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Evolution of Traffic Signal Control Systems: From Webster’s Fixed-Time Model to AI-Driven Intelligent Intersections — A Comprehensive Review

Sajid Mohammed1, Geethu Ganesh2, Abhishek Mohan M K3, Mohammed Yousaf N4 and Anisha S5
1Department of Civil Engineering, RIET
2Department of Civil Engineering, RIET
3Department of Civil Engineering, RIET
4Department of Civil Engineering, RIET
5Department of Civil Engineering, RIET

Abstract - This document expressions the mandatory format and appearance of a essay prepared for ISJEM ejournals. The abstract should consist of a solo paragraph containing no more than 200 words. It should be a summary of the paper and not an starter. Because the immaterial may be used in abstracting and indexing databases, it should be self-sufficient (i.e., no numericalreferences) and essential in nature, presenting concisely the intentions, organisation used, results found, and their connotation. A list of up to six keywords ought to immediately follow, with the keywords disconnected by commas and culmination with a period. Traffic signal control systems have evolved significantly over the past several from fixed-time mathematical models to advanced intelligent systems capable of real-time adaptation. This review examines the progression of signal control strategies, beginning with classical deterministic approaches such as Webster’s optimization model, followed by actuated and adaptive control systems, and culminating in modern artificial intelligence (AI)-based methods. The study analyzes the principles, operational frameworks, and performance outcomes of each stage, with emphasis on key indicators including delay reduction, queue management, fuel efficiency, and emission control. Recent developments in machine learning and reinforcement learning are highlighted for their ability to enable predictive and data driven decision-making at intersections. The review also discusses practical challenges related to infrastructure, data requirements, and system integration, particularly in the context of connected and autonomous vehicles. Overall, the findings demonstrate a clear shift from reactive timing mechanisms to intelligent, self-optimizing systems that enhance traffic efficiency and contribute to sustainable urban mobility.

Key Words: Traffic signal control, Webster’s model, adaptive systems, artificial intelligence, intelligent transportation systems, smart cities. decades, transitioning