Decision Makers' Guidebook
Why is it important to predict impacts?
As we indicate in Sections 9, 10 and 11, it is difficult to state in advance what will be the effect of introducing a particular policy instrument or strategy. Individual policy instruments may have a wide range of impacts on demand and supply, some of them immediate and others arising as users change their habits. In the extreme, with land use policies, some effects may take a decade or more to occur. At the same time we need to understand these impacts, not just on demand and supply, but on our seven underlying objectives. Such analyses are often helped by using a model of the land use and transport system.
What is a model?
A model is a formal mathematical representation of a real world system. A land use and transport model could represent how people’s travel behaviour responds to changes in the transport system provided; how the performance of the system changes as patterns of use change; how these changes affect indicators such as congestion, pollution and accidents; how land use changes affect patterns of use; or how land use is itself influenced by changes in the cost of using the transport system.
Why do we need models?
The answers to these questions are complex, and it can thus be difficult to estimate how the transport and land use system will change in the medium and long term (Section 3) without some analytical tools to provide those estimates. Moreover, the range of policy instruments (Section 9) and of ways in which they can be combined (Section 11) makes it particularly difficult to decide what is the best strategy. Authorities need information on likely effects on their land use and transport systems for a range of scenarios. Computer-based mathematical models of the urban land use and transport system can provide this.
What types of model are available?
Any model is supposed to be a simplification of the system being studied. It is not, and should not try to account for, everything. It should instead be a well-made caricature, where the characteristics of the modelled system are brought out with no more brush strokes than necessary. This makes it easier for the modeller to understand the system, and for others to use it. This in turn means that the results are more likely to be trusted. However, simplicity cannot be the main objective. The key to a good model is to drop unnecessary detail and complexity. This will be a greater challenge when dealing with integrated strategies in which more elements need to be modelled.
In the PROSPECTS Methodological Guidebook we provide advice on three types of model, in order of increasing complexity and the specialist skills required:
- Policy explorers, which provide a very simplified representation of a hypothetical city, and help users to understand the types of impact which a policy might have
- Sketch planning models which represent the main interactions between demand, supply and land use at a strategic level for the city in question, without giving detailed information on transport networks or land use patterns; and
- Land use—transport interaction (LUTI) models, which represent transport networks and land use patterns and their interactions in greater detail, while still focusing on strategic issues.
In addition, there are conventional network and transport planning models, which are less complex than full LUTI models, but which typically ignore the land use effects.
PROPOLIS provides a valuable example of the use of a range of LUTI models to test a common set of strategies in seven cities, and argues that such models are essential for understanding the complex interactions between transport and land use in larger cities. ISHTAR has developed a suite of programs which go further in assessing the impacts of transport on pollution and the built environment.
What are the limitations on models?
There are dangers both in over-use and under-use of models. The traditional rational, analytical approach to planning (Section 4) can all too easily lead to over-reliance on models, and a failure to realise that other issues are important, and that others will mistrust the experts and their results. Model-based analysis therefore needs to be used as a contribution to strategy formulation, rather than being seen as the whole process. Model assumptions need to be made clear, and results need to be able to be presented in a user-friendly way to decision-makers and to stakeholders as part of the participation process (Section 5). Ideally models should also be available for non-experts to use, as a tool to support “deciding together”. However, most current models are unfortunately not well designed for this.
Limitations of models
- Representation of freight trafficMeasurement of journey reliability, quality and information
- Responses to journey reliability, quality and information
- Effects of air pollution on health
- Distributional and equity impacts
- Responses to telecommunications
- Transport supplier responses
Many cities do not use models themselves, often because they do not have the resources or expertise to do so. Cost, and the need for specialist skills, have often been a barrier, but the sketch planning models which we describe are now much less expensive, and much simpler for those without specialist expertise to use. Another concern is that models may be unreliable. It is certainly the case that, because models are simplifications of reality, they will omit some of the interactions in the real system, and approximate others. In our review of the requirements and capabilities of models we identified the limitations in the box as of particular importance.
Where can I find out more?
- DETR (2000a)
- Mackie & Nellthorp (2003)
- Minken et al (2003)
- PROSPECTS D2
- PROSPECTS D3
There are also approaches that do not depend on mathematical models; for example, the EU project ASI has developed a qualitative ‘tool box’ to assess the effects on ‘life quality’ of urban transport and mobility policies. In practice it may be sensible to combine mathematical modelling to predict indicators which can be quantified with qualitative approaches for those indicators (such as ‘life quality’) which cannot.
These are all areas for further research and development. Even so, it will be easier to plan a land use and transport strategy for a city with a model, in the knowledge of these imperfections, than to estimate the effects without one. Indeed, there is a need for further research to develop guidance for the prediction of impacts when models are not available.
Instruments can complement others by