Dangų degradacijos modeliai ir jų taikymas Lietuvos automobilių keliams

Abstract

Planning road maintenance and development activities, prioritizing road construction, reconstruction and rehabilitation works, performing project economic evaluations, forecasting road operation expenditures and road user effect always requires prediction of pavement behaviour. For this purpose models of pavement deterioration are used. Commonly they are integrated in more sophisticated computational systems, known as Pavement Management systems (PMS) and Highway Development and Management systems (HDM). The implementation of these systems started in Lithuania shortly after the Re-establishment of the Independence. This was triggered by the violent drop in financing of the road sector, forcing to change obsolete road management strategy and planning approach. The need for project economic evaluations, transport modelling and long term pavement performance forecasts grew up after Lithuania joined the European Union and this brought the opportunity for financing road infrastructure projects from the EU funds. At present only on the Lithuanian state road network the total value of implemented projects, justified by evaluations and modelling with PMS, amounts to about 500 million Litas annually. Any Pavement Management System is just as good as the models within it, used for pavement deterioration prediction. The performed test calculations show that prediction models, currently used for this purpose in PMS we have in Lithuania, are of doubtful accuracy and have to be improved. The aim of the research is to introduce scientific methods and means of adaptation of pavement deterioration models to Lithuanian automobile roads, and perform the adaptation of the most important models, using the methodology suggested and the research data gathered. The dissertation describes the authors’ investigation on pavement deterioration models, their adaptation to the local conditions methods, possibilities of pavement deterioration prediction on Lithuanian state roads with bituminous pavements. Model adaptation involves two basic stages: - input data collection, processing and adaptation to the model; - calibration of the model outputs by adjusting the model parameters to enhance how well the forecast and model outputs represent the changes and influences over time and under particular local conditions. Model adaptation and adopted model evaluation were performed by incorporating theoretical, analytical and statistical-mathematical analysis methods.