International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
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Intelligent Traffic Light Control System Surya Vishnuvardhan Joka1, Taha Bhagat1, Krishnaram Bhavesh1, Prof. Mahesh A. Kamthe2 1Student, Dept. of Electronics and communication, MIT ADT University, Pune, Maharashtra, India
2Professor, Dept. of Electronics and communication, MIT ADT University, Pune, Maharashtra, India.
-----------------------------------------------------------------------------***---------------------------------------------------------------------------Research is also being done on using artificial intelligence ABSTRACT and machine learning algorithms to optimize traffic light Traffic congestion remains a pervasive challenge in many systems. These algorithms can analyze large amounts of data metropolitan areas worldwide, with severe impacts on road to identify patterns and make predictions about traffic flow, users' safety and the economy.[1] Despite changes in traffic enabling more efficient signal timing and reducing patterns, traditional traffic control systems, including traffic congestion. lights at intersections, have remained largely static for over 80 However, the current traffic signal system remains outdated, years. In response, we propose a new digital-logic based leading to inefficient time management at road intersections system, the Intelligent Traffic Light Control System (ITLCS), [2]. which promises to be more efficient and responsive to traffic conditions. The ITLCS system leverages a simple yet innovative The traditional traffic signals operate by assigning a fixed principle, whereby the signal remains green until the present fraction of time to each road, regardless of the flow density cars have passed. The algorithm captures a snapshot of the or the number of vehicles present. This results in inefficient traffic and analyzes the number of vehicles present in each traffic flow and does not distribute time based on traffic lane, enabling the system to adjust signal timings dynamically congestion. During certain periods of the day, some roads based on real-time traffic conditions. This approach reduces may have higher traffic volume than others, necessitating the average wait time for all vehicles and accounts for both more time to alleviate congestion. Unfortunately, the macroscopic and microscopic changes in traffic, ensuring traditional traffic signal system cannot cater to this need. optimal traffic flow and safety for all road users. The ITLCS model requires object detection, including data acquisition Therefore, there is an urgent need for a new traffic signal and training a deep learning model to identify different classes system that can detect the presence of vehicles at an of vehicles. By implementing the proposed ITLCS, we aim to intersection and directly close the signal once there are no address the pressing issue of traffic congestion and reduce the more vehicles present, thereby opening the next road and number of accidents, particularly those occurring at reducing unnecessary waiting. intersections. The ITLCS represents a significant improvement over traditional traffic control systems, and its adoption could The proposed model will be utilizing multiple cameras based have far-reaching benefits for metropolitan areas worldwide. on the number of cross-roads at an intersection, the cameras capture information in real-time and the information is Keywords processed through and object detection algorithm which helps classify the vehicles on the road as per the individual Intersection; YOLOv5; Object detection; Traffic; Data. time required by the vehicle for traversing the intersection.
1.
INTRODUCTION
The proposed model’s central purpose is to reduce the time complexity at an intersection to increase efficiency of traveltime and also make travel through congestion at intersections.
Traffic light systems are an essential part of urban transportation, and they play a crucial role in regulating the flow of vehicles and pedestrians on the roads. The current state of research in traffic light systems is focused on developing advanced technologies to optimize traffic flow, reduce congestion, and improve safety.
2.
The objective of this proposed model is to formulate a solution for the heavy congestion caused by time-based traffic signals at crossroads. The proposed solution involves a machine learning-based traffic signal that can create a congestion-free environment. The current time-based switch system often leaves many roads empty during unnecessary times while causing traffic congestion on roads with heavy traffic. The ML-based traffic signal will dynamically adjust the signal timings by analyzing real-time traffic data and
One of the most significant areas of research is the development of intelligent traffic management systems that use data from various sources, such as traffic sensors, cameras, and GPS devices, to dynamically adjust traffic signal timings in real-time. These systems can help reduce congestion by providing more efficient signal timing based on traffic patterns.
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