Intelligent Transportation Systems, Prediction, Regression, SVR, ELM
Intelligent Transportation Systems are applications of information and communication technologies aimed at improving the transportation area. Providing information about bus arrival time on the bus stop is very important and useful to passengers and transit managers. This paper presents a proposed bus arrival time prediction system at the bus stop where user is located. For this, an experimental study on bus route named Campina do Barreto No. 722 in Recife-PE, was performed by comparing the regression model for Support Vector Machine (SVR) and the neural network Extreme Learning Machine (ELM) to estimate the time it takes to go through adjacent bus stops. The experiments were performed using the bus GPS log data in the metropolitan region of Recife, and the results showed that for this application the SVR significantly outperforms ELM.
Coquita, Kássio Ribeiro; Ristar, Arley Ramalho Rodrigues; de Oliveira, Adriano Lorena Inácio; and Tedesco, Patricia Cabral de Azevedo Restelli, "Prediction System of Bus Arrival Time Based on Historical Data Using Regression Models" (2015). Proceedings of the XI Brazilian Symposium on Information Systems (SBSI 2015). 84.