How the brain navigates cities(news.mit.edu)
news.mit.edu
How the brain navigates cities
https://news.mit.edu/2021/how-brain-navigates-cities-1018
51 comments
I used to walk across SF on a daily basis and I would usually go out of my way to avoid certain streets. Some because of homeless people/blocked sidewalks, others because of hyper-aggressive traffic. I'd happily add 10 minute to my walking commute just to start my day on slightly more pleasant streets.
I often use a different "optimization": instead of crossing streets at intersections and waiting for traffic lights, I cross them mid-block when traffic allows. Of course that's easier to do in Munich than in New York...
I do the same (Kraków). I also prefer to do "mid-block" crossing on speed bumps, because the traffic is guaranteed to be slow, and sometimes make an impromptu decision to cross the street earlier on a lights-free intersection when I spot a bus or a tram making a turn upstream, as it takes its time and blocks off incoming traffic for the duration.
Humans have a complex goal function when optimizing their route, and they do online optimization (i.e. adjust as they go).
Humans have a complex goal function when optimizing their route, and they do online optimization (i.e. adjust as they go).
>Of course that's easier to do in Munich than in New York...
That really depends on the street.
That really depends on the street.
right, my route changes throughout the year as I optimize for more/less shadows to avoid hot/cold
I did that as a teenager, because I had stable routes (to/from school at roughly the same times). As an adult, I maintain awareness of the sun's position and keep following/avoiding the shadows on hot/cold days, sometimes crossing the street back and forth or in advance of a shade I'd like to take/avoid.
It's almost an automatic process, but it has a visual perception component - on hot days, the lit side looks "too bright" to me, and on cold days, the shaded side looks "too dark" - so I take the side that looks "just right".
It's almost an automatic process, but it has a visual perception component - on hot days, the lit side looks "too bright" to me, and on cold days, the shaded side looks "too dark" - so I take the side that looks "just right".
I'm always surprised that more people don't do this. It will be a hot sunny day, and I'll see people standing at an intersection waiting to cross. They'll be out in the sun, when mere feet away are shady spots they could wait in. I don't understand how/why they tolerate the heat instead of expending the tiniest effort to get in the shade.
Personally, I have a pretty wide range of tolerance thanks to a career of working in the field so unless it is truly unbearably hot I just may not bother to find shade if I'll only be standing there a minute or two waiting for the light to change for me, for example.
it’s pretty high on the hierarchy of needs, most people are just preoccupied… I tend to over analyze small optimizations like this to exert control over an otherwise chaotic reality
My kids gave it a name: shade hopping
Some people want to tan; others are trying to avoid it.
> It's efficient to cross wherever you see a walk sign early
Don't forget that jaywalking.
Don't forget that jaywalking.
The Seattle area (though not signifcant swaths of Seattle itself) are built on a cardinal grid, meaning you can get pretty much anywhere with just 1 turn, ignoring dead end streets.
It is pretty nice, it means getting lost around here is hard.
Our addressing system is absurdly logical, first 2-3 digits of house address are the street #, then you have the cross street as the 2nd part of the address. (Named streets actually are also numbered on the grid, and you can see the real street # above the name sign!)
This means you can give me an address and I:
1. Know the exact location 2. Can navigate there
Again with a sad exception for named streets, you'll have to look up the # of the street first before you head out.
Because everything is on a cardinal grid, you just head north/south and then east/west.
The best part is, if you get lost, it is easy to re-orientate yourself!
If you get wet and the water tastes salty, you went too far west!
If you get wet and it is fresh water with a hint of sewage, you went too far east!
If everyone around you gets really polite, you are way too far north and have ended up in Canada, and if you see gas station attendants pumping gas, you've gone too far south and have landed in Oregon. Easy peasy!
It is pretty nice, it means getting lost around here is hard.
Our addressing system is absurdly logical, first 2-3 digits of house address are the street #, then you have the cross street as the 2nd part of the address. (Named streets actually are also numbered on the grid, and you can see the real street # above the name sign!)
This means you can give me an address and I:
1. Know the exact location 2. Can navigate there
Again with a sad exception for named streets, you'll have to look up the # of the street first before you head out.
Because everything is on a cardinal grid, you just head north/south and then east/west.
The best part is, if you get lost, it is easy to re-orientate yourself!
If you get wet and the water tastes salty, you went too far west!
If you get wet and it is fresh water with a hint of sewage, you went too far east!
If everyone around you gets really polite, you are way too far north and have ended up in Canada, and if you see gas station attendants pumping gas, you've gone too far south and have landed in Oregon. Easy peasy!
> This means you can give me an address and I: 1. Know the exact location 2. Can navigate there
Haha, but can you get back on I5 going north from downtown Seattle or Capitol Hill? You have to know where the secret onramps are, and when traffic is heavy have to position yourself in the correct line well in advance. If you're lucky you might find the Sacred Portal onto the express lanes.
Haha, but can you get back on I5 going north from downtown Seattle or Capitol Hill? You have to know where the secret onramps are, and when traffic is heavy have to position yourself in the correct line well in advance. If you're lucky you might find the Sacred Portal onto the express lanes.
The secret I5 on-ramps, yeah WTF.
No idea where the express lane on-ramp is, haven't bothered figuring that out!
No idea where the express lane on-ramp is, haven't bothered figuring that out!
> No idea where the express lane on-ramp is
Seattle doesn't let just anyone enter the Sacred Portal. One has to be worthy.
Seattle doesn't let just anyone enter the Sacred Portal. One has to be worthy.
I feel like there are some flaws in this, we don't usually have a "top-down" look at a mile around us if not given information (ie. fog of war), feels like we tend to point A to point B repeat because we are comfortable to take a route until otherwise told by someone else there is a shorter path. For example if someone had a drone/scout around I am sure you would be able to determine best routes and chokepoints, traffic, etc.
I think this is a big factor. If I'm pointed towards my destination, then I always know I'm making progress, and it's easy to stay oriented. In a less "direct" (but shorter) route, it may not be obvious if you make an incorrect turn.
I think another factor is just habit. The first few times you take a walk, you'll likely take the "easiest" route, even if it's not optimal by other measures. On subsequent trips, you'll likely just use the route you already know, instead of experimenting with different paths.
I think another factor is just habit. The first few times you take a walk, you'll likely take the "easiest" route, even if it's not optimal by other measures. On subsequent trips, you'll likely just use the route you already know, instead of experimenting with different paths.
Related: Navigation-related structural change in the hippocampi of taxi drivers (2000)
Structural MRIs of the brains of humans with extensive navigation experience, licensed London taxi drivers, were analyzed and compared with those of control subjects who did not drive taxis. The posterior hippocampi of taxi drivers were significantly larger relative to those of control subjects. A more anterior hippocampal region was larger in control subjects than in taxi drivers. Hippocampal volume correlated with the amount of time spent as a taxi driver (positively in the posterior and negatively in the anterior hippocampus). These data are in accordance with the idea that the posterior hippocampus stores a spatial representation of the environment and can expand regionally to accommodate elaboration of this representation in people with a high dependence on navigational skills. It seems that there is a capacity for local plastic change in the structure of the healthy adult human brain in response to environmental demands.
https://www.pnas.org/content/97/8/4398
Structural MRIs of the brains of humans with extensive navigation experience, licensed London taxi drivers, were analyzed and compared with those of control subjects who did not drive taxis. The posterior hippocampi of taxi drivers were significantly larger relative to those of control subjects. A more anterior hippocampal region was larger in control subjects than in taxi drivers. Hippocampal volume correlated with the amount of time spent as a taxi driver (positively in the posterior and negatively in the anterior hippocampus). These data are in accordance with the idea that the posterior hippocampus stores a spatial representation of the environment and can expand regionally to accommodate elaboration of this representation in people with a high dependence on navigational skills. It seems that there is a capacity for local plastic change in the structure of the healthy adult human brain in response to environmental demands.
https://www.pnas.org/content/97/8/4398
This is only tangentially related, but I wonder if other people have noticed the phenomenological changes that happen as you become familiar with a city.
When I come to a new city everything seems "flat," for want of a better word. The four directions at an intersection all have the same weight and pull and elevation.
Once I get to know a city, my brain starts to introduce a sense of "upwardness" and "downwardness." Usually this is simply the cardinal directions, but not always, and in any case it rarely relates to actual changes in elevation. Once I know a city well, it's impossible to get the sense of "flatness" again, except for rare occasions when I come out of a subway stop and I'm disoriented, and then it can feel like a new city again.
When I come to a new city everything seems "flat," for want of a better word. The four directions at an intersection all have the same weight and pull and elevation.
Once I get to know a city, my brain starts to introduce a sense of "upwardness" and "downwardness." Usually this is simply the cardinal directions, but not always, and in any case it rarely relates to actual changes in elevation. Once I know a city well, it's impossible to get the sense of "flatness" again, except for rare occasions when I come out of a subway stop and I'm disoriented, and then it can feel like a new city again.
yeah that's sorta what Kevin Lynch's book "The Image of the City" is about: https://en.wikipedia.org/wiki/The_Image_of_the_City
very influential book
very influential book
I see this is about point-to-point navigation optimization but it's very curious this article doesn't mention grid cells – essentially, neurological ~1:~1 representations of physical space.
> They were awarded the 2014 Nobel Prize in Physiology or Medicine together with John O'Keefe for their discoveries of cells that constitute a positioning system in the brain. The arrangement of spatial firing fields, all at equal distances from their neighbors, led to a hypothesis that these cells encode a neural representation of Euclidean space.[1] The discovery also suggested a mechanism for dynamic computation of self-position based on continuously updated information about position and direction.
https://en.wikipedia.org/wiki/Grid_cell
> They were awarded the 2014 Nobel Prize in Physiology or Medicine together with John O'Keefe for their discoveries of cells that constitute a positioning system in the brain. The arrangement of spatial firing fields, all at equal distances from their neighbors, led to a hypothesis that these cells encode a neural representation of Euclidean space.[1] The discovery also suggested a mechanism for dynamic computation of self-position based on continuously updated information about position and direction.
https://en.wikipedia.org/wiki/Grid_cell
This article indicates a 1:1 relationship doesn't apply in 3D. I haven't had time to read and understand this enough but it seems worth passing on the article since its something on my list to dig into this weekend.
"But when researchers were finally able to record from grid cells in animals navigating 3D spaces, the findings got “much more dramatic,” Ulanovsky said — seeming to demonstrate not just deviations from the framework, but departures from it. ... To their surprise, the hexagonal patterns that defined the cells’ behavior in 2D were gone entirely: The researchers couldn’t find even traces of that global order. Instead, the clumps of grid cell activity seemed to be distributed throughout the three-dimensional space at random. “Some properties were preserved,” Jeffery said, “but the most visually striking property of grid cells was not.”"
https://www.quantamagazine.org/how-animals-map-3d-spaces-sur...
"But when researchers were finally able to record from grid cells in animals navigating 3D spaces, the findings got “much more dramatic,” Ulanovsky said — seeming to demonstrate not just deviations from the framework, but departures from it. ... To their surprise, the hexagonal patterns that defined the cells’ behavior in 2D were gone entirely: The researchers couldn’t find even traces of that global order. Instead, the clumps of grid cell activity seemed to be distributed throughout the three-dimensional space at random. “Some properties were preserved,” Jeffery said, “but the most visually striking property of grid cells was not.”"
https://www.quantamagazine.org/how-animals-map-3d-spaces-sur...
there are also "vector cells" https://www.nature.com/articles/s41593-020-00761-w
Neuronal vector coding in spatial cognition: https://www.nature.com/articles/s41583-020-0336-9?proof=t
Neuronal vector coding in spatial cognition: https://www.nature.com/articles/s41583-020-0336-9?proof=t
There is a quote saying 'humans are not optimal navigators'... but it just depends on what you are optimizing for. We optimize for minimal cognitive load.
I had to traverse about 50 miles each way to a generating station for a year back in the 1980s. I learned how to get there from my boss, then quickly optimized the route as I drove it daily. After a week or two, I started searching widely for alternatives, and over time I just explored and picked the fun routes, or fast routes depending on my timeliness that day.
I can reliably get back anywhere I've driven, assuming I started at home. On vacation it takes a day or two for that to be true. I doubt those now dependent on Navigation aids can do so.
I can reliably get back anywhere I've driven, assuming I started at home. On vacation it takes a day or two for that to be true. I doubt those now dependent on Navigation aids can do so.
> Several years ago, the lab acquired a dataset of anonymized GPS signals from cell phones of pedestrians as they walked through Boston and Cambridge, Massachusetts, over a period of one year.
I sure hope those people gave their consent and were adequately compensated for their data, because repeated observations as people walk between their home and their workplace is among the least-anonymizable data I can imagine.
I sure hope those people gave their consent and were adequately compensated for their data, because repeated observations as people walk between their home and their workplace is among the least-anonymizable data I can imagine.
I have news for you...
https://techcrunch.com/2019/05/16/a-year-after-outcry-carrie...
https://techcrunch.com/2019/05/16/a-year-after-outcry-carrie...
I remember while I was a kid, my father pointed me to a conundrum. In a front of our house there was a rectangle made of paths, and often we needed to cross this rectangle diagonally, but naturally we walked by its sides. And somehow we chose one path when coming home and another when moving from home. Why one path seems shorter when walking one direction and longer when walking the other one? I was grown enough to see that it is just plain stupid: both paths are of equal length. But at the same time one seemed shorter, and which one depended on a direction.
He proposed a solution: we choose "more pointed" path, so we move a long side of rectangle first and a shorter one then. It is funny to see how scientists come to the same conclusion 30 years after my father.
He proposed a solution: we choose "more pointed" path, so we move a long side of rectangle first and a shorter one then. It is funny to see how scientists come to the same conclusion 30 years after my father.
I wonder if there's also a preference in the mind to stay on a particular street as long as possible, because the street architecture, street furniture and amount of traffic stays roughly the same, and therefore predictable and easy to walk on.
Like the example given in the article, I also take different routes from and to work regularly, with my bicycle. This habit developed naturally, I didn't really plan it. I was reflecting on why I do this, and your explanation of street continuation seems to be a better fit.
When I start in either direction, I do not have a clear heading of the destination, as there is no line of sight, so the pointiness from the article makes less sense. I guess continuing forward on the same street feels getting there faster, as making a turn feels slow.
When I start in either direction, I do not have a clear heading of the destination, as there is no line of sight, so the pointiness from the article makes less sense. I guess continuing forward on the same street feels getting there faster, as making a turn feels slow.
This is evergreen. MIT has been singing this tune for more than sixty years. Since Kevin Lynch's The Image of the City was published by MIT press in 1960. https://en.wikipedia.org/wiki/The_Image_of_the_City
A great book (or as Bezos wants us to say, "a Goodread"). Highly recommended if you're interested in this sort of urban analysis. My architectural mentor, the late David Crane, FAIA was Lynch's research assistant while a grad student at Harvard;'s GSD. He's listed in the acknowledgements.
A great book (or as Bezos wants us to say, "a Goodread"). Highly recommended if you're interested in this sort of urban analysis. My architectural mentor, the late David Crane, FAIA was Lynch's research assistant while a grad student at Harvard;'s GSD. He's listed in the acknowledgements.
I remember going back and forth between the student center and the computer lab in college, in different buildings. I noticed that I took a different route in each direction... surely, not optimal.
On my way to the student center, I'd leave the library by the nearest door. On my way from the student center, I'd enter the library by the nearest door. I figured that my brain was breaking it down into hierarchical steps: the computer center is inside the library, so the first step in getting to the computer center is entering the library, and I would do that by the nearest door, rather than choose a door close to the activities building.
On my way to the student center, I'd leave the library by the nearest door. On my way from the student center, I'd enter the library by the nearest door. I figured that my brain was breaking it down into hierarchical steps: the computer center is inside the library, so the first step in getting to the computer center is entering the library, and I would do that by the nearest door, rather than choose a door close to the activities building.
Related:
Vector-based pedestrian navigation in cities - https://news.ycombinator.com/item?id=28915494 - Oct 2021 (6 comments)
Vector-based pedestrian navigation in cities - https://news.ycombinator.com/item?id=28915494 - Oct 2021 (6 comments)
Having lived in Cambridge for a year, the shortest path is not always the most efficient path due to stoplights and traffic. It's a bit like UPS only making right turns.
Also, there are streets that you would totally avoid if you need to stop in and pick something up, or get coffee (not sure on the fidelity of their data). Or to avoid walking down a basically empty road with no exits (just lined by buildings) vs. walking down a more populated road with store fronts.
It's interesting, and humans are sub-optimal navigators on some dimensions, but not all of them.
Also, there are streets that you would totally avoid if you need to stop in and pick something up, or get coffee (not sure on the fidelity of their data). Or to avoid walking down a basically empty road with no exits (just lined by buildings) vs. walking down a more populated road with store fronts.
It's interesting, and humans are sub-optimal navigators on some dimensions, but not all of them.
I recall as a young child, first learning about the Pythagorean theorem, and the moment I realized that cutting across a parking lot is almost always a 'short cut'. It was like I had discovered a secret of the universe.
Quite different experience as an adult navigating a dense urban core and realizing that I could probably get to the Starbucks 4 blocks up and 3 blocks over faster than I could get to another one that was a straight shot, even without shortcuts, just because of the damn crosswalks.
Quite different experience as an adult navigating a dense urban core and realizing that I could probably get to the Starbucks 4 blocks up and 3 blocks over faster than I could get to another one that was a straight shot, even without shortcuts, just because of the damn crosswalks.
For anyone who looks for a good read on this subject I suggest Kevin Lynch's Image of the City (1960). Lynch was an urban planner who deeply engaged with how humans perceive and navigate the city. His work continues to influence planners today and remains as relevant as ever in an increasingly urban environment.
Tangentially related book recommendation:
Jeff Hawkins, A Thousand Brains: A New Theory of Intelligence. It describes the importance of reference frames for intelligence, for locating limbs relative to the body, locating the body in space, locating objects in space (even abstract objects in abstract spaces), and a possible "implementation" of that in the columns of the neocortex (by, basically, if I understood correctly, positing certain neurons that encode location, eg via intersection of coordinates, and certain neurons that encode features, and then learning a connection between those).
A short and interesting read (with quite some implications for progress in AI).
Podcast with Sam Harris: https://samharris.org/podcasts/255-future-intelligence/
Jeff Hawkins at Wikipedia: https://en.wikipedia.org/wiki/Jeff_Hawkins
The tech developed by his AI company: https://en.wikipedia.org/wiki/Hierarchical_temporal_memory
Book at Amazon: https://www.amazon.com/Thousand-Brains-New-Theory-Intelligen...
ETA: Oh, quite some previous discussion on HN:
https://news.ycombinator.com/item?id=20326396
https://news.ycombinator.com/item?id=19311279
https://news.ycombinator.com/item?id=26240901
https://news.ycombinator.com/item?id=26794286
Jeff Hawkins, A Thousand Brains: A New Theory of Intelligence. It describes the importance of reference frames for intelligence, for locating limbs relative to the body, locating the body in space, locating objects in space (even abstract objects in abstract spaces), and a possible "implementation" of that in the columns of the neocortex (by, basically, if I understood correctly, positing certain neurons that encode location, eg via intersection of coordinates, and certain neurons that encode features, and then learning a connection between those).
A short and interesting read (with quite some implications for progress in AI).
Podcast with Sam Harris: https://samharris.org/podcasts/255-future-intelligence/
Jeff Hawkins at Wikipedia: https://en.wikipedia.org/wiki/Jeff_Hawkins
The tech developed by his AI company: https://en.wikipedia.org/wiki/Hierarchical_temporal_memory
Book at Amazon: https://www.amazon.com/Thousand-Brains-New-Theory-Intelligen...
ETA: Oh, quite some previous discussion on HN:
https://news.ycombinator.com/item?id=20326396
https://news.ycombinator.com/item?id=19311279
https://news.ycombinator.com/item?id=26240901
https://news.ycombinator.com/item?id=26794286
I forgot how to navigate when I started relying on Waze.
Before Waze, I'd look at a map, find where I was going, and figure out how to get there. I'd remember it.
Now, if I just type it into Waze and drive there, I still need Waze the next time. Waze is just too much of a crutch.
Before Waze, I'd look at a map, find where I was going, and figure out how to get there. I'd remember it.
Now, if I just type it into Waze and drive there, I still need Waze the next time. Waze is just too much of a crutch.
This is because of how apps display and center you, relative to your surroundings. If you navigate by a paper map, you trace your position along a route. If you make the same trip with a navigation app, it will constantly orient what it shows around your position in the center, so your brain finds it harder to map physical landmarks encountered on the trip to where they fit along the path, as you can't see the whole path.
Humans are very good at navigating by landmark, but apps/gps distract from learning and placing them relative to the entire trip.
Humans are very good at navigating by landmark, but apps/gps distract from learning and placing them relative to the entire trip.
You are probably right. I definitely lose my sense of direction and place when following Waze.
I once tried to move "forward" through old EU city streets, and instead managed to move in a circle and come back to the starting point, because I got confused about which way "forward" is, due to non-right angles between streets and lack of known to me landmarks.
I once moved to a new city and immediately started a graveyard shift job. Since I was basically never out and about during daylight hours, for the first few weeks something was just...off. I couldn't gel my location and directions properly.
Until I pulled up google maps and found, to my chagrin, that without having seen the sun to 'calibrate' myself, I had my cardinal directions off. Once I realize what was actually north, I was good to go.
Until I pulled up google maps and found, to my chagrin, that without having seen the sun to 'calibrate' myself, I had my cardinal directions off. Once I realize what was actually north, I was good to go.
I find the whole premise that we're not trying to follow the shortest path weird. In our _evolutionary_ surroundings if you turn towards the thing you want to get to, and then walk, you're pretty much following the shortest path.
Maybe on a featureless frictionless plane that is true. There are hills, woods, rocks, rivers, all sorts of geographical barriers that make the easiest path often a longer one. Even with our technology today, mountain roads switchback rather than ascend directly to the summit.
It's all about finding the diagonals, I feel like a fool when I walk in squares for no good reason.
Venice was very different though, there's water everywhere and you have to nail the bridges to get anywhere.
Venice was very different though, there's water everywhere and you have to nail the bridges to get anywhere.
I wonder how this is affected by one way (for cars) streets. Do people think their way there by car then walk along those pavements?
the map design of the user modified computer-game Team Fortress (quake fortress, team fortress classic, TF2 from half-life series) has navigation: mirroring one side of the map to the other side, applying 2 colours (on either side); at first the map confuses then "the brain" grows accustomed
while I like the topic and think this is an interesting lens, this study seems to start from the position that navigation can be understood to be a geometry problem alone, but uses sample data from the real world, which is not an abstract environment lacking in local qualities. This seems like a pretty large mismatch between the study's lens and the data set in question. I'm reading both this posting and the study here: https://www.nature.com/articles/s43588-021-00130-y.pdf
> pedestrians appear to choose paths that seem to point most directly toward their destination, even if those routes end up being longer. They call this the “pointiest path.”
The sample in the article for how people walk versus the shortest path has a lot of other attributes beyond "it looks like it points there". The example trip is in Boston, the destination is probably the Boston Marriott on Huntington Ave. Who is taking this path? Have they spent time in the area, or is it their first time here? At what time of day are they walking? Are all path segments similarly well-lit? Do they have any sense of urgency? Are all path segments equally interesting?
There is a reward for walking down an interesting street: it's interesting. You're stimulated. Is there a reward for making it to your destination in two minutes and ten seconds instead of two minutes and twenty seconds?
In the example trip, pedestrians along the sub-optimal path are mostly taking Dartmouth Street, which is a main street for that neighborhood. Most people who have spent any amount of time there will know that Dartmouth hits Huntington, so you can just take Dartmouth; a local would give directions as such, and a local would probably walk as such. Their optimal route along Canton and Harcourt Street requires pedestrians to twice know that there is a path that can continue when it does not appear on a street map; twice the path is disjoint. This doesn't appear to be acknowledged in the study. You would have to know the side streets very well to know that path was even an option, and explaining it to a tourist would be very cumbersome and involve a lot of steps. For example, assuming the pedestrian is exiting a building facing south, the path chosen by pedestrians can be explained thusly: "make a right when you get outside, then take your first right along Dartmouth, and keep going until you see a big intersection and make a left on Stuart". The optimal route: "make a right when you get outside, when the street ends take a right onto Cantor, and then stay on Cantor until it ends, cross over the pedestrian zone and you'll be on Harcourt. When you get to the corner of Harcourt and St Botolph, go over the sidewalk to continue along Harcourt because Harcourt is disjoint. Keep going along Harcourt until you reach the six-way intersection, and make a slight right onto Huntington." I know how ridiculous this is because I lived over there for five years. To compare these two routes as geometric shapes and ignore their actual features is of unclear value. The route preferred by Google Maps to go from 79 Warren Ave to Boston Marriott Copley Place is the shortest route; the route that people do _not_ take.
> pedestrians chose routes that were slightly longer but minimized their angular deviation from the destination
this is one way of looking at it, but another way of looking at it is that people take main roads because they know how the main roads connect but aren't sure which sidestreets connect and which ones have dead ends. The study also doesn't seem to mention time of day for the data and density of street lights; a more direct route going through an unlit street is likely not going to be the preference of a person walking at night.
Anyway, there is a very good book called "The Image of the City" by Kevin Lynch, which is about how people form mental models of the built environment. People use these mental models to navigate. One of the model cities in that book is also Boston, and the book also came from MIT. It is curious that none of the concepts mentioned in Lynch's book appear in this study; it seems to suggest that the authors believe that people only imagine the geometry of a space. https://en.wikipedia.org/wiki/The_Image_of_the_City
> pedestrians appear to choose paths that seem to point most directly toward their destination, even if those routes end up being longer. They call this the “pointiest path.”
The sample in the article for how people walk versus the shortest path has a lot of other attributes beyond "it looks like it points there". The example trip is in Boston, the destination is probably the Boston Marriott on Huntington Ave. Who is taking this path? Have they spent time in the area, or is it their first time here? At what time of day are they walking? Are all path segments similarly well-lit? Do they have any sense of urgency? Are all path segments equally interesting?
There is a reward for walking down an interesting street: it's interesting. You're stimulated. Is there a reward for making it to your destination in two minutes and ten seconds instead of two minutes and twenty seconds?
In the example trip, pedestrians along the sub-optimal path are mostly taking Dartmouth Street, which is a main street for that neighborhood. Most people who have spent any amount of time there will know that Dartmouth hits Huntington, so you can just take Dartmouth; a local would give directions as such, and a local would probably walk as such. Their optimal route along Canton and Harcourt Street requires pedestrians to twice know that there is a path that can continue when it does not appear on a street map; twice the path is disjoint. This doesn't appear to be acknowledged in the study. You would have to know the side streets very well to know that path was even an option, and explaining it to a tourist would be very cumbersome and involve a lot of steps. For example, assuming the pedestrian is exiting a building facing south, the path chosen by pedestrians can be explained thusly: "make a right when you get outside, then take your first right along Dartmouth, and keep going until you see a big intersection and make a left on Stuart". The optimal route: "make a right when you get outside, when the street ends take a right onto Cantor, and then stay on Cantor until it ends, cross over the pedestrian zone and you'll be on Harcourt. When you get to the corner of Harcourt and St Botolph, go over the sidewalk to continue along Harcourt because Harcourt is disjoint. Keep going along Harcourt until you reach the six-way intersection, and make a slight right onto Huntington." I know how ridiculous this is because I lived over there for five years. To compare these two routes as geometric shapes and ignore their actual features is of unclear value. The route preferred by Google Maps to go from 79 Warren Ave to Boston Marriott Copley Place is the shortest route; the route that people do _not_ take.
> pedestrians chose routes that were slightly longer but minimized their angular deviation from the destination
this is one way of looking at it, but another way of looking at it is that people take main roads because they know how the main roads connect but aren't sure which sidestreets connect and which ones have dead ends. The study also doesn't seem to mention time of day for the data and density of street lights; a more direct route going through an unlit street is likely not going to be the preference of a person walking at night.
Anyway, there is a very good book called "The Image of the City" by Kevin Lynch, which is about how people form mental models of the built environment. People use these mental models to navigate. One of the model cities in that book is also Boston, and the book also came from MIT. It is curious that none of the concepts mentioned in Lynch's book appear in this study; it seems to suggest that the authors believe that people only imagine the geometry of a space. https://en.wikipedia.org/wiki/The_Image_of_the_City
So, "shortest path" might not be quickest path. And it might be an uglier or a more dangerous path; I think I've read elsewhere that people will often pick streets that look nicer or are more pedestrian-friendly.
> Human beings are not optimal navigators.
They should reconsider their definition of "optimal"!