AI-Based Yolo V4 Intelligent Traffic Light Control System

Title

AI-Based Yolo V4 Intelligent Traffic Light Control System

Creator

Prathap B.R.; Kumar K.P.; Chowdary C.R.; Hussain J.

Description

With the growing number of city vehicles, traffic management is becoming a persistent challenge. Traffic bottlenecks cause significant disturbances in our everyday lives and raise stress levels, negatively impacting the environment by increasing carbon emissions. Due to the population increase, megacities are experiencing severe challenges and significant delays in their day-to-day activities related to transportation. An intelligent traffic management system is required to assess traffic density regularly and take appropriate action. Even though separate lanes are available for various vehicle types, wait times for commuters at traffic signal points are not reduced. The proposed methodology employs artificial intelligence to collect live images from signals to address this issue in the current system. This approach calculates traffic density, utilizing the image processing technique YOLOv4 for effective traffic congestion management. The YOLOv4 algorithm produces better accuracy in the detection of multiple vehicles. Intelligent monitoring technology uses a signal-switching algorithm at signal intersections to coordinate time distribution and alleviate traffic congestion, resulting in shorter vehicle waiting times. 2022 Boppuru Rudra Prathap et al., published by Sciendo.

Source

Journal of Automation, Mobile Robotics and Intelligent Systems, Vol-16, No. 4, pp. 53-61.

Date

2022-01-01

Publisher

Sciendo

Subject

artificial intelligence; intelligent monitoring; signal switching algorithm; Traffic jams; traffic light system; traffic management

Coverage

Prathap B.R., Department of Computer Science and Engineering, Christ University, Karnataka, Bangalore, 560074, India; Kumar K.P., Department of Computer Science and Engineering, Christ University, Karnataka, Bangalore, 560074, India; Chowdary C.R., Department of Computer Science and Engineering, Christ University, Karnataka, Bangalore, 560074, India; Hussain J., Department of Computer Science and Engineering, Christ University, Karnataka, Bangalore, 560074, India

Rights

All Open Access; Hybrid Gold Open Access

Relation

ISSN: 18978649

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.14313/jamris/4-2022/33

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176244517&doi=10.14313%2fjamris%2f4-2022%2f33&partnerID=40&md5=8f45c80533ae54fc5e66c176628c454f