JUCS - Journal of Universal Computer Science 25(8): 946-966, doi: 10.3217/jucs-025-08-0946

Planning of Urban Public Transportation Networks in a Smart City

Jonathan Frez^‡, Nelson Baloian^§, José A. Pino^§, Gustavo Zurita, Franco Basso^‡

‡ Universidad Diego Portales, Santiago, Chile§ Universidad de Chile, Santiago, Chile

Corresponding author: Jonathan Frez ( jonathan.frez@mail.udp.cl )

This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.

Citation: Frez J, Baloian N, Pino JA, Zurita G, Basso F (2019) Planning of Urban Public Transportation Networks in a Smart City. JUCS - Journal of Universal Computer Science 25(8): 946-966. https://doi.org/10.3217/jucs-025-08-0946

Abstract

Planning efficient public transport is a key issue in modern cities. When planning a route for a bus or a line for a tram or subway, it is necessary to consider people's demand for this service. In this work we present a method to use existing crowdsourced data (like Waze and OpenStreetMap) and cloud services (like Google Maps) to support a transportation network decision making process. The method is based on the Dempster-Shafer Theory to model transportation demand. It uses data from Waze to provide a congestion probability and data from OpenStreetMap to provide information about location of facilities such as shops, in order to predict where people may need to start or end their trips using public transportation vehicles. The paper also presents an example using this method with real data. The example shows an analysis of the current availability of public transportation stops in order to discover its weak points.

Keywords

Dempster-Shafer theory, transportation networks, smart cities, Origin-Destination planning problem