SMART TRAFFIC CONGESTION CONTROL
Date
2020
Authors
THAHER, MAY
AHMAD, JAMILA
HASSAN, RAWAN
SUWAN, NOUR
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
SMART TRAFFIC CONGESTION CONTROL
It is clear that transportation has a major impact on human life throughout history. All aspects of
life either political, economic, etc. depend on transportation in one way or another. The main
problems of the transportation system have been solved over time with the application of new
inventions and using advanced technologies. Innovation continues now and concern is to
increase the transportation efficiency of system facilities.
Traffic congestion is one of the biggest problems facing cities around the world, and perhaps the
most important factors that led to it are the large increase in the number of people, the lack of
good infrastructure and poor coordination between traffic lights. Among the problems facing us
in Palestine is the presence of the Israeli occupation, which works to hinder the development and
prevent drilling in many areas of infrastructure development, in addition to the lack of advanced
radio communication networks such as the fifth generation.
Traffic management can play a role in reducing traffic congestion, improving safety, and
reducing gases produced by cars. It also reduces human control of the vehicle.
To solve this problem, we used several methods to detect and count cars.
1. Solve traffic congestion by image processing
This method is used to track vehicles, counting, the average speed of each vehicle,
analysis of traffic targets and vehicle classification. Parameters can provide us with
complete information about traffic flow, which meets the requirements of traffic
management theory, and image tracking for moving vehicles can provide us with a
description Quantification of Traffic Flow .
2. A Computer Vision Based Vehicle Detection and Counting System in
MATLAB
The proposed method uses the background subtraction technique to find the forward
compounds in the video sequence. In order to detect moving vehicles with high accuracy
and explained.
First, the background subtraction technique is used to find the image of the objects in the
foreground. Second, the area of interest in the image is manipulated with several
techniques, including adaptive morphological processes, to remove noise and improve
foreground objects. Then, the center point is calculated for each object in the front and
used to represent the vehicle's position. A dividing line separates the right from the left so
that each portion is counted. Finally, vehicles are recorded and counted
3. Solve traffic congestion by Video processing in Python
using video processing process some things can be controlled and the video analyzed
motions. Video processing includes pre-filters, which can cause contrast changes and
noise elimination along with video frames pixel size conversions. Highlighting particular
areas of videos, deleting unsuitable lighting effects, eliminating camera motions and
removing edge-artifacts are performable using video processing methods. OpenCV
library of python is equipped with functions that allow us to manipulate videos and
images. OpenCV Python makes use of Numpy, which is a library for numerical
operations with a MATLAB-style syntax.
Based on our project, we counting the cars and controlling the traffic light according to the
number of cars, so that if the number exceeds the number 15, the green signal will open for a
longer period, and the rest of the intersections will be red. But we were unable to apply this thing
at a real crossroads due to the prevailing conditions in the country.