0:00:03 > 0:00:05Good evening and welcome to the show.
0:00:05 > 0:00:06Have you just arrived home?
0:00:06 > 0:00:09Have you fought your way through queues and off crowded trains
0:00:09 > 0:00:12and did you do the British thing of queuing very politely,
0:00:12 > 0:00:15but actually inwardly seething?
0:00:15 > 0:00:19With this country's population growing to 70 million people,
0:00:19 > 0:00:23- we're going to have to learn how to cope in crowded places, aren't we? - We are.
0:00:23 > 0:00:25So, in tonight's show,
0:00:25 > 0:00:27Jem experiences the crush of a crowded gig
0:00:27 > 0:00:30and finds out where's the worst place to stand...
0:00:30 > 0:00:33It's a bit of a squeeze to say the least!
0:00:33 > 0:00:37Number-crunching Legend Johnny Ball hits the streets of London and counts cabs
0:00:37 > 0:00:41to show how maths can help you guess the size of a crowd.
0:00:41 > 0:00:44Whether we'll get this right, I can't be sure.
0:00:44 > 0:00:47And later, I'll be seeing if a random group of people
0:00:47 > 0:00:51can cooperate with each other without even knowing it.
0:00:51 > 0:00:54Not only have they figured it out, they're actually playing a game.
0:00:54 > 0:00:57So if you haven't guessed it yet...
0:00:57 > 0:01:00Tonight's show is all about the science of crowds,
0:01:00 > 0:01:02- the hows...- The whats... - ..the whens- ..and the whys.
0:01:07 > 0:01:12Where better to start than outside a football stadium on match day?
0:01:12 > 0:01:14- Who do we love? - ALL: Arsenal.
0:01:14 > 0:01:17THEY LAUGH
0:01:17 > 0:01:21We're all used to, aren't we, phrases like group mentality
0:01:21 > 0:01:23or following the crowd?
0:01:23 > 0:01:25But is there any actual basis to that
0:01:25 > 0:01:28and can being part of a large group
0:01:28 > 0:01:32actually make you do things that you wouldn't normally do?
0:01:39 > 0:01:41I've never seen Arsenal play live,
0:01:41 > 0:01:44but I can already feel the camaraderie here rubbing off on me.
0:01:46 > 0:01:49It's almost kind of like you belong to something.
0:01:49 > 0:01:51You're reclaiming it for yourselves,
0:01:51 > 0:01:54all the things you wouldn't normally do, like walk in the middle of the road,
0:01:54 > 0:01:58it's suddenly OK. People talking to each other and everyone bonding.
0:01:58 > 0:02:00It feels nice.
0:02:00 > 0:02:02Being in this crowd doesn't make me want to go on the rampage
0:02:02 > 0:02:06and from what I've seen, no one else here is about to riot either.
0:02:06 > 0:02:10But is there some kind of Jekyll and Hyde switch
0:02:10 > 0:02:14that can bring out our worst or our best when we're in a big group?
0:02:14 > 0:02:17I've joined world expert on crowd psychology,
0:02:17 > 0:02:21Steve Reicher to find out. And he's a Spurs fan.
0:02:21 > 0:02:23Yes, people do behave differently in groups.
0:02:23 > 0:02:26They are transformed in groups.
0:02:26 > 0:02:27That sense of empowerment,
0:02:27 > 0:02:31you making history and controlling the world on your own terms,
0:02:31 > 0:02:34that's exhilarating, that's exciting,
0:02:34 > 0:02:36that's one of the things people get out of crowd behaviour.
0:02:36 > 0:02:41Behind that empowerment is a shared sense of identity.
0:02:41 > 0:02:44This crowd are united just by the colours of red and white,
0:02:44 > 0:02:46wherever they come from.
0:02:46 > 0:02:49These Arsenal fans down here are going to be thrilled
0:02:49 > 0:02:54if somebody, often from another country, kicks a ball into the goal.
0:02:54 > 0:02:56Not because they've done anything,
0:02:56 > 0:02:58not because they've achieved anything,
0:02:58 > 0:03:00because the group has done well.
0:03:00 > 0:03:02And in groups and in crowds
0:03:02 > 0:03:04it's the fate of the group that you care about.
0:03:04 > 0:03:08If they do well, you've done well. If they are valued, you are valued.
0:03:08 > 0:03:13That doesn't mean that they just do anything and get carried away.
0:03:13 > 0:03:15But there are instances perhaps within a group,
0:03:15 > 0:03:19there was a chap, I remember in the student loan protest
0:03:19 > 0:03:21who threw a fire extinguisher...
0:03:21 > 0:03:24Potentially he's not going to do that when he's not in a group?
0:03:24 > 0:03:27People just don't behave in that way generally.
0:03:27 > 0:03:29The interesting thing in that incident
0:03:29 > 0:03:32was there had been confrontation with the police.
0:03:32 > 0:03:35There had been a certain level of conflict, but at that moment,
0:03:35 > 0:03:38when somebody did something which threatened life and limb,
0:03:38 > 0:03:42which so clearly violated people's sense of what was acceptable,
0:03:42 > 0:03:45actually, that de-escalated the conflict.
0:03:45 > 0:03:49OK, so being in a crowd can change your behaviour,
0:03:49 > 0:03:52but it doesn't automatically make us all rioters.
0:03:52 > 0:03:57In fact, you're usually reined in by the crowd if you get out of control.
0:03:57 > 0:04:00Quite how being part of crowd could have such a profound effect on us
0:04:00 > 0:04:02has always been a mystery.
0:04:05 > 0:04:06But here at the University of Nijmegen,
0:04:06 > 0:04:10Dr Vasily Klucharev thinks he may have found an answer.
0:04:10 > 0:04:15And in order to show me, he needs me inside his functional MRI scanner.
0:04:15 > 0:04:20While I'm in here, he wants me to perform a test.
0:04:20 > 0:04:25On a screen above me, 100 faces are displayed, one after the other.
0:04:25 > 0:04:27I have to score them for beauty out of eight.
0:04:27 > 0:04:30Here's the weird part - after each score I give,
0:04:30 > 0:04:35the screen shows me how other people rated that face.
0:04:37 > 0:04:4020 minutes later, Vasily shows me the inside of my head
0:04:40 > 0:04:45and explains his testing had nothing to do with beauty
0:04:45 > 0:04:49and everything to do with those red bits in my brain.
0:04:49 > 0:04:51So in fact, this experiment
0:04:51 > 0:04:53was about social conformity.
0:04:53 > 0:04:55We are interested in how much
0:04:55 > 0:04:58actually you change your opinion in line with others.
0:04:58 > 0:05:00I thought there was something fishy going on,
0:05:00 > 0:05:02because I was trying to figure out,
0:05:02 > 0:05:06why were you showing me what other people were thinking?
0:05:06 > 0:05:08Basically, we hypothesise
0:05:08 > 0:05:11that whenever your opinion deviates from the group opinion,
0:05:11 > 0:05:14your brain will emit certain error signals,
0:05:14 > 0:05:19that you did something wrong when you judged faces differently.
0:05:19 > 0:05:21- So, you've done something wrong? - Exactly.
0:05:21 > 0:05:25Is this an unconscious thing we do because we want to follow the crowd?
0:05:25 > 0:05:27It's very automatic response.
0:05:27 > 0:05:32During the scanning, we saw when you experienced a conflict with others,
0:05:32 > 0:05:35your brain emitted this kind of signal.
0:05:35 > 0:05:39If I chose one thing and the group chose something different
0:05:39 > 0:05:41I actually felt, blimey, did I miss something here?
0:05:41 > 0:05:43Have I done something wrong?
0:05:44 > 0:05:47It's that hard-wired alarm signal in the brain
0:05:47 > 0:05:51that Vasily has been looking at over the last few years.
0:05:51 > 0:05:53And by looking at the size of that response,
0:05:53 > 0:05:58he can now categorise people as conformists, or rebels.
0:05:58 > 0:06:02I just wanted to show you, that here in the medial pre-frontal cortex,
0:06:02 > 0:06:06this area is very important for learning
0:06:06 > 0:06:09and it drives behavioural adjustments.
0:06:09 > 0:06:12In conformists, we see that area lights up.
0:06:12 > 0:06:16In nonconformist, this area doesn't respond.
0:06:16 > 0:06:20So all these terms, peer pressure, following the crowd,
0:06:20 > 0:06:22these are things we're all familiar with,
0:06:22 > 0:06:26they're actually backed up really, by real, solid data?
0:06:26 > 0:06:29Exactly, so we've perhaps for the first time,
0:06:29 > 0:06:32suggested real neurobiological mechanisms for this.
0:06:32 > 0:06:35So looking at the picture of my brain,
0:06:35 > 0:06:38am I a conformist, or am I a rebel?
0:06:38 > 0:06:41- Am I a free thinker? - Let's have a look.
0:06:41 > 0:06:44You have a smaller, but still some activity here,
0:06:44 > 0:06:48so I would say that your brain activity is somewhere in between.
0:06:48 > 0:06:51What does he mean "somewhere in between"?
0:06:51 > 0:06:54My rebel legend dreams shattered.
0:06:54 > 0:06:58Vasily reckons he can prove his diagnosis
0:06:58 > 0:07:00in the final stage of the test.
0:07:00 > 0:07:01He reckons I can never override
0:07:01 > 0:07:07my annoyingly slightly conformist tendencies,
0:07:07 > 0:07:09so when faced with those same 100 pictures,
0:07:09 > 0:07:14I'll subconsciously adjust my scores closer to the groups' scores.
0:07:14 > 0:07:18Although now I can't remember any of the scores from before,
0:07:18 > 0:07:22I'm determined not to be influenced and 10 minutes later...
0:07:22 > 0:07:24OK, I'm good.
0:07:24 > 0:07:27..I'm ready for the results.
0:07:27 > 0:07:30- This is an index of extreme conformist.- Yes.
0:07:30 > 0:07:32The person changed a lot in the second session
0:07:32 > 0:07:35and this is your change.
0:07:35 > 0:07:37You can see you changed a bit your opinion,
0:07:37 > 0:07:40on average, slightly in line with the group.
0:07:40 > 0:07:43It's a defeat.
0:07:43 > 0:07:47Despite my best efforts to score the faces exactly as before,
0:07:47 > 0:07:53I have been swayed by the group opinion, just as Vasily predicted.
0:07:55 > 0:07:57Tell me, why does this happen?
0:07:57 > 0:08:01Why is there perhaps a tendency for human beings to want to conform?
0:08:01 > 0:08:03Is there a selective reason?
0:08:03 > 0:08:07Because I'm a biologist, I'm very much biased by biology
0:08:07 > 0:08:10and I think there is an evolutionary reason for this.
0:08:10 > 0:08:13Simply the group is smart.
0:08:13 > 0:08:17The average group opinion is better than individual opinion.
0:08:17 > 0:08:21So, hang on, I think I'm a nonconformist.
0:08:21 > 0:08:26What we'll do is hook you up to Vasily's MRI scan and have a closer look.
0:08:26 > 0:08:27Looking forward to that.
0:08:27 > 0:08:30As we all know, last year was a census year.
0:08:30 > 0:08:3370 million people now living in the UK, which got us to thinking,
0:08:33 > 0:08:36how do you figure out the size of the population
0:08:36 > 0:08:38if you don't actually have a census form?
0:08:38 > 0:08:40Had you count the number of fish in the sea, for example?
0:08:40 > 0:08:42Very simple. You use maths.
0:08:42 > 0:08:46Not my forte, I'll be honest, but made bearable when I was a kid
0:08:46 > 0:08:50by this week's special guest, none other than Johnny Ball himself.
0:08:50 > 0:08:52We asked him to think of a number.
0:08:52 > 0:08:54He'd never heard that joke before.
0:08:55 > 0:08:58Hello. As it happens,
0:08:58 > 0:09:02I know a very good mathematical way of estimating an unknown population.
0:09:02 > 0:09:04Using, ping-pong balls.
0:09:05 > 0:09:08What a lot of ping-pong balls. But how many?
0:09:08 > 0:09:12Well, I don't know so I'm going to try to estimate the number.
0:09:12 > 0:09:15I could count them one by one, but that would take ages,
0:09:15 > 0:09:16so this is a little more tricky.
0:09:16 > 0:09:19What I do is take a good sample,
0:09:19 > 0:09:22quite a few balls and I mark them with a felt tip pen. Here we go.
0:09:22 > 0:09:24One, two...
0:09:24 > 0:09:27This technique is called capture, recapture.
0:09:27 > 0:09:32Biologists use it to find out animal populations.
0:09:32 > 0:09:35..98, 99, 100.
0:09:35 > 0:09:40Now what do I do? I pour all these back in again.
0:09:40 > 0:09:42With real animals you might clip or tag them
0:09:42 > 0:09:46and then set them free and hope that they mix back randomly.
0:09:46 > 0:09:49I think that might be pretty random
0:09:49 > 0:09:53but I'm going to choose another 100, but this time,
0:09:53 > 0:09:57we're going to use a blindfold.
0:09:57 > 0:09:59Four, five, six...
0:09:59 > 0:10:02'I've put the blindfold on so I can't see whether I'm choosing the ones
0:10:02 > 0:10:05'that are marked or not.' 100.
0:10:05 > 0:10:09The question is how many of those hundred are marked? So here we go.
0:10:09 > 0:10:13'Knowing how many are marked by my original mark....'
0:10:13 > 0:10:14One mark. Two mark.
0:10:14 > 0:10:17'..will help me to work out how many there are overall.'
0:10:17 > 0:10:1917.
0:10:21 > 0:10:22Nope. No.
0:10:22 > 0:10:24No.
0:10:24 > 0:10:26This is the theory.
0:10:26 > 0:10:30If you divide the 17 balls into the second sample of 100 balls,
0:10:30 > 0:10:33the proportion should be the same as dividing the first
0:10:33 > 0:10:38sample of 100 balls into the total number of balls.
0:10:38 > 0:10:41'So, second sample divided by 17...'
0:10:41 > 0:10:45Equals 5.88.
0:10:45 > 0:10:48'Now the first sample multiplied up - and that gives...'
0:10:48 > 0:10:53588 balls.
0:10:53 > 0:10:57That's our estimate.
0:10:57 > 0:11:02It is time to reveal the actual number of balls.
0:11:02 > 0:11:04There are...
0:11:05 > 0:11:07600.
0:11:07 > 0:11:10Not bad at all.
0:11:10 > 0:11:14'It's all very well finding out how many ping-pong balls are in a tank...'
0:11:15 > 0:11:19Taxi! 'But things get much more difficult in the real world.'
0:11:22 > 0:11:25So here is another capture recapture experiment.
0:11:25 > 0:11:27How many black cabs are there in London?
0:11:27 > 0:11:32By using the same maths as I did with the ping-pong balls, I'll try to estimate that number.
0:11:32 > 0:11:36'I genuinely have no idea how many they are out there,
0:11:36 > 0:11:40'there must be thousands. So I will need some help.'
0:11:40 > 0:11:41- Off you go!- OK.
0:11:41 > 0:11:45'The bigger the sample, the more accurate our estimate will be.
0:11:45 > 0:11:49'So we spent two hours counting cabs in five places across London.'
0:11:49 > 0:11:52This counting taxis is not as easy as it looks.
0:11:52 > 0:11:56Whether we will get this right, I can't be sure.
0:11:56 > 0:12:02'We are noting the unique licence numbers as our way of tagging the taxis.
0:12:02 > 0:12:06'We then come back the same time the next day to count taxis for another two hours,
0:12:06 > 0:12:11'to see what proportion of them we've tagged the day before.
0:12:11 > 0:12:15'Now into the warm for some maths.'
0:12:15 > 0:12:20So there we are, we have counted taxis on two separate days for two hours each session.
0:12:20 > 0:12:22We've fed all the figures into the computer
0:12:22 > 0:12:25so now it is the moment of truth.
0:12:25 > 0:12:26How many taxis did we count?
0:12:26 > 0:12:30The number of taxis we spotted on both days, having run them
0:12:30 > 0:12:34through the computer, is 321.
0:12:34 > 0:12:37So we now do the same maths that we did with the ping-pong balls,
0:12:37 > 0:12:39and it should give us our estimate.
0:12:39 > 0:12:44So the second day's numbers divided by the number of repeats.
0:12:44 > 0:12:50Equals 6.64 or roughly a sixth of the cabs we saw on day two had been
0:12:50 > 0:12:52marked the day before as well.
0:12:52 > 0:12:53So all we need to do is take 6.64
0:12:53 > 0:12:58and multiply it by the number of cabs we saw on day one to
0:12:58 > 0:13:02get our estimate of the number of cabs on London's streets.
0:13:04 > 0:13:09The total estimate is 12,140. With some decimal places.
0:13:10 > 0:13:14'So how accurate is that? I know just the person to ask.
0:13:14 > 0:13:16'Bob Oddy is a long-time taxi driver
0:13:16 > 0:13:19'and now General Secretary of the Cabbies' Union.
0:13:19 > 0:13:22'So what did he think of our number?'
0:13:22 > 0:13:26Well, the total number of taxis licensed in London would be about 23,000 -
0:13:26 > 0:13:30- give or take a dozen or so. - We were miles out! Wow!
0:13:30 > 0:13:34- But you're talking about the number of cabs working at any one time. - Yes.
0:13:34 > 0:13:37Well, allowing for day shift, night shift, overlaps,
0:13:37 > 0:13:4011-12,000.
0:13:40 > 0:13:41We were spot on!
0:13:41 > 0:13:43Bob, thanks ever so much.
0:13:43 > 0:13:45Taxi!
0:13:45 > 0:13:48So this capture recapture system worked very well for us
0:13:48 > 0:13:50and it does work in quite a lot of places.
0:13:50 > 0:13:54As for me, I will be happy to catch a London cab any time.
0:13:54 > 0:13:57But as far as counting was concerned, never again.
0:14:04 > 0:14:09It's a good job taxis work in shifts. Imagine the chaos
0:14:09 > 0:14:11if they all crowded onto the roads at once.
0:14:13 > 0:14:16But there are times when PEOPLE simply can't avoid
0:14:16 > 0:14:21crowding together - at rush-hour, sports events and big rock concerts.
0:14:21 > 0:14:23One-two, one-two.
0:14:23 > 0:14:27When you get a large crowd, you can have hundreds of tons
0:14:27 > 0:14:30of people sloshing around like a liquid.
0:14:30 > 0:14:33When that happens you get the human version of flows,
0:14:33 > 0:14:35waves and pressures building up.
0:14:35 > 0:14:38I've come to Bucks New University to find out how that is measured
0:14:38 > 0:14:41and what it's like to be in the thick of it.
0:14:43 > 0:14:48This is Professor Chris Kemp, an expert in crowd safety.
0:14:48 > 0:14:51He has designed a pressure suit capable of monitoring impact
0:14:51 > 0:14:55and temperature readings from anywhere in the crowd.
0:14:55 > 0:14:58One, two, three, four - let's go, guys!
0:15:00 > 0:15:04I'm going to put the suit into action at this specially staged concert.
0:15:04 > 0:15:07Like most of us, I've headed straight for the front.
0:15:09 > 0:15:10Just run in.
0:15:10 > 0:15:15Chris directs wave after wave of sweaty students
0:15:15 > 0:15:16to pile on the pressure.
0:15:16 > 0:15:19It's a bit of a squeeze to say the least!
0:15:19 > 0:15:24With about 100 of them charging into me, this was a pretty realistic simulation.
0:15:26 > 0:15:28Chris, I've not felt crowd pressures like that
0:15:28 > 0:15:31since Friday nights out in Telford in the late '80s.
0:15:31 > 0:15:33I remember bars where you could be up there
0:15:33 > 0:15:36and lift your feet off the floor and you don't fall.
0:15:36 > 0:15:38What do the numbers say from your read-outs?
0:15:38 > 0:15:41This is where the first row of people hit you, OK?
0:15:41 > 0:15:42I remember.
0:15:42 > 0:15:44Then it goes down because the pressure isn't sustained.
0:15:44 > 0:15:47Is that a significant difference?
0:15:47 > 0:15:49It is, because it is one pound per square inch.
0:15:49 > 0:15:52This is where the second row hits you, then the third row,
0:15:52 > 0:15:54then the fourth row, etc.
0:15:54 > 0:15:58The pressure on the barrier was 2.67 kilonewtons per metre.
0:15:58 > 0:16:02To translate, that is over a quarter of a ton of crowd pressure.
0:16:02 > 0:16:07That's like a small horse falling on you. It is!
0:16:07 > 0:16:10Is that typical of an intense gig or does it get bigger than that?
0:16:10 > 0:16:14It does. The biggest recorded crowd pressure that
0:16:14 > 0:16:16we know about is 8.6 kilonewtons at a gig.
0:16:16 > 0:16:20But that has just been for a second. It is when it is sustained that it's dangerous.
0:16:20 > 0:16:25If you take Hillsborough, that was sustained pressure in one small area with a lot of people.
0:16:25 > 0:16:29That's why the fences were taken down because there was no way out.
0:16:29 > 0:16:34Research has shown that a sustained 1.2 kilonewtons
0:16:34 > 0:16:37for 15 minutes is enough to be fatal.
0:16:37 > 0:16:41Are there times when it really drops off or times when it really peaks?
0:16:41 > 0:16:45What does happen is that if you are on a barrier, a wall,
0:16:45 > 0:16:47or a fence, you have the ability to push backwards,
0:16:47 > 0:16:52but then if people are coming forwards, one metre to one-and-a-half metres,
0:16:52 > 0:16:55the people there have the double pressure coming into them.
0:16:55 > 0:16:58That's where you have got to watch a little bit.
0:16:58 > 0:17:00So the message is don't stand a couple of rows
0:17:00 > 0:17:05back from the front if you want to avoid the highest pressures.
0:17:05 > 0:17:09But pressure isn't the only thing to watch out for in a crowd. There's also heat.
0:17:09 > 0:17:15When you first came into the pit the temperature around you was 24 degrees.
0:17:15 > 0:17:19As you gradually go through there's a curve upwards to 32 degrees
0:17:19 > 0:17:21over a half an hour period.
0:17:21 > 0:17:24That's an eight degree increase in the temperature around you.
0:17:24 > 0:17:27- That's quite high.- And it felt high.
0:17:27 > 0:17:31Would you say that heat is almost more of a danger in big crowds than pressure?
0:17:31 > 0:17:34It can be, and it's interesting when we record this
0:17:34 > 0:17:37because last summer at a very hot festival we recorded
0:17:37 > 0:17:42a 14 degree increase in temperature on two of the girls who were in the pit.
0:17:42 > 0:17:45That's because they were very small and the lads around them
0:17:45 > 0:17:49were very tall and it traps the air inside that so it can't get out.
0:17:49 > 0:17:56But if you do get into trouble what's the best time to get out?
0:17:56 > 0:18:00Pressure drops significantly when people put their hands in the air to clap at the end.
0:18:00 > 0:18:03- Right.- The actual body mass of the arms is taken out of the equation. It's in the air.
0:18:03 > 0:18:06If you want to move when you're in a crowd like that,
0:18:06 > 0:18:09wait until the end of the song and then sneak through.
0:18:09 > 0:18:11What we want is for everybody to be as safe as possible
0:18:11 > 0:18:14so anything we can do to support that we will do.
0:18:14 > 0:18:18What an amazing crowd you are. You're so amazing.
0:18:20 > 0:18:23It's time for this week's brain teaser with the great
0:18:23 > 0:18:28brain teaser himself Dr Yan. Yan? Yan?
0:18:30 > 0:18:34This week I'm going to try and guess how many buses there are in the whole of London,
0:18:34 > 0:18:39but unlike Johnny Ball I'm not going to do any counting whatsoever.
0:18:39 > 0:18:42Can you guess how I'm going to do it? I'll give you a clue.
0:18:42 > 0:18:46The answer is hopefully all around me.
0:18:46 > 0:18:50As always, you can find Yan's answer on our website,
0:18:50 > 0:18:53and whilst you're there follow the links to the Open University
0:18:53 > 0:18:55for more crowd science.
0:18:57 > 0:19:00Don't forget to check for details of the Bang live roadshows.
0:19:00 > 0:19:04You can get hands on with us in Edinburgh in a couple of weeks.
0:19:04 > 0:19:06Then we are off to Sheffield and Poole.
0:19:06 > 0:19:08Tickets are free from our website.
0:19:09 > 0:19:15OK. So far we've been looking at the problems with crowds, but we've all seen schools of fish
0:19:15 > 0:19:19or flocks of birds moving beautifully as a single unit.
0:19:19 > 0:19:21Almost as if they have a collective consciousness
0:19:21 > 0:19:24and this is one of science's greatest mysteries.
0:19:24 > 0:19:28It got me thinking, could human beings behave the same way?
0:19:28 > 0:19:32In about 20 minutes or so, this cinema is going to fill up
0:19:32 > 0:19:35with a few hundred people, fingers crossed.
0:19:35 > 0:19:37They will be taking part in an experiment
0:19:37 > 0:19:42and the thing is they have no idea about what this experiment is about.
0:19:42 > 0:19:44And I'm not going to tell them anything,
0:19:44 > 0:19:45but it all comes down
0:19:45 > 0:19:50to this plastic paddle with a red and a green side.
0:19:50 > 0:19:53The question is, will they be able to figure out for themselves what it's all about?
0:19:53 > 0:20:00Our guinea pigs in this social experiment are visitors to Birmingham's Giant Screen.
0:20:00 > 0:20:05Each one of them has been given one of the reflective paddles on their way in.
0:20:05 > 0:20:09And watching them all from beneath the giant screen are cameras which
0:20:09 > 0:20:12record which side of the reflective paddles they are holding up.
0:20:12 > 0:20:16Our crowd don't know it yet but the experiment starts as soon as they sit down.
0:20:16 > 0:20:21People are looking at their paddles, everyone is looking at it and wondering what on earth
0:20:21 > 0:20:27it's for, like "What is this for?" Look, here's something interesting, look. Here we go.
0:20:27 > 0:20:31Suddenly everybody's holding their paddle up to the screen...
0:20:33 > 0:20:36..and they're making the connection now almost instantaneously.
0:20:36 > 0:20:39Just a couple of people did it and suddenly everyone did it.
0:20:39 > 0:20:43You can see them pointing with their fingers. "There's me. There's me."
0:20:43 > 0:20:48Another thing the audience don't realise is that we've actually divided them into two teams.
0:20:48 > 0:20:52We're going to introduce something else - the classic video game Pong.
0:20:52 > 0:20:56Obviously we've updated the graphics a bit, but the aim is still
0:20:56 > 0:21:00to bounce the shark across the screen past the opposing team's bat.
0:21:00 > 0:21:05The teams have to work together to control their bat.
0:21:05 > 0:21:08It'll only move right to the top if they all showed green at once
0:21:08 > 0:21:11and the more red that they show, the further down it moves.
0:21:11 > 0:21:17That's amazing because it's all about cooperation.
0:21:17 > 0:21:19Between them they have realised that some people have to be red
0:21:19 > 0:21:22and some people have to be green.
0:21:24 > 0:21:27It's difficult to keep it moving because you've got to get the right
0:21:27 > 0:21:31amount of people showing red and the right amount of people showing green
0:21:31 > 0:21:33depending on where you want it.
0:21:33 > 0:21:35Obviously these guys are just sensing each other,
0:21:35 > 0:21:39feeling it, and working it out amongst themselves.
0:21:39 > 0:21:40FROM CROWD: Right, go red.
0:21:40 > 0:21:44Oh, they just got it in time.
0:21:44 > 0:21:49In hardly any time at all each team is suddenly working as one.
0:21:49 > 0:21:52CHEERING
0:21:52 > 0:21:57Here's the incredible thing. This has happened with no instruction whatsoever.
0:21:57 > 0:22:00CHEERING
0:22:00 > 0:22:02Pong was always my favourite videogame.
0:22:02 > 0:22:04CHEERING
0:22:06 > 0:22:08APPLAUSE
0:22:12 > 0:22:15What made you decide, "I will do a bit of green, no, I will do a bit of red"?
0:22:15 > 0:22:18I know most people are going to go red because everyone was
0:22:18 > 0:22:19shouting red, we'll go green.
0:22:19 > 0:22:21I can't believe the way it works.
0:22:21 > 0:22:26How that's coordinated I've no idea.
0:22:26 > 0:22:29I didn't think they would get that so quickly.
0:22:29 > 0:22:32You see what we can do when we work together?
0:22:32 > 0:22:34If that kind of cooperation is possible,
0:22:34 > 0:22:37even at a subconscious level,
0:22:37 > 0:22:40you wouldn't know it in the chaos of morning rush-hour.
0:22:40 > 0:22:45Up and down the country, as the trains are pulling in, it's every man for himself.
0:22:48 > 0:22:55Britain's population recently passed 70 million and the majority of these people live in our cities.
0:22:57 > 0:23:02Huge numbers like these can create real challenges for urban planners
0:23:02 > 0:23:05because they have to make sure that crowds that big
0:23:05 > 0:23:08can move around quickly and safely.
0:23:08 > 0:23:12Delays and queues aren't the only worries.
0:23:12 > 0:23:13Tragedies can and do happen,
0:23:13 > 0:23:16especially during emergency evacuations.
0:23:16 > 0:23:19I've come to a very windy vantage point
0:23:19 > 0:23:22high above the streets of London to find out how
0:23:22 > 0:23:25scientists are tackling the problem.
0:23:25 > 0:23:30Andrew, from here when you look at that massive crowd it does look
0:23:30 > 0:23:32fairly organised and calm despite the number of people.
0:23:32 > 0:23:33That's right.
0:23:33 > 0:23:38Especially at large densities, you start to see collective behaviour emerging.
0:23:38 > 0:23:40The crowd doesn't just act as individuals on their own.
0:23:40 > 0:23:43It starts to exhibit good behaviour.
0:23:43 > 0:23:47Andrew uses computer models to analyse the way crowds move
0:23:47 > 0:23:48through a cityscape.
0:23:48 > 0:23:50This can help him predict bottlenecks
0:23:50 > 0:23:55and ultimately to make cities safer for us all.
0:23:55 > 0:23:58Aside from razing everything to the ground and starting again,
0:23:58 > 0:24:01what can we do to deal with the growing number of people
0:24:01 > 0:24:02moving into our cities?
0:24:02 > 0:24:04It would be lovely to demolish everything
0:24:04 > 0:24:06and start again, wouldn't it?
0:24:06 > 0:24:10We have to work with the cities we have. The only way that is good to happen is
0:24:10 > 0:24:14if we use the new technologies that are emerging to understand
0:24:14 > 0:24:17the crowd and even to start to influence the crowd in subtle ways.
0:24:20 > 0:24:22'With his colleague Anders Johansson from the University of Bristol,
0:24:22 > 0:24:28'Andrew has been studying how crowd flow is affected by the most common
0:24:28 > 0:24:29'bottleneck - the doorway.
0:24:29 > 0:24:34'They've asked me to round up some friends to help carry out an experiment.'
0:24:34 > 0:24:38As an added extra incentive we've got some cupcakes at the other
0:24:38 > 0:24:39end of the doorway.
0:24:39 > 0:24:43There are not enough cupcakes for all of you.
0:24:43 > 0:24:47The challenge is to get to that cupcake without actually killing
0:24:47 > 0:24:48the person next to you.
0:24:48 > 0:24:51- Are you guys ready? ALL:- Yes.
0:24:51 > 0:24:54OK, three, two, one, go!
0:24:54 > 0:24:57SHOUTING
0:24:57 > 0:24:59Whoa!
0:24:59 > 0:25:01Filter through, filter through.
0:25:01 > 0:25:04SHOUTING AND LAUGHTER
0:25:04 > 0:25:10- They are really packing through. - 20.75 seconds.
0:25:10 > 0:25:16There was a lot of jamming and then flowing again, jamming and then flowing again. Is that normal?
0:25:16 > 0:25:18What we are see during evacuation conditions,
0:25:18 > 0:25:20we have periods of total blockage
0:25:20 > 0:25:23and then sudden outbursts of small groups, intermittent outflows.
0:25:23 > 0:25:26OK. Really that's a classic example of how what can go wrong
0:25:26 > 0:25:29when too many people are trying to rush through a tiny narrow
0:25:29 > 0:25:34- entrance like that.- Exactly. This is the faster-is-slower effect.
0:25:34 > 0:25:40The more that people push, it lowers the outflow of people through the doorway.
0:25:40 > 0:25:41OK, fair enough.
0:25:41 > 0:25:46The team's research has produced some surprising solutions to the problem.
0:25:46 > 0:25:51We really want to prevent people from clogging in the doorway.
0:25:51 > 0:25:54One way to achieve that is to put an obstacle in front of the door which
0:25:54 > 0:25:58will prevent people from clogging, it will split up the crowd.
0:25:58 > 0:25:59OK that sounds counterintuitive,
0:25:59 > 0:26:03to put an obstacle in that narrow doorway while all of you are
0:26:03 > 0:26:06trying to squeeze past. It sounds like it's going to slow everything down.
0:26:06 > 0:26:10- But let's see what happens.- Yes. - What are we using as an obstacle? A chair?
0:26:10 > 0:26:13Let's use you, Liz! We'll put you in front of this!
0:26:13 > 0:26:15After what I have just seen I don't think that's a good idea!
0:26:15 > 0:26:18Oh, Lord! OK, are you guys ready?
0:26:18 > 0:26:19- ALL:- Yes!
0:26:19 > 0:26:25Please don't hurt me! Three, two, one, go!
0:26:26 > 0:26:29Whoa! Barging through!
0:26:32 > 0:26:37Easy does it, guys. Nice. Keep going, keep going.
0:26:37 > 0:26:4116.37. Result.
0:26:41 > 0:26:42APPLAUSE
0:26:42 > 0:26:44Who knew?
0:26:44 > 0:26:49'It's that 20 percent speed increase that excites Andrew and Anders.
0:26:49 > 0:26:52'But their discovery is still too radical for many architects.'
0:26:52 > 0:26:58It's so counterintuitive that putting an obstacle in front of a doorway
0:26:58 > 0:26:59would actually improve the flow,
0:26:59 > 0:27:04that quite often building designers don't want to do that in case
0:27:04 > 0:27:05it makes people feel less safe.
0:27:07 > 0:27:10Until such measures are widely adopted
0:27:10 > 0:27:15Andrew can offer us a few techniques to help speed you through doors.
0:27:15 > 0:27:18One of the classic tricks is, if there is a single doorway that
0:27:18 > 0:27:22a crowd is trying to move through, generally moving around the edge of the crowd
0:27:22 > 0:27:25and walking along the surface of the obstacle
0:27:25 > 0:27:26will get you there quicker.
0:27:29 > 0:27:33Good science if you want to design, say, the Olympic Stadium
0:27:33 > 0:27:36and you need to get everyone in and out really quickly.
0:27:36 > 0:27:38Exactly. If you visit the Olympic Village you'll find that
0:27:38 > 0:27:41every doorway has been designed with science in mind.
0:27:41 > 0:27:44If you see a random bollard, it's there for a reason.
0:27:44 > 0:27:46- Brilliant thinking. - That's all for now.
0:27:46 > 0:27:49We'll see you in two weeks when we will be looking at phone
0:27:49 > 0:27:53and Wi-Fi signals, the effect they have on our health,
0:27:53 > 0:27:56and how they could be used to beam free electricity from space.
0:27:56 > 0:28:00- Goodbye from us from Oxford Circus. See you soon.- Bye.
0:28:13 > 0:28:16Subtitles by Red Bee Media Ltd