
at slow speeds, might serve similar R&D aims as the current, unpaid efforts
and would offer a potential opportunity to cement a leadership position in the
field while generating revenue.
Self-driving
cars, capable of full city and highway use without special lanes or a standby
driver are still a long ways off for general use, and the eventual payoff for
the producers of such vehicles is questionable. Short range, slower vehicles
face no particular obstacle to immediate adoption, however, and everybody from
ULTra to Google to Uber to Zip and the various auto makers should jump on this
opportunity to become leaders in this transitional space. Meanwhile PRT
wannabes need to take note that the current technological backdrop no longer
supports slower, station-intensive, short range systems. Instead, PRT companies
should concentrate on designs that foster the cheapest, fastest network of
elevated track possible, filling that one niche that automation itself cannot
address.
Elevation has always been the answer to surface traffic congestion, but
has always been prohibitively expensive (not to mention ugly and in-the-way) when
scaled for heavy vehicles, and so gridlock continues. Like fiber-optics compared
to copper, some form of light, affordable, high-speed “pipes” for moving people
are inevitable, and the first barrier, autonomous yet cooperative automation, is
falling away fast. Like that fiber-optic cable, the second barrier is what
happens at each end – how data is efficiently transmitted and received.
Hopefully self-driving vehicles will help provide comparable, easy-to-implement
solutions for either end of the mobility solution that cities need so badly - that
Urban Wormhole technology called PRT.
