Data-driven quality assessment of cycling networks

Abstract

Most planning guidelines for bicycle networks define a consistent set of qualitative criteria. All relevant destinations should be reached by bike in a safe, coherent (i.e., continuous bicycle facilities), direct (i.e., minimal detours), comfortable and attractive way. For transportation planners, few information exist on the degree to which these qualitative criteria are (still) fulfilled for already existing bicycle networks. However, these information are essential for the definition and prioritization of appropriate bicycle infrastructure measures under limited budget. Until now, no standardized methodology for the purely data-driven quantitative assessment of all of these five (and potentially more) qualitative bicycle network criteria exists. This paper develops a data-driven quality assessment methodology for bicycle networks. Based on an extensive literature review of existing guidelines, design manuals and literature on bicycle network planning, a comprehensible set of relevant qualitative criteria for bicycle networks including sub-criteria are defined in detail. For each sub-criterion, possible measurable indicators and data sources are identified as well. Indicators are translated into precise and transparent evaluation scales with a strong foundation. They are based on widely used guidelines and design manuals for bicycle traffic in European countries, especially the ones of pioneer countries for cycling such as the Netherlands. The work differentiates between local indicators of single bicycle facilities (edge-based, e.g., surface quality), route-wide indicators (e.g., travel time ratio) and network-wide indicators (e.g., network density) and integrates these into an overall framework. A methodology is developed that combines and weights several sub-criteria to consolidated scores for each criterion as well as one final overall score for bicycle network quality. Finally, the applicability of the approach is shown within a case study for the city of Munich, Germany. The key findings for Munich’s cycling network are as follows. The cycling network has a medium level of quality, indicating clear potential for improvement. The analysis of sub-criteria revealed that the city of Munich should focus primarily on expanding the main cycling network, on decreasing the number of conflict points and on decreasing the travel time of cyclists.