Big Data Analytics & Visualisation

Big Data Analytics & Visualisation


Transportation data can be collected in real time from various types of sensors, e.g. fixed loop detectors, video sensors and automatic vehicle location (AVL) mobile sensors, which are in abundance in taxi and transit fleets.

To obtain precise traffic measurements and state estimations, various methodologies have been exploited, e.g. (Extended, Unscented) Kalman filter from estimation theory and classification and clustering methods from data mining field.

Recently, the emergence and steady increase of public deployment of user-based data collection systems, e.g. GPS-equipped vehicles and vehicle re-identification using cell phones or wireless magnetic sensors, provide a great potential for probe vehicles in ITS applications.

The focus is on automated traffic state estimation and prediction, and decision support systems based on probe vehicle data. Moreover, utilizing the abundant traveller data (crowdsourcing) could shed light to humans’ mobility dynamics in metropolitan areas.

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