# Transportation Economics/Modeling

*All forecasts are wrong; some forecasts are more wrong than others.* -
anonymous

**Modeling** is a means for representing reality in an abstracted way.
Your mental models are your **world view**: your outlook on life, and
the world. The world view is your *internal model of how the world
works*; it is employed every time you make a prediction: what do you
expect, what is a surprise. The expression "Where you stand depends on
where you sit" epitomizes this idea. Your world view is shaped by your
experience and your position.

When modeling, the issue of **Point of View** should be considered. It
must be clear who (and what) the results are for. If you are modeling
for personal pleasure, it will naturally reflect your own worldview, but
if you are working for an employer or client, their point of view must
also be considered, if the inputs or results deviate significantly from
their worldview, they may adapt their worldview, but more likely will
dismiss the model.

Modeling can be conducted both for subjective **advocacy** and for
objective **analysis**. The same methods may be employed in either, and
the ethical modeler will produce the same results in either case, but
they may be used differently.

## Why Model?

There are a variety of reasons to model. Modeling helps

-   gain insight into complex situations by understanding simpler
    situations resembling them
-   optimize the use of resources in building or maintaining systems
-   operate system, particularly by testing alternative operational
    scenarios
-   educate and provide experience for model-builders
-   provide a platform for testing contending ideas and use in
    negotiations.

Particular applications in transportation include:

-   Forecasting traffic
-   Testing scenarios (alternative land uses, networks, policies)
-   Planning projects/corridor studies
-   Regulating land use: Growth management/public facility adequacy
-   Managing complexity, when eyeballs are insufficient, (different
    people have different intuitions)
-   Understanding travel behavior
-   Influencing decisions
-   Estimating traffic in the absence of data

## Developing Models

As an engineer, economist, or planner you may be given a model to use.
But that model was not spontaneously generated, it came from other
engineers, economists, or planners who undertook a series of steps to
translate raw data into a tool that could be used to generate useful
information.

The first step, specification, tells us what depends on what (the number
of trips leaving a zone may depend on the number of households). The
estimation step tells us how strong these relationships mathematically
are, (each household generates two trips in the peak hour).
Implementation takes those relationships and puts them into a computer
program. Calibration looks at the output of the computer program and
compares it to other data, if they don\'t match exactly, adjustments to
the models may be made. Validation compares the results to data at
another point in time. Finally the model is applied to look at a project
(e.g. how much traffic will use Granary Road after Washington Avenue is
closed to traffic).

-   Specification:
    -   $y=f(X)\,\!$
-   Estimation:
    -   $y=mX+b\,\!$; m=1, b=2
-   Implementation
    -   If Z \> W, Then $y=mX+b\,\!$
-   Calibration
    -   $y_{predicted}+k=y_{observed}\,\!$
-   Validation
    -   $y_{predicted1990}+k=y_{observed1990}\,\!$
-   Application

## Specification

When building a model system, numerous decisions must be made. These are
discussed below:

### Types of Models

There are numerous types of models, a short list is below. Each has
different applicability, multiple methods may be used in pursuit of the
same question, sometimes they are complementary, and sometimes
competitive techniques.

-   Network analysis
-   Linear Programming
-   Nonlinear Programming
-   Simulation
-   Deterministic queuing
-   Probabilistic queuing
-   Regression
-   Neural Nets
-   Genetic Algorithm
-   Cost/ Benefit Analysis
-   Life-cycle costing
-   System Dynamics
-   Control Theory
-   Difference Equations
-   Differential Equations
-   Probabilistic Risk Assessment
-   Supply/Demand Equilibrium
-   Game Theory
-   Statistical Decision Theory
-   Markov Models
-   Cellular Automata
-   Etc.

### Model Trade-offs

Building a model requires trading-off time and resource constraints. One
could always be more detailed, more accurate, or more comprehensive if
resources were not constrained. However, the following must also be
considered.

-   Money,
-   Data,
-   Computation,
-   Labor,
-   Ease of Use,
-   Convincing (e.g. Graphic Displays),
-   Extendable,
-   Evidence of Model Benefits,
-   Measuring Model Success

### Organization of Model System

-   Hierarchy of Models
-   Centralized vs. Decentralized (Optimization (Global) vs. Agent,
    Local Optimization)

### Time

-   Time Frame
-   Static vs. Dynamic
-   Real Time vs. Offline
-   Short Term vs. Long Term (Partial vs. General Equilibrium)
-   Proactive vs. Reactive (Predictive vs. Responsive)

### Space

-   Scale/Detail
-   Spatial Extent
-   Boundaries (Boundary Effects)
-   Macroscopic vs. Microscopic (Zones, Flows vs. Individuals, Vehicles)

### Process

-   Stochastic vs. Deterministic
-   Linear vs. Nonlinear
-   Continuous vs. Discrete
-   Numerical Simulation vs. Closed Form Solution
-   Equilibrium vs. Disequilibrium

### Type

-   Behavioral vs. Aggregate Model
-   Physical vs. Mathematical Models

## Solution Techniques

When solving the model, the system as a whole must be understood.
Several questions arise:

-   Does the solution exist?
-   Is the solution unique?
-   Is the solution feasible?

Solution techniques often trade-off accuracy vs. speed. Some solution
techniques may only guarantee a local optima, while others (such as
brute force techniques) can guarantee a global optimum, but may be much
slower.

## "Four-Step" Urban Transportation Planning Models

!A green transport
hierarchy
We want to answer a number of related questions (who, what, where, when,
why, and how):

-   Who is traveling or what is being shipped?
-   Where are the origin and destination of those trips, shipments?
-   When do those trips begin and end (how long do they take, how far
    away are the trip ends)?
-   Why are the trips being made, what is their purpose?
-   How are the trips getting there, what routes or modes are they
    taking?

If we know the answers to those questions, we want to know what are the
answers to those questions a function of?

-   Cost: Money, Time spent on the trip,
-   Cost: Money and Time of alternatives.
-   Benefit (utility) of trip (e.g. the activity at the destination)
-   Benefit of alternatives

The reason for this is to understand what will happen under various
circumstances:

-   How much "induced demand" will be generated if a roadway is
    expanded?
-   How many passengers will be lost if bus services are cut back?
-   How many people will be "priced off" if tolls are implemented?
-   How much traffic will a new development generate?
-   How much demand will I lose if I raise shipping costs to my
    customers?

In short, for urban passenger travel, we are trying to predict the
number of trips by:

-   Origin Activity,
-   Destination Activity,
-   Origin Zone,
-   Destination Zone,
-   Mode,
-   Time of Day, and
-   Route.

This is clearly a multidimensional problem.

In practice, the mechanism to do this is to employ a \"four-step\" urban
transportation planning model, each step will be detailed in subsequent
modules. These steps are executed in turn, though there may be feedback
between steps:

-   Trip Generation - How many trips $T_{i}$ or $T_{j}$ are entering or
    leaving zone $i$ or $j$
-   Trip Distribution or Destination Choice - How many trips $T_{ij}$are
    going from zone $i$ to zone $j$
-   Mode Choice - How many trips $T_{ijm}$ from $i$ to $j$ are using
    mode $m$
-   Route Choice - Which links are trips $T_{ijmr}$ from $i$ to $j$ by
    mode $m$ using route $r$

## Thought Questions

-   Is past behavior reflective of future behavior?
-   Can the future be predicted?
-   Is the future independent of decisions, or are prophecies
    self-fulfilling?
-   How do we know if forecasts were successful?
-   Against what standard are they to be judged?
-   What values are embedded in the planning process?
-   What happens when values change?

## Additional Problems

-   Homework
-   Additional
    Problems

## Key Terms

-   Rational Planning
-   Transportation planning model
-   Matrix, Full Matrix, Vector Matrix, Scalar Matrix
-   Trip table
-   Travel time matrix
-   Origin, Destination
-   Purpose
-   Network
-   Zone (Traffic Analysis Zone or Transportation Analysis Zone, or TAZ)
-   External station or external zone
-   Centroid
-   Node
-   Link
-   Turn
-   Route
-   Path
-   Mode

## Video

-   Models

## References

