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.
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References
Laney, D.: 3D Data Management: Controlling Data Volume, Velocity, and Variety. META Group Inc., Stamford (2001)
Quinn, E.: Discovering big data’s value with graph analytics. White Paper, Enterprise Strategy Group (2013)
Understanding big data: the seven V’s. http://dataconomy.com/seven-vs-big-data/
Podesta, J., Pritzer, P., Moniz, E.J., Holdren, J., Zients, J.: Big Data: Seizing Opportunities, Preserving Values. Executive Office of the President, Washington (2014)
A comprehensive list of big data statistics. http://wikibon.org/blog/big-data-statistics/
Daas, P., Loo, M.: Big data (and official statistics) (2013)
Browse traffic loop detectors by list (ONE-ITS). http://128.100.217.245/web/etr-407/trafficreports2
Waze mobile. https://www.waze.com/
Roadify. http://www.roadify.com/
Statista Inc.: Number of passenger cars and commercial vehicles in use worldwide from 2006 to 2013 (in millions). http://www.statista.com/statistics/281134/number-of-vehicles-in-use-worldwide/
Hitachi Data Systems: The Internet on Wheels. Technical report (2014)
Campbell, J.L.: SHRP2 naturalistic driving study: data collection is complete - now what? In: Northwest Transportation Conference (2014)
Data Management Group at UofT: Transportation Tomorrow Survey. http://dmg.utoronto.ca/transportation-tomorrow-survey/tts-introduction
Koulakezian, A., Abdelgawad, H., Tizghadam, A., Abdulhai, B., Leon-Garcia, A.: Robust network design for roadway networks unifying framework and application. IEEE ITS Mag. 7(2), 34–46 (2015)
Abdelgawad, H., Abdulhai, B., Wahba, M.: Multiobjective optimization for multimodal evacuation. J. Transp. Res. Rec. 2196, 21–33 (2010)
Kang, J.-M., Lin, T., Bannazadeh, H., Leon-Garcia, A.: Software-defined infrastructure and the SAVI testbed. In: 9th International Conference on Testbeds and Research Infrastructures for the Development of Networks & Communities (Tridentcom) (2014)
Koulakezian, A., Graydon, W. E., Abdelgawad, H., Chiu, Y.-C., Abdulhai, B., Leon-Garcia, A.: Speedup of DTA-based simulation of large metropolises for quasi real-time ITS applications. In: IEEE 18th International Conference on ITS (2015)
Aboudina, A., Abdulhai, B.: Win-win dynamic congestion pricing for congested urban areas. In: ITS Canada - ACGM (2012)
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Kamel, I.R., Abdelgawad, H., Abdulhai, B. (2016). Transportation Big Data Simulation Platform for the Greater Toronto Area (GTA). In: Leon-Garcia, A., et al. Smart City 360°. SmartCity 360 SmartCity 360 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 166. Springer, Cham. https://doi.org/10.1007/978-3-319-33681-7_37
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DOI: https://doi.org/10.1007/978-3-319-33681-7_37
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