Integrating DBSCAN clustering and Dijkstra's algorithm for enhanced route planning: a case study of Oran, Algeria

This paper presents a novel approach to optimizing urban transport in Oran, Algeria, by addressing the issue of fragmented connectivity through the integration of clustering techniques with Dijkstra’s algorithm. The study begins with the collection and management of geo-referenced data for urban transport lines and bus stops. Using a customized DBSCAN clustering method, bus stops are grouped based on geographic and traffic data, simplifying the network for more efficient analysis. Dijkstra’s algorithm is then applied to calculate the shortest paths within the clustered network, optimizing routes and reducing travel times, which improves overall system efficiency. Additionally, a web-based application has been developed for Oran’s residents, with initial testing indicating promising usability for practical implementation. This integrated approach provides significant advancements in urban transport planning, offering valuable tools and insights for transport practitioners and decision-makers.