Intelligent Management System of the Automobile Road’s Technical and Operational Condition in the Cryolithozone

Abstract

A functional scheme of technical and operational condition (TOC) management of the automobile road located on permafrost soil is offered. An intelligent information system is used to collect information about current state of the automobile road, weather and climatic conditions, characteristics of traffic flows. It is shown that regulatory TOC’s maintenance is based on two management processes. The first process of current management is fast and low-inertia and is based on the current state of the management object. The second process of long-term management, due to the influence of the climate change, is much slower and has a high inertia; to ensure required management quality, it is necessary to carry out this process on the basis of the object’s state forecasting and to produce management actions (stabilization of the soil temperature regime) in advance, before the appearance of visible automobile road’s TOC deterioration. Predicting the condition is based on simulation modelling, which results in determining the expected settlement of thawing soil at the formation, which causes roadway’s numerous defects. The results of numerical simulation of the predicted state of the automobile road in the climatic conditions of Yakutsk and Urengoy are shown, including the case with applying measures to stabilize the soil temperature regime (use of seasonal cooling devices – SCD). It is shown that the dynamics of changes in the state of the object occurring under the influence of the climate change is described by only two path functions in the state space – without the use of SCD and in their presence. Perspective management of the object’s state resides in choosing the path function (corresponding to a certain structural characteristics of SCD) and determining the most rational time of transition to this path function. At a low intensity of climatic changes in the territory of the automobile road location, the simulation results’ sensitivity to the accuracy of the climatic parameters’ forecast increases.