Bus Route Optimization based on Demand obtained by GNSS Positioning Data

Abstract

Urban growing from the perspective of territory and population became one of the main world’s concerns of this century. Due to this phenomenon, public transportation management agencies seek to provide a high level of service based on an optimized transportation network systems. Understanding the demand level is an important task in this process. Thus, the proposed method aims to define automatically the variation of bus passengers demand using GNSS (Global Navigation Satellite System) positioning data provided by an Internet of Things (IoT) platform. In addition, this work aims to identify variations on passenger volume through density maps and optimize public transport service routes. The University of Campinas was set as the study area. Experiments were performed from one of the routes of the university transportation system. The results were satisfactory, as they showed a reduction of 1.43 km in distance compared to the original route, which represents an initial cost expense reduction of 18% to the annual transportation service contract. Therefore, the method presents itself as a feasible alternative for obtaining fundamental data for routing tasks for campus bus lines, and it can be replicated for the other routes of the university's public transport system.