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.
Authors
- Thitima Srivatanakul
- Niwesh Koirala (ORCID: https://orcid.org/0000-0003-4148-9650)
Institutions
- York College, City University of New York (US)
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
Funders
- National Science Foundation