Térinformatikai módszerek alkalmazása a budapesti forgalomirányítási rendszerben

Abstract

This study presents a comprehensive GIS-based methodology for addressing key spatial data challenges in urban traffic management in Budapest. The research focuses on analysing the spatial heterogeneity of traffic detector networks, developing network-based methods for imputing missing data, and integrating meteorological information into traffic models. Network-analytic techniques and topological data propagation enable more accurate estimation of traffic patterns, while multitemporal data processing reveals the temporal dynamics of urban mobility. The practical relevance of the proposed methodology is demonstrated through the analysis of the Google–BKK harmonised traffic signal control system, where incorporating spatial relationships significantly improved traffic forecasting accuracy. Our findings highlight that advanced GIS approaches are essential for effective urban traffic management, providing robust tools for handling spatial data gaps, modelling traffic flows, and supporting real-time operational decision-making. The presented framework is adaptable to other metropolitan environments, Our results demonstrate that advanced geospatial tools play a key role in modern urban traffic management.”