Smart Traffic Light Control System Using Arduino Mega

Abstract

This article presents the \"Smart Traffic Light Control System using Arduino Mega\" design. These systems manage traffic flow at intersections, aiming for smooth vehicle movement. However, synchronizing multiple traffic lights at adjacent junctions is complex because of a number of variables. Conventional systems struggle with fluctuating traffic flows and lack consideration for emergencies, pedestrian crossings, and accidents. This often leads to congestion and traffic jams. The suggested method resolves these problems by integrating advanced control mechanisms to adjust traffic signals dynamically, enhancing overall traffic management efficiency and safety.

Introduction

I. INTRODUCTION

In many nations, traffic congestion is a serious problem, especially in places where there are dense populations like Gaza and India. Road accidents and congestion have become commonplace due to rising population and automotive usage, resulting in fatalities and financial losses. These intricate problems can no longer be solved by traditional traffic management techniques, which calls for the creation of more clever and effective solutions. Taking proactive steps is essential to effectively addressing traffic congestion. Predictive technologies such as navigation systems can help drivers bypass critical zones with high traffic density. Additionally, advanced traffic control systems can utilize various sensors and techniques to detect and manage traffic flow, thereby minimizing congestion and accidents. Using technology like Arduino boards, ultrasonic sensors, and traffic light modules, one creative method uses an algorithm for controlling traffic lights based on density. These systems dynamically modify the timing of traffic light sequence according to the quantity of vehicles on each lane of a route. Through traffic flow optimisation, these systems minimise travel times and congestion by giving priority to lanes with higher volume of traffic. Emergency vehicles face significant delays in traffic, jeopardizing lives. Emergency vehicles can be prioritised and detected by with the use of intelligent traffic signal systems, they can safely and swiftly navigate junctions. This not only speeds up emergency response times but also improves traffic control and safety in general. The deployment of smart traffic management systems is crucial for lowering environmental effects like carbon emissions likewise for enhancing urban mobility and productivity.

II. LITERATURE REVIEW

1. Using IOT technologies, David William and Priya designed a Traffic Control system. To efficiently control signal timing and manage vehicle density at intersections, their system utilizing Arduino UNO, IR sensors, and LEDs to effectively manage signal timing and regulate vehicle density at intersections.
2. Karthiga and Dharani proposed a Traffic Control system useful for emergency vehicles. Their system utilizes IR sensors to detect vehicle density prior to signaling, enabling Arduino to modify the time of the signal in accordance with the quantity of cars, while employing radio frequency transmitter and receiver for traffic clearance, detecting emergency vehicles and transitioning signal color from red to green, thereby aiding in traffic congestion avoidance and facilitating emergency vehicle passage
3. Ghazal, Chahine and Kherfan proposed a Smart Traffic light system. Their system utilizing a PIC microcontroller to assess traffic density via IR sensors, enabling dynamic timing slots with varying levels, alongside a portable controller device aimed at addressing the issue of emergency vehicles encountering congestion on overcrowded roads.
4. Liang Qi, Meng Chu Zhou, and Wenjing Luan designed a real-time emergency traffic system tailored for intersections dealing with accidents, aimed at advancing current practices in managing traffic accidents and enhancing intersection safety in real-time.

III. METHODOLOGY

This paper's main theme is to use smart traffic signal management systems to lessen both time and traffic congestion. Table 1 displays the hardware and software requirements for the proposed system.

Table.1: Hardware and Software Requirements

The mechanism for controlling traffic lights combines both manual and automatic operations to effectively manage traffic flow. In manual mode, traffic police utilize buttons in way to manage the traffic lights, ensuring smooth traffic regulation. In automatic mode, the system offers two distinct approaches: fixed time intervals and dynamic adjustments based on vehicle density. With fixed intervals, the switch for the traffic lights according to predetermined schedules. However, the dynamic mode employs ultrasonic sensors across all junctions to detect vehicle density, allowing for adaptive changes. Thus, locations with increased traffic volume receive extended green light times, easing congestion, and minimizing traffic jams. To further enhance efficiency, a Blynk app connectivity feature is incorporated, helping emergency vehicles. Authorized personnel can access the app to promptly switch traffic lights from red to green, ensuring swift the passage for emergency vehicles and potentially saving lives. Additionally, pedestrians are alerted to traffic light changes via a buzzer system, enhancing safety and awareness. Overall, this innovative system aims to alleviate traffic congestion, prioritize the smooth flow of both regular and emergency vehicles, and enhance pedestrian safety, ultimately contributing to a more efficient and secure urban environment. Incorporating both manual and automatic modes, the proposed traffic light system efficiently manages traffic flow, prioritizing safety and reducing congestion.

IV. RESULTS & DISCUSSION

This project results in controlling traffic lights based on vehicle density. It combines Arduino Mega, ultrasonic sensors, Wi-Fi module, traffic lights modules, and buttons to ensure strong access control. Also, it uses the Blynk IoT app for emergencies, allowing vehicles to reach their destination. Overall, the system offers dynamic, time-sensitive functionalities, enhancing convenience, accessibility, and operational efficiency under diverse conditions.

Conclusion

In conclusion, this project improved traffic signal control system intended to at swiftly clearing traffic jams, particularly to aid emergency vehicles, thereby reducing response time delays. Implementation of this system has the ability to save many lives by facilitating quicker access for emergency vehicles. Additionally, it contributes to traffic congestion, ensuring smoother passage for both emergency and regular vehicles towards their respective destinations. By minimizing traffic congestion and reducing waiting times at signals, this system optimizes overall travel time for people.

References

[1] R.S. Karthiga, J. Vanmathi, D. Dharani and Ms. S. Janaranjani. “Intelligent Traffic Control system using Arduino”, International Journal of Science and Engineering Research, Vol-9, Issue-3, 2018. [2] L. Jacioa, “Programming 16-bit microcontrollers in C. Learning to fly the PIC 24”, 1st Edition, Newnes Elsevier, 2007. [3] D. Smith, “PIC in Practice. A Project-based approach”, 2nd Edition, Newnes Elsevier, 2006. [4] David William Raj, N. Ranjani Priya, D. Nandika. “Intelligent Traffic control system using Arduino”, International Research Journal of Engineering and Technology (IRJET), Vol-8, 2021. [5] Bilal Ghazal, Khaled Chahine and Mohamad Kherfan. “Smart Traffic Light Control System”, IEEE, 2016, ISBN: 978-1-4673-6942.

Copyright

Copyright © 2024 Mrs. N. Prameela, Ch. Srujana Sri, G. Kedarnath, P. Sairam Venkat. 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.