The Role of Intelligent Transport Systems and Smart Technologies in Urban Traffic Management in Polish Smart Cities

Ewa Puzio (), Wojciech Drożdż and Maciej Kolon
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Ewa Puzio: Faculty of Economics, Finance and Management, Institute of Management, University of Szczecin, 71-004 Szczecin, Poland
Wojciech Drożdż: Research Center for Management of Energy Sector, Institute of Management, University of Szczecin, 71-004 Szczecin, Poland
Maciej Kolon: Independent Researcher, 71-004 Szczecin, Poland

Energies, 2025, vol. 18, issue 10, 1-26

Abstract: Today’s cities are facing the challenges of increasing traffic congestion, emissions, and the need to improve road safety. The solution to these problems is the use of artificial intelligence (AI) and the Internet of Things (IoT) in intelligent traffic management. The purpose of the article is to analyze and evaluate AI- and IoT-based solutions implemented in Polish cities and to identify innovative proposals that can improve traffic management. The study uses a mixed-method approach, including the analysis of crowdsourced mobility data (from GPS, smartphones, and municipal reports), GIS tools for mapping congestion, big data analytics, and machine learning algorithms, to evaluate trends and predict traffic scenarios. The evaluation focused on seven major Polish cities—Warsaw, Krakow, Wroclaw, Gdansk, Poznan, Katowice, and Lodz—where intelligent transportation systems such as dynamic traffic lights, intelligent pedestrian crossings, accident prediction systems, and parking space management have been implemented. The effectiveness of these solutions was assessed using the following six key indicators: waiting time at intersections, travel time, congestion level, CO 2 emissions, energy consumption, and number of traffic incidents. The article provides a comprehensive analysis of these solutions’ impacts on traffic flow, emissions, energy efficiency, and road safety. A key contribution of the paper is the presentation of new proposals for improvements, such as the inclusion of behavioral data in traffic modeling, integration with GPS navigation, and dynamic emergency and public transport priority management. The article also discusses further digitization and interoperability needs. The findings show that the implementation of intelligent transportation systems not only improves urban mobility and safety but also enhances environmental sustainability and residents’ quality of life.

Keywords: smart cities; intelligent traffic systems; urban mobility; AI in transport; traffic management; IoT (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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