Katinka – Gathering a Reference Data Set of Bicycle Traffic for Transport Models

Abstract

Active transport modes play an important role in the decarbonization of urban transportation. Transport models and data are important decision supporting tools for infrastructure investments. For active mobility modes only a minimum data quantity and quality is available, an unleveled playing field in decision making processes is predestined. This paper presents a mixed-method approach to generate a reference dataset for cycling in a certain study area. The approach combines short-term, long-term and permanent bicycle counts together with interviews. The resulting outcome provides a better reference for decision making processes. This enables city- and transport-planners to better assess the effects of actions in the public space for all transport modalities. By implementing the generated reference data in transportation models that include active modes, it is possible to determine in an objective manner, whether proposed actions in the public space contribute to the aims as posed in traffic strategy and policy documents. This will enable evidence-based improvements for active mobility modes.