The Impact of Intelligent Transport Systems on Safety, Emissions Reduction, and Travel Time: A Review

Abstract

The intensive development of road transportation and the increasing number of vehicles have led to significant challenges related to road safety, traffic congestion, travel time, energy consumption, and negative environmental impacts. In this context, intelligent transport systems (ITS) represent a significant approach to improving the efficiency and sustainability of modern transportation systems. The aim of this paper is to present and systematize the application of modern ITS technologies for improving road safety, reducing emissions, and shortening travel time. Based on an analysis of the relevant literature, the fundamental components and architecture of ITS are presented, including sensor systems, V2X communication, IoT, cloud and edge computing, as well as the application of artificial intelligence in traffic data processing and prediction. The analyzed studies demonstrate that ITS enables dynamic traffic flow management, route optimization, reduction in congestion and emissions, and more efficient responses to emergency situations. Particular attention is devoted to the possibility of simultaneously considering travel time, energy consumption, emissions, noise, and road safety. As a synthesis of the analyzed findings, an integrated algorithm for intelligent traffic management is proposed, operating as a closed feedback loop encompassing data collection, state assessment, prediction, optimization, and control. Future ITS development is expected to focus on the integration of AI, IoT, 6G, and edge computing technologies and their validation using real-world traffic data.