Günter Emberger

THE USE OF RESPONSE SURFACES IN SPECIFYING TRANSPORT STRATEGIES

Integrated transport strategies can involve a wide range of measures, each varying in the intensity with which it is applied. Objective functions can be specified to reflect public policy objectives, and their value will change as changes are made in the measures included and their intensity, generating a response surface. This process has been used in earlier research to identify the optimum combination of measures for a given objective function. In this paper the data generated is used to explore the shape of the response surface around the optimum as individual policy measures are varied in intensity. Results are presented for three cities, using different models. They indicate particular sensitivity to changes in pricing and service frequency, and greater sensitivity for economic objective functions than those which include environmental attributes. Performance is particularly sensitive when public transport is deregulated. Changes in objective function also lead to marked changes in the optimum values for pricing measures. Road pricing performance is very sensitive to the definition of the charging method. Response surfaces have been shown to be particularly useful in indicating sensitivity to a given policy instrument; in determining the loss of benefit if a sub-optimal level is required; and in assessing robustness of strategies against changes in objectives.

MARS meets ANIMAP: Interlinking the Model MARS with dynamic Internet Cartography

Abstract Transport plays a major role in our daily lives. The characteristics of a transport system influence the structure of our economy, the settlement structure and, as a consequence, the social and natural environment. The simulation model MARS (Metropolitan Activity Relocation Simulator), developed by the Institute for Transport Planning and Traffic Engineering at the Vienna University of Technology, is used to assess and to quantify the impacts of transport and/or land use policy instruments on economy, land use and environment. MARS is an integrated dynamic land use and transport model which simulates the effects of different transport- and land use planning policies over a time period of 30 years. An important point in communicating simulation results to different stakeholder groups such as transport planners, traffic modellers and decision makers is to present information regarding the model design and model results at an adequate abstraction level. For example a transport planner is more interested in the exact mathematical formula and used parameters, whereas a decision maker is more interested in the overall impact a policy might have. To present the simulation outcomes appropriately, it is necessary to map the spatial effects chronologically. The integration of the dynamic cartography application ANIMAP in MARS enables the visualisation of the historic and spatial development of an arbitrary number of indicators. The objective of this paper is to describe the technical implementation of temporal-spatial mapping and to illustrate how this improvement facilitates communication and understanding between model developers and stakeholder groups.