Research Article
Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA)
@INPROCEEDINGS{10.1007/978-3-319-33681-7_37, author={Islam Kamel and Hossam Abdelgawad and Baher Abdulhai}, title={Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA)}, proceedings={Smart City 360°. First EAI International Summit, Smart City 360°, Bratislava, Slovakia and Toronto, Canada, October 13-16, 2015. Revised Selected Papers}, proceedings_a={SMARTCITY360}, year={2016}, month={6}, keywords={Big data Smart city Traffic simulation Intelligent Transportation Systems Greater Toronto Area}, doi={10.1007/978-3-319-33681-7_37} }- Islam Kamel
Hossam Abdelgawad
Baher Abdulhai
Year: 2016
Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA)
SMARTCITY360
Springer
DOI: 10.1007/978-3-319-33681-7_37
Abstract
This paper presents how big data could be utilized in preparing for smart cities. Within this context, smart cities require intelligent decisions in real time, while processing large amount of data. One big component that relates to smart cities in ITS applications is using artificial intelligent techniques that rely heavily on simulation environments for the evaluation and testing of ITS strategies. In this paper, we present a model for the GTA transportation network. While the model enables big data transportation applications to run in real time, its building process implied intensive work with big data. Within this paper, we show the structure, the calibration, and the outputs of the model. Moreover, some applications, which use the proposed model, are presented. These big data applications are a step towards the smart city of Toronto. Finally, we conclude with some thoughts of future work and the next generation of big data models.
