Considering that sustainable urban mobility consists one of the key challenges facing urban centers internationally, the aim of this Ph.D. is to provide integrated support of new sustainable and environmentally friendly forms of urban mobility, using and analyzing big data. Emphasis will be placed on combined transport, shared transport services, focusing on active modes of transport such as walking, cycling, electric bicycles, etc. and Public Transport. For this purpose, high resolution data will be collected from a number of modern applications such as smartphones sensors, telematics applications, urban traffic management centers, etc. Advanced machine learning and artificial intelligence algorithms will be developed to utilize the collected data while innovative statistical models will be created. In this way, conclusions will arise for the optimization of economic feasibility and the environmental footprint of contemporaneous transport modes.
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