SDN-enabled Quantized LQR for smart traffic light controller to optimize congestion

Abstract

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.