DYNAMIC ROUTING IN URBAN TRANSPORT LOGISTICS UNDER LIMITED TRAFFIC INFORMATION

Abstract

A method for online dynamic routing of freight delivery under limited traffic information using an ant colony algorithm, has been proposed. This method leverages real-time IoT data on traffic flow (TF) intensity from traffic sensors on urban road network (URN) sections, combined with averaged historical data on TF parameters (speed, density, intensity) obtained from traffic sensors on representative sections of homogeneous clusters within the URN. The procedure for forming homogeneous clusters within the URN and identifying representative sections is described. The results of simulation studies using the URN of Kyiv as an example indicate the potential of this method for urban transport logistics in conditions of complex traffic.