Integrated Urban Models: Design Issues for Integrated Urban Models

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Integrated Urban ModelsDesign Issues for
Integrated Urban Models
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Definitions (Miller et al)

• Models are defined as mathematical algorithms
  which simulate human activities, such as travel
  behavior. Once they are calibrated against
  existing (known) conditions, the models can be
  used to forecast these activities. For present
  purposes, however, it is appropriate also to
  include theory and data, in addition to
  algorithms, in the definition of a model.

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Definitions (Miller et al)

• Travel demand forecasting models are used to
  predict travel on a transportation network.
  Travel demand -- i.e., traveler behavior -- is a
  function of both human activities (generally
  represented in the models by land-use see below)
  and network characteristics (including the
  services provided and their costs where costs
  generally are expressed in terms of time and/or
  money expended by the user and/or the
  transporter, and possibly intangibles such as
  comfort, etc.). Therefore, travel forecasts will
  vary according to changes in human activities or
  network characteristics.

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Definitions (Miller et al)

• Land-use models generally are mathematical tools
  that forecast demographic and economic measures
  of land-based activities. These measures can be
  described as meaningful attributes of the
  population (e.g., age-group cohorts, income,
  jobs, etc.), but also can be expressed in terms
  of development (e.g., residential dwelling units,
  commercial floor space, etc.). They take into
  account trends and policies regarding demographic
  and economic development, as well as the supply
  of developable land. The shape of the
  transportation network, and its possible
  influence on the location of human activities are
  taken into account, but usually in a generalized
  manner. Among other uses, the results serve as
  input to a travel demand forecasting model.
  However, generally there is little or no feedback
  from travel demand forecasting models into
  land-use models.

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Definitions (Miller et al)

• Integrated transportation - land-use models
  simulate the interaction of land-use and
  transportation. They are intended to provide a
  feedback mechanism between land-use models and
  travel demand forecasting models. For example, a
  new or improved transportation link can influence
  the timing, type and extent of development in a
  particular area, which in turn can influence the
  need for further network improvements. Similarly,
  the evolution of land-based human activities
  influences the demand for improved transportation
  services, which in turn further influences
  development. Therefore, integrated models take
  land-use models a step further, by also
  simulating the location of human activities as a
  function of transportation accessibility.
  Similarly, integrated models do not simply
  provide land-use input to travel demand
  forecasting models.

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Definitions (Miller et al)

• Transit accessibility describes how well a given
  point in an urban area is connected by transit to
  other points within the area. "Accessibility" can
  be defined in many ways
• the absolute existence of a physical means of
  traveling between two points, where no other link
  exists (in this case, by transit)
• the relative level of service (speed, cost,
  comfort, etc.) of a particular transit link,
  where alternate transit links exist and which may
  offer different levels of service and
• the relative level of service of a particular
  transit link, compared with alternate modes
  (e.g., auto) which provide the same link.

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Model Development Life Cycle

• Requirements Analysis
• Conceptual Design
• Model Specification
• Data Development
• Model Estimation
• Application Software
• Model System Validation
• Model Application
• Model and Software Documentation

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Model Development Life Cycle

• Requirements Analysis
• What questions should the model address?
• What level of detail is needed?
• Who will use it, and for what applications?
• What data are available to use in developing it?
• What resource and time constraints apply?
• How should trade-offs be made on design choices
• Accuracy
• Policy-sensitivity
• Complexity
• Resource requirements

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Model Development Life Cycle

• Conceptual Design
• What modeling framework best addresses the
  requirements, under the time and resource
  constraints?
• Given a particular modeling framework, what are
  the major model components that need to be
  designed?
• How should model components interact within a
  model system?
• Given a high-level conceptual design, are there
  requirements that cannot be met? Should the
  design or the requirements be modified to be
  consistent?
• How should data and resource requirements be
  modified, given this conceptual design?

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Model Development Life Cycle

• Model Specification
• For each model component, how should the
  equations be specified?
• What is the dependent variable? (continuous,
  discrete?)
• What are the independent variables? What does
  theory suggest should be included?
• Are any effects likely to be nonlinear? What
  transformations would be appropriate? (log,
  quadratic)
• Are there likely to be interactions between
  variables? (if so, add interaction variables)

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Model Development Life Cycle

• Data Development
• What data are needed to estimate the model
  parameters?
• What processing needs to be done?
• What quality control checks should be done?
• How should missing data be handled?
• How should outliers be handled?

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Model Development Life Cycle

• Model Estimation
• For each specified model equation, need to
  estimate the parameters associated with each
  independent variable.
• Depending on the nature of the model
  specification, will need specialized econometric
  software
• Multiple regression
• Multinomial logit
• Nested Logit

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Model Development Life Cycle

• Application Software
• What kind of software is needed to implement the
  model for use in forecasting and policy analysis,
  using the estimated model?
• What language should it be implemented in?
• How can it be modularized to make it easy to
  maintain and evolve?
• What kind of user-interface does it require?
• What other performance or functional requirements
  are there?

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Model Development Life Cycle

• Model System Validation
• Once the estimated model is implemented in
  application software, it is operational.
• How should we test how well the model is working?
• Are the model predictions generally reasonable?
• Are the results sensitive to changes in model
  inputs and assumptions in ways that seem
  plausible?
• Are there observed data that we can use to
  compare the model results to, in order to
  validate the model?
• Are adjustments needed to equation constants to
  improve the overall fit of the predictions to the
  observed data?

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Model Development Life Cycle

• Model Application
• What initial real-world projects could be used
  to apply the model to?
• Helpful not to start with extremely large, or
  politically sensitive topics
• Results may still reveal problems in the model
  that need further adjustment or refinement
• Once model has been tested successfully on a few
  non-critical projects, can be applied to more
  important ones

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Model Development Life Cycle

• Model and Software Documentation
• Last, but not least, the model needs to be
  documented
• Good documentation of operational models often is
  provided in three levels
• Executive Summary
• Reference Guide
• User Guide