V2I-VTL: IoT-Enabled adaptive traffic light controller and emission reduction at intersection

Abstract

Traffic congestion is a growing concern in urban centers worldwide, leading to significant delays, particularly for emergency vehicles such as fire trucks and ambulances. This not only increases emergency response time but also the risk of life and property loss. To address this issue, our research introduces a traffic control system that prioritizes emergency vehicle egress and mitigates intersection congestion. Other than validation through simulation, the system’s efficacy is further substantiated by real-world hardware implementation. The system employs an access point (AP) at intersections to receive location and direction data from approaching vehicles. Emergency vehicles are given precedence, while non- emergency vehicle data is used to adjust traffic light durations, thereby optimizing the traffic flow. The simulation results demonstrate the system’s reduced lane opening times and average waiting periods for emergency vehicles. Advancing from simulation to application, we have executed a real-world hardware validation at a high-traffic intersection. This phase entailed the precise installation and calibration of the necessary hardware components, transitioning from theoretical models to practical, operational technology. The hardware setup confirms the system’s practical viability and offers a more comprehensive assessment of its impact on traffic efficiency and emergency response times. This dual approach of simulation and hardware validation provides a thorough evaluation of the system’s capabilities, establishing a foundation for future traffic management solutions. Additionally, the implementation of the system leads to a notable reduction in CO2 emissions at intersections, contributing to environmental sustainability efforts.

Keywords

• CO2 emissions
• Emergency vehicle
• IoT
• Traffic light controller
• V-2-I communication