###### Abstract  
Traffic congestion in urban areas presents significant challenges to mobility, road safety, and the overall quality of the urban traffic network. This study presents a simulation-based modeling framework for dynamic lane assignment (DLA) systems designed to optimize traffic flow on Vukovar Street in Zagreb, Croatia, which is an urban corridor where the existing infrastructure fails to meet capacity demands during peak morning and afternoon hours. Using real-time traffic data and the PTV VISSIM environment, an adaptive DLA model responsive to current traffic conditions was developed and evaluated. The proposed model improves traffic flow efficiency with minimal physical infrastructure changes, focusing on maximizing capacity within existing corridor constraints. The results of this research indicate that the proposed model reduces average vehicle delay by 21.4% and shortens queue lengths by 19%. The effectiveness of the DLA approach is evaluated through comparative analysis with traditional static traffic configurations, demonstrating significant improvements in traffic efficiency, reduced travel times, and enhanced network performance. While this study is limited to a simulation environment, it provides a strong foundation for future real-world applications and offers a practical approach to improving traffic network efficiency. Article  
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and noise levels [2; 3]. Also, the research in [4] suggests that congestion may reduce urban productivity significantly, with cumulative economic impacts seen globally. The traditional approach with \"static\" and non-responsive infrastructure is insufficient to meet the stochastic nature of modern urban traffic flows. Traffic management authorities explore adaptive and intelligent control systems that can respond to real-time traffic [5]. These systems and services are typically implemented in corridors where physical infrastructure expansion is limited and where the real-time control of traffic capacity variations can maximize the quality of the traffic network. Adaptive signal control, variable lane usage, and the integration of other Intelligent Transport Systems (ITS) services are being applied in urban areas, supporting both efficiency and sustainability goals. The following chapter provides a detailed review of these approaches, including international examples of their effectiveness. Within the framework of the ITS concept, dynamic lane assignment (DLA) was introduced for its potential to reallocate traffic infrastructure in response to demand variations. DLA is defined as the dynamic redefinition of lane directions based on real-time data, enabling flexible responses to directional traffic demands [6; 7; 8; 9]. Specific lanes can be reassigned during peak periods to match the dominant flow, while during off-peak periods, lane usage is returned to balanced (original) configurations. Unlike fixed systems, DLA responds to ongoing changes and can be integrated with other ITS services, contributing to an increase in traffic network quality in high-demand, spatially limited urban areas [10; 11]. Recent studies have demonstrated the value of DLA in improving traffic efficiency and reducing congestion, especially at signalized intersections and corridors with time-dependent directional flows [12; 13]. Also, adaptive control strategies combined with machine learning models and algorithms show good potential for further refining DLA performance by combining historical and real-time traffic data [14]. The authors in [15] developed a Roadrunner framework that integrates DLA with autonomous intersection control, showing an increase of over 11% in intersection capacity and reduced travel delay (under high traffic volume of over 6376 CAVs/h) by 5%.