No abstract

ABSTRACT

The Directive 2008/96/EC of the European Parliament and of the Council of 19 November 2008 on Road Infrastructure Safety Management requires that the Member States shall establish and implement the network safety ranking. Safety performance of existing roads should be increased by targeting investments to the highest accident concentration sections and (or) to the road sections or crossings with the highest accident reduction potential. Road network safety management is applied within the road network in operation covering the selection of traffic safety improvement measures in optimal locations, evaluation of the safety effects and implementing the measures. The article describes the method for selecting and prioritising road sections which have higher than the average accident saving potential in each road category. When selecting road sections for treatment, a potential reduction of accident costs shall be taken into consideration. Road sections in each category are studied and classified by the factors related to road safety, such as the number of accidents, traffic flow and road characteristics. The article describes how the procedure of the road network safety ranking and the ranking of high accident concentration sections is implemented in Lithuania and propose further steps.

Recently, concern for a rapid increase in heavy metal pollutants released by railway transport has been expressed. Most of pollutant emissions from combustion processes are related to fuel consumption in the internal combustion engines of traction rolling stock. The main pollutants released into the environment cover particulate matter, volatile non-methane organic compounds, sulphur dioxide and nitrogen oxides. In this way, it is likely that the biggest polluters of the environment are traction units with internal combustion engines. However, other types of pollution are possible, where polluters can be not only traction rolling stock with the internal combustion engines, but also electric locomotive. For example, when due to friction of metals and deterioration of rolling stock wheels, heavy metals such as aerosols are released into the atmosphere, soil, surface and ground water, etc. and severely pollute the railway environment. Along with an increase in the electrification of railways, local environmental pollution is likely to be increased in the future. High pollution by heavy metals can also occur near the track storing creosote-impregnated wooden railway sleepers. Having analysed railway transport intensity and in order to assess pollution level, the stations of three major cities of Lithuania (Vilnius, Kaunas and Klaipėda) were selected to investigate heavy metal pollutants (lead (Pb), cadmium (Cd), zinc (Zn)) acting as the most toxic and widespread elements. The highest concentrations of Pb (up to 50 mg/kg) were found at a distance of 5.0 m from railway sleepers in the upper (up to 10 cm) soil layer at Vilnius Railway Station. A comparison of the results of the investigated soil across the tested stations showed that Klaipėda Railway Station was the area most polluted with Cd. The highest concentrations of Cd (up to 1.5…1.8 mg/kg) were established at a varying distance of 5…10 m from the sleepers in the upper (up to 10 cm) soil layer of light loam. Among the investigated stations, the lowest pollution by heavy metals, including Zn, was found at Kaunas Railway Station where sandy loam dominated. A comparison of heavy metal pollutants deposited on the intact used and rotten wooden railway sleepers disclosed that the latter were more heavily contaminated with heavy metals and made from 8 to 13 mg/kg for Pb, from 0.3 to 1.2 mg/kg for Cd, from 13.8 to 66 mg/kg for Zn.

The thesis is written in Lithuanian and is available from the author upon request. Chapter 1 describes the analysis of road infrastructure safety management procedures and their implementation. Chapter 2 gives the overview of accident prediction models and the principles of their development. Chapter 3 presents the designed accident prediction algorithm for the roads of national significance of Lithuania, the developed mathematical accident prediction models for homogenous groups of roads and junctions, the implemented network safety ranking and the determined road sections with a potentially high accident concentration. Chapter 4 describes the testing and analysis of software intended for the implementation of accident prediction algorithm.