Category Archives: T – cities
Inside the Fake Town Built Just for Self-Driving Cars
“Mcity,” which officially opened Monday, is a 32-acre faux metropolis designed specifically to test automated and connected vehicle tech. It’s got several miles of two-, three-, and four-lane roads, complete with intersections, traffic signals, and signs. Benches and streetlights line the sidewalks separating building facades from the streets. It’s like an elaborate Hollywood set.
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This is about more than safety, too. Mcity allows engineers to test a wide range of conditions that aren’t easily created in the wild. They can test vehicles on different surfaces (like brick, dirt, and grass) and see how their systems handle roundabouts and underpasses. They can erect construction barriers, spray graffiti on road signs, and work with faded lane lines, to see how autonomous tech reacts to real-world conditions.
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Such a site is a great tool, but the technology must also prove itself on public roads. A simulated environment has a fundamental limitation: You can only test situations you think up. Experience—and dash cams—have taught us our roads can be crazy in ways we never think to expect. Sinkholes can appear in the road, tsunamis can rage across the land, roadside buildings can collapse and send debris flying. Humans can be even harder to anticipate. But even every day actions, the things we do almost subconsciously.
Ref: Inside the Fake Town Built Just for Self-Driving Cars – Wired
Should a Driverless Car Decide Who Lives or Dies?
The industry is promising a glittering future of autonomous vehicles moving in harmony like schools of fish. That can’t happen, however, until carmakers answer the kinds of thorny philosophical questions explored in science fiction since Isaac Asimov wrote his robot series last century. For example, should an autonomous vehicle sacrifice its occupant by swerving off a cliff to avoid killing a school bus full of children?
Auto executives, finding themselves in unfamiliar territory, have enlisted ethicists and philosophers to help them navigate the shades of gray. Ford, General Motors, Audi, Renault and Toyota are all beating a path to Stanford University’s Center for Automotive Research, which is programming cars to make ethical decisions and see what happens.
“This issue is definitely in the crosshairs,” says Chris Gerdes, who runs the lab and recently met with the chief executives of Ford and GM to discuss the topic. “They’re very aware of the issues and the challenges because their programmers are actively trying to make these decisions today.”
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That’s why we shouldn’t leave those decisions up to robots, says Wendell Wallach, author of “A Dangerous Master: How to Keep Technology from Slipping Beyond Our Control.”
“The way forward is to create an absolute principle that machines do not make life and death decisions,” says Wallach, a scholar at the Interdisciplinary Center for Bioethics at Yale University. “There has to be a human in the loop. You end up with a pretty lawless society if people think they won’t be held responsible for the actions they take.”
Ref: Should a Driverless Car Decide Who Lives or Dies? – Bloomsberg
What Crazy Dash Cam Videos Teach Us About Self-Driving Cars
THE FIRST SELF-DRIVING CARS are expected to hit showrooms within five years. Their autonomous capabilities will be largely limited to highways, where there aren’t things like pedestrians and cyclists to deal with, and you won’t fully cede control. As long as the road is clear, the car’s in charge. But when all that computing power senses trouble, like construction or rough weather, it will have you take the wheel.
The problem is, that switch will not—because it cannot—happen immediately.
The primary benefit of autonomous technology is to increase safety and decrease congestion. A secondary upside to letting the car do the driving is letting you can focus on crafting pithy tweets, texting, or do anything else you’d rather be doing. And while any rules the feds concoct likely will prohibit catching Zs behind the wheel, there’s no arguing that someone won’t try it.
Audi’s testing has shown it takes an average of 3 to 7 seconds—and as long as 10—for a driver to snap to attention and take control, even when prompted by flashing lights and verbal warnings. This means engineers must ensure an autonomous Audi can handle any situation for at least that long. This is not insignificant, because a lot can happen in 10 seconds, especially when a vehicle is moving more than 100 feet per second.
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The point is, the world’s highways are a crazy, unpredictable place where anything can happen. And they don’t even have the pedestrians and cyclists and buses and taxis and delivery vans and countless other things that make autonomous driving in an urban setting so tricky. So how do you prepare for every situation imaginable?
Ref: What Crazy Dash Cam Videos Teach Us About Self-Driving Cars – Wired
CyberSyn – The origin of the Big Data Nation
That was a challenge: the Chilean government was running low on cash and supplies; the United States, dismayed by Allende’s nationalization campaign, was doing its best to cut Chile off. And so a certain amount of improvisation was necessary. Four screens could show hundreds of pictures and figures at the touch of a button, delivering historical and statistical information about production—the Datafeed—but the screen displays had to be drawn (and redrawn) by hand, a job performed by four young female graphic designers. […] In addition to the Datafeed, there was a screen that simulated the future state of the Chilean economy under various conditions. Before you set prices, established production quotas, or shifted petroleum allocations, you could see how your decision would play out.
One wall was reserved for Project Cyberfolk, an ambitious effort to track the real-time happiness of the entire Chilean nation in response to decisions made in the op room. Beer built a device that would enable the country’s citizens, from their living rooms, to move a pointer on a voltmeter-like dial that indicated moods ranging from extreme unhappiness to complete bliss. The plan was to connect these devices to a network—it would ride on the existing TV networks—so that the total national happiness at any moment in time could be determined. The algedonic meter, as the device was called (from the Greekalgos, “pain,” and hedone, “pleasure”), would measure only raw pleasure-or-pain reactions to show whether government policies were working.
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“The on-line control computer ought to be sensorily coupled to events in real time,” Beer argued in a 1964 lecture that presaged the arrival of smart, net-connected devices—the so-called Internet of Things. Given early notice, the workers could probably solve most of their own problems. Everyone would gain from computers: workers would enjoy more autonomy while managers would find the time for long-term planning. For Allende, this was good socialism. For Beer, this was good cybernetics.
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Suppose that the state planners wanted the plant to expand its cooking capacity by twenty per cent. The modelling would determine whether the target was plausible. Say the existing boiler was used at ninety per cent of capacity, and increasing the amount of canned fruit would mean exceeding that capacity by fifty per cent. With these figures, you could generate a statistical profile for the boiler you’d need. Unrealistic production goals, overused resources, and unwise investment decisions could be dealt with quickly. “It is perfectly possible . . . to capture data at source in real time, and to process them instantly,” Beer later noted. “But we do not have the machinery for such instant data capture, nor do we have the sophisticated computer programs that would know what to do with such a plethora of information if we had it.”
Today, sensor-equipped boilers and tin cans report their data automatically, and in real time. And, just as Beer thought, data about our past behaviors can yield useful predictions. Amazon recently obtained a patent for “anticipatory shipping”—a technology for shipping products before orders have even been placed. Walmart has long known that sales of strawberry Pop-Tarts tend to skyrocket before hurricanes; in the spirit of computer-aided homeostasis, the company knows that it’s better to restock its shelves than to ask why.
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Flowers suggests that real-time data analysis is allowing city agencies to operate in a cybernetic manner. Consider the allocation of building inspectors in a city like New York. If the city authorities know which buildings have caught fire in the past and if they have a deep profile for each such building—if, for example, they know that such buildings usually feature illegal conversions, and their owners are behind on paying property taxes or have a history of mortgage foreclosures—they can predict which buildings are likely to catch fire in the future and decide where inspectors should go first.
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The aim is to replace rigid rules issued by out-of-touch politicians with fluid and personalized feedback loops generated by gadget-wielding customers. Reputation becomes the new regulation: why pass laws banning taxi-drivers from dumping sandwich wrappers on the back seat if the market can quickly punish such behavior with a one-star rating? It’s a far cry from Beer’s socialist utopia, but it relies on the same cybernetic principle: collect as much relevant data from as many sources as possible, analyze them in real time, and make an optimal decision based on the current circumstances rather than on some idealized projection.
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It’s suggestive that Nest—the much admired smart thermostat, which senses whether you’re home and lets you adjust temperatures remotely—now belongs to Google, not Apple. Created by engineers who once worked on the iPod, it has a slick design, but most of its functionality (like its ability to learn and adjust to your favorite temperature by observing your behavior) comes from analyzing data, Google’s bread and butter. The proliferation of sensors with Internet connectivity provides a homeostatic solution to countless predicaments. Google Now, the popular smartphone app, can perpetually monitor us and (like Big Mother, rather than like Big Brother) nudge us to do the right thing—exercise, say, or take the umbrella.
Companies like Uber, meanwhile, insure that the market reaches a homeostatic equilibrium by monitoring supply and demand for transportation. Google recently acquired the manufacturer of a high-tech spoon—the rare gadget that is both smart and useful—to compensate for the purpose tremors that captivated Norbert Wiener. (There is also a smart fork that vibrates when you are eating too fast; “smart” is no guarantee against “dumb.”) The ubiquity of sensors in our cities can shift behavior: a new smart parking system in Madrid charges different rates depending on the year and the make of the car, punishing drivers of old, pollution-prone models. Helsinki’s transportation board has released an Uber-like app, which, instead of dispatching an individual car, coördinates multiple requests for nearby destinations, pools passengers, and allows them to share a much cheaper ride on a minibus.
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For all its utopianism and scientism, its algedonic meters and hand-drawn graphs, Project Cybersyn got some aspects of its politics right: it started with the needs of the citizens and went from there. The problem with today’s digital utopianism is that it typically starts with a PowerPoint slide in a venture capitalist’s pitch deck. As citizens in an era of Datafeed, we still haven’t figured out how to manage our way to happiness. But there’s a lot of money to be made in selling us the dials.
Ref: The Planning Machine – The NewYorker
Cobot
PredPol – Predictive Policing
Ref: PredPol
Renew – Internet Connected Bins
The idea is to bring internet tracking cookies to the real world. The bins record a unique identification number, known as a MAC address, for any nearby phones and other devices that have Wi-Fi turned on. That allows Renew to identify if the person walking by is the same one from yesterday, even her specific route down the street and how fast she is walking.