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

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Presentation on theme: "Complexity Science & Transport Systems Jeffrey Johnson & Joan Serras Design, Development, Environment & Materials The Open University to infinity … and."— Presentation transcript:

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

2 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 parts can only be modelled on computers. How to represent and modelling huge heterogeneous multilevel road systems such as the whole of the UK or Europe ?

3 You are here You came in here or here

4 You are here

5

6

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8

9 … and you’re still in England Wales ! There’s a lot of stuff

10 … how can we represent so much stuff ? There’s a lot of stuff

11 … how can we represent so much stuff ? There’s a lot of stuff

12 from micro to macro ? There’s a lot of stuff

13 Traffic Modelling Conference 31-March-2009 Open University Everything is becoming more & more connected Milton Keynes Bedford

14 Traffic Modelling Conference 31-March-2009 Open University Everything is becoming more & more connected Milton Keynes Bedford

15 Traffic Modelling Conference 31-March-2009 Open University Everything is becoming more & more connected Milton Keynes Bedford

16 Traffic Modelling Conference 31-March-2009 Open University Everything is becoming more & more connected Milton Keynes Bedford Cannot divide & rule - the are connected !

17 Traffic Modelling Conference 31-March-2009 Open University Objectives of the research To model road system in an holistic way such that: captures the dynamics of road traffic: microdynamics: e.g. shock waves macrodynamics: e.g. transmission of congestion

18 Traffic Modelling Conference 31-March-2009 Open University Objectives of the research To model road system in an holistic way such that: captures the dynamics of road traffic: microdynamics: e.g. shock waves macrodynamics: e.g. transmission of congestion includes all the smallest level links – nothing left out! aggregates bottom-up dynamics – no information loss!

19 Traffic Modelling Conference 31-March-2009 Open University Objectives of the research To model road system in an holistic way such that: captures the dynamics of road traffic: microdynamics: e.g. shock waves macrodynamics: 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

20 Traffic Modelling Conference 31-March-2009 Open University Objectives of the research To model road system in an holistic way such that: captures the dynamics of road traffic: microdynamics: e.g. shock waves macrodynamics: 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 illustrate by huge road systems, e.g. London, Europe

21 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this

22 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this Plots of land – ‘zones’

23 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this Plots of land – ‘zones’ Activity Land Uses

24 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this Plots of land – ‘zones’ Activity Land Uses

25 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this origin destination Trips are made between located activities

26 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this origin destination

27 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this origin destination

28 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this origin destination

29 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this origin destination

30 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this origin destination

31 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this origin destination A route traverses a set of zones at different ‘levels’

32 Traffic Modelling Conference 31-March-2009 Open University Starting point: it is like this Plots aggregate into larger areas – zones

33 Traffic Modelling Conference 31-March-2009 Open University Zones aggregate into larger zones

34 Traffic Modelling Conference 31-March-2009 Open University Zones aggregate into larger zones

35 Traffic Modelling Conference 31-March-2009 Open University Zones aggregate into larger zones

36 Traffic Modelling Conference 31-March-2009 Open University Larger zones aggregate into even larger zones

37 Traffic Modelling Conference 31-March-2009 Open University Larger zones aggregate into even larger zones

38 Traffic Modelling Conference 31-March-2009 Open University Larger zones aggregate into even larger zones

39 Traffic Modelling Conference 31-March-2009 Open University Even larger zones aggregate into even larger zones

40 Traffic Modelling Conference 31-March-2009 Open University Even larger zones aggregate into even larger zones

41 Traffic Modelling Conference 31-March-2009 Open University … and so on to zones for London, England, Europe, …

42 Traffic Modelling Conference 31-March-2009 Open University We assume there is a hierarchical set of zones Z N-3 … Z N-1  Z N  Z N+2 …  Z N+k-1  Z N+k

43 Traffic Modelling Conference 31-March-2009 Open University We assume there is a hierarchical set of zones link between junction nodes kitchen house plot, road segment Z N-3 … Z N-1  Z N  Z N+2 …  Z N+k-1  Z N+k

44 Traffic Modelling Conference 31-March-2009 Open University We assume there is a hierarchical set of zones link between junction nodes kitchen house plot, road segment Z N-3 … Z N-1  Z N  Z N+2 …  Z N+k-1  Z N+k Abstract higher level lines (to be explained)

45 Traffic Modelling Conference 31-March-2009 Open University Define a set of nodes - where a vehicle can cross a road zone boundary

46 Traffic Modelling Conference 31-March-2009 Open University Define a set of nodes - where a vehicle can cross a road zone boundary A link is defined by a pair of nodes

47 Traffic Modelling Conference 31-March-2009 Open University Define a set of nodes - where a vehicle can cross a road zone boundary A link is defined by a pair of nodes ‘conventional’ links exist at Level N

48 Traffic Modelling Conference 31-March-2009 Open University A B A Level-N route is a set of Level N links

49 Traffic Modelling Conference 31-March-2009 Open University A B There are many N-Level routes between A and B

50 Traffic Modelling Conference 31-March-2009 Open University A B There are many N-Level routes between A and B

51 Traffic Modelling Conference 31-March-2009 Open University A B There are many N-Level routes between A and B

52 Traffic Modelling Conference 31-March-2009 Open University A B Let this set of routes be a Level N+2 Link

53 Traffic Modelling Conference 31-March-2009 Open University There are ~8000 Level-N routes between A and B A B ~ 20 routes

54 Traffic Modelling Conference 31-March-2009 Open University Put a N+2-level nodes on the boundaries A B

55 Traffic Modelling Conference 31-March-2009 Open University Make Level N+2 links and a Level N+2 route A B

56 Traffic Modelling Conference 31-March-2009 Open University Make Level N+2 links and a Level N+2 route A B

57 Traffic Modelling Conference 31-March-2009 Open University Make Level N+2 links and a Level N+2 route A B

58 Traffic Modelling Conference 31-March-2009 Open University We now have 20 + 20 + 20 + 1 = 61 << 8000 routes ! A B ~ 20 routes

59 Traffic Modelling Conference 31-March-2009 Open University We now have ~ 100,000 possible routes ! A B ~ 50 routes

60 Traffic Modelling Conference 31-March-2009 Open University We now have ~150 + 9 = ~159 <<< 100,000 routes! A B ~ 50 routes

61 Traffic Modelling Conference 31-March-2009 Open University If the routes cross a Level N+3 Zone.. A B

62 Traffic Modelling Conference 31-March-2009 Open University A B … make a Level N+3 link as the set of N+2 routes

63 Traffic Modelling Conference 31-March-2009 Open University A B Hierarchical routes used for routing trips Level N+2 links Level N+1 links Level N+1 Level N links Within hierarchical zones, always use the highest level links available

64 Traffic Modelling Conference 31-March-2009 Open University A B Higher level links have lower variance ! Level N+2 links Level N+1 links Level N+1 Level N links relative frequency travel time, minutes travel timetravel time, hours 100% relative frequency

65 Traffic Modelling Conference 31-March-2009 Open University A B Hierarchical routes used for routing trips Level N+2 links Level N+1 links Level N+1 Level N links Note: higher level links have more stable flow and travel time statistics than lower level links  initialisation heuristics ?

66 Traffic Modelling Conference 31-March-2009 Open University TRANSIMS – from Micro simulation to Macro dynamics

67 Traffic Modelling Conference 31-March-2009 Open University TRANSIMS – from Micro simulation to Macro dynamics

68 Traffic Modelling Conference 31-March-2009 Open University TRANSIMS – from Micro simulation to Macro dynamics

69 Traffic Modelling Conference 31-March-2009 Open University TRANSIMS – from Micro simulation to Macro dynamics

70 Traffic Modelling Conference 31-March-2009 Open University TRANSIMS – from Micro simulation to Macro dynamics

71 Traffic Modelling Conference 31-March-2009 Open University 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

72 Traffic Modelling Conference 31-March-2009 Open University 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 !


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