Analysis & Design of Traffic Signals at Mudal Titta Road Junction Used AI Technology

Abstract

Rapid urbanization and the continuous growth in vehicular population have led to increased traffic congestion, delays, and accidents at major intersections. Conventional traffic signal systems, which operate on fixed time intervals, often fail to adapt to dynamic traffic conditions, resulting in inefficient traffic management. This project presents the analysis and design of traffic signals at Mudal Titta Road Junction using Artificial Intelligence (AI) technology to improve traffic flow and reduce congestion. The study begins with a detailed traffic survey at the Mudal Titta junction, including vehicle count, peak hour analysis, and traffic flow patterns. Based on the collected data, existing signal timings and intersection performance are evaluated. The proposed system integrates AI techniques such as machine learning and real-time data processing to dynamically adjust signal timings according to traffic density on each approach road.

Introduction

The text discusses the growing traffic congestion problem caused by rapid urbanization and increased vehicle usage, especially at intersections, which are critical points in transportation networks. Traffic signals are used to manage vehicle movement and improve safety, but most traditional systems rely on fixed-time scheduling that does not adjust to real-time traffic conditions, making them less efficient in dynamic traffic environments.

It explains rotary intersections, where vehicles move around a central island in a circular flow to reduce conflicts and improve continuity of movement, especially when traffic volume is high.

The literature review highlights several approaches to improving intersection management, including pedestrian-friendly signal optimization, real-time adaptive signal control using sensors, actuated signal systems that perform better during off-peak hours, and multi-modal designs that accommodate vehicles, buses, and pedestrians more efficiently.

The project focuses on Mudal Titta Road Junction in Kolhapur, aiming to analyze current traffic conditions such as volume, delays, and congestion, and then design an AI-based adaptive traffic signal system. The objectives include studying existing traffic patterns, identifying issues, and improving safety and efficiency through simulation and optimization.

Methodologically, the design uses principles like Webster’s method to calculate optimal signal cycle time, considering factors such as green, red, and amber intervals, along with lost time during phase changes. Proper phase design is emphasized to separate conflicting traffic movements and reduce congestion.

Conclusion

The study on Analysis and Design of Traffic Signals at Mudal Titta Road Junction using AI Technology demonstrates the significant benefits of integrating intelligent systems into urban traffic management. Through detailed traffic data collection, analysis, and comparison of conventional and AI-based signal systems, it was observed that AI provides substantial improvements in traffic flow, reduces vehicle delays, and decreases queue lengths. Conventional fixed-time signals, while simple to implement, fail to adapt to real-time traffic variations, leading to congestion, longer waiting times, and increased fuel consumption.

References

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Copyright

Copyright © 2026 Prof. P. A. Desai, Sudesh Patil, Parth Halade, Suraj Koli, Chandana Supale. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.