Complexity Science & Transport Systems Jeffrey Johnson & Joan Serras Design, Development, Environment & Materials The Open University to infinity … and

Complexity Science & Transport Systems

Jeffrey Johnson & Joan SerrasDesign, Development, Environment & Materials

The Open University

to infinity … and beyond

The Complex Systems Perspective:

Road systems - interconnected systems of dynamic systems.

Many subsystems: Populations, roads, railways, land uses, regulations. All have multilevel structure, e.g. people, families, neighbourhoods, cities. All have dynamics => emergent dynamics of whole

Subsystems have thousands or millions of partscan only be modelled on computers.

How to represent and modelling huge heterogeneous multilevel road systems such as the whole of the UK or Europe ?

You are here You came in here

or hereor here

You are here

… and you’re still in England Wales !

There’s a lot of stuff

… how can we represent so much stuff ?


… how can we represent so much stuff ?


from micro to macro ?


Traffic Modelling Conference 31-March-2009 Open University

Everything is becoming more & more connected

Milton Keynes

Bedford



Milton Keynes

Bedford



Milton Keynes

Bedford



Milton Keynes

Bedford

Cannot divide & rule

- the are connected !


Objectives of the research

To model road system in an holistic way such that:

• captures the dynamics of road traffic:

microdynamics: e.g. shock wavesmacrodynamics: e.g. transmission of congestion






• includes all the smallest level links – nothing left out!

• aggregates bottom-up dynamics – no information loss!








• distributes computation and data naturally across administrative levels








• distributes computation and data naturally across administrative levels

• illustrate by huge road systems, e.g. London, Europe


Starting point: it is like this



Plots of land – ‘zones’




Activity Land Uses




Activity Land Uses



origin

destination

Trips are made between located activities



origin

destination



origin

destination



origin

destination



origin

destination



origin

destination



origin

destination

A route traverses a set of zones at different ‘levels’



Plots aggregate into larger areas – zones


Zones aggregate into larger zones






Larger zones aggregate into even larger zones






Even larger zones aggregate into even larger zones


Even larger zones aggregate into even larger zones


… and so on to zones for London, England, Europe, …


We assume there is a hierarchical set of zones

ZN-3 … ZN-1 ZN ZN+2 … ZN+k-1 ZN+k



link between junction nodes

kitchen

house plot, road segment




link between junction nodes

kitchen

house plot, road segment


Abstract higher level lines (to be explained)


Define a set of nodes -

where a vehicle can cross a road zone boundary




A link is defined by a pair of nodes




A link is defined by a pair of nodes

‘conventional’ links exist at Level N


A

B

A Level-N route is a set of Level N links


A

B

There are many N-Level routes between A and B


A

B



A

B



A

B

Let this set of routes be a Level N+2 Link


There are ~8000 Level-N routes between A and B

AB

~ 20 routes ~ 20 routes ~ 20 routes


Put a N+2-level nodes on the boundaries

AB


Make Level N+2 links and a Level N+2 route

AB



AB



AB


We now have 20 + 20 + 20 + 1 = 61 << 8000 routes !

AB



We now have ~ 100,000 possible routes !

AB



We now have ~150 + 9 = ~159 <<< 100,000 routes!

AB



If the routes cross a Level N+3 Zone ..

AB


AB

… make a Level N+3 link as the set of N+2 routes


AB

Hierarchical routes used for routing trips

Level N+2 links

Level N+1 linksLevel N+1

Level N links

Level N links

Within hierarchical zones, always use the highest level links available


AB

Higher level links have lower variance !

Level N+2 links


Level N links

Level N links

rela

tive

fr

equ

ency

travel time, minutes travel time travel time, hours

100%

rela

tive

fr

equ

ency

rela

tive

fr

equ

ency


AB

Hierarchical routes used for routing trips

Level N+2 links


Level N links

Level N links

Note: higher level links have more stable flow and travel time statistics than lower level links initialisation heuristics ?


TRANSIMS – from Micro simulation to Macro dynamics










Level N+7

Level N+6

Level N+5

Level N+4

Level N+3

Level N+2

Level N+1

Level N

Level N-1

Level N-2

Level N-3

The World !

Region (e.g. the Americas, Asia )

Nation (e.g. USA, UK )

State (e.g. Virginia, Buckinghamshire)

City, rural region (e.g. New River Valley)

Small town (e.g. Blacksburg, Milton Keynes)

Neighbourhood (e.g. VT Campus)

Conventional Links and zones

Road segment, plot of land

House, garden, garage

Rooms


Research in Progress

1.Devise new microlevel simulation

2. Implement at microlevel for Milton Keynes

3. Implement hierarchical routing schemes

4.New synthetic micropopulation – all properties

5. Run the system for Milton Keynes

6. … extend to UK

7. … extend to Europe

8. … extend to infinity, and beyond !

Documents

Complexity Science & Transport Systems Jeffrey Johnson & Joan Serras Design, Development, Environment & Materials The Open University to infinity … and