Mapping connectedness

The site Switched On Or Switched Off uses short videos and zoomable maps to illustrate concepts in cartography and show how cartographers use maps to reveal connectedness in the modern world. Just one quick example below: using isochrones to measure ground travel times in the US reveals fractal patterns in road networks that resemble naturally-developing transport corridors, such as the circulatory system. 

Why is Google Maps so terrible at predicting travel times?

Every time I start a trip of any significant distance, I cue up google maps, which helpfully provides an estimated arrival time. Every time I finish the trip, inevitably later than google thought I would, I wonder why a company with so much data at its disposal is so atrociously bad at guessing how long I'll be on the road. 

Take a recent trip along major highways on the east coast. I left at 9AM. Predicted travel time: 6 hours, 32 minutes. Actual travel time: 9 hours. 

In contrast, google does a terrific job of predicting the duration of a trip across town, or home from my firehouse when I get off duty at 6AM. Intuitively, this makes sense, but when you really think about it, the duration of longer trips should be even easier to predict. 

Why? For starters, little delays during the course of a long trip will tend to smooth out the overall result. If I'm taking a drive of ten minutes and get stuck at two stoplights, adding two minutes to the trip, I've just skewed the results by 20%. But over hours, a delay at one red light will be offset by a green light elsewhere. The longer the time on the road, the more these small factors will tend to move the result toward an average.

Second, google has years of data on traffic speeds, particularly along major roadways. July 4th northbound Interstate 95 between Richmond Virginia and Washington DC? Google could probably predict travel time within 10 minutes for any time of the day, even allowing for one or two inevitable delays due to fender-benders along the way. It's (probably) impossible to predict major incidents, but aggregated traffic data should yield remarkably accurate results for normal days. And the longer the trip, the more accurate the prediction should be, because there should be less variability in the average number of disruptions. 

I have no idea how google guesstimates its travel times, but it appears to use a bafflingly simple approach of calculating the trip as if you were simultaneously passing through all waypoints at the moment of departure. So if you're departing at 5AM, it assumes you'll be cruising at full speed the entire way, instead of projecting forward - hey, it looks like you'll be passing through crushing gridlock in [major metropolitan area] during rush hour... that might just slow things down by, say, hours. Google should be utilizing its vast stores of data on how long it took other people like you passing through the same area during the same time before, even if no such delays exist at the time of departure. Heck, it could throw in 1) during similar weather conditions, 2) on this day of the week or around this major holiday, even incorporating 3) how you drive, if you're willing to let them harvest your data with such abandon.

All I know is, it's far more annoying to be given foolishly optimistic estimates, which are revised backward as you drive, than it is to be given the bad news up front. Listen up, google competitors, if any of you still exist. If you can give me an estimated time of arrival that doesn't diverge from reality more as the duration of the trip gets longer, I will drop google like a hot, inaccurate potato. 

Listen upward

Radio Garden allows you to drag a circle around a world map and tune into live radio from the selected area - a neat interface for discovering different stations outside your normal listening area. While apps like TuneIn offer much more selection from foreign radio markets (I often use it to listen to familiar stations in places where I once lived), Radio Garden offers a more exploratory environment that led me to more serendipitous discoveries. 

I see plans within plans

I'm not exactly sure what itch this scratches in me, but I liked these imaginatively drawn floorplans from fictional houses in popular TV shows. Most of them matched up with the mental maps I'd constructed from watching characters move through the nonexistent spaces, but this one made me realize I'd fundamentally misconstrued the layout of the central house from Stranger Things. I had to fast-forward through the first episode and observe the interior scenes to verify that I had it all wrong, and this map was accurate.

Real-time runners

I don't know if it's because I love to run or because I love new applications of mapping technology, but I'm mesmerized by this site, which allows you to view a sped-up rendering of all the athletes running the 2016 Berlin Marathon. As the race unfolds, the pack gradually spreads into a lopsided bell curve, with the most competitive runners outpacing the rest by a compelling distance, and a "long tail" of less fit runners stretching far behind the leading edge. The longer you go into the race, the more the curve appears to normalize around the average pace. 

Expect more mapping-related posts as we approach the release of You are Here: Tales of Cartographic Wonders, from SFFWorld. My story "The Shape of the World's Skin" appears alongside the work of 16 other science fiction and fantasy writers. 

Coming soon: Tales of Cartographic Wonders

I'm really, really excited about the forthcoming anthology You are Here: Tales of Cartographic Wonders, from SFFWorld. Yes, I'll admit that this is in part because my story "The Shape of the World's Skin" will appear in it. But I've been poking around the websites and catalogues of my fellow authors, and discovering I'm in the company of a lot of talent and some accomplished writers. This should be a very interesting collection.

You are Here has a tentative release date of November 12. Watch for it, or just keep watching here, because it's a pretty safe bet I'll continue to promote it.