Promoting active mobility: Evidence-based decision-making using statistical models

摘要

Shifting traffic to active transport modes (eg. walking/cycling) poses one of the most promising ways of tackling the persisting challenges that arise from motorized traffic. However, planning and policy making in walking and cycling domains is frequently impeded by a small-scaled and heterogeneous political landscape that rarely acts based on evidence thus limiting cost-effectiveness and target achievement. This paper proposes a largely data-driven planning approach that builds upon aggregated statistical models explaining walling and cycling modal shares. In addition to investigating a comprehensive set of influencing factors in relevant fields such as environment, climate, infrastructure or demographics, we bring attention to the role of political and administrative commitment in aggregated modal share modeling. Results suggest that our holistic approach is feasible both methodologically and in terms of its applicability in planning practice. As a first step towards evidence-based decision making the incremental effects of individual planning measures can be simulated and thus be used to rank options according to their effectiveness. Another outcome lies in the data-driven identification of spatial target areas for specific agenda setting in terms of awareness, mobility behavior, infrastructure, settlement structure and other planning-relevant domains.