1. Types of Models
"Essentially, all models are wrong but some are
useful." George Box
To gain a better understanding of the behavior of urban areas, several operational
transportation / land use models (TLUM) have been developed. The reasons behind
using TLUM are numerous, such as the ability to forecast future urban patterns
based on a set of economic assumptions or to evaluate the potential impacts
of legislations pertaining to environmental standards. Other uses of TLUM relate
to testing theories, policies and practices about urban systems. With a simulation
model, urban theories can be evaluated and the impacts of policy measures, such
as growth management and congestion pricing can be measured. It is not surprising
that since TLUM are planning tools per se, their development and application
has mainly been done by various government agencies related to transportation,
regional planning and the environment.
Broadly taken, a model is an information construct used to represent and
process relationships between a set of concepts, ideas, and beliefs. Models
have a language, commonly mathematics, an intended use and a correspondence
to reality. There are four levels of complexity related to the modeling transportation
/ land use relationships:
- Static modeling. Express the state of a system at a given point
in time through the classification and arithmetic manipulation of representative
variables. Measuring accessibility can be considered as static modeling.
- System modeling. Express the behavior of a system with a given
set of relationships between variables. The gravity model is an example of
system modeling as it tries to evaluate the generation and attraction of movements.
- Modeling interactions between systems. Tries to integrate several
models to form a meta-system (a large and complex system). A
transportation / land use model offers such a perspective.
- Modeling in a decision-taking environment. This not only implies
the application of a transportation / land use model, but the analysis and
reporting of its results in order to find strategies and recommendations.
Geographic Information Systems are useful tools for that purpose as they can
include the modeling, its graphic display as well as being the platform over
which decision making can take place.
On average, models tend to be relevant for constrained and well structured
problems with a specified number of variables, well-defined goals, and firmly
established technical solutions. This in itself limits significantly the applicability
of TLUM as urban systems are complex entities. Still, these models have pros
and cons:
- Advantages. Incites a conceptualization of urban economic and spatial
processes. Advances in urban and regional sciences are often linked with advances
in modeling, notably conceptual representations such as land economics. Moving
from an urban concept to an urban model is simply a step forward, albeit an
important one. The data requirements of TLUM are often an incentive to perform
surveys from which useful information about urban mobility and spatial structure
can be gathered. This information has the additional advantage of triggering
related studies that are not necessarily related to TLUM, but that contribute
to advances in the understanding of the dynamics of urban systems.
- Drawbacks. Models may gear towards a mechanistic approach of urban
dynamics where processes are compartmentalized. This leads to difficulties
of "thinking outside the box" and often fail to grasp significant economic,
technological and social changes. They may also give the impression that a
system can effectively be controlled since all its major elements have been
summarized. Solving a problem is thus a matter of tweaking parameters. TLUM
are consequently privileged tools of government agencies as they fit such
an unimaginative mindset.
2. Four Stages Transportation / Land Use Modeling
The core foundation of TLUM involves two components, which are of course
the land use and the transportation components. The land use component, which
is based on the location of housing, industrial and commercial activities, tends
to be more stable than the transportation component which is highly dynamic.
Most of TLUM have been applied regionally, mainly at the urban level, as a larger
scale would be prohibitively complex to model. The modeling of the transportation
components is particularly relevant and is divided in
four sequential stages for the estimation of travel demand, from where movements
originate, how they are allocated, what modes are used and finally what segments
of the transport network are being used:
- The first stage is called trip generation and deals with trip rate
estimates, usually at the zonal level. The most common methods for trip generation
are cross-classification (also referred to as category analysis) and multiple
regression analysis. Cross-classification seeks to identify specific socioeconomic
groups within the population that have common trip generation characteristics.
The trip generation of a zone will thus be the outcome of its composition.
Regression analysis estimates the number of trips generated by a zone (dependant
variable) as a function of a series of independent variables.
- The second stage is referred to as trip distribution and deals
with spatial movement patterns; the links between trip origins and destinations.
The most common technique for estimating trip distribution is the gravity
model. There are various forms of the gravity model and various calibration
techniques as well. Cross-classification and multiple regression can also
be used to estimate the number a trips a zone would attract.
- The third stage is modal split;
the proportion of trips made by automobile drivers and passengers,
transit, cyclists, and walking. Logit modeling is commonly used as it evaluates
the preference of each user in terms of probability of using a specific mode
for a specific origin / destination pair.
- Finally, once the spatial patterns of
movements by various modes are estimated, trips are assigned
to the various transport links. This is done mostly by using operations research
methods aiming at minimizing travel costs or time over a transport network.
3. Data Requirements
Applying TLUM requires an
extensive range of data, most of it related to spatial units, land use,
spatial interactions and the transportation network. The most important information
for TLUM is however origin-destination data. A variety of survey methods
are used to collect this data including roadside questionnaires, telephone interviews,
and detailed activity modeling. Data availability and limitation is an important
factor behind the applicability of such models and there is a constant trade-off
between the costs of fulfilling the data requirements and the benefits supplementary
data may offer. Additionally, data needs to constantly be updated as demographic,
economic and technological changes are taking place. This is one of the major reasons
why the transportation / land use modeling process, although theoretically and
conceptually sound, has not been applied comprehensively. Among the major types
of variables, it is possible to identify:
- Land use data. Include socio-economic variables pertaining to the
area under investigation, such as population, employment, income level, commercial
activity, etc. Such data is used to estimate or calibrate the amount of
travel generated and attracted by each zone.
- Travel generation factors. Considering the available land use data,
these factors estimate the number of trips, people and/or freight, each level
of economic activity generates. They consider a multitude of issues such as
income, modal preferences and consumption levels. Most of this information
can be gathered using surveys or inferring from observations made elsewhere.
- Friction of distance factors. They represent the difficulty of
traveling between different locations of the area under investigation, commonly
measured in terms of time, distance of cost. There is a significant variance
according to mode and purpose of travel. Friction of distance factors enable
to assess trip distribution and modal split.
- Calibration factors. It is uncommon that the results produced by
an uncalibrated model are corresponding to the reality. Calibration factors
thus try to match the results produced by the model with data based on observations,
surveys or common sense. Calibration can often be an obscure process, because
it tries to incorporate factors that are not explained by the model itself.
- Transportation networks. A representation of the structure and
geometry of transportation within the area under investigation, mainly composed
of nodes and links. Transportation networks are commonly divided by modes.
For road transportation, a node could represent an intersection, a stop or
a parking lot, while a segment could be linked with attributes such as permitted
speed, distance and capacity. For public transit, a node could represent a
bus stop or a metro station, while a segment could have attributes such as
capacity and frequency of service. Transportation networks, along with origin-destination
matrices, are fundamental elements of the traffic assignment procedure.
4. Major Models
There are a wide variety of TLUM, most of them developed during the quantitative
revolution that transformed geography in the 1960s and 1970s. Among the best
known are:
-
Lowry Model. Considered to be the first transportation / land use model
(1964), it links two spatial interaction components. The first calculates
spatial interactions between basic employment activities and zones of residence,
while the second calculates spatial interactions between service employment
activities and zones of residence. The Lowry model is discussed in more details
in the Method 2 section.
-
ITLUP. The Integrated Transportation and Land Use Package is composed
of a residential allocation model, an employment allocation model, and a travel
demand model.
-
MEPLAN. This model is a derivative of the Lowry model, since it is based
on the economic base theory. It considers the two components of the transportation
/ land use system as markets, one market for land use and one market for transportation.
- TELUS. Transport Economic Land Use System. (under construction)
The core of most transportation / land use model is some kind of regional
economic forecast that predicts and assigns the location of the basic employment
sector. As such, they are dependent on the reliability and accuracy of macro-economic
and micro-economic forecasting. Traditionally, such forecasting tends not to
be very accurate as it fails to assess the impacts of economic, social and technological
changes. For instance, globalization and the emergence of global commodity chains
have significantly altered the dynamics of regional economies.
Additionally, few TLUM are dealing with freight transportation. This can
be explained by the fact that passengers transportation in urban areas tends
to be highly regulated by governmental agencies (e.g. public transit) while
freight transportation is dominantly controlled by private entities.
Copyright © 1998-2008, Dr. Jean-Paul Rodrigue, Dept. of Economics & Geography,
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