Decision support system for street-road network objects repair

Abstract

The article analyzes factors influencing managerial decisions adoption on repair of road network facilities (RN). Road repair is a challenge that must take into account a number of conflicting criteria. It is shown that decision-making process is a complex mental activity that consists in choosing the most effective strategy and, at present, repair work planning should be carried out using decision support systems (DSS), that is, a class of knowledge-based systems. DSS developing necessity for repair planning of RN has been substantiated. DSS architecture is described and it is shown that DSS allows increasing knowledge base by adding new knowledge without changing the structure, as well as encapsulating new knowledge into the system, increasing intellectual resource used in decision-making process. The parameters are determined, on the basis of which rules in DSS are formulated, which are necessary for making decisions on determining scope, timing, cost and sequence of repair and restoration work. Production rules examples are given. The general scheme of algorithm for planning repair and restoration works at RNF, as well as algorithm scheme for complex indicator calculating of transport and operational state-ensuring movement design speed dare described. Planning process formalized description and control actions development has been completed. It is shown that intelligent decision-making is an iterative, multi-level procedure, within which decisions table is analyzed to assess technical condition of RN facilities based on regulatory and technical documentation analysis. Situation description is consistently expanded by taking into account the quality of RN road marking, traffic intensity, road construction materials volumes, repair and restoration work cost, traffic management, seasonality and weather conditions, etc. (the number of taken into account parameters and levels of their description is not limited). The advantages of proposed approach to DSS implementation are described. It is shown that proposed DSS version provides situational adaptive intelligent control with ability to issue justified recommendations for carrying out repairs. The prospects for work development in this direction were considered and conclusion was made that management digitalization of repair activities, the digital transformation of management model and business processes in the field of RN repair will increase profits, increase operational efficiency, reduce repair costs and improve its quality.