International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 07 | Jul 2023
p-ISSN: 2395-0072
www.irjet.net
Traffic Management system using Deep Learning Khushi Gupta1, Trishul Shrivas2, Siddharth Sharma3, Uma Raj4 1,2,3UG Scholar, Electronics & Telecommunication Engineering Department, Shah and Anchor Kutchhi Engineering
College, Mumbai, Mumbai University, Maharashtra, India
4Assistant Professor, Electronics & Telecommunication Engineering Department, Shah and Anchor Kutchhi
Engineering College, Mumbai, Mumbai University, Maharashtra, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract – Traffic hazards are increasing, and road
extracting the background and automatically detecting the vanishing point [4].
accidents are occurring on a regular basis, resulting in massive loss of life, property. This problem affects many aspects as modern society including economic development, traffic accidents, increase in greenhouse gas emission, time spent and health issues. The purpose of this project is to address this effect using machine learning based traffic management system (TMS). The major reason behind the accidents is the over speeding of the vehicles. People tend to be in hurry to reach their work-place or any event and sometimes knowingly cross the speed limit of the vehicle to reach on time and this leads to accidents. So, vehicle speed detection is also implemented in the project using image processing algorithms and OpenCV.
1.1 Problem Statement To manage the traffic signal depending on the number of vehicles present so that unnecessary traffic can be reduced and will help people save time. To decrease accident cases by detecting the vehicles crossing the speed limit.
2. BLOCK DIAGRAM 2.1 Traffic Management Module
Key Words: Traffic management, vehicle detection, YOLO, speed detection, Alexnet
1.INTRODUCTION According to the requirements of large populations, government wants manage and develop the infrastructure in which smart / autonomous traffic management is key feature to smoothen the traffic [1]. How to manage the traffic automatically? Another situation is while in larger traffic how to cross the ambulance from that traffic. Considering such situations, the proposed traffic management system will dynamically change the signal based on traffic requirement [2]. This project uses some of the algorithms, datasets and mathematical calculations based on machine learning and python. The python programming language used can provide a platform to do some operations like object detection, image processing, and video processing etc. [3]. Vehicle speed is the most important risk factor for road accidents, injuries, severity, and fatalities. At any given time, half of drivers in urban areas exceed the speed limit. This causes accidents not only for the person speeding, but also for other people walking or driving nearby, endangering their lives [4]. The aim of this project is also to detect the speed of the vehicle which is the main cause of accidents. By extracting frames from the video and comparing the speed between two given points, it can be determined whether the vehicle is moving above the permissible limit or not. The system involves a traffic surveillance setup that can detect and track vehicles at night, along with a process for
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Fig -1: Block Diagram for Traffic Management
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