The Living Crowd - Transport Studies Unit Tokyo Tech · 2013-03-07 · 02/03/13, Prof. Dr. Serge Hoogendoorn Challenge the Future Delft University of Technology The Living Crowd...

02/03/13, Prof. Dr. Serge Hoogendoorn

Challenge the Future

DelftUniversity ofTechnology

The Living Crowd...From crowd dynamics to principles for crowd management

Crowd Management 2

Crowd Management

Showing societal urgency...

Overview of crowd-related incidents

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Event (year) Cause Deaths/ injuries

Love Parade (2010) Crowd got dead locked in the tunnel system in front of the entrance. Stampede followed when a breach was made

20 / 200+

Himachal, Pradesh, India (2008)

Hindu worshippers were crushed to death as a result of a massive crowd surge, upon hearing a landslide was imminent.

150 / 50

Hajj (2006,2004,1998) Crushed and trampled to death following progressive crowd collapse, caused by the excessive number of pilgrims

363 / 298+ 251 / 244 188 / 434

Kalubai temple (2005) Crushed to death in a narrow alleyway 340+ / ?

Minsk, Belarus (1999) Slipping, trampling and crushing occurred as a crowd of 2500 people rushed to get out of the rain at the train station

53 / 150

Hillsborough football stadium (1989)

Severe overcrowding at entrances, poor ground design and lack of crowd management

96 / 400+

Bradford Football stadium fire (1985)

Fans seated at the rear of the stand were trapped in narrow corridor

56 / 450

Heizeldrama (1985) Assault of a neutral ring of supporters, in the following stampede lives were lost.

39 / 400+

Research questions...

•Can we predict if safety issues occur, both:

- External threat (e.g. fire): is there enough time to get out of the building?

- Internal (crushing): is crushing likely to occur (e.g. in case of large scale evacuation or events where many people gather)

•Can we come up with rules or approaches for managing large flows efficiently and safely?

•Can we come up with design guidelines?

Deep understanding of the dynamics of pedestrian flows are required (& models!)

•Consider a room (a stadium, or whatever) with N people

•Suppose that the exits have a total capacity of C Peds/min

•How long does it take to clear the room?

•Use of simple bottleneck model would lead to following expression:

•Is C know? Is C constant?

Challenge the future

Simple calculation example

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How much time does it take to clear a room?

N

C

Tevac = NC


What determines capacity?

•Experimental research on behalf of the ministry of housing

•Pedestrian experiments considering different conditions and flow compositions

•Empirical basis for expression of capacity as a function of different factors:

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Factors influencing capacity


Microscopic analyses

•Open door (90 degrees) causes capacity reduction of 7%

•Detailed analysis of pedestrian trajectories reveals cause

•Pedestrians are reluctant to temporarily accept being very close to / in physical contract with others (contrary to the ‘no door’ scenario)

•Importance of detailed analysis

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Example: impact of open door on capacity

0 1 2 3 4 5 6 7 8

1

2

3

4

5

6 Looprichting

X-positie (in m)

Y-positie (in m) Walking direction

X-position (in m) Y-

posi

tion

(in m

)

What else could affect the capacity of a door?

Courtesy of Majid Sarvi

Pedestrian flow capacity drop

•Capacity drop also occurs in pedestrian flow

•Faster = slower effect

•Pedestrian experiments (TU Dresden, TU Delft) have revealed that outflow reduces substantially when evacuees try to exit room as quickly as possible (rushing)

•Capacity reduction is caused by friction and arc-formation in front of door due to increased pressure

•Capacity reduction causes severe increases in evacuation times


Building up pressure...

•Increasing (time-) pressure causes severe reduction in capacity due to arc formation

•Keep density below critical density to keep flow running smoothly

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Faster = slower effect


Increasing door capacity

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How old Dutch traditions can improve evacuation times

The ‘polonaise’ increases door capacity by 20%


More complex situations?

•Real-life situations are often much more complex

•Multi-directional pedestrian flows, e.g.:

• Bi-directional flows through (narrow) hallways

• Crossing flows at plazas

•Reason to organize first large scale walking experiments in 2002 (world premiere)

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Multi-directional pedestrian flows...


Intermezzo: some preliminaries...

•Pedestrians require space to move

•The faster you walk, the more space you will need, e.g.:

•Density = number of pedestrians / square meter:

•This allows expressing speed as a decreasing function of density:

•Is the a valid expression for all densities?

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The Pedestrian Fundamental Diagram

A(v) = A

0+ γ ⋅v

k = 1/A(v)

v = v(k) = γ −1(A

0−1/k)



•Speed-density relation:

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v = v(k) = γ −1(A

0−1/k)

Congested branch

Free-flowbranch

Free speed

Jam density

Challenge the future 14

•Example below shows fundamental diagram for regular situation from Weidman

•Expression for speed v = V(k) and flow q = kV(k)




Fascinating self-organization!

•Dynamically formed walking lanes

•High efficiency in terms of capacity and observed walking speeds (see next slide)

•Experiments by Hermes group show similar results

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and flow efficiency impacts...


Fascinating self-organization!

•Lane formation process appears chaotic

•Probability that certain number of lanesforms / sustains depends on density

•Efficiency impact is limited

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and flow efficiency impacts...


•Observable differences between uni-directional and bi-directional flow speed-density relation?

•Capacity of bi-directional flow as a function of composition shows relatively limited impact

Fascinating self-organization!and flow efficiency impacts...


•Efficient self-organization very common in pedestrian flows

•Example shows formation of diagonal homogeneous stripes in a crossing flow situation

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Fascinating self-organization!crossing flows...


Self-organization in non-controlled conditions

•Use of UAS (Unmanned Airborne Systems) to collect data from the air

•All forms of self-organization are clearly visible from these data


Limits to self-organization?

•When conditions become too crowded (density larger than critical density), efficient self-organization ‘breaks down’

•Flow performance (effective capacity) decreases substantially, potentially causing more problems as demand stays at same level

•Importance of ‘keeping things flowing’, i.e. keeping density atsubcritical level maintaining efficientand smooth flow operations

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Abrupt phase transitions


Limits to self-organization?

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Consequences of failing self-organization

•Locations with failing self-organization (e.g. blocked hallway, blocked plaza) may be the origin of severe queuing problems in a pedestrian network

•Recall operations at Duisburg

Crowd Management

Physical contact and high pressure yields new phase

Turbulence

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Force networks

•Forces are ‘passed on’ from the one pedestrian to the next

•Pressure on some of the pedestrians becomes extremely high

•Compare to the pressure exerted on a grain silo, often resulting in spontaneous ruptures

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Results of stagnation of flows


Force networks

•Acceptable force on adult has a maximum of 800 N

•Crushing (crush ashpyxia) occurs due to high peak pressure or long exposure, for instance:

• 15 s long, force of 6227 N

• 4-6 min long, force of of 1112 N

•Example shows measures pressureduring a popconcert

•In this case, several peoplefainted (medical assistance)

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Results of stagnation of flows


Network level dynamics

•Relation between network production and number of pedestrians (accumulation)

•Caused by capacity drop and spill-back effects (intersection flows)

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Model for deteriorating network performance


Crowd Management basics

• Self-destructive nature of pedestrian networks: when network load is high, production reduces causing problems to worsen further - the causes for network deterioration and deterioration itself provide directions for design and crowd management (golden rules):

1. Prevent blockades: separate flows to prevent bi-directional or crossing flows as much as possible in particular for high-demand areas

2. Increase throughput: identify major bottlenecks and aim to increase their effective capacity (e.g. by preventing capacity drop from occurring at critical areas in network)

3. Distribute flows over network: ensure using under-utilized parts of the network (e.g. using guidance)

4. Limit inflow if needed: keep number of pedestrians in (critical) facility below critical number (e.g. by perimeter control)

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Implications of pedestrian flow dynamics...


Design and management solutions

• Already problems during Hajj and Ramadan; demand is growing

• Required capacity increase: from 50.000 P/day to 100.000 P/day

• Redesign + crowd management system (guidance, perimeter control)

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•Separate in- and outgoing flows as much as possible

•Control inflow by means of access fates

•Improve use of 1st and 2nd floor by info and guidance

•Increase capacity at pinch regions

•Provide more space (adding floor)

Applying these concepts to design of Al Mataf

Courtesy of Prof. Hani Mahmassani

Crowd Management

Voorbeeldontwerp Al Mataf

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Crowd Management

Tools to monitor and measure flows in stations

SmartStation application

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CCB

data filtering & analyse

Doel:weten waar onze reizigers lopen

Bluetooth/WIFI


Looking back to Duisburg...

•Importance of good organization

•Importance of good and timely communication (situation can quickly deteriorate)

•Be pro-active if possible

•Importance of having a profound understanding of pedestrian flow dynamics and application of the golden rules

•Be sensible!

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What have we learnt?

Crowd Management

Subtitle Text

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Thanks for your attention

The Living Crowd - Transport Studies Unit Tokyo Tech · 2013-03-07 · 02/03/13, Prof. Dr. Serge Hoogendoorn Challenge the Future Delft University of Technology The Living Crowd...

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