This project analyzes the road network of Chapel Hill, NC to classify streets by their Level of Traffic Stress (LTS) for cyclists. Using R and ArcGIS Pro, the analysis identifies safer, low-stress routes and suggests strategic bike lane additions to improve cycling safety and accessibility.
The ultimate goal is to support safer cycling infrastructure, assist UNC’s Department of City and Regional Planning, and help reduce demand for the limited campus parking. 🎯
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Classified Chapel Hill road network by LTS using key factors such as:
- Lane count
- Number of intersections
- Traffic flow volume
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Created vector layers in ArcGIS Pro visualizing:
- Low-stress bike-friendly routes 🚲
- Recommended locations for new bike lanes 🛤️
- Promote cycling safety and encourage low-stress routes for all rider types
- Provide actionable bike lane recommendations to city planners
- Support UNC’s sustainability goals by reducing campus parking demand ♻️
- R: Data processing, LTS classification calculations, and data visualization 📊
- ArcGIS Pro: Geospatial mapping, vector layer creation, and spatial analysis 🗺️
- Load and preprocess road network data in R
- Perform LTS classification based on roadway and traffic characteristics
- Export classified data to GIS for mapping and visualization
- Use ArcGIS Pro to create bike lane recommendation layers and maps