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Good evening and welcome to the show. | 0:00:03 | 0:00:05 | |
Have you just arrived home? | 0:00:05 | 0:00:06 | |
Have you fought your way through queues and off crowded trains | 0:00:06 | 0:00:09 | |
and did you do the British thing of queuing very politely, | 0:00:09 | 0:00:12 | |
but actually inwardly seething? | 0:00:12 | 0:00:15 | |
With this country's population growing to 70 million people, | 0:00:15 | 0:00:19 | |
-we're going to have to learn how to cope in crowded places, aren't we? -We are. | 0:00:19 | 0:00:23 | |
So, in tonight's show, | 0:00:23 | 0:00:25 | |
Jem experiences the crush of a crowded gig | 0:00:25 | 0:00:27 | |
and finds out where's the worst place to stand... | 0:00:27 | 0:00:30 | |
It's a bit of a squeeze to say the least! | 0:00:30 | 0:00:33 | |
Number-crunching Legend Johnny Ball hits the streets of London and counts cabs | 0:00:33 | 0:00:37 | |
to show how maths can help you guess the size of a crowd. | 0:00:37 | 0:00:41 | |
Whether we'll get this right, I can't be sure. | 0:00:41 | 0:00:44 | |
And later, I'll be seeing if a random group of people | 0:00:44 | 0:00:47 | |
can cooperate with each other without even knowing it. | 0:00:47 | 0:00:51 | |
Not only have they figured it out, they're actually playing a game. | 0:00:51 | 0:00:54 | |
So if you haven't guessed it yet... | 0:00:54 | 0:00:57 | |
Tonight's show is all about the science of crowds, | 0:00:57 | 0:01:00 | |
-the hows... -The whats... -..the whens -..and the whys. | 0:01:00 | 0:01:02 | |
Where better to start than outside a football stadium on match day? | 0:01:07 | 0:01:12 | |
-Who do we love? -ALL: Arsenal. | 0:01:12 | 0:01:14 | |
THEY LAUGH | 0:01:14 | 0:01:17 | |
We're all used to, aren't we, phrases like group mentality | 0:01:17 | 0:01:21 | |
or following the crowd? | 0:01:21 | 0:01:23 | |
But is there any actual basis to that | 0:01:23 | 0:01:25 | |
and can being part of a large group | 0:01:25 | 0:01:28 | |
actually make you do things that you wouldn't normally do? | 0:01:28 | 0:01:32 | |
I've never seen Arsenal play live, | 0:01:39 | 0:01:41 | |
but I can already feel the camaraderie here rubbing off on me. | 0:01:41 | 0:01:44 | |
It's almost kind of like you belong to something. | 0:01:46 | 0:01:49 | |
You're reclaiming it for yourselves, | 0:01:49 | 0:01:51 | |
all the things you wouldn't normally do, like walk in the middle of the road, | 0:01:51 | 0:01:54 | |
it's suddenly OK. People talking to each other and everyone bonding. | 0:01:54 | 0:01:58 | |
It feels nice. | 0:01:58 | 0:02:00 | |
Being in this crowd doesn't make me want to go on the rampage | 0:02:00 | 0:02:02 | |
and from what I've seen, no one else here is about to riot either. | 0:02:02 | 0:02:06 | |
But is there some kind of Jekyll and Hyde switch | 0:02:06 | 0:02:10 | |
that can bring out our worst or our best when we're in a big group? | 0:02:10 | 0:02:14 | |
I've joined world expert on crowd psychology, | 0:02:14 | 0:02:17 | |
Steve Reicher to find out. And he's a Spurs fan. | 0:02:17 | 0:02:21 | |
Yes, people do behave differently in groups. | 0:02:21 | 0:02:23 | |
They are transformed in groups. | 0:02:23 | 0:02:26 | |
That sense of empowerment, | 0:02:26 | 0:02:27 | |
you making history and controlling the world on your own terms, | 0:02:27 | 0:02:31 | |
that's exhilarating, that's exciting, | 0:02:31 | 0:02:34 | |
that's one of the things people get out of crowd behaviour. | 0:02:34 | 0:02:36 | |
Behind that empowerment is a shared sense of identity. | 0:02:36 | 0:02:41 | |
This crowd are united just by the colours of red and white, | 0:02:41 | 0:02:44 | |
wherever they come from. | 0:02:44 | 0:02:46 | |
These Arsenal fans down here are going to be thrilled | 0:02:46 | 0:02:49 | |
if somebody, often from another country, kicks a ball into the goal. | 0:02:49 | 0:02:54 | |
Not because they've done anything, | 0:02:54 | 0:02:56 | |
not because they've achieved anything, | 0:02:56 | 0:02:58 | |
because the group has done well. | 0:02:58 | 0:03:00 | |
And in groups and in crowds | 0:03:00 | 0:03:02 | |
it's the fate of the group that you care about. | 0:03:02 | 0:03:04 | |
If they do well, you've done well. If they are valued, you are valued. | 0:03:04 | 0:03:08 | |
That doesn't mean that they just do anything and get carried away. | 0:03:08 | 0:03:13 | |
But there are instances perhaps within a group, | 0:03:13 | 0:03:15 | |
there was a chap, I remember in the student loan protest | 0:03:15 | 0:03:19 | |
who threw a fire extinguisher... | 0:03:19 | 0:03:21 | |
Potentially he's not going to do that when he's not in a group? | 0:03:21 | 0:03:24 | |
People just don't behave in that way generally. | 0:03:24 | 0:03:27 | |
The interesting thing in that incident | 0:03:27 | 0:03:29 | |
was there had been confrontation with the police. | 0:03:29 | 0:03:32 | |
There had been a certain level of conflict, but at that moment, | 0:03:32 | 0:03:35 | |
when somebody did something which threatened life and limb, | 0:03:35 | 0:03:38 | |
which so clearly violated people's sense of what was acceptable, | 0:03:38 | 0:03:42 | |
actually, that de-escalated the conflict. | 0:03:42 | 0:03:45 | |
OK, so being in a crowd can change your behaviour, | 0:03:45 | 0:03:49 | |
but it doesn't automatically make us all rioters. | 0:03:49 | 0:03:52 | |
In fact, you're usually reined in by the crowd if you get out of control. | 0:03:52 | 0:03:57 | |
Quite how being part of crowd could have such a profound effect on us | 0:03:57 | 0:04:00 | |
has always been a mystery. | 0:04:00 | 0:04:02 | |
But here at the University of Nijmegen, | 0:04:05 | 0:04:06 | |
Dr Vasily Klucharev thinks he may have found an answer. | 0:04:06 | 0:04:10 | |
And in order to show me, he needs me inside his functional MRI scanner. | 0:04:10 | 0:04:15 | |
While I'm in here, he wants me to perform a test. | 0:04:15 | 0:04:20 | |
On a screen above me, 100 faces are displayed, one after the other. | 0:04:20 | 0:04:25 | |
I have to score them for beauty out of eight. | 0:04:25 | 0:04:27 | |
Here's the weird part - after each score I give, | 0:04:27 | 0:04:30 | |
the screen shows me how other people rated that face. | 0:04:30 | 0:04:35 | |
20 minutes later, Vasily shows me the inside of my head | 0:04:37 | 0:04:40 | |
and explains his testing had nothing to do with beauty | 0:04:40 | 0:04:45 | |
and everything to do with those red bits in my brain. | 0:04:45 | 0:04:49 | |
So in fact, this experiment | 0:04:49 | 0:04:51 | |
was about social conformity. | 0:04:51 | 0:04:53 | |
We are interested in how much | 0:04:53 | 0:04:55 | |
actually you change your opinion in line with others. | 0:04:55 | 0:04:58 | |
I thought there was something fishy going on, | 0:04:58 | 0:05:00 | |
because I was trying to figure out, | 0:05:00 | 0:05:02 | |
why were you showing me what other people were thinking? | 0:05:02 | 0:05:06 | |
Basically, we hypothesise | 0:05:06 | 0:05:08 | |
that whenever your opinion deviates from the group opinion, | 0:05:08 | 0:05:11 | |
your brain will emit certain error signals, | 0:05:11 | 0:05:14 | |
that you did something wrong when you judged faces differently. | 0:05:14 | 0:05:19 | |
-So, you've done something wrong? -Exactly. | 0:05:19 | 0:05:21 | |
Is this an unconscious thing we do because we want to follow the crowd? | 0:05:21 | 0:05:25 | |
It's very automatic response. | 0:05:25 | 0:05:27 | |
During the scanning, we saw when you experienced a conflict with others, | 0:05:27 | 0:05:32 | |
your brain emitted this kind of signal. | 0:05:32 | 0:05:35 | |
If I chose one thing and the group chose something different | 0:05:35 | 0:05:39 | |
I actually felt, blimey, did I miss something here? | 0:05:39 | 0:05:41 | |
Have I done something wrong? | 0:05:41 | 0:05:43 | |
It's that hard-wired alarm signal in the brain | 0:05:44 | 0:05:47 | |
that Vasily has been looking at over the last few years. | 0:05:47 | 0:05:51 | |
And by looking at the size of that response, | 0:05:51 | 0:05:53 | |
he can now categorise people as conformists, or rebels. | 0:05:53 | 0:05:58 | |
I just wanted to show you, that here in the medial pre-frontal cortex, | 0:05:58 | 0:06:02 | |
this area is very important for learning | 0:06:02 | 0:06:06 | |
and it drives behavioural adjustments. | 0:06:06 | 0:06:09 | |
In conformists, we see that area lights up. | 0:06:09 | 0:06:12 | |
In nonconformist, this area doesn't respond. | 0:06:12 | 0:06:16 | |
So all these terms, peer pressure, following the crowd, | 0:06:16 | 0:06:20 | |
these are things we're all familiar with, | 0:06:20 | 0:06:22 | |
they're actually backed up really, by real, solid data? | 0:06:22 | 0:06:26 | |
Exactly, so we've perhaps for the first time, | 0:06:26 | 0:06:29 | |
suggested real neurobiological mechanisms for this. | 0:06:29 | 0:06:32 | |
So looking at the picture of my brain, | 0:06:32 | 0:06:35 | |
am I a conformist, or am I a rebel? | 0:06:35 | 0:06:38 | |
-Am I a free thinker? -Let's have a look. | 0:06:38 | 0:06:41 | |
You have a smaller, but still some activity here, | 0:06:41 | 0:06:44 | |
so I would say that your brain activity is somewhere in between. | 0:06:44 | 0:06:48 | |
What does he mean "somewhere in between"? | 0:06:48 | 0:06:51 | |
My rebel legend dreams shattered. | 0:06:51 | 0:06:54 | |
Vasily reckons he can prove his diagnosis | 0:06:54 | 0:06:58 | |
in the final stage of the test. | 0:06:58 | 0:07:00 | |
He reckons I can never override | 0:07:00 | 0:07:01 | |
my annoyingly slightly conformist tendencies, | 0:07:01 | 0:07:07 | |
so when faced with those same 100 pictures, | 0:07:07 | 0:07:09 | |
I'll subconsciously adjust my scores closer to the groups' scores. | 0:07:09 | 0:07:14 | |
Although now I can't remember any of the scores from before, | 0:07:14 | 0:07:18 | |
I'm determined not to be influenced and 10 minutes later... | 0:07:18 | 0:07:22 | |
OK, I'm good. | 0:07:22 | 0:07:24 | |
..I'm ready for the results. | 0:07:24 | 0:07:27 | |
-This is an index of extreme conformist. -Yes. | 0:07:27 | 0:07:30 | |
The person changed a lot in the second session | 0:07:30 | 0:07:32 | |
and this is your change. | 0:07:32 | 0:07:35 | |
You can see you changed a bit your opinion, | 0:07:35 | 0:07:37 | |
on average, slightly in line with the group. | 0:07:37 | 0:07:40 | |
It's a defeat. | 0:07:40 | 0:07:43 | |
Despite my best efforts to score the faces exactly as before, | 0:07:43 | 0:07:47 | |
I have been swayed by the group opinion, just as Vasily predicted. | 0:07:47 | 0:07:53 | |
Tell me, why does this happen? | 0:07:55 | 0:07:57 | |
Why is there perhaps a tendency for human beings to want to conform? | 0:07:57 | 0:08:01 | |
Is there a selective reason? | 0:08:01 | 0:08:03 | |
Because I'm a biologist, I'm very much biased by biology | 0:08:03 | 0:08:07 | |
and I think there is an evolutionary reason for this. | 0:08:07 | 0:08:10 | |
Simply the group is smart. | 0:08:10 | 0:08:13 | |
The average group opinion is better than individual opinion. | 0:08:13 | 0:08:17 | |
So, hang on, I think I'm a nonconformist. | 0:08:17 | 0:08:21 | |
What we'll do is hook you up to Vasily's MRI scan and have a closer look. | 0:08:21 | 0:08:26 | |
Looking forward to that. | 0:08:26 | 0:08:27 | |
As we all know, last year was a census year. | 0:08:27 | 0:08:30 | |
70 million people now living in the UK, which got us to thinking, | 0:08:30 | 0:08:33 | |
how do you figure out the size of the population | 0:08:33 | 0:08:36 | |
if you don't actually have a census form? | 0:08:36 | 0:08:38 | |
Had you count the number of fish in the sea, for example? | 0:08:38 | 0:08:40 | |
Very simple. You use maths. | 0:08:40 | 0:08:42 | |
Not my forte, I'll be honest, but made bearable when I was a kid | 0:08:42 | 0:08:46 | |
by this week's special guest, none other than Johnny Ball himself. | 0:08:46 | 0:08:50 | |
We asked him to think of a number. | 0:08:50 | 0:08:52 | |
He'd never heard that joke before. | 0:08:52 | 0:08:54 | |
Hello. As it happens, | 0:08:55 | 0:08:58 | |
I know a very good mathematical way of estimating an unknown population. | 0:08:58 | 0:09:02 | |
Using, ping-pong balls. | 0:09:02 | 0:09:04 | |
What a lot of ping-pong balls. But how many? | 0:09:05 | 0:09:08 | |
Well, I don't know so I'm going to try to estimate the number. | 0:09:08 | 0:09:12 | |
I could count them one by one, but that would take ages, | 0:09:12 | 0:09:15 | |
so this is a little more tricky. | 0:09:15 | 0:09:16 | |
What I do is take a good sample, | 0:09:16 | 0:09:19 | |
quite a few balls and I mark them with a felt tip pen. Here we go. | 0:09:19 | 0:09:22 | |
One, two... | 0:09:22 | 0:09:24 | |
This technique is called capture, recapture. | 0:09:24 | 0:09:27 | |
Biologists use it to find out animal populations. | 0:09:27 | 0:09:32 | |
..98, 99, 100. | 0:09:32 | 0:09:35 | |
Now what do I do? I pour all these back in again. | 0:09:35 | 0:09:40 | |
With real animals you might clip or tag them | 0:09:40 | 0:09:42 | |
and then set them free and hope that they mix back randomly. | 0:09:42 | 0:09:46 | |
I think that might be pretty random | 0:09:46 | 0:09:49 | |
but I'm going to choose another 100, but this time, | 0:09:49 | 0:09:53 | |
we're going to use a blindfold. | 0:09:53 | 0:09:57 | |
Four, five, six... | 0:09:57 | 0:09:59 | |
'I've put the blindfold on so I can't see whether I'm choosing the ones | 0:09:59 | 0:10:02 | |
'that are marked or not.' 100. | 0:10:02 | 0:10:05 | |
The question is how many of those hundred are marked? So here we go. | 0:10:05 | 0:10:09 | |
'Knowing how many are marked by my original mark....' | 0:10:09 | 0:10:13 | |
One mark. Two mark. | 0:10:13 | 0:10:14 | |
'..will help me to work out how many there are overall.' | 0:10:14 | 0:10:17 | |
17. | 0:10:17 | 0:10:19 | |
Nope. No. | 0:10:21 | 0:10:22 | |
No. | 0:10:22 | 0:10:24 | |
This is the theory. | 0:10:24 | 0:10:26 | |
If you divide the 17 balls into the second sample of 100 balls, | 0:10:26 | 0:10:30 | |
the proportion should be the same as dividing the first | 0:10:30 | 0:10:33 | |
sample of 100 balls into the total number of balls. | 0:10:33 | 0:10:38 | |
'So, second sample divided by 17...' | 0:10:38 | 0:10:41 | |
Equals 5.88. | 0:10:41 | 0:10:45 | |
'Now the first sample multiplied up - and that gives...' | 0:10:45 | 0:10:48 | |
588 balls. | 0:10:48 | 0:10:53 | |
That's our estimate. | 0:10:53 | 0:10:57 | |
It is time to reveal the actual number of balls. | 0:10:57 | 0:11:02 | |
There are... | 0:11:02 | 0:11:04 | |
600. | 0:11:05 | 0:11:07 | |
Not bad at all. | 0:11:07 | 0:11:10 | |
'It's all very well finding out how many ping-pong balls are in a tank...' | 0:11:10 | 0:11:14 | |
Taxi! 'But things get much more difficult in the real world.' | 0:11:15 | 0:11:19 | |
So here is another capture recapture experiment. | 0:11:22 | 0:11:25 | |
How many black cabs are there in London? | 0:11:25 | 0:11:27 | |
By using the same maths as I did with the ping-pong balls, I'll try to estimate that number. | 0:11:27 | 0:11:32 | |
'I genuinely have no idea how many they are out there, | 0:11:32 | 0:11:36 | |
'there must be thousands. So I will need some help.' | 0:11:36 | 0:11:40 | |
-Off you go! -OK. | 0:11:40 | 0:11:41 | |
'The bigger the sample, the more accurate our estimate will be. | 0:11:41 | 0:11:45 | |
'So we spent two hours counting cabs in five places across London.' | 0:11:45 | 0:11:49 | |
This counting taxis is not as easy as it looks. | 0:11:49 | 0:11:52 | |
Whether we will get this right, I can't be sure. | 0:11:52 | 0:11:56 | |
'We are noting the unique licence numbers as our way of tagging the taxis. | 0:11:56 | 0:12:02 | |
'We then come back the same time the next day to count taxis for another two hours, | 0:12:02 | 0:12:06 | |
'to see what proportion of them we've tagged the day before. | 0:12:06 | 0:12:11 | |
'Now into the warm for some maths.' | 0:12:11 | 0:12:15 | |
So there we are, we have counted taxis on two separate days for two hours each session. | 0:12:15 | 0:12:20 | |
We've fed all the figures into the computer | 0:12:20 | 0:12:22 | |
so now it is the moment of truth. | 0:12:22 | 0:12:25 | |
How many taxis did we count? | 0:12:25 | 0:12:26 | |
The number of taxis we spotted on both days, having run them | 0:12:26 | 0:12:30 | |
through the computer, is 321. | 0:12:30 | 0:12:34 | |
So we now do the same maths that we did with the ping-pong balls, | 0:12:34 | 0:12:37 | |
and it should give us our estimate. | 0:12:37 | 0:12:39 | |
So the second day's numbers divided by the number of repeats. | 0:12:39 | 0:12:44 | |
Equals 6.64 or roughly a sixth of the cabs we saw on day two had been | 0:12:44 | 0:12:50 | |
marked the day before as well. | 0:12:50 | 0:12:52 | |
So all we need to do is take 6.64 | 0:12:52 | 0:12:53 | |
and multiply it by the number of cabs we saw on day one to | 0:12:53 | 0:12:58 | |
get our estimate of the number of cabs on London's streets. | 0:12:58 | 0:13:02 | |
The total estimate is 12,140. With some decimal places. | 0:13:04 | 0:13:09 | |
'So how accurate is that? I know just the person to ask. | 0:13:10 | 0:13:14 | |
'Bob Oddy is a long-time taxi driver | 0:13:14 | 0:13:16 | |
'and now General Secretary of the Cabbies' Union. | 0:13:16 | 0:13:19 | |
'So what did he think of our number?' | 0:13:19 | 0:13:22 | |
Well, the total number of taxis licensed in London would be about 23,000 - | 0:13:22 | 0:13:26 | |
-give or take a dozen or so. -We were miles out! Wow! | 0:13:26 | 0:13:30 | |
-But you're talking about the number of cabs working at any one time. -Yes. | 0:13:30 | 0:13:34 | |
Well, allowing for day shift, night shift, overlaps, | 0:13:34 | 0:13:37 | |
11-12,000. | 0:13:37 | 0:13:40 | |
We were spot on! | 0:13:40 | 0:13:41 | |
Bob, thanks ever so much. | 0:13:41 | 0:13:43 | |
Taxi! | 0:13:43 | 0:13:45 | |
So this capture recapture system worked very well for us | 0:13:45 | 0:13:48 | |
and it does work in quite a lot of places. | 0:13:48 | 0:13:50 | |
As for me, I will be happy to catch a London cab any time. | 0:13:50 | 0:13:54 | |
But as far as counting was concerned, never again. | 0:13:54 | 0:13:57 | |
It's a good job taxis work in shifts. Imagine the chaos | 0:14:04 | 0:14:09 | |
if they all crowded onto the roads at once. | 0:14:09 | 0:14:11 | |
But there are times when PEOPLE simply can't avoid | 0:14:13 | 0:14:16 | |
crowding together - at rush-hour, sports events and big rock concerts. | 0:14:16 | 0:14:21 | |
One-two, one-two. | 0:14:21 | 0:14:23 | |
When you get a large crowd, you can have hundreds of tons | 0:14:23 | 0:14:27 | |
of people sloshing around like a liquid. | 0:14:27 | 0:14:30 | |
When that happens you get the human version of flows, | 0:14:30 | 0:14:33 | |
waves and pressures building up. | 0:14:33 | 0:14:35 | |
I've come to Bucks New University to find out how that is measured | 0:14:35 | 0:14:38 | |
and what it's like to be in the thick of it. | 0:14:38 | 0:14:41 | |
This is Professor Chris Kemp, an expert in crowd safety. | 0:14:43 | 0:14:48 | |
He has designed a pressure suit capable of monitoring impact | 0:14:48 | 0:14:51 | |
and temperature readings from anywhere in the crowd. | 0:14:51 | 0:14:55 | |
One, two, three, four - let's go, guys! | 0:14:55 | 0:14:58 | |
I'm going to put the suit into action at this specially staged concert. | 0:15:00 | 0:15:04 | |
Like most of us, I've headed straight for the front. | 0:15:04 | 0:15:07 | |
Just run in. | 0:15:09 | 0:15:10 | |
Chris directs wave after wave of sweaty students | 0:15:10 | 0:15:15 | |
to pile on the pressure. | 0:15:15 | 0:15:16 | |
It's a bit of a squeeze to say the least! | 0:15:16 | 0:15:19 | |
With about 100 of them charging into me, this was a pretty realistic simulation. | 0:15:19 | 0:15:24 | |
Chris, I've not felt crowd pressures like that | 0:15:26 | 0:15:28 | |
since Friday nights out in Telford in the late '80s. | 0:15:28 | 0:15:31 | |
I remember bars where you could be up there | 0:15:31 | 0:15:33 | |
and lift your feet off the floor and you don't fall. | 0:15:33 | 0:15:36 | |
What do the numbers say from your read-outs? | 0:15:36 | 0:15:38 | |
This is where the first row of people hit you, OK? | 0:15:38 | 0:15:41 | |
I remember. | 0:15:41 | 0:15:42 | |
Then it goes down because the pressure isn't sustained. | 0:15:42 | 0:15:44 | |
Is that a significant difference? | 0:15:44 | 0:15:47 | |
It is, because it is one pound per square inch. | 0:15:47 | 0:15:49 | |
This is where the second row hits you, then the third row, | 0:15:49 | 0:15:52 | |
then the fourth row, etc. | 0:15:52 | 0:15:54 | |
The pressure on the barrier was 2.67 kilonewtons per metre. | 0:15:54 | 0:15:58 | |
To translate, that is over a quarter of a ton of crowd pressure. | 0:15:58 | 0:16:02 | |
That's like a small horse falling on you. It is! | 0:16:02 | 0:16:07 | |
Is that typical of an intense gig or does it get bigger than that? | 0:16:07 | 0:16:10 | |
It does. The biggest recorded crowd pressure that | 0:16:10 | 0:16:14 | |
we know about is 8.6 kilonewtons at a gig. | 0:16:14 | 0:16:16 | |
But that has just been for a second. It is when it is sustained that it's dangerous. | 0:16:16 | 0:16:20 | |
If you take Hillsborough, that was sustained pressure in one small area with a lot of people. | 0:16:20 | 0:16:25 | |
That's why the fences were taken down because there was no way out. | 0:16:25 | 0:16:29 | |
Research has shown that a sustained 1.2 kilonewtons | 0:16:29 | 0:16:34 | |
for 15 minutes is enough to be fatal. | 0:16:34 | 0:16:37 | |
Are there times when it really drops off or times when it really peaks? | 0:16:37 | 0:16:41 | |
What does happen is that if you are on a barrier, a wall, | 0:16:41 | 0:16:45 | |
or a fence, you have the ability to push backwards, | 0:16:45 | 0:16:47 | |
but then if people are coming forwards, one metre to one-and-a-half metres, | 0:16:47 | 0:16:52 | |
the people there have the double pressure coming into them. | 0:16:52 | 0:16:55 | |
That's where you have got to watch a little bit. | 0:16:55 | 0:16:58 | |
So the message is don't stand a couple of rows | 0:16:58 | 0:17:00 | |
back from the front if you want to avoid the highest pressures. | 0:17:00 | 0:17:05 | |
But pressure isn't the only thing to watch out for in a crowd. There's also heat. | 0:17:05 | 0:17:09 | |
When you first came into the pit the temperature around you was 24 degrees. | 0:17:09 | 0:17:15 | |
As you gradually go through there's a curve upwards to 32 degrees | 0:17:15 | 0:17:19 | |
over a half an hour period. | 0:17:19 | 0:17:21 | |
That's an eight degree increase in the temperature around you. | 0:17:21 | 0:17:24 | |
-That's quite high. -And it felt high. | 0:17:24 | 0:17:27 | |
Would you say that heat is almost more of a danger in big crowds than pressure? | 0:17:27 | 0:17:31 | |
It can be, and it's interesting when we record this | 0:17:31 | 0:17:34 | |
because last summer at a very hot festival we recorded | 0:17:34 | 0:17:37 | |
a 14 degree increase in temperature on two of the girls who were in the pit. | 0:17:37 | 0:17:42 | |
That's because they were very small and the lads around them | 0:17:42 | 0:17:45 | |
were very tall and it traps the air inside that so it can't get out. | 0:17:45 | 0:17:49 | |
But if you do get into trouble what's the best time to get out? | 0:17:49 | 0:17:56 | |
Pressure drops significantly when people put their hands in the air to clap at the end. | 0:17:56 | 0:18:00 | |
-Right. -The actual body mass of the arms is taken out of the equation. It's in the air. | 0:18:00 | 0:18:03 | |
If you want to move when you're in a crowd like that, | 0:18:03 | 0:18:06 | |
wait until the end of the song and then sneak through. | 0:18:06 | 0:18:09 | |
What we want is for everybody to be as safe as possible | 0:18:09 | 0:18:11 | |
so anything we can do to support that we will do. | 0:18:11 | 0:18:14 | |
What an amazing crowd you are. You're so amazing. | 0:18:14 | 0:18:18 | |
It's time for this week's brain teaser with the great | 0:18:20 | 0:18:23 | |
brain teaser himself Dr Yan. Yan? Yan? | 0:18:23 | 0:18:28 | |
This week I'm going to try and guess how many buses there are in the whole of London, | 0:18:30 | 0:18:34 | |
but unlike Johnny Ball I'm not going to do any counting whatsoever. | 0:18:34 | 0:18:39 | |
Can you guess how I'm going to do it? I'll give you a clue. | 0:18:39 | 0:18:42 | |
The answer is hopefully all around me. | 0:18:42 | 0:18:46 | |
As always, you can find Yan's answer on our website, | 0:18:46 | 0:18:50 | |
and whilst you're there follow the links to the Open University | 0:18:50 | 0:18:53 | |
for more crowd science. | 0:18:53 | 0:18:55 | |
Don't forget to check for details of the Bang live roadshows. | 0:18:57 | 0:19:00 | |
You can get hands on with us in Edinburgh in a couple of weeks. | 0:19:00 | 0:19:04 | |
Then we are off to Sheffield and Poole. | 0:19:04 | 0:19:06 | |
Tickets are free from our website. | 0:19:06 | 0:19:08 | |
OK. So far we've been looking at the problems with crowds, but we've all seen schools of fish | 0:19:09 | 0:19:15 | |
or flocks of birds moving beautifully as a single unit. | 0:19:15 | 0:19:19 | |
Almost as if they have a collective consciousness | 0:19:19 | 0:19:21 | |
and this is one of science's greatest mysteries. | 0:19:21 | 0:19:24 | |
It got me thinking, could human beings behave the same way? | 0:19:24 | 0:19:28 | |
In about 20 minutes or so, this cinema is going to fill up | 0:19:28 | 0:19:32 | |
with a few hundred people, fingers crossed. | 0:19:32 | 0:19:35 | |
They will be taking part in an experiment | 0:19:35 | 0:19:37 | |
and the thing is they have no idea about what this experiment is about. | 0:19:37 | 0:19:42 | |
And I'm not going to tell them anything, | 0:19:42 | 0:19:44 | |
but it all comes down | 0:19:44 | 0:19:45 | |
to this plastic paddle with a red and a green side. | 0:19:45 | 0:19:50 | |
The question is, will they be able to figure out for themselves what it's all about? | 0:19:50 | 0:19:53 | |
Our guinea pigs in this social experiment are visitors to Birmingham's Giant Screen. | 0:19:53 | 0:20:00 | |
Each one of them has been given one of the reflective paddles on their way in. | 0:20:00 | 0:20:05 | |
And watching them all from beneath the giant screen are cameras which | 0:20:05 | 0:20:09 | |
record which side of the reflective paddles they are holding up. | 0:20:09 | 0:20:12 | |
Our crowd don't know it yet but the experiment starts as soon as they sit down. | 0:20:12 | 0:20:16 | |
People are looking at their paddles, everyone is looking at it and wondering what on earth | 0:20:16 | 0:20:21 | |
it's for, like "What is this for?" Look, here's something interesting, look. Here we go. | 0:20:21 | 0:20:27 | |
Suddenly everybody's holding their paddle up to the screen... | 0:20:27 | 0:20:31 | |
..and they're making the connection now almost instantaneously. | 0:20:33 | 0:20:36 | |
Just a couple of people did it and suddenly everyone did it. | 0:20:36 | 0:20:39 | |
You can see them pointing with their fingers. "There's me. There's me." | 0:20:39 | 0:20:43 | |
Another thing the audience don't realise is that we've actually divided them into two teams. | 0:20:43 | 0:20:48 | |
We're going to introduce something else - the classic video game Pong. | 0:20:48 | 0:20:52 | |
Obviously we've updated the graphics a bit, but the aim is still | 0:20:52 | 0:20:56 | |
to bounce the shark across the screen past the opposing team's bat. | 0:20:56 | 0:21:00 | |
The teams have to work together to control their bat. | 0:21:00 | 0:21:05 | |
It'll only move right to the top if they all showed green at once | 0:21:05 | 0:21:08 | |
and the more red that they show, the further down it moves. | 0:21:08 | 0:21:11 | |
That's amazing because it's all about cooperation. | 0:21:11 | 0:21:17 | |
Between them they have realised that some people have to be red | 0:21:17 | 0:21:19 | |
and some people have to be green. | 0:21:19 | 0:21:22 | |
It's difficult to keep it moving because you've got to get the right | 0:21:24 | 0:21:27 | |
amount of people showing red and the right amount of people showing green | 0:21:27 | 0:21:31 | |
depending on where you want it. | 0:21:31 | 0:21:33 | |
Obviously these guys are just sensing each other, | 0:21:33 | 0:21:35 | |
feeling it, and working it out amongst themselves. | 0:21:35 | 0:21:39 | |
FROM CROWD: Right, go red. | 0:21:39 | 0:21:40 | |
Oh, they just got it in time. | 0:21:40 | 0:21:44 | |
In hardly any time at all each team is suddenly working as one. | 0:21:44 | 0:21:49 | |
CHEERING | 0:21:49 | 0:21:52 | |
Here's the incredible thing. This has happened with no instruction whatsoever. | 0:21:52 | 0:21:57 | |
CHEERING | 0:21:57 | 0:22:00 | |
Pong was always my favourite videogame. | 0:22:00 | 0:22:02 | |
CHEERING | 0:22:02 | 0:22:04 | |
APPLAUSE | 0:22:06 | 0:22:08 | |
What made you decide, "I will do a bit of green, no, I will do a bit of red"? | 0:22:12 | 0:22:15 | |
I know most people are going to go red because everyone was | 0:22:15 | 0:22:18 | |
shouting red, we'll go green. | 0:22:18 | 0:22:19 | |
I can't believe the way it works. | 0:22:19 | 0:22:21 | |
How that's coordinated I've no idea. | 0:22:21 | 0:22:26 | |
I didn't think they would get that so quickly. | 0:22:26 | 0:22:29 | |
You see what we can do when we work together? | 0:22:29 | 0:22:32 | |
If that kind of cooperation is possible, | 0:22:32 | 0:22:34 | |
even at a subconscious level, | 0:22:34 | 0:22:37 | |
you wouldn't know it in the chaos of morning rush-hour. | 0:22:37 | 0:22:40 | |
Up and down the country, as the trains are pulling in, it's every man for himself. | 0:22:40 | 0:22:45 | |
Britain's population recently passed 70 million and the majority of these people live in our cities. | 0:22:48 | 0:22:55 | |
Huge numbers like these can create real challenges for urban planners | 0:22:57 | 0:23:02 | |
because they have to make sure that crowds that big | 0:23:02 | 0:23:05 | |
can move around quickly and safely. | 0:23:05 | 0:23:08 | |
Delays and queues aren't the only worries. | 0:23:08 | 0:23:12 | |
Tragedies can and do happen, | 0:23:12 | 0:23:13 | |
especially during emergency evacuations. | 0:23:13 | 0:23:16 | |
I've come to a very windy vantage point | 0:23:16 | 0:23:19 | |
high above the streets of London to find out how | 0:23:19 | 0:23:22 | |
scientists are tackling the problem. | 0:23:22 | 0:23:25 | |
Andrew, from here when you look at that massive crowd it does look | 0:23:25 | 0:23:30 | |
fairly organised and calm despite the number of people. | 0:23:30 | 0:23:32 | |
That's right. | 0:23:32 | 0:23:33 | |
Especially at large densities, you start to see collective behaviour emerging. | 0:23:33 | 0:23:38 | |
The crowd doesn't just act as individuals on their own. | 0:23:38 | 0:23:40 | |
It starts to exhibit good behaviour. | 0:23:40 | 0:23:43 | |
Andrew uses computer models to analyse the way crowds move | 0:23:43 | 0:23:47 | |
through a cityscape. | 0:23:47 | 0:23:48 | |
This can help him predict bottlenecks | 0:23:48 | 0:23:50 | |
and ultimately to make cities safer for us all. | 0:23:50 | 0:23:55 | |
Aside from razing everything to the ground and starting again, | 0:23:55 | 0:23:58 | |
what can we do to deal with the growing number of people | 0:23:58 | 0:24:01 | |
moving into our cities? | 0:24:01 | 0:24:02 | |
It would be lovely to demolish everything | 0:24:02 | 0:24:04 | |
and start again, wouldn't it? | 0:24:04 | 0:24:06 | |
We have to work with the cities we have. The only way that is good to happen is | 0:24:06 | 0:24:10 | |
if we use the new technologies that are emerging to understand | 0:24:10 | 0:24:14 | |
the crowd and even to start to influence the crowd in subtle ways. | 0:24:14 | 0:24:17 | |
'With his colleague Anders Johansson from the University of Bristol, | 0:24:20 | 0:24:22 | |
'Andrew has been studying how crowd flow is affected by the most common | 0:24:22 | 0:24:28 | |
'bottleneck - the doorway. | 0:24:28 | 0:24:29 | |
'They've asked me to round up some friends to help carry out an experiment.' | 0:24:29 | 0:24:34 | |
As an added extra incentive we've got some cupcakes at the other | 0:24:34 | 0:24:38 | |
end of the doorway. | 0:24:38 | 0:24:39 | |
There are not enough cupcakes for all of you. | 0:24:39 | 0:24:43 | |
The challenge is to get to that cupcake without actually killing | 0:24:43 | 0:24:47 | |
the person next to you. | 0:24:47 | 0:24:48 | |
-Are you guys ready? ALL: -Yes. | 0:24:48 | 0:24:51 | |
OK, three, two, one, go! | 0:24:51 | 0:24:54 | |
SHOUTING | 0:24:54 | 0:24:57 | |
Whoa! | 0:24:57 | 0:24:59 | |
Filter through, filter through. | 0:24:59 | 0:25:01 | |
SHOUTING AND LAUGHTER | 0:25:01 | 0:25:04 | |
-They are really packing through. -20.75 seconds. | 0:25:04 | 0:25:10 | |
There was a lot of jamming and then flowing again, jamming and then flowing again. Is that normal? | 0:25:10 | 0:25:16 | |
What we are see during evacuation conditions, | 0:25:16 | 0:25:18 | |
we have periods of total blockage | 0:25:18 | 0:25:20 | |
and then sudden outbursts of small groups, intermittent outflows. | 0:25:20 | 0:25:23 | |
OK. Really that's a classic example of how what can go wrong | 0:25:23 | 0:25:26 | |
when too many people are trying to rush through a tiny narrow | 0:25:26 | 0:25:29 | |
-entrance like that. -Exactly. This is the faster-is-slower effect. | 0:25:29 | 0:25:34 | |
The more that people push, it lowers the outflow of people through the doorway. | 0:25:34 | 0:25:40 | |
OK, fair enough. | 0:25:40 | 0:25:41 | |
The team's research has produced some surprising solutions to the problem. | 0:25:41 | 0:25:46 | |
We really want to prevent people from clogging in the doorway. | 0:25:46 | 0:25:51 | |
One way to achieve that is to put an obstacle in front of the door which | 0:25:51 | 0:25:54 | |
will prevent people from clogging, it will split up the crowd. | 0:25:54 | 0:25:58 | |
OK that sounds counterintuitive, | 0:25:58 | 0:25:59 | |
to put an obstacle in that narrow doorway while all of you are | 0:25:59 | 0:26:03 | |
trying to squeeze past. It sounds like it's going to slow everything down. | 0:26:03 | 0:26:06 | |
-But let's see what happens. -Yes. -What are we using as an obstacle? A chair? | 0:26:06 | 0:26:10 | |
Let's use you, Liz! We'll put you in front of this! | 0:26:10 | 0:26:13 | |
After what I have just seen I don't think that's a good idea! | 0:26:13 | 0:26:15 | |
Oh, Lord! OK, are you guys ready? | 0:26:15 | 0:26:18 | |
-ALL: -Yes! | 0:26:18 | 0:26:19 | |
Please don't hurt me! Three, two, one, go! | 0:26:19 | 0:26:25 | |
Whoa! Barging through! | 0:26:26 | 0:26:29 | |
Easy does it, guys. Nice. Keep going, keep going. | 0:26:32 | 0:26:37 | |
16.37. Result. | 0:26:37 | 0:26:41 | |
APPLAUSE | 0:26:41 | 0:26:42 | |
Who knew? | 0:26:42 | 0:26:44 | |
'It's that 20 percent speed increase that excites Andrew and Anders. | 0:26:44 | 0:26:49 | |
'But their discovery is still too radical for many architects.' | 0:26:49 | 0:26:52 | |
It's so counterintuitive that putting an obstacle in front of a doorway | 0:26:52 | 0:26:58 | |
would actually improve the flow, | 0:26:58 | 0:26:59 | |
that quite often building designers don't want to do that in case | 0:26:59 | 0:27:04 | |
it makes people feel less safe. | 0:27:04 | 0:27:05 | |
Until such measures are widely adopted | 0:27:07 | 0:27:10 | |
Andrew can offer us a few techniques to help speed you through doors. | 0:27:10 | 0:27:15 | |
One of the classic tricks is, if there is a single doorway that | 0:27:15 | 0:27:18 | |
a crowd is trying to move through, generally moving around the edge of the crowd | 0:27:18 | 0:27:22 | |
and walking along the surface of the obstacle | 0:27:22 | 0:27:25 | |
will get you there quicker. | 0:27:25 | 0:27:26 | |
Good science if you want to design, say, the Olympic Stadium | 0:27:29 | 0:27:33 | |
and you need to get everyone in and out really quickly. | 0:27:33 | 0:27:36 | |
Exactly. If you visit the Olympic Village you'll find that | 0:27:36 | 0:27:38 | |
every doorway has been designed with science in mind. | 0:27:38 | 0:27:41 | |
If you see a random bollard, it's there for a reason. | 0:27:41 | 0:27:44 | |
-Brilliant thinking. -That's all for now. | 0:27:44 | 0:27:46 | |
We'll see you in two weeks when we will be looking at phone | 0:27:46 | 0:27:49 | |
and Wi-Fi signals, the effect they have on our health, | 0:27:49 | 0:27:53 | |
and how they could be used to beam free electricity from space. | 0:27:53 | 0:27:56 | |
-Goodbye from us from Oxford Circus. See you soon. -Bye. | 0:27:56 | 0:28:00 | |
Subtitles by Red Bee Media Ltd | 0:28:13 | 0:28:16 |