MODELING CITY TRAFFIC MANAGEMENT AND IDENTIFICATION OF COMPETITIVE ROUTES USING INTELLIGENT TRANSPORTATION SYSTEMS

Abstract

This article presents a conceptual approach to modelling city traffic management and identifying competitive routesusing intelligent transportation systems. It argues that modelling traffic in transport streams, considering the behaviour ofeach individual vehicle, yields the most reliable results for real-time modelling of specific intersections in city trafficmanagement. The proposed methodology for developing an algorithm to detect competitive routes allows users to choosethe optimum route. The method is based on the statistical relationship between route indicators and helps to accuratelycalculate the demand for the implementation and improvement of the transportation network with subsequent changes inits operation. Redistribution of traffic flows for the identification of competitive routes in transport corridors and the impactof random variable values on route indicators are discussed. It is proven that the probability of describing the distributionof intervals between vehicles entering the network is of utmost importance for describing processes in a transport corridor,with the exponential distribution being typically used for these purposes. The conclusion is made that the micro-levelmodel for calculating vehicle movement modes should meet the requirements necessary for solving the task of modelingcity traffic management and identifying competitive routes using ITS. Such conditions are characterized by significantfluctuations in vehicle movement modes, stops at regulated intersections and in traffic jams, lane and trajectory changes,which significantly affect the algorithm for finding a competitive route in the transport corridor.