Abstract
This article is built on the exploration of the possibilities of using Big Data, Machine Learning and the Internet of Things technologies for the needs of transport planning and modeling. The authors analyze the problems arising in the transport infrastructure because of the growing urbanization of cities and propose a solution to the problems based on the use of processing large amounts of data. As a result of the study, a comparative table was created showing the possible application of Big Data technologies in integration with other modern technologies and what problems of transport planning they will solve.
1. Introduction
In today’s world, we are facing rapidly growing urbanization resulting in increasing stress on transportation infrastructure. The population growth as well as increased quantity of vehicles brings us to the problems of air pollution, road accidents and traffic congestions (Zannat and Choudhury, 2019). Moreover, passengers demand decreased travel time, predictable schedule and tracking ability, which result in overall comfortability of public transport usage. At the same time, public transportation faces several challenges due to financial support, adequate economic efficiency and limited investments.
9. Conclusion
Analysis of Big Data technology in the transport sector made it possible to identify the main goals of a transport company that need to be achieved to improve its efficiency:
increased use of vehicles,
reducing the company's operating costs or the cost of fulfilling a transportation order,
reduced fuel consumption,
avoiding delays in the execution of orders for transportation.
