The co evolution of land use and transport theory and application to london
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The Co-Evolution of Land Use and Transport: Theory and Application to London. David Levinson University of Minnesota Imperial College, London February 21, 2007. With Bhanu Yerra, Feng Xie, Shanjiang Zhu, Ahmed El-Geneidy. General Points.

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The co evolution of land use and transport theory and application to london

The Co-Evolution of Land Use and Transport: Theory and Application to London

David Levinson

University of Minnesota

Imperial College, London

February 21, 2007

With Bhanu Yerra, Feng Xie, Shanjiang Zhu, Ahmed El-Geneidy


General points

General Points

  • Transportation and Land use are interdependent shapers of urban form

    • Concentration of commercial activities (suburbanization of residences) and prosperity of public transport at the first half of 20th century.

    • Decentralization of both commercial and residential activities accompanied by expanding automobile/highway system in second half of 20th century.


Organization of talk

Organization of Talk

  • Movie: http://rational.ce.umn.edu (go to SIMS)

  • Orderliness in London

  • SIGNAL - A Simulation Model of Co-evolution

  • Twin Cities & Next steps


The sequence of development

The Sequence of Development?

This extension of the railway system by means of feeder lines means that in many ways the early development of the system can be viewed, not in terms of booms and slumps, but in rational steps. By the end of 1833, three of the five English provincial towns with a population of more than 100,000 had railway links with London under construction; by the end of 1836 only Portsmouth remained among English towns of over 50,000 population without a line authorized; and by the end of 1837 most towns of more than 20,000 inhabitants were on or close to the route of an authorized railway. - M.C. Reed


Orderliness hypothesis

Orderliness Hypothesis

  • H: Places will be connected to the network roughly in order of their population density (density is used to control for area). The places that have the highest population per unit area (or population density) will get the network first.

  • Tested in London


Background

Background

  • 1836 London and Greenwich Railway

  • 1846 Royal Commission on Railway Termini

  • 1854 Metropolitan Railway chartered

  • 1863 Metropolitan Railway opens

  • 1884 “Circle” closed

  • 1890 City and South London Railway (first tube)

  • Railways not permitted to be developers except Metropolitan Railway --> Metro-Land

  • Greenbelt


Surface rail population

Surface Rail & Population


Underground population

Underground & Population


Boroughs without underground service

Boroughs without Underground Service


City of london

City of London


Leads and lags

Leads and Lags


Qualitative model

Qualitative Model

  • Rail first inter-city: connects outside -> in

  • Underground first connects termini, then other points in developed area, and finally connects to new suburbs: inside -> out

  • Has a decentralizing effect for residences, lowering population density in center, increasing it in suburbs.

  • Other factors; entrepreneurs, construction costs, South vs. North (income, rail embeddedness, geology, competition, south already more local than north (London in south of England)


Signal

SIGNAL

  • Simulator of Integrated Growth of Network and Land use

    • Simulate the co-evolution of land use and road networks.

    • Implement a bottom-up process that incorporates independent route choices of travelers, location decisions of businesses (jobs) and residents (workers), as well as investment decisions of autonomous roads.

    • Kept as simple as possible to capture salient components, while enabling us to display and analyze the emergent patterns of land use and network on a large scale.


Model framework

Model Framework


Travel demand models

Travel Demand Models

3. Mode Choice

Single mode is assumed

1.Trip Generation

4. Traffic Assignment

Calibrated Stochastic User Equilibrium (SUE)

2.Trip Distribution


Road investment models

Road Investment Models

1. Revenue Model

a

b

2. Cost Model

3. Investment Model


The co evolution of land use and transport theory and application to london

SONG (fixed Land Use)Base Case: Uniform Initial Speeds and Land use (U/U)(left) Spatial distribution of uniform speed for the initial network; (right) Spatial distribution of speed for the network at equilibrium reached after 8 iterations.


The co evolution of land use and transport theory and application to london

Uniform initial speeds and random initial land use(U/R)Spatial distribution of speed for experiment U/R after reaching equilibrium;


The co evolution of land use and transport theory and application to london

Random initial speeds and random initial land use(R/R)(left) Spatial distribution of initial speed for experiment R/R (random initial speeds and random initial land use); (right) Spatial distribution of speeds for the network after reaching equilibrium; The color and thickness of the link shows its relative speed or flow.


The co evolution of land use and transport theory and application to london

Uniform initial speeds and bell-shaped initial land use(U/B)Spatial distribution of final speeds for experiment U/B (uniform initial speeds and bell shaped land use)


Access and land use models

Access and Land use Models

  • Assumptions

    • Residence and employment are the only types of activities, and their totals are kept equal and constant.

    • Accessibility to population and to employment are the only factors that affect location decisions.

    • People want to live near jobs, but far from other people to maximize available space and to avoid potential competitors for jobs, while employment wants to be accessible both to other employment and to people (who are their suppliers of labor and customers).


Access land use models

Access & Land use Models

1. Accessibility

3. Redistribution

2. Potential


Measures

Measures

Equivalent radius (r)

  • Gini

Where

Ej= employment of zone j

dj= distance of zone j to the center of a region


Numerical example

Numerical Example

  • A hypothetical metropolitan area where:

    • both the population and employment are distributed over a two-dimensional grid, stretching 10 km in both dimensions, divided into a 20X20 grid lattice of land use cells (400 zones).

    • A total of 400,000 people are living in the city, which is equivalent to an average of 1,000 residents in each zone. Total employment equals 400,000 as well (and each resident holds a job).

    • Two-way roads connect the centroids of each pair of adjacent zones, thus forming a 20X20 grid of road network as well, comprising 400 nodes and 1520 links.


Experiments and hypotheses

Experiments and Hypotheses

Experiments

Hypotheses

  • Initially flat land uses become more concentrated, and initially concentrated become less so.

  • The degree to which land uses are concentrated is reinforced when road networks are allowed to vary rather than remain constant.


Result activity density

Result: activity density

Evolution of employment without network dynamics

Evolution of employment with network dynamics


Results gini

Results: Gini

1 less equitable

0 more equitable


Results equivalent radius

Results: Equivalent Radius


Sensitivity

Sensitivity


Sensitivity1

Sensitivity


Summary

Summary

  • A simple co-evolution model of transportation and land use which incorporates independent route choices of travelers, location decisions of businesses (jobs) and residents (workers), as well as investment decisions of autonomous roads.

  • Experimental results show that the degree of both employment and population concentration is reinforced when road networks are allowed to vary rather than remain constant.

  • Contemporary integrated transportation and land use models that neglect road dynamics could underestimate the concentration of land uses.


Next steps

Next Steps

  • Application to Twin Cities

  • Estimation & Calibration of Models (Markov Chain, Cellular Automata, MCCA, SIGNAL) using detailed empirical dataset.


Future models

Future Models …

  • Modeling

    • Explicitly consider co-evolution

    • Dynamic transportation network instead of static network

    • Dynamic land use rather than fixed land use

    • Variable rather than static demand

    • Bottom-up process (Cellular Automata/Agent-Based) instead of top-down (Allocation, Equilibrium, Optimization)


Thank you

Thank You

  • More available at: Rational.ce.umn.edu

  • Email: [email protected]


Orderliness

Orderliness


The co evolution of land use and transport theory and application to london

Random initial speeds and bell-shaped initial land use(R/B)(top) Spatial distribution of initial speed for experiments R/B (random initial speeds and bell shaped land use); (bottom) Spatial distribution of speeds for the network after reaching equilibrium


The co evolution of land use and transport theory and application to london

Gravity model parameter variations with uniform network and land use (U/U) Spatial distribution of relative speeds at equilibrium for (top)w = 0.02 (less sensitive to travel cost); (bottom)w = 0.8 (more sensitive to travel cost).


Variation of average traffic flow left speed right with w for 10x10 11x11 and 15x15 networks

Variation of average traffic flow (left) speed (right) with w for 10X10, 11X11 and 15X15 networks.


Slice of a bell shaped downtown land use pattern

Slice of a bell-shaped downtown land use pattern


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