FORECASTING IMPACT OF TRANSPORT FLOWS ON THE INDUSTRIAL CITY ROAD NETWORK
Journal Title: Вчені записки Таврійського національного університету імені В. І. Вернадського. Серія: Технічні науки - Year 2018, Vol 29, Issue 1
Abstract
The purpose of this work is to develop of short-term forecasting method of traffic flow parameters within a road network taking into account an industrial city specific. The structural characteristics of industrial cities transport flows have been analysed in morning and evening peak traffic periods. Analyse of qualitative and quantitative indicators of transport clusters in the environment of the industrial cities road network has allowed to propose a hypothesis about occlusivity of transport clusters, both in the time and geographic location. The occlusivity can be characterized by the transport flow density indicator, and the occlusivity point is the maximum rolling stock units concentration level in the transport cluster that is investigated. The mathematical model of the road network of an industrial city is based on Euler’s graph. There is an ordered sequence of nodes and linear elements of Euler’s graph. And this graph describes the sustainable routes of traffic clusters in the road network. The most acceptable mathematical approach for the short-term forecast of transport clusters that form the traffic flow of an industrial city is the low-parametric representation of the transport clusters position at different times. This approach is based on the definition of the occlusivity point position of the transport clusters. The parameter estimation of an industrial city transport flows is realized in three ways by means of the least square method. The proposed mathematical relation specifies the transport cluster parameters transformation at specific points in the past into parameter values at current time points. Further implementation of this approach can be used to model the neural network for urban transport system managing.
Authors and Affiliations
А. О. Лямзін, І. В. Ніколаєнко
Keywords
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