Sustainability is one of today's major public concerns. There is evidence that transport and land use systems of cities all over the world are unsustainable. Indicators backing up this hypothesis are among others:
urban sprawl, pollution and consumption of non-renewable resources.
As urban planning has become increasingly complex, decision support tools are essential to help to achieve the overall objective of sustainability. Recent research has shown that any single policy instrument cannot achieve sustainability. Policy strategies employing several instruments are needed to be successful. The use of formal models and optimisation methods is suggested to be used to identify the best performing strategy.
Why another model?
Research of the last decades has shown that land use and transport form a closely linked dynamic system. Therefore integrated land use and transport models are needed to assess the performance of urban policy strategies. A literature review has shown that a variety of operational transport and/or land use models exists. The current trend in land use and transport modelling is characterised by an extreme disaggregation even down to individual household level. This extremely detailed modelling approach is, independently from its theoretical appeal, inappropriate for identifying sustainable policy strategies. Despite the ever-increasing computational power, model runs take too long to be able to consider a reasonable number of instruments. Additionally data needs are very high. Even synthetic data have to be produced to match the level of model disaggregation. Data requirements might be one of the reasons why the use of integrated land use and transport models is still not widespread. A different approach was therefore chosen here.
The rather high aggregated integrated, dynamic urban land use and transport model MARS was developed as the core of a sustainability assessment framework. The underlying hypothesis is that cities are self-organising systems and that the principles of synergetics can be applied to describe collective behaviour. A qualitative model was developed based on Viennese research. The method of causal loop diagrams was used for this task. From this basis a quantitative model was built and written into code. MARS was calibrated for the city of Vienna. An extensive model-testing program was carried out using observed data from 1981 to 2001. A back casting exercise and sensitivity tests have proven the usability of MARS.