Route Recommendation Using Community Detection Algorithm (Case: Kota Bandung)

Abstract

Bandung public transport route, known as Angkutan Kota (Angkot), has 39 routes to serve intra city transportation. These routes connect more than 40 bus stations in star topology. The centrality analysis of this routes shows that many of them are overlapped into each other in certain location, thus may potentially cause congestion and increased competition for passengers among routes. To achieve operational break event, most fleet tend to conduct activities that reduce its service quality and disturb traffic flow. Having public transport with inconsistent level of service leave passengers with no choice but to find another mode of transportation, including owning private vehicle, which lead public transportation into deeper vicious circle. Some effort to break this circle is to subsidised public transport fare, car restraint (such as 3 in 1 policy), and priority lane for public transport (such as bus way). This paper suggests another way to increase usability of public transport by implementing graph theory to generate new routing strategy. Instead of having path formed from node sequence, we propose nodes that grouped geographically, creating modular routes that cover certain area and can be managed independently. The graph or network is formed by using bus stops/stations as nodes and routes to connect the nodes. We apply Louvain's community detection algorithm to groups bus stops and stations into communities. By assuming that each community is a route coverage, we can define 14 Angkot routes. The proposed routes feature fewer routes and can significantly reduce overlapping between routes while still having similar performance with conventional route.