Smart Traffic Light Control System with Emergency Vehicle Detection and Boom Barriers Using Arduino

Urbanization and modernization have significantly increased traffic congestion, creating challenges for daily commuters and emergency services. The traditional traffic light system, which runs on a fixed timer, results in commuters often being stuck in unnecessary traffic, wasting time and fuel, while emergency services face delays costing crucial time in emergency situations. Additionally, intersection-related accidents account for 40% of all traffic incidents and nearly half of all serious injuries, with red-light running causing approximately 165,000 accidents annually, resulting in 700 to 800 fatalities. This study investigates the use of an Arduino-driven traffic control system to integrate real-time traffic density monitoring, emergency vehicles prioritization, and enforcement mechanisms such as boom barriers to enhance intersection safety and optimize traffic flow. The system demonstrated the ability to detect the density of vehicles in each lane of the road using ultrasonic sensors and prioritize emergency vehicles using sound sensors. These sensors provide data that serve as input to the Arduino which results in boom barriers to function accordingly. The prototype simulated traffic challenges at traffic intersections with approaching emergency vehicles. Results showed that a scaled prototype demonstrated reduced congestion, improved intersection safety, and enhanced emergency vehicle response times. This prototype system offers a cost-effective, scalable solution to modern urban traffic management challenges. Future work will focus on developing the prototype on a larger scale, addressing system maintenance challenges, and exploring its usage in diverse urban environments to further enhance safety and efficiency.

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Publication Details

Published
2025-04-20
DOI
https://doi.org/10.1109/sustech63138.2025.11025771
Citations
1
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
0.71

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article

Smart Traffic Light Control System with Emergency Vehicle Detection and Boom Barriers Using Arduino

Thitima Srivatanakul, Niwesh Koirala
1 citations
IoT and GPS-based Vehicle Safety Systems
0.71
article

Smart Traffic Light Control System with Emergency Vehicle Detection and Boom Barriers Using Arduino

Thitima Srivatanakul, Niwesh Koirala
article en
1 citations

Abstract

Urbanization and modernization have significantly increased traffic congestion, creating challenges for daily commuters and emergency services. The traditional traffic light system, which runs on a fixed timer, results in commuters often being stuck in unnecessary traffic, wasting time and fuel, while emergency services face delays costing crucial time in emergency situations. Additionally, intersection-related accidents account for 40% of all traffic incidents and nearly half of all serious injuries, with red-light running causing approximately 165,000 accidents annually, resulting in 700 to 800 fatalities. This study investigates the use of an Arduino-driven traffic control system to integrate real-time traffic density monitoring, emergency vehicles prioritization, and enforcement mechanisms such as boom barriers to enhance intersection safety and optimize traffic flow. The system demonstrated the ability to detect the density of vehicles in each lane of the road using ultrasonic sensors and prioritize emergency vehicles using sound sensors. These sensors provide data that serve as input to the Arduino which results in boom barriers to function accordingly. The prototype simulated traffic challenges at traffic intersections with approaching emergency vehicles. Results showed that a scaled prototype demonstrated reduced congestion, improved intersection safety, and enhanced emergency vehicle response times. This prototype system offers a cost-effective, scalable solution to modern urban traffic management challenges. Future work will focus on developing the prototype on a larger scale, addressing system maintenance challenges, and exploring its usage in diverse urban environments to further enhance safety and efficiency.

York College, City University of New York (US)
National Science Foundation
Sustainable cities and communities
Openalex Percentile: Top 31%
IoT and GPS-based Vehicle Safety Systems
0.71
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