Better software to reduce traffic

Adaptive traffic software has helped reduce congestion in Ann Arbor:

Ann Arbor’s adaptive traffic signal control system has been playing god for more than a decade, but fiddling engineers continue to tweak its inputs and algorithms. Now it reduces weekday travel times on affected corridors by 12 percent, and weekend travel time by 21 percent. A trip along one busy corridor that took under three minutes just 15 percent of the time in 2005 now comes in under that mark 70 percent of the time. That’s enough to convince Ann Arbor’s traffic engineers, who just announced they’ll extend this system to all its downtown traffic lights and its most trafficked corridors.

To combat congestion, each hopped-up signal uses pavement-embedded sensors or cameras to spot cars waiting at red lights. The signals send that information via fiber network to the Big Computer back at traffic management base, which compiles the data.

This stuff works on a macro and micro level: If there are four cars lined up to go one way through an intersection, and zero cars lined up to move perpendicular to them, the light might turn green for the four. But a network of connected lights—like in Ann Arbor—will analyze the entire grid, and figure out who to prioritize to get the most people to their destinations the fastest. Advanced traffic control systems can even predict delays and congestion build-up before they happen, based on the ebb and flow of commutes…

The system knows when to lay off the change. “People kind of freak out if the signal is really different from yesterday or different from what it was five years ago,” says Richard Wallace, who directs the Center for Automotive Research’s transportation systems analysis group. For the most part, the system looks to tweak light patterns, not reshape the whole shebang from one hour to the next.

As we wait for the complete takeover by driverless cars, this could help ease our troubles. Small but consistent improvements like this could make a big difference to many commuters. Of course, it could also have the effect of encouraging more drivers who see that the commute is not so bad. Perhaps this is why the lights should be somewhat haphazard; it might unnerve a few of those drivers.

I assume there are some costs associated with putting in sensors and cameras as well as in developing the software and having employees to set up and run the system. How do these costs compare to the money saved in shorter driving trips? Or, what if this money had been put into opportunities like mass transit that would remove drivers from the roads?

Imagine corporate highways with autonomous vehicles

Pair self-driving vehicles with highways that can coordinate their movement and corporations may be interested. More on those highways:

Amazon was awarded a patent for a network that manages a very specific aspect of the self-driving experience: How autonomous cars navigate reversible lanes…

In the patent, Amazon outlines a network that can communicate with self-driving vehicles so they can adjust to the change in traffic flow. That’s particularly important for self-driving vehicles traveling across state lines onto new roads with unfamiliar traffic laws…

The patent also indicates that the roadway management system will help “assign” lanes to autonomous vehicles depending on where the vehicle is going and what would best alleviate traffic…

The main difference is that Amazon’s proposed network would be owned and operated by Amazon, not each individual automaker. It also appears to be designed so any carmaker’s vehicles can take advantage of the technology.

We’ve seen highways funded or operated with private money. But, imagine a highway built and run by Amazon for the primary purposes of moving Amazon traffic. With the traffic management capabilities and the autonomous vehicles, you could reduce the number of required lanes, increase speeds, and cut labor costs. Roads still aren’t cheap to construct but this may be feasible monetarily in particular corridors.

Even better: an Amazon Hyperloop.

Making carpooling in America great again

A scientist discusses the issues that need to be solved for Americans to voluntarily carpool in larger numbers:

Maybe carpooling apps should let drivers set clear terms about the kind of behaviors they expect and encourage in their car, says Glasnapp. Maybe they permit conference calls and snacking, or maybe they’d prefer friendly, food-and-phone-free conversation. (Or total silence!) Riders should have the option to choose specific types of in-car experiences, too, with the understanding that the lower cost they are paying to carpool comes with a different set of expectations than does ride-hailing.

Technology has simplified the logistics of the rider/driver experience, says Glasnapp, but that sometimes comes at the expense of control. Most carpool apps offer specific time brackets during which drivers and riders can schedule rides—for example, on Scoop, morning trips have to be solidified by 9 PM the night before, and evening trips by 3:30 PM the same day, and matches are made after that deadline. That clarity is nice, says Glasnapp, but it’s almost too inflexible, since the system penalized him for making changes afterwards, and didn’t notify him if his ride offer had been accepted until after the cut-off. On the other hand, Waze operates its carpool system at any time of the day that drivers are on the road, which can be somewhat chaotic for riders’ expectations, says Glasnapp. The best carpool app will find a balancing point between structure and flexibility…

Finding the sweet spot for payment might be the most elusive goal for a great carpool system. Each app Glasnapp tested had their own approach to setting prices and payments for passengers and drivers: On Waze, riders pay a price that reflects the federal mileage reimbursement rate of $.54 per mile; this money is transferred directly to the driver. Lyft took the approach of setting flat fares, where carpool drivers earned up to $10, and riders paid anywhere between $4 and $10. Scoop pricing follows a similar model, and it also partners with local employers to provide discounted trips for riders, Glasnapp says. So long as drivers are still getting their cut, that’s an attractive strategy for all parties.

Even if the mileage rate is attractive on its face, though, the length of the journey has to match up to the driver’s expectation of fair compensation. If you’re already driving 40 miles to work, a request from a rider who is 17 minutes out of the way might require a pretty healthy compensation for you to accept—more than, say, the $10-and-under that a standard Lyft or Waze trip paid. “I think there is a magic number for every driver based on amount of inconvenience,” Glasnapp says. This is also sort of a chicken-and-egg problem—if there were more carpool drivers on the road, they wouldn’t be receiving such far-flung requests. But a great carpool app will need to nail the (highly individual!) question of pricing, so that more drivers want in.

A few other problems I could imagine:

  1. The lack of personal space. Is there a way to design carpool vehicles where each person has this own compartment? This would cut down on the problems of differences in behavioral expectations and have the passengers and drivers not even interact or possibly even see each other.
  2. Can everyone who wants to find someone to carpool with? I’m imagining it would be tougher for those with irregular work hours or who live in certain locations (or have unique paths). Would this be seen as a penalty for certain people for circumstances that may be difficult to control?
  3. Is the answer necessarily an app?
  4. The article suggests Americans have done this twice before – World War II and the 1970s Oil Crisis. This could be reassuring …or not. Might it suggest that Americans will only carpool when circumstances really demand it?

Avoid public wi-fi

Here is a helpful reminder:

And finally, don’t forget for one minute that public Wi-Fi is dangerous.

This one illustration is humorous:

Evan, now 11, programmed fake Wi-Fi portals and took them to food courts shopping centers across the Austin, Texas, area and waited to see how many agreed to some pretty outrageous conditions. For the love of free internet access, they’d have to give their OK for the Wi-Fi owner to do things like “reading and responding to your emails, monitoring of input and/or output, and ‘bricking’ of your device.”

More than half of the shoppers shown these terms accepted them.

I like that this the article ties this issue to shopping malls. This might primarily be due to this time of year when plenty of people are out purchasing gifts. However, it also works because shopping malls are about as close as we get as Americans to public spaces. Where else can you regularly go for a safe environment to be around other people to do one of the ultimate American activities (consume)? While this article reminds us that the mall may not be so safe, is it odd that Americans tend to think of it as a safe place? And if malls want to keep attracting people (who then spend money), shouldn’t they do something about protecting their wi-fi?

I see an opportunity for either malls or security firms: ensuring that your public wi-fi experience is a good one.

The Internet and social media can help us see more small things but the bigger picture is still fuzzy

On one hand, the Internet and what comes along with it allows us unprecedented access to what is going on in the world. Information galore. Bypassing the traditional gatekeepers of the media. Access to millions of stories we might not have otherwise seen or heard.

On the other hand, it is a glut of stories and information. The social media feeds just keep going. The 24 hour news cycle of cable TV news is now an up to the second compendium of events big and small. There is a lot to take in. Some of the research I’ve done with the social media use of emerging adults suggests some have a hard time keeping up with it all. What should we pay attention to?

Going forward, I fear the extra information we now have – an unprecedented amount in human history – isn’t helping as much as it might. This is the case for at least four reasons. First, even though we have more information, we still don’t have all the information. As Max Weber once said, social life is so complex that it is difficult to imagine even social scientists understanding all aspects of social phenomena. Second, we’re not necessarily good as humans or trained well in how to process all the information. Certain things catch our eye – for example, such as information that agrees with what we already think (confirmation bias) – while we see others but they don’t register at all. Third, there is simply too much. Perhaps humans were not made to think at this scale; for much of human history, we lived in relatively small settings and had close relationships with people who were pretty similar to us. See Dunbar’s Number as an example of how the limits of humans comes up against friends and followers on social media.

Fourth, and this is where my sociological perspective particularly comes in, it is difficult work to connect individual level data – what we might call microsociology – with larger societal trends – macrosociology. Take this example: we see a post of involving a person with particular traits leaving no tip for a waitperson which they have posted on social media. Unfortunately, such negative interactions happen frequently. But, are we to take this single example as just an attempt to point out a wrong done by a single customer or does this one event reflect on an entire people group? Or, is a serious weather event on the other side of the world (one we would have had little knowledge about even a few decades ago) evidence for climate change or for deniers? When we are immersed in so many small events and their immediate interpretations, how are we to form big picture understandings of patterns? It requires us to step back and try to make sense of it all rather than simply slotting each small event into our existing heuristics.

Our capacities to deal with all of this information may improve in coming years as it becomes the new normal. Or, some may go another direction – though it is hard to imagine – where they retreat from this information overload. Either way, we’ll need to figure out ways to help everyone see the broader patterns so we all don’t lose the forest for the tees.

Let Amazon’s big data tractor trailer drive to you

Americans like big trucks and hard drive space so why not put the two together?

Amazon announced the new service, confusingly named Snowmobile, at its Re:Invent conference in Las Vegas this week. It’s designed to shuttle as many as 100 petabytes–around 100,000 terabytes–per truck. That’s enough storage to hold five copies of the Internet Archive (a comprehensive backup of the web both present and past), which contains “only” about 18.5 petabytes of unique data...

Using multiple semis to shuttle data around might seem like overkill. But for such massive amounts of data, hitting the open road is still the most efficient way to go. Even with a one gigabit per-second connection such as Google Fiber, uploading 100 petabytes over the internet would take more than 28 years. At an average speed of 65 mph, on the other hand, you could drive a Snowmobile from San Francisco to New York City in about 45 hours—about 4,970 gigabits per second. That doesn’t count the time it takes to actually transfer the data onto Snowmobile–which Amazon estimates will take less than 10 days–or from the Snowmobile onto Amazon’s servers. But all told, that still makes the truck much, much faster. And because Amazon has data centers throughout the country, your data probably won’t need to travel cross-country anyway.

One could make a strong case that semis make America go. And all the money that the government has put into highways and roads certainly helps.

Your McMansion is so big, you need a wifi mesh

Coming soon to a McMansion near you: a wifi mesh from Google.

Google Wifi is available for pre-order in the US at retailers like the Google Store. A single Wifi point retails for $129, and covers homes up to 1,500 square feet. The three-pack, at $299, covers homes up to 4,500 square feet. Google Wifi ships on December 6th, just in time for fast Wi-Fi for all of your holiday guests.

All the Wifi points are connected to each other. Data can take several paths toward its destination — and Google uses their Network Assist technology to ensure that Google Wifi points always choose the fastest route from your device to the internet. This means that you get faster Wi-Fi speeds for things like streaming and gaming.

Because it would defeat the purpose of having an impressive McMansion if you and your guests couldn’t enjoy a wonderful wifi experience…

I’m waiting to see more McMansions and regular homes build around the all-important wifi as the central feature. Forget all of this about open concept living, great rooms, separate spaces for men, women, and the kids; homes should start with great wifi and build around that. With the Internet of Things supposedly just around the corner, this may happen soon.

UPDATE 11/20/16 at 1:16 PM: This is no joke. I keep hearing Comcast ads pushing their faster Internet. The reason you need it? So all of your holiday guests can do all they need to do on the wifi at the same time. Aren’t all those holiday guests supposed to be interacting or spending time together as a family?