Not-so-smart cities

First, I want to say I totally agree with the last half of the last sentence in Greg Lindsay’s opinion piece in the New York Times:

…the smartest cities are the ones that embrace openness, randomness and serendipity — everything that makes a city great.

The rest of the piece I don’t quite get.  Lindsay objects to the new city being built in New Mexico which will have no residents, but be used solely for testing “smart city” technology like “smart power grids, cyber security and intelligent traffic and surveillance systems”.  He objects because he feels computer simulations are not robust enough to capture human’s inherent “randomness”.  To support his case, he uses an example of a RAND corporation study, from 1968 (!), that failed to “smartly” reconfigure fire service.

Take the 1968 decision by New York Mayor John V. Lindsay to hire the RAND Corporation to streamline city management through computer models. It built models for the Fire Department to predict where fires were likely to break out, and to decrease response times when they did. But, as the author Joe Flood details in his book “The Fires,” thanks to faulty data and flawed assumptions — not a lack of processing power — the models recommended replacing busy fire companies across Brooklyn, Queens and the Bronx with much smaller ones.

What RAND could not predict was that, as a result, roughly 600,000 people in the poorest sections of the city would lose their homes to fire over the next decade. Given the amount of money and faith the city had put into its models, it’s no surprise that instead of admitting their flaws, city planners bent reality to fit their models — ignoring traffic conditions, fire companies’ battling multiple blazes and any outliers in their data.

The final straw was politics, the very thing the project was meant to avoid. RAND’s analysts recognized that wealthy neighborhoods would never stand for a loss of service, so they were placed off limits, forcing poor ones to compete among themselves for scarce resources. What was sold as a model of efficiency and a mirror to reality was crippled by the biases of its creators, and no supercomputer could correct for that.

First, any good planner or engineer will tell you that models and software should be a starting point, not a finishing point.  I have no doubt that any new technology that comes out of the Center for Innovation, Testing and Evaluation (that is the new city’s name) will be refined in the real world as it’s performance among us mammals is tested.  If the RAND corporation couldn’t (or wouldn’t) adjust in 1968, they were bad planners.

Second, we shouldn’t use technology because politics could get in the way?  Don’t fault technology, fault bad process and implementation.  Also, where does this line of reasoning lead us?

Third and finally, this is the only example Lindsay gives of a failure of “smart” systems in the real world (except for a reference to something Jane Jacobs said), and it occurred in 1968.  Lindsay omits the myriad “smart city” technologies that are already commonplace and are generally deemed to have net positive impacts.  Here is a partial list (and I’m no expert):

And coming soon:
None of the second list, and I’m pretty sure none of the first list (at least computerized versions thereof) even existed in 1968.  The fact that many of these systems currently exist, and regularly operate without massive failure, seems to refute Lindsay’s assertion that we shouldn’t continue to develop them.

Road Trains Tested In The Real World

Road Train Test

Road trains (also called vehicle platooning) are convoys of semi-autonomous vehicles with a professional driver in the lead vehicle.  The Safe Roads and Trains for the Environment initiative (SARTRE) describes road trains as:

…a convoy of vehicles where a professional driver in a lead vehicle drives a line of other vehicles. Each car measures the distance, speed and direction and adjusts to the car in front. All vehicles are totally detached and can leave the procession at any time. But once in the platoon, drivers can relax and do other things while the platoon proceeds towards its long haul destination.

Road trains were actually tested in the real world by Volvo, who is part of the SARTRE team, in December.  They cite the benefits of road trains as numerous:

Platooning is designed to improve a number of things: Firstly road safety, since it minimises the human factor that is the cause of at least 80 percent of the road accidents. Secondly, it saves fuel consumption and thus CO2 emissions by up to 20 percent. It is also convenient for the driver because it frees up time for other matters than driving. And since the vehicles will travel at highway speed with only a few meters gap, platooning may also relieve traffic congestion.

There are some potential downsides to road trains as well, but ideally they can deliver many of the benefits of intra-city transit without some of the drawbacks.  Really road trains are just a stepping stone to fully autonomous cars, and caveats of same apply here as well.

The Rest Of The Story On Robot Cars

The City Fix scooped me on using the Johnny Cab image, but tribute must be paid to such a forward-looking film.

The internet seemed to resound with almost unmitigated delight when Google announced their progress on driverless cars last week.  German scientists see a “golden future” for their driverless vehicles.  There are, however, some key implications that are being missed about what it means if our cars are driven by robots.  I’ll preface the rest of this post by saying that I think the benefits of robot cars probably outweigh the drawbacks.  However, robot cars are not a panacea, and we shouldn’t overlook unintended consequences.

David Levinson at The Transportationist does an excellent job summarizing why robot cars matter, but in my opinion doesn’t go far enough explaining the potential downsides.  Here are some of my thoughts on why we should adopt robot cars carefully, even with their myriad advantages.   Continue reading