Humans are pretty complicated creatures, right? So if we want to understand and
predict our behavior, you’d think we would need a pretty complicated model.
After all there are people who spend their entire careers in subjects like psychology
and sociology, to try to figure out all the complex ways we operate.
What if I were to tell you that, no,
all you really need to understand most human behavior is physics?
This might seem outrageous or even insulting – to suggest that you and I can be regarded
as a collection of particles just responding to mechanical forces.
But before you get too judgmental, let me show you what I’m talking about.
I’m going to show you how shockingly far we can go in understanding the behavior of crowds,
traffic and pedestrians using principles borrowed from physics. And you’ll also see how those same
ideas that apply to groups of humans, can also explain what had been some of the most mysterious
group behaviors we see in other animals, from flocks of birds to schools of fish.
Stick around because that’s coming up right now...
now.
Before we get into it, I’d like to recommend a documentary that I think
will really help you get a great feel for group behavior in other animals,
in this case from the point of view of birds. The documentary is called “Migrating Birds,
Scouts of Distant Worlds.” It’s available on MagellanTV, today’s sponsor.
Some of the fascinating things I learned from this documentary is how group behavior of birds
can debilitate a predator, how flying in certain group formations allow birds to migrate farther,
and how groups of thousands of birds can change course in an instant simply
by individuals following just 7 of their closest neighbors.
MagellanTV is completely ad-free and includes a growing collection of new
4K videos ladded weekly. You can actually watch this documentary,
and the rest of Magellan TV’s extensive collection of 3000 plus documentaries for free right now.
Just click the special link in the description, or type the URL that’s right here on the screen.
Now let’s back to how this all fits with crowd physics.
* We go
about our daily lives planning, talking to one another, weighing decisions,
responding to unexpected events. It’s kind of complicated being human.
But if we zoom out from our lives and take a wider, birds-eye view, all those little
details don’t seem to matter much. Everyone in a crowd has their own thoughts and plans and
problems – but they don’t seem to make much of a difference to what the whole crowd does together.
When we watch many people moving around over a long time, we can start to see
patterns and regularities that aren’t evident if you follow just one person.
This is a bit like what we find when we look at stuff that isn’t alive – a gas,
say, made up of countless particles too small to see.
If we track a single particle, it seems to move around at random,
shifting this way and that because of all the collisions it has with other
particles. We can’t really predict what it will do at some point in the future.
But if we zoom out and look at all the trillions upon trillions of particles,
then we can identify some simple laws, and use them to make very accurate predictions.
For example, we can see that for a given volume of gas in a closed box,
the hotter it gets, the higher its pressure.
And we can write down equations that will predict
precisely what the pressure will be if we know some other conditions.
This is the case even though, again,
the individual particles are bouncing around like crazy.
To go from individual particles to the properties of a whole cloud of gas,
we need to think about averages.
It doesn’t really matter what each particle does on its own;
all that matters to understand properties like pressure is what they do on average.
So we need to look at the statistics of all those motions: for example, what proportions of the
molecules have different energies and velocities, and how these statistical distributions change if
we, say, heat the gas up. This approach is called the kinetic theory of gases, and it was developed
in the late nineteenth century by the physicists James Clerk Maxwell and Ludwig Boltzmann.
It evolved into the science now called "statistical mechanics," or just "Statistical physics."
In 1971 a mechanical engineer at the University of Sydney named Leroy Henderson wondered whether
some of the concepts that scientists use to understand gases might be applied to human crowds.
Henderson measured the speeds of people moving in crowds in
public spaces in Sydney:walking around the university campus or street intersections,
and children in playgrounds. He found that in all these cases, the distribution of speeds
looked just like those that Maxwell and Boltzmann had assumed for the speeds of particles in a gas.
Now, we know that one thing a gas can do if you cool it down,
or if you squeeze it, is to condense into a liquid.
In liquids, the particles still move quite randomly,
but they are much more densely packed and they bump into each other more often.
The switch from a gas to a liquid happens quite suddenly
at the condensation temperature, and is called a phase transition.
Henderson wondered if crowds might undergo phase transitions too, from a “crowd gas”
to a “crowd liquid”, for example if they get squeezed together at a ticket barrier.
In the late 1980s physicist Dirk Helbing at the University of Göttingen in Germany
thought that Henderson’s gas model of crowds might be a good starting
point for a more sophisticated theory of how pedestrians and crowds move about.
The particles in gases and liquids interact with one another: they attract over long distances,
but repel each other when they come very close.
That might seem very different to how people interact when they move about. But is it really?
When two people walking in opposite directions on the sidewalk get close,
they veer past each other to avoid a collision – as long as they are
paying attention! It looks like some short-ranged repulsive force has kept
them from colliding. There’s not really such a force that we could measure with a meter.
But Helbing and his colleague Peter Molnar figured that if they made a computer model
that represents people as particles interacting through a repulsive force,
they might move in much the same way as they do in real life.
In 1995 the pair ran computer simulations of how such, people-particles if you will,
behave when crowds of them move in opposite directions down a corridor.
They found that the people organized themselves spontaneously into counterflowing streams,
in which some followed behind others in a line.
And that’s exactly what we do do, for example when we’re moving along a crowded sidewalk.
We’re certainly not just mindless particles – but in this situation,
it looks as though we might as well be!
Physicists call this collective behavior, where particles seem to coordinate what they do.
There was nothing built into the model to enforce it – the people only interacted through the
repulsive, collision-avoiding force. Yet this collective way of moving looks intelligent,
because it means that there is less chance of collisions than if every
particle blindly follows its own independent path.
In other words, what looks like a kind of intelligent behavior
emerges from a model in which the simulated people – by the way they
are usually called them agents – have no intelligence whatsoever.
These simulations of pedestrians show the phenomenon called emergence,
where some behavior or structure emerges in a complex system of many interacting
components from the interactions among them, even though those interactions themselves
might be very simple and contain no hint of that collective pattern.
Classic phase transitions like freezing and evaporating are also examples of emergence.
It’s not at all obvious, if you look at the forces between water molecules,
that they will suddenly all freeze into ice at exactly the same temperature. But they do.
Compared to pedestrian motion, road traffic is an even simpler and more constrained situation,
because we’re bound by law to stay on the right side of the road,
moving one after another in single file.
So it’s not surprising that agent-based
models are now being widely used to understand and predict road traffic.
These models just assume that the agents – drivers in their vehicles – try to go in
one direction at the speed they prefer, but to slow down if necessary to avoid
colliding with the car in front, as if there’s a repulsive force between them.
With no more ingredients than this, these traffic models can produce amazingly complex behavior.
If the traffic is very light, each vehicle moves just as it pleases,
hardly interacting with others – like a kind of traffic gas.
But above a certain threshold in traffic density – how many vehicles
there are on each mile of road – there’s a switch to a sort of traffic liquid,
where everyone keeps moving quite smoothly even through the flow is quite dense.
If the density increases a bit more, there’s another transition:
to a traffic solid. You probably all know what that’s like,
because you’ve all been in one. It’s a traffic jam, in which the vehicles barely move at all.
Once the traffic density is high enough for a jam to form,
it doesn’t take much to trigger it. Just one little disturbance to the fluid-like flow,
like a single driver braking too suddenly, might be enough.
That little disturbance might be only fleeting, and so it seems to most of the
other drivers that the jam doesn’t have a real cause at all: it’s a phantom jam.
Agent-based traffic models show that it’s just another kind of emergent behavior.
But nothing we’ve seen so far in human crowds matches the beautiful
emergent behavior in groups of other animals, like the coordinated flocking
of birds called a murmuration or the predator-avoiding schooling of fish.
This behavior used to be such a mystery that in the early twentieth century some
zoologists suggested that birds have a kind of telepathy that lets them coordinate their
movements. But thanks to agent-based models, we now know that nothing so weird is needed.
In 1987, computer engineer Craig Reynolds decided to see if the murmurations of
blackbirds he watched in a local cemetery in California might be mimicked in a computer
program in which agent-like particles move around according to simple rules.
Reynolds called these agents “boids”. He suspected that the blackbirds were doing nothing more than
responding to the movements of their neighbors. They had no global sense of the whole flock.
The rules for the boids were that each would try to match its speed to the average of all those
within a particular range, that they would move towards the centre of that local group,
and that they would change direction to avoid collisions. That’s all there is to it.
Reynolds’ boids did coordinate their movements like a real flock of blackbirds.
These simulations were so good, and yet so simple,
that they were quickly adopted by Hollywood filmmakers for animated special effects
such as a swarm of bats in Batman Returns and a herd of stampeding wildebeest in The Lion King.
These group movements of animals make flocks,
schools, packs and herds rather like a kind of fluid: they seem to flow.
Close up, it might look as though the creatures are just jostling randomly.
But seen from afar, there’s often a clear pattern to the movement.
So these agent-based models can capture some pretty complicated
movements by assuming only that the agents are being pushed and pulled by blind forces.
Maybe now you’re wondering: is that really all I am? Just a particle bouncing this way and that
because of forces that I can’t even sense, let alone control? You’re not really, of course:
atoms and molecules can’t make and watch YouTube videos? But then how come the same
theories work that for atoms and molecules also work for people, traffic, and sheep?
That’s actually telling us something deep about the way the universe works – something that gets
lost when we present that question …as a search for ever more fundamental theories of matter,
from atoms to quarks to strings. The universe we experience is filled with
many things interacting, and so you could say that the most fundamental physics is
that which deals not with fundamental particles but with objects interacting.
And the amazing thing is that this physics – statistical physics – is renormalizable. That
means we can keep bundling together groups of objects into bigger ones – atoms and molecules
into cells, cells into people, people into crowds and societies – and find that then
the lower-level details become irrelevant and the same physical phenomena, like phase transitions,
keep happening again and again but at much bigger scales. Maybe you’ll find
that a comforting thought and not get so upset, the next time the traffic freezes
and you’re stuck in its solid state: in a traffic jam. It’s just physics my friend.
I’ll see you in the next video.