Bikeability and walkability: Quantitative assessment of infrastructure suitability for cycling and walking

Suggested by: Christian Werner, Martin Loidl

Short description: Transport infrastructure shapes the way we move. It enables mobility, but especially for cycling and walking, deficits regarding infrastructure quality cause safety risks and pose obstacles for increasing the modal share of sustainable modes. To overcome these issues, removing bottlenecks and improving infrastructure quality for active modes is crucial. For effectively and efficiently spending limited resources, quantification of infrastructure suitability for cycling and walking is needed. This enables systemic assessment and prioritization of measures. Various approaches for deriving safety and suitability indices from network data evolved during the past decades, originating from different domains. These developments give plenty of opportunities for further exploration, research and improvement. Such work can make use of the bikeability and walkability workflow developed at the Mobility Lab of University of Salzburg (NetAScore).

Research for this master thesis should address one or more of the following topics (but is not limited to):

• Assessing transferability and consistency of an existing bikeability / walkability index based on OpenStreetMap data. (transfer to different areas of interest, semantic consistency, data consistency)
• Validation of the existing bikeability index (NetAScore) using quantitative and qualitative surveys.
• Quantitative comparison of different bikeability and walkability metrics and conceptual assessment.
• Extension of bikeability and walkability to dynamic aspects such as season, weather or daylight
• Extension of bikeability and walkability to neighbourhood aspects: effect of neighbourhood characteristics such as socio-demographic structure and safety indicators on bikeability and walkability
• Individualized bikeability and walkability: Creation of a diverse set of cyclist and/or pedestrian profiles, taking into account different target groups and their individual weighting of indicators.

References, suggested reading:

• Loidl, M., & Zagel, B. (2014). Assessing Bicycle Safety in Multiple Networks with Different Data Models. GI-Forum, Salzburg, 144–154.
• Buehler, R., & Dill, J. (2016). Bikeway Networks: A Review of Effects on Cycling. Transport Reviews, 36(1), 9–27. https://doi.org/10.1080/01441647.2015.1069908
• https://github.com/plus-mobilitylab/netascore

Related to projects: several projects, depends on individual focus 

Start/finish: anytime

Prerequisites/qualifications: Interest in mobility research and planning. Depending on individual topic: Scripting, database, spatial analytics (network analysis) and geovisualization skills.
Depending on interest and availability, this master thesis project could be linked to a study assistent position.