Conference Proceedings

Traffic Forecasting In Complex Urban Networks: Leveraging Big Data and Machine Learning

Florin Schimbinschi, Vinh Nguyen Xuan, James Bailey, Chris Leckie, Hai Vu, Rao Kotagiri, H Ho (ed.), BC Ooi (ed.), MJ Zaki (ed.), XH Hu (ed.), L Haas (ed.), V Kumar (ed.), S Rachuri (ed.), SP Yu (ed.), MHI Hsiao (ed.), J Li (ed.), F Luo (ed.), S Pyne (ed.), K Ogan (ed.)

PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON BIG DATA | IEEE | Published : 2015

Abstract

Accurate network-wide real time traffic forecasting is essential for next generation smart cities. In this context, we study a novel and complex traffic data set and explore the potential to apply big data and machine learning analysis. We evaluate several hypotheses and find that the availability of big data is able to facilitate more accurate predictions. Furthermore, we find that spatial aspects have more influence than temporal ones and that careful choice of thresholding parameters is crucial for high performance classification.