Scaling up impact assessment results through statistics and simulation

Abstract

For a successful introduction of Intelligent Transport Systems (ITS) it is important to determine (socio-economic) impacts and societal costs and benefits of these systems beforehand, and to develop business models. Governments usually make investment decisions based on these aspects. In the field of ITS tools exist for the separate parts of this analysis, but an integrated tool that combines impact assessment, cost benefit analysis and business modelling is lacking. A crucial step in such an integrated tool is scaling up: translating small scale traffic effects to large scale societal benefits. Traffic effects are usually determined in an experiment, for example a Field Operational Test or micro simulation, for scenarios limited in time and geographical scale. A societal cost benefit analysis demands results on for example country or EU level, for a whole year. In practice little attention is paid to the methodology for scaling up. In the European project ITS Test Beds TNO has developed a practical methodology for scaling up, integrating the tools for micro simulation and cost benefit analysis using statistics. Another way of scaling up small scale traffic effects is using macro simulation. This paper describes the problems that play a role in scaling up, and works out the two mentioned scaling up methods. An illustration of scaling up with statistics is given with a case study on Speed Alert.