Modeling and querying trajectories using Neo4j spatial and TimeTree for carpool matching

With the the exponential growth of location aware devices, analysis of human movements has been the subject of several studies. Problems related to urban mobility such as vehicle congestion are serious concern in cities. Carpooling is one of the solutions to soften congestion problem. This paper presents a novel matching method for carpooling. Trajectories are firstly modeled using Neo4j spatial and Neo4j TimeTree libraries. Then, temporal and locational filtering steps are operated. We extensively evaluate the efficiency and efficacy of the proposed system on Geolife trajectory dataset.