Stepping right when your next destination is straight ahead

Stepping right when your next destination is straight ahead: Your ultimate plans guide your navigation now

When Christopher Columbus reached the new world, he famously thought he had circumnavigated the globe and landed in India. This may be history’s most famous navigational error but it is far from the only one. Although people are quite good at managing their daily travel through space, a large number of biases and potential sources of error exist.

For example, geographical or political knowledge can intrude into spatial judgments, when we believe that Reno, Nevada, is to the East of San Diego, or when we think Vienna, Austria, is to the West of Prague. In both cases, those beliefs are well-founded—Nevada is to the East of California and during the cold war Czechoslovakia was part of the Eastern Warsaw Pact that opposed the West—but also quite wrong.

Even subtle cues, such as presumed gravitational effects, can affect our (mis-)perception of travel times. Apparently most people think that traveling the same distance north, away from the equator, takes more time than traveling southbound. Why? Perhaps because we are so used to seeing north as “up” and south as “down” on maps that traveling “down”, aided by gravity, might be faster than travel in the reverse direction.

And as if that weren’t enough, apparently even bras (yes, brassieres) can cause potentially fatal navigational errors, according to the Mountaineering Council of Scotland.

recent article in the Psychonomic Society’s journal Memory & Cognition reviewed some of those findings about human navigation abilities and investigated a new phenomenon, namely the effect of later destinations on people’s initial route choice.

Researchers Fu, Bravo, and Roskos first reviewed the existing literature and summarized our knowledge about human navigation succinctly in a few memorable points:

  • When people plan a route, they seek to minimize the number of turns and they prefer a route that has a long initial segment.
  • People also seek to minimize the deviation from a straight line from the start to the destination.
  • When navigating between distinct neighborhoods or regions, we seek to minimize the distance between regions first, and then plan how to get to the destination within the target region once we get there.

The question that Fu and colleagues were particularly interested in was how those known biases would be affected by the presence of multiple subsequent destinations. Would your choice of route to India be affected by whether you next visit Ulan Bator or Grytviken?

The experimental setup is shown in the figure below.

Participants commenced each trial by sitting at a desk situated at the front of a classroom. This is labeled “R” in panel B above. From that position, participants could see sheets of paper of various colors that were placed on the next three rows of tables (e.g., blue, yellow, and pink in the figure above). Participants’ task was to visit the tables with sheets of paper in order of rows (i.e., from blue to yellow to pink) and to answer the multiple-choice question that was printed on each sheet. The cover story for the experiment was that the researchers were interested in decision making (hence the multiple choice questions) but what they were really measuring was the path people took from their starting position to the various destinations.

The measure of interest was which way people would turn to walk around the reception table (labeled R above) to get to the first destination (X), which was always in the center of the first row. Would people walk to the left or to the right of R to get to X? The two route choices are absolutely identical in terms of length or complexity and so on.

Intriguingly, people’s choices on their first leg were determined by the location(s) of the second and third destinations.

When there were only two destinations (i.e., “blue” and “yellow” above), the position of the yellow sheet had a marked effect on how people walked around the reception desk (R). When the yellow sheet was on the left, as shown above, people walked to the left of R on a whopping 80% of trials. When the yellow sheet was on the right table, people walked to the right of R an overwhelming 70% of the time. When “yellow” was in the middle, people were exactly evenly split between right and left.

So the second destination determined people’s choice between two identical routes for an earlier destination—and the effect was rather large, changing preferences between identical options from 80/20 to 70/30.

What if a third destination was present (in the third row)? That is when things got to be particularly intriguing and complex. I focus here on what happened when the yellow sheet was in the center of the second row. We know that if the central yellow sheet was the last destination, people were evenly split between right and left. When a third destination was added (pink sheet in the figure above), then the way in which people walked around the reception table depended on the location of that third destination: When the pink sheet was on the left (but yellow in the center), then people were less likely to turn right around R than when the pink sheet was on the right—and that effect was again quite large, ranging from 33% right turns (pink on left) to 62% (pink on right).

In other words, even a distant third destination exerted a strong “pull” on people’s very first choice between two identical routes.

In two further experiments Fu and colleagues showed that this “pull” from later destinations persist even when the final destinations are invisible at the outset and their location must be inferred from a map.

Fu and colleagues conclude that “The preferred routes to the first destination correspond generally to the least angle formed by the initial direction of the route and the direction of later destinations.” The well-known least-angle bias, in other words, can be triggered by future destinations even when the first route choice does not affect total path length, complexity, or any other variable that would objectively differentiate between routes.

What remains to be seen, and what’s next on Fu’s agenda, is if those laboratory results scale up to “real-world” situations in which people must navigate large distances with the aid of maps. If the results scale up, it would mean that the next time you drive from Washington, D.C. to Harrisburg, your choice of which way you take the Beltway around Baltimore might be affected by whether your final destination is Allentown or Bedford.

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