Implementation of two postdoc scientific projects started at Transport and Telecommunication Institute on the 1st of October. The projects are supported by the European Regional Development Fund (ERDF), within the activity 188.8.131.52 Post-doctoral Research Aid.
Project “Spatiotemporal urban traffic modelling using big data” (184.108.40.206/VIAA/1/16/112)
Postdoc: Dr.sc.ing. Dmitry Pavlyuk
The goal 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
Project “Nontraditional regression models in transport modelling” (220.127.116.11/VIAA/1/16/075)
Postdoc: Dr.sc.ing. Nadezda Spiridovska
The goal of the project is to develop nontraditional 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
Both projects are devoted to development of scientific and innovative capacity of Latvian institutions and match objectives of TSI Research Programme 2015-2020.