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Safety is often celebrated as the biggest benefit of a world full of driverless cars, but two other presumed social improvements follow closely behind. One is that the technology could reduce traffic congestion, since shorter gaps between cars means more cars per lane. The other is that car travel will become more productive time for either business or pleasure—the way riding a train is today.
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A new simulation-based study of driverless cars questions how well these two big secondary benefits—less traffic and more comfort—can coexist. Trains are conducive to productivity in large part because they aren't as jerky as cars. But if driverless cars mimic the acceleration and deceleration of trains, speeding up and slowing down more smoothly for the rider's sake, they might sacrifice much of their ability to relieve traffic in the process.
An interesting point. The tomorrowland we envision is always shinier than the reality we get. We imagine that driverless vehicles will offer us the opportunity to do other things, in the same way we can on a train. But this comfort may be that this is in direct conflict with the other goal, reduced travel times. That said, train-like acceleration is unrealistic, as car passengers routinely already put up with the study's baseline accelerations.
The entire point is moot -- a huge gap remains between the fantasies peddled by the dreamers, and what current technology can actually support and, more to the point, adapt to a mass-market.
The experiments proposed by Google and a handful of others with access to large amounts of resources are conducted on closed courses -- with all the subtleties of the local system well-known and outside factors tightly controlled; it simply isn't like that in the real world.
Faith in "driverless cars" seems likely to meet the same end as the prediction, now at least half a century old, that the average American would one day own a personal airplane.
The experiments proposed by Google and a handful of others with access to large amounts of resources are conducted on closed courses -- with all the subtleties of the local system well-known and outside factors tightly controlled; it simply isn't like that in the real world.
As of April 2014, Google announced that their fleet of driverless vehicles have logged nearly 700,000 autonomous miles (on city streets & highways). These aren't confined to closed course tests anymore.
No big deal. They'll be more comfortable and flexible than public transportation which already has significantly longer commute times than private automobiles do. Personally, I think it's great. I maybe spend 10 hours a week driving for work. If that changes to 12 hours and becomes productive time, fantastic. That's something I'd be happy to add another $20,000 or so onto the purchase price of a car for.
Driverless cars will actually be controlled by highway electronics. When cars enter the limited access highway they will come under control, when they exit they will return to control to the driver. the purpose will be traffic control, not driver convenience.
Not really very far away in my opinion. 10 maybe 20 years.
Back in 1970, I took, and "aced" a 400-level course in Business Logistics at Penn State taught by Dr. Joseph Carroll (whom, it delights me to say, is still serving in an emeritus role). The course was devoted almost entirely to simulation models, called "queueing theory" in those days.
The models in those days were very simple -- we studied waiting lines at barge canal locks, ferry services, and even supermarket checkouts. Nobody gave much thought to the movement of vehicles between those points, but the railroad buff in me was wondering how much could be adapted to rail systems which, of course, operate over a very limited network, and are very much adaptable to centralized control.
So we came up with a "dispatcher's algorithm" in our spare time, and I continued to pursue it, along with a few other people with similar interests.
What we found was that, although the model worked well with a limited number of moves, particularly when fairly scheduled and predictable, each addition of another variable resulted in a near-exponential increase in the number of decisions faced by the control system. At that point, in the real world, the model would simply overload, or "freeze up", and a real human being would have to override the system with his/her own input.
This is what I see as the largest obstacle facing the advocates of "driverless" technology; the real world is simply overloaded with external factors -- not merely other vehicles or pedestrians, but subtle variations in the gradients and curvature of individual roads -- not to mention weather and other constraints.
If complete and total control of a vehicle is the goal in mind, then the railroads and transit systems are obviously much closer to full fruition. But very little investigation of this possibility has been raised -- even in the trade press. The risk of accident is simply too great, and too multifaceted in its origins.
Yet the tea-time talk-show ladies continue to host gadflies who predict that "A self-driving auto will be here in a few years."
Last edited by 2nd trick op; 01-29-2015 at 04:16 PM..
I live very near to Google and see the self-driving cars on the road all the time. (Daily) They drive in some very congested areas with school kids crossing, parents picking up kids and double parking at will (without turn signal on ,) road construction, etc and they seem to do better than the human driven cars around them.
I've never seen one honk or make a rude gesture when cut off
As many as I see it is hard to believe that they won't be available soon.
Also Tesla is manufactured here... lots on the road... and I want one, but sigh, my Camry will have to do.
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,) road construction, etc and they seem to do better than the human driven cars around them. 
