Alternate Scale Maps and Decisionmaking
The problem with assumptions is that they are invisible but not universal. Individuals are barely aware of the fact that they information that they ‘intuitively’ take from a page of statistics or data is colored by the assumptions they have. Another problem is that assumptions can happen at a level of consciousness significantly higher than the simple ‘fundamental mind.’
This post is about speed limits.
In the pre-MapQuest era, looking at a paper map had the primary purpose of helping people estimate routing. The task of routing is fantastic, not only because it’s has given birth to many cool algorithms that are useful in other areas, but because it is not a single-variable optimization problem: you are not just trying to get from point A to point B in the shortest time. Road conditions, tolls, and highway driving are all factors that change the routing decision in complex ways. I’d posit that before MapQuest, another factor, familiarity, played a massive role, since ‘shortcuts’ were far less reliable and more costly to perform when the driver needs to remember every turn correctly.
What is the function of a driving map? In many cases, a folding paper map is used to estimate the best way to get from one point to another, and it’s arguable that this does a very poor job of this. The human tendency in routing is to simply choose a straight path, or the one that avoids the most obvious obstacles, but that is rarely the best decision given road systems, and traditional maps do little to alleviate this problem.
Highways are faster than side roads, but precisely the same length on paper, and drivers care about real length – not physical length, but the time taken to get from one place to another. Maps attempt to represent speed differences by making highways thicker, but this distinction isn’t natural; it’s something that’s learned – domain-specific knowledge, in a way. And, even if the higher brain is thinking about a smart route using highways, it’s unlikely that, combined with the intuitive shortest-route, the natural human calculation is best.
So the first idea that I came up with was to create a map that preserved all roads but converted physical distance to practical distance: time. This would create some zany map much like a cartogram.
But cartograms aren’t very cool. While they look cool, they don’t, at the end of the day, serve as a great information source.
Routes are decisions, not descriptions. I will say that, like a few other people, I had an idea quite similar to the do I need an umbrella website, but didn’t implement it. The idea is really vital, though. Weather forecasts were descriptions of conditions, when they truly are used as prescriptions of what to do. The same goes for routes – a map of a twisty, curvy two-hundred and fourteen mile journey from my apartment in DC to home in New Jersey is a great description of what my actions will cause, but is a waste of space for instructions.
Here’s a map that I figured might do a slightly better job. Also, given the threat that this could be called an arcmap (like ArcMap), let’s call it a routemap.
I thought about implementing this, and I have some half-baked code at the ready, both some that parses OpenStreetMap data and one that grabs data from Google Maps API directions, but here’s the idea first.
Update: Bing Destination Maps
Bing Maps recently implemented an idea somewhat in line with this thinking: Destination Maps. Infosthetics has a great summary and screenshots for those who don’t want to install Silverlight. Basically the idea is that excessive context quickly becomes visual noise when you have a good idea of what a user wants – so focus more on the actual path taken rather than every alternative. Bing maps in particular are very noisy by default – satellite Bing maps include visual garishness like drop shadows and glows – so this is an ideal feature for the service.
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