SDN-enabled Quantized LQR for Smart Traffic Light Controller to Optimize Congestion

Existing intersection management systems, in urban cities, lack in meeting the current requirements of selfconfiguration, lightweight computing, and software-defined control, which are necessarily required for congested road-lane networks. To satisfy these requirements, this work proposes effective, scalable, multi-input and multi-output, and congestion prevention-enabled intersection management system utilizing a softwaredefined control interface that not only regularly monitors the traffic to prevent congestion for minimizing queue length and waiting time but also offers a computationally efficient solution in real-time. For effective intersection management, a modified linear-quadratic regulator, i.e., Quantized Linear Quadratic Regulator (QLQR), is designed along with Software-defined Networking (SDN)-enabled control interface to maximize throughput and vehicles speed and minimize queue length and waiting time at the intersection. Experimental results prove that the proposed SDN-QLQR improves the comparative performance in the interval of 24.94%-49.07%, 35.78%-68.86%, 36.67%-59.08%, and 29.94%-57.87% for various performance metrics, i.e., average queue length, average waiting time, throughput, and average speed, respectively.