People navigate with their destination in front of them — even if it’s not the most efficient route

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The path people follow is recorded by their mobile phones. Anonymous data from thousands of phones shows the way people follow in Boston (top) and San Francisco (bottom). Credits: Carlo Ratti, CC BY-ND

Consider a morning walk to work, school, or your favorite coffee shop. Do you take the shortest route to your destination? According to a big data survey conducted by a colleague and I The answer is no: People’s brains are not wired for optimal navigation.

Instead of calculating Shortest path, People try to point straight towards their destination. This is called the “most pointed road”, but it is not the most efficient way to walk.

As a researcher Study urban environment and human behavior, I was always interested in how people experience the city and how studying it can tell researchers something. Human nature And how have we evolved?

Chase the premonition

Long before I experimented, I had a premonition. Twenty years ago, I was a student at Cambridge University, but I realized that the path between the bedroom at Darwin University and the faculty at Chaucer Road was actually two different paths. On my way to Chaucer, I take a pair of turns. Another on the way home.

Sure, one route was more efficient than the other, but I was crazy about adapting two, one in each direction. I have found it small but frustrating for students who are consistently inconsistent and devoted their lives to rational thinking. Was it just me, or did my fellow classmates, and my fellow humans, do the same?

About 10 years ago, I found a tool that would help me answer my Senseable City Lab The Massachusetts Institute of Technology pioneered the science of understanding cities by analyzing big data, especially digital traces from mobile phones. Studying human mobility, as a whole, People’s routes were not conservativeThat means that the path from A to B did not hold the same path in the opposite direction from B to A.

But with the technology and analytical methods of the time, we couldn’t learn much more. In 2011, it was not possible to make a definite distinction between pedestrians and cars. We were nearby, but there were still some technical steps to tackle the mystery of human navigation in the city.

Big city, big data

Today, access to datasets of unmatched size and accuracy allows us to go even further.Every day, everyone’s smartphones and apps collect thousands of smartphones and apps Datapoint.. In collaboration with colleagues at MIT Brain Cognitive Science and other international scholars, we Analyzed a large database of anonymized pedestrian movement patterns In San Francisco and Boston. Our results take into account questions that my young self in Cambridge didn’t know to ask.

An analysis of pedestrian movements revealed that I was not the only one navigating in this way. Humans are not the best navigators. After considering the potential for interference from people who let Google Maps choose a path, analysis of big datasets facilitated some interrelated discoveries.

First, humans consistently deviate from the shortest route possible, and our deviations increase over long distances. This discovery probably seems intuitive.How the previous study is already People rely on landmarks and miscalculate street lengths..

Our research went one step further. The idea is to develop a model with the ability to accurately predict the slightly irrational paths found in the data. The most predictive model of the most common mode of urban navigation is not the fastest path, but a model that seeks to minimize the angle between the direction in which a person travels and the line from person to destination. I found out.

The findings appear to be consistent in different cities. Evidence was found that pedestrians are trying to minimize this angle, both in Boston’s famous complex streets and in San Francisco’s orderly grid.Scientist recorded Similar behavior in animals, Described in the research literature as vector-based navigation. Perhaps the entire animal kingdom shares a peculiar tendency that confused me on a walk to work.

Evolution: From Savannah to Smartphone

Why does everyone travel this way? The desire to point in the right direction can be a legacy of evolution. In the savanna, calculating the shortest route and pointing the target straight will give very similar results. Only today has it become clear that people’s shorthands are not completely optimal due to traffic, congestion, ring roads and other restrictions on urban life.

Still, vector-based navigation may be appealing.Evolution Trade-off storyThe cognitive load of perfect computation, not optimization road Rather than relying on simpler pointing methods, it may not be worth saving a few minutes. After all, early humans had to maintain their brain power to fend off elephants in stagnation, just as people today need to focus on avoiding aggressive SUVs. .. This imperfect system was sufficient for countless generations.

But people no longer walk or think alone.They are getting married more and more Digital technologyTo the point that the phone represents an extension of one’s body.Some people insisted on it Humans are becoming cyborgs..

This experiment reminds us of a catch: technical prostheses don’t think like their creators. The computer is perfectly rational. They do what the code tells them to do. On the other hand, the brain is “Bounded rationality“Good enough” and the necessary compromise. As these two different entities become more and more intertwined and clash (on Google Maps, Facebook, or self-driving cars), it’s important to remember how they differ from each other.

Looking back on my college days, it’s a cool idea that human biological source code is much more like the source code of a mouse in the street than the computer code in our pocket. The more people are absorbed in technology, the more important it is to create technology that addresses human irrationality and peculiarity.

How the brain navigates the city: seems to be wired to calculate the “most pointed” path instead of the shortest path

For more information:
Christian Bongiorno et al, Vector-based pedestrian navigation in cities, Nature Computational Science (2021). DOI: 10.1038 / s43588-021-00130-y

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People navigate with their destination in front of them — even if it’s not the most efficient route

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