Nontraditional regression models in transport modelling

The goal of the project is to develop non-traditional regression models, namely the Markov-modulated regression for analysis and forecasting of traffic flows and adjacent transport tasks in transport modelling and find algorithms for their parameter estimation for big data.

The main objectives of the project are:

• Estimation of the Markov-modulated linear regression parameters and forecasting of traffic flows on real data, taking into account the influence of the "external environment"
• Development of the Markov-modulated linear regression model (multivariate regression, the case of a sample with missing data)
• Development of algorithms for estimating Markov-modulated regression parameters on the basis of big data