Spatiotemporal Urban Traffic Modelling Using Big Data

The goal of the project is enhancing of the methodological base of urban traffic flow analysis with responsive multivariate spatiotemporal models and algorithms of their parameter estimation for big data.

The key project objectives are:

• Applying modern multivariate models for traffic flow forecasting for testing their validity and identifying shortcomings
• Developing responsive models, which take potential unexpected changes of a road network into account in real-time
• Developing computational algorithms, which will allow estimating multivariate model parameters on the base of large data sets and adapting these estimates for dynamically obtained data