|An ULTra PRT vehicle on a test track. (Wikimedia Commons)|
Of the dozens of proposals and prototypes, the Morgantown PRT that links WVU campuses is the only one of that era ever to be deployed at scale. The rest were either cancelled entirely or were defeatured into automated people mover systems like you find at many airports.
In 2011 two new systems opened, ULTra PRT at London's Heathrow Airport and the 2getthere system in Masdar UAE. Both are relatively small systems each with fewer than five passenger stations and fewer than 25 vehicles. But the new systems also represent an important departure from previous PRT designs. Both use battery powered vehicles with autonomous control. They run on rubber tires and steer themselves so there's no switching gear on the guideway. They are powered by batteries that automatically recharge when the cars wait at stations. This contrasts with previous PRT designs that used powered guiderails and a central control and switching system.
The primary barrier to PRT systems has been the cost of the tracks or "guideways." It's estimated that it would cost beween $30 million and $40 million a mile to expand the Morgantown system. That's because the guideway has to incorporate precision guide curbs, power transmission, track switches and even a heating system to melt snow and ice to keep it safe in bad weather.
In contrast, the ULTra guideway is estimated to cost between $7 and $15 million per mile. That's because it's a simple concrete pathway with no active systems.
Which brings me to Driverless Cars.
In essence, the ULTra and 2getthere systems are self-driving electric cars in which the environment has been constrained enough to simplify the self-guidance problem. High curbs make it easier for the cars to center themselves in lanes, dedicated roadways minimize pedestrian and obstacle avoidance. Strategically placed charging stations let them be electrically powered using batteries of modest capacity.
Meanwhile, Google's self-driving cars have driven themselves more than 300,000 miles accident-free, on conventional roads, without special infrastructure. Like many, I've wondered why Google is building such cars. They're in the information business, not transportation. A talk by Big Data guru, Ed Lazowska clued me in. Before the Google people let a car drive a route by itself, they first have a human drive the car over the same route. During the trip, its sensors scan the environment, picking out landmarks and obstacles, measuring road conditions and fine-tuning its GPS map of the roadway. Google is interested in supplying data to enable driverless cars and they're doing research to determine what data is needed.
A recent Freakonomics post on the subject suggested that driverless cars will arrive incrementally starting with the already common cruise control, adding adaptive cruise control, collision avoidance and self-parking before fully driverless operation arrives.
But I'm afraid that calling these "driverless cars" is the 21st Century equivalent of calling automobiles "horseless carriages". In each case the focus is on what's missing (the driver or the horse) instead of what new capacity has been introduced. "Horseless carriage" doesn't exactly describe a vehicle capable of sustaining 65 miles per hour with a range of over 300 miles. Nor does it conjure images of the megacities it enables or the endless parking lots it requires.
Consider this possibility: driverless technology enables the PRT dream on existing infrastructure. Instead of dedicated guideways costing tens to hundreds of millions, a PRT system built on driverless technology would rely on GPS and 3G data networks, both of which are already in place. Initial deployments can be restricted to certain neighborhoods that meet high standards of traffic signals, lane markings and crosswalk protection. Even a system restricted to certain lanes and certain streets would offer PRT of greater scale and capacity than anything yet deployed. Yet the investment to get started is regulatory permission, a few vehicles and some signage.
Fancy stations aren't required – only some curb space. Cars would be summoned using smartphones. And it wouldn't just be a peoplemover. Cargo, also, could be sent unattended. Grocery stores could use the same infrastructure for home (or corner) delivery. In the long run, even mail delivery and garbage collection could be automated.
We can learn something from this:
There are some fundamental principles at work here that can be applied to other large-scale problems:
- Infrastructure is usually the most expensive component. Whenever possible, use infrastructure that's already in place and share infrastructure with other projects.
- Push control (or decision making) as close as possible to the application or beneficiary.
- Inform the distributed control with global data.
- Build systems that can be scaled incrementally; where adding capacity is a matter of buying more of the same rather than periodic large investments to get to the next capacity threshold.