Urban Public Transport Digital Planning based on an Intelligent Transportation System

Abstract

there is presented an original concept of intelligent transportation system for public urban passenger transport advanced management, analysis and control. The proposed approach uses intelligent information technologies based on neural networks and methods of Big Data processing, allowing real time adaptation to dynamically changing conditions. Considering the up-to-date research results and technologies related to the transportation problem domain there is introduced a formal model that describes the public transport helping to reveal the main issues. Using the model there is presented a generalized route network planning algorithm. Description of the software implementation includes the specification of solution modules (components). The proposed solution is illustrated by an example of a transport model covering the territory of the Samara city district, Russia. The results of its probation and practical use prove the efficiency of the intelligent transportation system application for public urban passenger transport management.