An Optimized Graph Based Implementation for Efficient Journey Planning with Public Transport in Kathmandu Valley

Abstract

Kathmandu Valley’s public transport system, serving 28% of the population with only 3% of registered vehicles, lacks centralized route information, causing inefficiencies in commuting. This paper proposes an optimized graph-based journey planning system tailored for the valley’s semi-formal transit network. The system integrates multi-modal routing algorithms, optimizing routes based on travel time, cost, transfers, and walking distance. A combination of data collection methods, including user surveys and on-site validation, informs the route recommendations. Evaluation results show that the system reduces average journey time by 18%, with 73% of users discovering more efficient routes. The findings highlight the potential for data-driven optimization in urban mobility without major infrastructure changes, offering insights applicable to other developing cities.