Analysis of the Potential Use of Unmanned Aerial Vehicles and Image Processing Methods to Support Road and Parking Space Management in Urban Transport

Artur Kujawski () and Mariusz Nürnberg
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Artur Kujawski: Faculty of Engineering and Economics of Transport, Maritime University of Szczecin, Wały Chrobrego 1-2, 70-500 Szczecin, Poland
Mariusz Nürnberg: Faculty of Engineering and Economics of Transport, Maritime University of Szczecin, Wały Chrobrego 1-2, 70-500 Szczecin, Poland

Sustainability, 2023, vol. 15, issue 4, 1-14

Abstract: Progressive urban density affects city centers especially and results in growing congestion, lack of parking spaces, and increasing environmental costs of transportation, causing increased air pollutant emissions and noise. These phenomena reduce the attractiveness of the city and result in a degradation of the quality of life for its residents. In light of these phenomena, there is a clear need for intelligent management of urban space using new technologies that would be complementary to existing intelligent transportation systems. Expanding information resources obtained from mobile cameras will have a positive impact on increasing the efficiency of transportation management and use of limited space in city centers. It will also have an impact on reducing external transport costs and increasing the quality of logistics services provided in the city. The main aim of the paper is to develop a concept of a transport management system in cities using mobile vision systems mounted on unmanned aerial vehicles. The model will concern the cases of lane occupation by freight vehicles and the analysis of parking spaces in the city in order to improve their management. The results of the developed model will contribute to the automation of the parking space management process and increase the efficiency of the use of city parking space resources.

Keywords: city logistics; transport management; intelligent transportation system; unmanned aerial vehicle; urban space; image processing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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