Transportation / Land Use Modeling

Author: Dr. Jean-Paul Rodrigue

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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 (expressed as functions in various computer programming languages), 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 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 about "thinking outside the box" and by its nature modeling often fails 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. 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)
• Cellular automata. A new range of models where space is represented as a grid (raster) with a set rules enforced to govern the state of a cell depending on the configuration of its adjacent cells.

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. Paradoxically, while freight related activities such as terminals and distribution centers tend to occupy a large amount of space, they do not generate a large amount of passenger traffic.