Macroscopic GA-based Multi-Objective Traffic Light Optimization prioritizing tramways

Urban traffic congestion significantly impacts city efficiency, environmental quality, public safety, and overall quality of life. The primary objective of this research has been to develop traffic light optimization strategies to reduce congestion in areas where tramways or high-speed buses need priority. To this end, a novel approach is presented in this paper as a Genetic Algorithm-based Multi-Objective Traffic Light Optimization (MaMoTLO). It takes into account multiple factors such as minimizing stops, reducing travel and waiting times (private and public), and ensures the synchronizations. This approach is particularly useful in urban areas where multiple tramways intersect with regular traffic, creating potential bottlenecks for private flows. The main innovative aspects are the insertion of structural constraints on flow and queues are junctions, the insertion of penalty constraint for the tramways passage, the capability of working at macroscale of the solution, the validation against real conditions, and the comparison with a large set of solutions. The work presented compares the new optimization strategies with existing state-of-the-art methods, including those based on Non-Dominated Sorting Genetic Algorithm II (NSGA-II/III), Simulation of Urban MObility) (SUMO) Actuated solutions, and Webster’s formula for traffic light timing. The proposed solutions have been tested using real traffic data from Florence, Italy, and simulated scenarios to measure their effectiveness in reducing congestion and improving traffic flow on Snap4City open platform. The findings indicate that selected MaMoTLO solutions substantially outperform stateof-the-art methods by providing more balanced and efficient traffic light solutions (presenting improvement of 10 % or higher in real conditions), which is crucial for urban areas with high tramway traffic. The proposed optimization improves the flow of vehicular traffic and ensures that public transportation systems like tramways operate smoothly without unnecessary delays. The research has been developed for the CN MOST, national center on sustainable mobility in Italy.