Abstract
The current study is devoted to the development and of intelligent transport systems solving problems of monitoring the current state of traffic flows, predicting the dynamics of state changes, processing and implementing optimal control actions according to specified criteria. The paper describes methods to fix the current state of traffic flow, information flows with data on the state and control effects, and methods for pre-processing data for their placement in specialized storage facilities. Data accumulated in this way are used to control traffic flows. The automated traffic flow control algorithm used in intelligent transport systems is also proposed. The algorithm is implemented as a solution of the optimization problem on the transportation network graph. The algorithm is based on sequential recurrent calculations allowing to redistribute capacity from underloaded to overloaded sections. The paper provides an example of a transportation network represented as a graph and modeled traffic flows on it. Found control actions are given. Applying this algorithm allows the reducing the number of congested sections.
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