Enhancing Connectivity via GIS-Based Bike-Sharing Optimization in Kigali City, Rwanda

Promoting sustainable mobility and understanding travel demand are critical for rapidly growing cities like Kigali. This research aims to address limitations of traditional transport models by integrating geospatial analysis to support multimodal planning and optimize bike-sharing infrastructure. The study combines the Four-Step Transport Model with Geographic Information Systems (GIS) to enhance spatial disaggregation and identify optimal bike-sharing station locations. It incorporates shortest-path analysis and accounts for topography, road networks, population density, and land use. A household survey of 1377 residents was conducted to validate the model output. High trip generation zones were found in Nyamirambo and Kinyinya, while Nyarugenge, Remera, and Kimironko emerged as strong trip attraction areas. Congestion hotspots were identified at the Muhima, Remera, and Nyabugogo intersections. GIS analysis revealed high biking potential in Kinyinya, Kimironko, and Gatsata, aligning with survey responses. The study proposes 187 new bike-sharing stations in high-priority congestion zones and integrates 19 existing stations to strengthen multimodal connectivity, along with a first and last mile solution. Additionally, 15 key employment and service zones covering 67 km were identified to support efficient travel routes. By reducing the need for petrol-engine vehicle rebalancing, the optimized bike-sharing network supports environmental sustainability in the city. The integration of GIS and transport modeling offers a scalable, evidence-based framework for active mobility planning in Kigali and other Sub-Saharan cities in similar conditions to Kigali city in Rwanda.