Forecasting bicycle traffic volume by origin and destination analysis with GIS and python scripting

Abstract

As a sustainable transportation for future cities, the non-motorized mode is considered to be the most ecological. It is also sustainable considering other aspects – human health, energy savings, positive influence on urban renewal, etc. While the benefits of increased pedestrian and bicycle mobility are obvious, there are number of unresolved issues arising in planning and providing the infrastructure for walking and cycling. The most important problem is forecasting the use of specific pathways in order to calculate the pay-back terms of investments. Existing cost-benefit analysis methods are not selfevident, they are not suitable for micro-level and therefore often are not welcomed by stakeholders. Proposed method uses GIS and Python scripting, it does not require highend software, therefore it is affordable for many potential users.