Title |
Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA) |
ID_Doc |
40478 |
Authors |
Kamel, IR; Abdelgawad, H; Abdulhai, B |
Title |
Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA) |
Year |
2016 |
Published |
|
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. |
Author Keywords |
Big data; Smart city; Traffic simulation; Intelligent Transportation Systems; Greater Toronto Area |
Index Keywords |
Index Keywords |
Document Type |
Other |
Open Access |
Open Access |
Source |
Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH) |
EID |
WOS:000393328700037 |
WoS Category |
Computer Science, Interdisciplinary Applications; Green & Sustainable Science & Technology; Transportation; Transportation Science & Technology; Urban Studies |
Research Area |
Computer Science; Science & Technology - Other Topics; Transportation; Urban Studies |
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