Spatial optimization of bus stop locations using gis and an integrated accessibility index in addis ababa Ethiopia

Efficient and accessible public transportation is critical for sustainable urban mobility in rapidly growing cities like Addis Ababa. This study evaluates and optimizes bus stop locations along a major transit corridor (Route 27) by integrating passenger satisfaction surveys with a Geographic Information Systems (GIS) analytical framework. Data from 161 passengers revealed significant dissatisfaction, with over half feeling unsafe at stops, 83% reporting inadequate disability access, and 42% dissatisfied with walking distances. Spacing analysis showed that over 40% of stops exceeded the 800-meter standard, creating service gaps. Spatial analysis was conducted by calculating a Combined Accessibility Index (CAI) for each stop based on road density, population served, and trip generation within a 400-meter walking buffer. Regression modeling confirmed that population served is the strongest positive predictor of accessibility. Stops were then categorized as Excellent, Good, Moderate, or Poor based on their CAI. Using the CAI alongside mandated spacing standards (500–800 m), an optimization model was developed. For the inbound direction, the proposal is to retain 5 stops, relocate 11, add 2 new stops, and eliminate 3. For the outbound direction, the proposal is to retain 10 stops, relocate 5, add 5 new stops, and eliminate 3. This restructuring aims to correct spatial inequities, improve coverage in underserved areas, and consolidate redundant stops. The study provides a replicable, data-driven methodology for transit authorities to enhance system efficiency, equity, and passenger experience in data-scarce urban environments.