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

Author:

Sachan Anuj1,Kumar Neetesh1

Affiliation:

1. Indian Institute of Technology-Roorkee, India

Abstract

Existing intersection management systems, in urban cities, lack in meeting the current requirements of self-configuration, 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 software-defined control interface that not only regularly monitors the traffic to prevent congestion for minimizing queue length and waiting time, it 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.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference43 articles.

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4. Simanta Barman and Michael W Levin. 2022. Performance Evaluation of Modified Cyclic Max-Pressure Controlled Intersections in Realistic Corridors. Transp. Res. Rec. (2022) 03611981211072807. Simanta Barman and Michael W Levin. 2022. Performance Evaluation of Modified Cyclic Max-Pressure Controlled Intersections in Realistic Corridors. Transp. Res. Rec. (2022) 03611981211072807.

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